WEBVTT 00:00:00.132 --> 00:00:01.560 (audience applauding) 00:00:01.560 --> 00:00:03.660 - [Dr. Sood] So I'm just gonna present preliminary results 00:00:03.660 --> 00:00:07.860 of our NICU Universal Screening Program for CMV 00:00:07.860 --> 00:00:09.810 in a large health system that delivers 00:00:09.810 --> 00:00:14.700 about 40-45,000 babies a year in New York. 00:00:14.700 --> 00:00:16.590 It's not an original study. 00:00:16.590 --> 00:00:18.960 I'm just following the footsteps of Birmingham, Alabama, 00:00:18.960 --> 00:00:20.430 which has been doing it for many years, 00:00:20.430 --> 00:00:25.430 as well as Pablo Sanchez and Nationwide Columbus Children's. 00:00:27.780 --> 00:00:29.370 How do I advance the slides? 00:00:29.370 --> 00:00:32.947 Sorry, just a button. 00:00:32.947 --> 00:00:35.447 - [Moderator] Point it, point it up in the corner. 00:00:39.570 --> 00:00:40.540 - [Dr. Sood] Sorry. 00:00:40.540 --> 00:00:42.390 Okay, thanks, sorry. (chuckles) 00:00:42.390 --> 00:00:46.890 So, so this is just a map that I showed last CMV meeting 00:00:46.890 --> 00:00:48.150 of our health system. 00:00:48.150 --> 00:00:50.400 It's all over the place in Downstate New York. 00:00:50.400 --> 00:00:52.710 So about 23 hospitals, about 10, 00:00:52.710 --> 00:00:54.540 those marked with those badges 00:00:54.540 --> 00:00:57.852 are the hospitals that deliver babies. 00:00:57.852 --> 00:01:02.852 And we actually have a very successful CMV, sorry, 00:01:03.810 --> 00:01:05.670 hearing-targeted program that's been going on 00:01:05.670 --> 00:01:06.690 for about five years. 00:01:06.690 --> 00:01:09.900 I have a poster about that in the corner over there. 00:01:09.900 --> 00:01:11.760 And so on the heels of that, 00:01:11.760 --> 00:01:15.543 we decided that we would like to implement it for our NICUs. 00:01:16.410 --> 00:01:19.920 The background for testing NICU babies is that 00:01:19.920 --> 00:01:23.040 if you develop, if you diagnose CMV in the NICU, 00:01:23.040 --> 00:01:25.080 there's a general incidence of cCMV, 00:01:25.080 --> 00:01:27.780 which we don't typically detect. 00:01:27.780 --> 00:01:30.720 Then there's postnatal acquisition that occurs in the NICU, 00:01:30.720 --> 00:01:33.450 presumably from expressed breast milk. 00:01:33.450 --> 00:01:35.760 But if detected after three weeks of age, 00:01:35.760 --> 00:01:38.850 as often NICU babies are, then it's impossible 00:01:38.850 --> 00:01:43.020 to distinguish cCMV from postnatal or pCMV. 00:01:43.020 --> 00:01:46.170 We are increasingly recognizing and treating CMV 00:01:46.170 --> 00:01:47.970 because of being more comfortable now 00:01:47.970 --> 00:01:49.860 with using PO Valganciclovir, 00:01:49.860 --> 00:01:51.690 even in low birth weight infants. 00:01:51.690 --> 00:01:54.750 And there is considerable impact from many studies 00:01:54.750 --> 00:01:57.060 on low birth weight infants. 00:01:57.060 --> 00:02:00.240 Just three slides, quick slides to highlight studies 00:02:00.240 --> 00:02:02.040 you've heard about before. 00:02:02.040 --> 00:02:04.950 This is from Tran and Tatiana's group, 00:02:04.950 --> 00:02:09.270 which is showing literally the double incidence 00:02:09.270 --> 00:02:13.680 that twice, you know, incidence in low birth weight infants 00:02:13.680 --> 00:02:16.770 versus very low birth weight infants. 00:02:16.770 --> 00:02:21.120 There is data that now suggest increased risk 00:02:21.120 --> 00:02:24.480 for failed hearing screen and other complications 00:02:24.480 --> 00:02:27.603 very low birth infants weight with postnatally-acquired CMV. 00:02:28.530 --> 00:02:30.750 And I might have skipped a slide, I'm sorry. 00:02:30.750 --> 00:02:32.223 Oh, my screen went blank. 00:02:35.880 --> 00:02:39.870 I think the slide that did not show is, 00:02:39.870 --> 00:02:42.720 this is a slide from Pablo Sanchez group, 00:02:42.720 --> 00:02:45.690 which is showing that the timing of hearing testing 00:02:45.690 --> 00:02:48.570 in the NICU is much, is very late, and therefore 00:02:48.570 --> 00:02:53.570 you do circumvent the chance to diagnose cCMV at birth. 00:02:54.120 --> 00:02:57.780 So January of this year, we started the program. 00:02:57.780 --> 00:03:00.600 We included all infants admitted to the NICU. 00:03:00.600 --> 00:03:04.230 Initially it was basically a pilot in two biggest NICUs. 00:03:04.230 --> 00:03:06.265 We excluded babies who were transferred from other hospitals 00:03:06.265 --> 00:03:08.820 after day 21 of life. 00:03:08.820 --> 00:03:12.000 And it's saliva bundled with colostrum care, 00:03:12.000 --> 00:03:14.725 which is timed two to three hours after breastfeeds 00:03:14.725 --> 00:03:16.980 in many of these low birth weight infants. 00:03:16.980 --> 00:03:20.220 The implementation, the test change we implemented 00:03:20.220 --> 00:03:23.610 was substituting a test which was sent out 00:03:23.610 --> 00:03:26.738 to Viracor Eurofins, which was a saliva PCR 00:03:26.738 --> 00:03:31.170 with now an in-house done at Northwell Health Labs, 00:03:31.170 --> 00:03:36.170 a lithium Meridian Bioscience CMV lamp technology assay. 00:03:36.240 --> 00:03:41.100 And we added this to the automatic admission NICU order set. 00:03:41.100 --> 00:03:44.250 We, like I said, the test was brought in house, 00:03:44.250 --> 00:03:45.810 and it's dry swab collection, 00:03:45.810 --> 00:03:48.120 which is validated internally so that the nurse 00:03:48.120 --> 00:03:51.240 at the bedside busy with the baby doesn't have to fiddle 00:03:51.240 --> 00:03:53.220 with the universal transport medium. 00:03:53.220 --> 00:03:54.750 And after internal validation, 00:03:54.750 --> 00:03:56.100 we're just using the dry swab, 00:03:56.100 --> 00:03:57.840 the COPAN swab shown here, 00:03:57.840 --> 00:04:00.030 the result is available in 12 to 24 hours, 00:04:00.030 --> 00:04:05.030 actually comes every 7:00 AM in my email inbox, and I have 00:04:05.670 --> 00:04:08.733 to find the time to look at it quickly every day. 00:04:09.740 --> 00:04:12.690 We started off with a bang, all these detects. 00:04:12.690 --> 00:04:14.280 So this is actually the third month, 00:04:14.280 --> 00:04:18.750 and we ran into a surprising series of positive babies, 00:04:18.750 --> 00:04:21.390 which was just not, it is just not possible. 00:04:21.390 --> 00:04:23.040 So we didn't believe this. 00:04:23.040 --> 00:04:26.428 And it turns out we did have a problem with the assay, 00:04:26.428 --> 00:04:30.570 at least briefly, where we, there were false positives. 00:04:30.570 --> 00:04:33.900 And so what our lab director did was, 00:04:33.900 --> 00:04:35.867 whenever there is a detection now 00:04:35.867 --> 00:04:40.560 he reruns the sample, on the same sample reruns it, 00:04:40.560 --> 00:04:42.060 and if it's negative, 00:04:42.060 --> 00:04:45.630 he reports it as indeterminate because sort of it is by, 00:04:45.630 --> 00:04:48.090 you know, by convention, lab reporting convention, 00:04:48.090 --> 00:04:50.310 he can't call it a negative because there was a positive 00:04:50.310 --> 00:04:51.143 on the record. 00:04:51.143 --> 00:04:54.472 So I know and he knows that indeterminate means negative, 00:04:54.472 --> 00:04:57.450 but the average clinician getting the result doesn't know. 00:04:57.450 --> 00:05:00.210 And so often these babies end up getting a urine PCR 00:05:00.210 --> 00:05:02.553 for confirmation, which adds to the expense. 00:05:03.840 --> 00:05:05.880 Sorry, so there's.. 00:05:05.880 --> 00:05:08.190 So the true positives are actually been 11, 00:05:08.190 --> 00:05:10.860 and again, I'm showing my screen just went dark, 00:05:10.860 --> 00:05:12.990 so hopefully it'll come back. 00:05:12.990 --> 00:05:17.990 But it's 11 of the denominator is 761 00:05:20.045 --> 00:05:22.971 over seven and a half months until the middle of August 00:05:22.971 --> 00:05:26.340 in two large, reporting only for the two largest NICUs, 00:05:26.340 --> 00:05:27.600 which is at the Children's Hospital 00:05:27.600 --> 00:05:29.802 and North Shore University Hospital. 00:05:29.802 --> 00:05:33.420 And of these only three were confirmed by urine. 00:05:33.420 --> 00:05:35.357 So we've had three true positives 00:05:35.357 --> 00:05:38.730 in this cohort over seven and a half months. 00:05:38.730 --> 00:05:42.123 These are the three babies it happened within, 00:05:43.995 --> 00:05:48.600 again, went blank, but by recollection I know it's February 00:05:48.600 --> 00:05:51.180 and then two were actually in August. 00:05:51.180 --> 00:05:54.660 So one of them, there they are. 00:05:54.660 --> 00:05:57.900 So one was a 40-week gestation baby 00:05:57.900 --> 00:05:59.640 who just transiently came to the NICU 00:05:59.640 --> 00:06:01.890 for low blood glucose monitoring, 00:06:01.890 --> 00:06:05.160 was appropriate for gestational age, asymptomatic. 00:06:05.160 --> 00:06:09.480 And her hearing has been confirmed as normal to date. 00:06:09.480 --> 00:06:13.110 The other two, again, I'm reading from recollection, 00:06:13.110 --> 00:06:14.953 but it's 37 weekers. 00:06:14.953 --> 00:06:15.840 (panelist chattering) 00:06:15.840 --> 00:06:16.673 Oh, are they back here? 00:06:16.673 --> 00:06:17.506 Okay, good. 00:06:17.506 --> 00:06:18.339 Great, sorry. 00:06:18.339 --> 00:06:22.260 So they were both the 37, 37 and 38 weekers. 00:06:22.260 --> 00:06:25.200 They were SGA, but that was actually not the reason 00:06:25.200 --> 00:06:26.033 for the testing. 00:06:26.033 --> 00:06:28.380 Again, it was because there's universal testing. 00:06:28.380 --> 00:06:30.844 So went back and looked at the clinical criteria 00:06:30.844 --> 00:06:33.150 and again, normal hearing to date. 00:06:33.150 --> 00:06:36.330 So babies, all these babies are actually, you know, 00:06:36.330 --> 00:06:38.220 have been doing well. 00:06:38.220 --> 00:06:41.523 But that's the preliminary data we have so far. 00:06:42.360 --> 00:06:46.290 But then I might have come to a screeching halt 00:06:46.290 --> 00:06:50.500 because just last week our neonatal chief 00:06:50.500 --> 00:06:53.400 reads the email from a New York State Newborn 00:06:53.400 --> 00:06:55.350 Screening Program, which you've heard about, 00:06:55.350 --> 00:06:56.820 started last Monday. 00:06:56.820 --> 00:06:58.140 And about two weeks prior, 00:06:58.140 --> 00:07:00.007 they had sent an email blast and said, 00:07:00.007 --> 00:07:02.767 "Oh, we can stop doing urine testing, 00:07:02.767 --> 00:07:04.207 "this universal testing anymore. 00:07:04.207 --> 00:07:05.857 "We don't need it, it's just too expensive, 00:07:05.857 --> 00:07:08.370 "and the state is gonna do it for us for free." 00:07:08.370 --> 00:07:11.670 And so I had to over the last two weeks come up with my list 00:07:11.670 --> 00:07:14.490 of counter-arguments because I wanted the parallel 00:07:14.490 --> 00:07:16.380 screening program to continue. 00:07:16.380 --> 00:07:19.560 Firstly, it's a study, it's a New York pilot one-year study. 00:07:19.560 --> 00:07:22.200 The heel stick blood spot is not going to be 00:07:22.200 --> 00:07:24.000 as sensitive as saliva. 00:07:24.000 --> 00:07:27.030 We know that, no matter how well it performs. 00:07:27.030 --> 00:07:29.730 And our NICU testing cost actually doesn't cost, 00:07:29.730 --> 00:07:32.280 to my knowledge, the neonatology department any money. 00:07:32.280 --> 00:07:34.920 It's bundled into the lab reimbursement from insurance, 00:07:34.920 --> 00:07:37.350 and the lab hasn't objected yet. 00:07:37.350 --> 00:07:38.382 Swab collection has become part 00:07:38.382 --> 00:07:40.710 of the routine workflow for the admitting nurse. 00:07:40.710 --> 00:07:43.320 It literally takes 10 seconds. 00:07:43.320 --> 00:07:45.810 And I think we will reintroduce confusion 00:07:45.810 --> 00:07:47.589 for the primary clinician in terms of, 00:07:47.589 --> 00:07:49.740 you know, targeted testing. 00:07:49.740 --> 00:07:51.960 And we will go back to missing babies 00:07:51.960 --> 00:07:54.330 with soft signs including some SGA babies. 00:07:54.330 --> 00:07:58.686 So if anybody has any suggestions that I can take back 00:07:58.686 --> 00:08:01.530 to argue back with my neonatal chief, let me know. 00:08:01.530 --> 00:08:06.530 My last slide is just what I perceive as the benefits, 00:08:07.230 --> 00:08:08.910 screening benefits for clinical care 00:08:08.910 --> 00:08:11.070 if you have a universal NICU program. 00:08:11.070 --> 00:08:15.120 We need to understand congenital CMV at birth. 00:08:15.120 --> 00:08:18.420 We need to use that baseline to understand postnatal CMV 00:08:18.420 --> 00:08:20.760 acquisition and establish better protocols 00:08:20.760 --> 00:08:22.080 for monitoring and treatment. 00:08:22.080 --> 00:08:23.208 Thank you. 00:08:23.208 --> 00:08:26.375 (audience applauding) 00:08:32.310 --> 00:08:35.490 - [Dr. Page] Well, I want to express my gratitude to be able 00:08:35.490 --> 00:08:39.120 to represent my group to talk about our study 00:08:39.120 --> 00:08:40.410 that we've worked on. 00:08:40.410 --> 00:08:41.640 And I know that eight minutes 00:08:41.640 --> 00:08:44.640 will strain my struggles with brevity. 00:08:44.640 --> 00:08:46.950 So those are our great people that worked on this. 00:08:46.950 --> 00:08:49.500 We have some other presentations at this conference as well. 00:08:49.500 --> 00:08:51.870 We had funding from the Ear Foundation 00:08:51.870 --> 00:08:54.300 and the Arizona Community Foundation and from Midwestern. 00:08:54.300 --> 00:08:57.450 And I do wanna acknowledge some assistance that we got 00:08:57.450 --> 00:09:01.020 from Dignity Healthcare, who helped facilitate our project. 00:09:01.020 --> 00:09:03.930 So this started with a group called Stop CMV Arizona. 00:09:03.930 --> 00:09:06.030 You may have heard a little discussion of that already today 00:09:06.030 --> 00:09:10.260 as an advocacy and education group. 00:09:10.260 --> 00:09:15.260 And as this is our first real foray into clinical science, 00:09:16.080 --> 00:09:18.540 as we started discussing what could be done 00:09:18.540 --> 00:09:21.390 in Arizona to move this forward. 00:09:21.390 --> 00:09:24.482 We started with the current CMV data in Arizona. 00:09:24.482 --> 00:09:27.690 And it looks like this. 00:09:27.690 --> 00:09:31.320 So, so little is known about our incidence in Arizona 00:09:31.320 --> 00:09:32.490 or anything that's going on 00:09:32.490 --> 00:09:34.740 because there are no screening programs and there are not 00:09:34.740 --> 00:09:36.630 even any hospital-based screening programs. 00:09:36.630 --> 00:09:38.430 And so we had to begin somewhere, 00:09:38.430 --> 00:09:40.493 and we decided to start with a pilot study 00:09:40.493 --> 00:09:42.570 of testing healthy newborns. 00:09:42.570 --> 00:09:45.420 So the main goal was to demonstrate feasibility 00:09:45.420 --> 00:09:47.940 of universal screening and then some secondary goals 00:09:47.940 --> 00:09:51.600 about beginning to gather data and to establish a protocol 00:09:51.600 --> 00:09:53.490 that would let us scale that up and use it 00:09:53.490 --> 00:09:57.123 for a larger network-wide and then statewide effort. 00:09:58.140 --> 00:10:00.720 So we started by assembling a consortium of key players, 00:10:00.720 --> 00:10:04.050 and this was crucial to what we were trying to accomplish. 00:10:04.050 --> 00:10:05.250 So we started with our group, 00:10:05.250 --> 00:10:07.932 but we began to put together funders and hospitals 00:10:07.932 --> 00:10:10.830 and universities and all these different people 00:10:10.830 --> 00:10:12.660 who had interest in this area 00:10:12.660 --> 00:10:14.475 so that we had all the expertise we needed 00:10:14.475 --> 00:10:16.260 and all the resource we needed to get it done. 00:10:16.260 --> 00:10:17.883 And this may be the most important part 00:10:17.883 --> 00:10:19.410 of our project today, 00:10:19.410 --> 00:10:21.660 is to talk about the collaboration that we were able 00:10:21.660 --> 00:10:24.420 to put together with all of these different institutions. 00:10:24.420 --> 00:10:27.720 So I do want to talk about the data that we gained, 00:10:27.720 --> 00:10:30.390 but that's less important I think in this early stage 00:10:30.390 --> 00:10:34.650 of our development compared to the process and the people. 00:10:34.650 --> 00:10:38.850 So we had to start with very basic things. 00:10:38.850 --> 00:10:40.800 So it turns out that our hospital does not 00:10:40.800 --> 00:10:42.570 have the instruments to run CMV. 00:10:42.570 --> 00:10:43.950 They were all being sent out. 00:10:43.950 --> 00:10:46.200 So our CMV PCRs were going elsewhere. 00:10:46.200 --> 00:10:47.790 We determined that when we started trying 00:10:47.790 --> 00:10:49.080 to set up this project. 00:10:49.080 --> 00:10:51.630 So we began to look at bringing the instruments in from some 00:10:51.630 --> 00:10:53.160 of the companies that are here today 00:10:53.160 --> 00:10:55.320 and look if we could accomplish that protocol. 00:10:55.320 --> 00:10:58.110 If not, then we need to have it run at another institution, 00:10:58.110 --> 00:11:00.660 which means we have to decide how the swabs 00:11:00.660 --> 00:11:01.710 get from one place to another 00:11:01.710 --> 00:11:03.810 and how the data gets from one place to another. 00:11:03.810 --> 00:11:05.760 So we had to build data-sharing agreements 00:11:05.760 --> 00:11:07.140 between the institutions. 00:11:07.140 --> 00:11:08.220 As you might know, 00:11:08.220 --> 00:11:09.930 those of you who work at academic institutions, 00:11:09.930 --> 00:11:11.654 people are very picky or institutions are very picky 00:11:11.654 --> 00:11:14.460 about where their data goes and who gets access to it. 00:11:14.460 --> 00:11:16.350 So all of this took time. 00:11:16.350 --> 00:11:17.700 We had to educate the clinical providers 00:11:17.700 --> 00:11:20.850 about even what the diagnosis is and why we were doing it. 00:11:20.850 --> 00:11:23.850 And then a workflow for newborns who were testing positive 00:11:23.850 --> 00:11:27.210 so we had a place to take them once we had those results. 00:11:27.210 --> 00:11:30.510 We gathered a lot of information, and we had a great deal 00:11:30.510 --> 00:11:31.343 of discussion about what we would need 00:11:31.343 --> 00:11:33.180 and the information we need to gather. 00:11:33.180 --> 00:11:35.266 To give you a timeframe here, we really got together 00:11:35.266 --> 00:11:38.698 to discuss this project just as the pandemic was setting on. 00:11:38.698 --> 00:11:41.370 And worked through some of the challenges of that, 00:11:41.370 --> 00:11:43.890 submitted our initial IRB 00:11:43.890 --> 00:11:47.430 or had acceptance of our IRB in May of 2021. 00:11:47.430 --> 00:11:50.160 And we started gathering data in November of 2022. 00:11:50.160 --> 00:11:53.130 So that's how long it took to put all the pieces together 00:11:53.130 --> 00:11:56.940 in our system that has not been prepared for this. 00:11:56.940 --> 00:11:58.475 So here are our results. 00:11:58.475 --> 00:12:02.490 We have, that looks like an old slide actually. 00:12:02.490 --> 00:12:03.330 Sorry about that. 00:12:03.330 --> 00:12:05.283 Here's our results, slightly larger. 00:12:06.120 --> 00:12:11.120 We screened 254 infants and had, or we enrolled 254. 00:12:11.310 --> 00:12:13.920 We screened 250 successfully. 00:12:13.920 --> 00:12:16.350 They were essentially even between male and female, 00:12:16.350 --> 00:12:17.820 mostly white. 00:12:17.820 --> 00:12:19.530 We had a wide range of birth weight. 00:12:19.530 --> 00:12:21.840 These were, no one was extremely low birth weight 00:12:21.840 --> 00:12:23.818 because we only screened healthy newborns. 00:12:23.818 --> 00:12:28.027 This did not go into our NICU or special care nursery. 00:12:28.027 --> 00:12:31.860 We had, 57% had a high school diploma or less in education. 00:12:31.860 --> 00:12:34.702 173 had siblings at home. 00:12:34.702 --> 00:12:36.172 We looked at that as a risk factor 00:12:36.172 --> 00:12:39.033 for CMV exposure to the parents. 00:12:40.080 --> 00:12:42.180 Three infants' primary address was in Mexico, 00:12:42.180 --> 00:12:44.460 which is a concern for follow-up. 00:12:44.460 --> 00:12:46.680 When we look at the actual data that we collected, 00:12:46.680 --> 00:12:48.360 two of our swabs were positive. 00:12:48.360 --> 00:12:51.540 One of those was confirmed on urine PCR. 00:12:51.540 --> 00:12:53.716 11 of our subjects total failed their hearing screening, 00:12:53.716 --> 00:12:55.710 all of whom were CMV negative. 00:12:55.710 --> 00:12:58.447 And our two positive swabs were both, 00:12:58.447 --> 00:13:00.363 had normal hearing screening. 00:13:02.490 --> 00:13:03.867 We looked at pregnancy complications, 00:13:03.867 --> 00:13:06.739 and you can see a variety of things. 00:13:06.739 --> 00:13:08.220 When we look at things that may be 00:13:08.220 --> 00:13:10.547 specifically associated with congenital CMV, 00:13:10.547 --> 00:13:12.780 there were no reported serious illnesses 00:13:12.780 --> 00:13:14.940 during pregnancy by any of the mothers. 00:13:14.940 --> 00:13:16.440 And we had zero patients 00:13:16.440 --> 00:13:17.940 that had intrauterine growth restriction. 00:13:17.940 --> 00:13:20.130 Again, this is in large part because we were looking 00:13:20.130 --> 00:13:22.023 at a healthy baby population. 00:13:23.430 --> 00:13:24.810 So our successes. 00:13:24.810 --> 00:13:27.180 So we were able to demonstrate that we could do this, 00:13:27.180 --> 00:13:28.740 and that was our primary goal. 00:13:28.740 --> 00:13:31.050 We put together a process that allowed us 00:13:31.050 --> 00:13:33.652 to screen all of these babies at a large birthing center 00:13:33.652 --> 00:13:36.270 in Arizona, something that hasn't been done before. 00:13:36.270 --> 00:13:37.890 We put together a data-sharing agreement 00:13:37.890 --> 00:13:42.840 that is already starting to benefit other parts of our, 00:13:42.840 --> 00:13:44.862 the interactions between our hospitals, 00:13:44.862 --> 00:13:47.765 as others have worked on research projects. 00:13:47.765 --> 00:13:50.400 And then we put together a network of interested people. 00:13:50.400 --> 00:13:53.130 So now we have a group of institutions 00:13:53.130 --> 00:13:55.809 and individuals who all have interest in CMV testing, 00:13:55.809 --> 00:13:59.760 education advocacy, and that is gonna be a huge 00:13:59.760 --> 00:14:00.903 step forward for us. 00:14:01.890 --> 00:14:05.040 As was mentioned in Dr. Muldoon's talk earlier, 00:14:05.040 --> 00:14:07.740 as part of what this organization has done, 00:14:07.740 --> 00:14:08.970 not particularly this study, 00:14:08.970 --> 00:14:13.770 we have had CMV Awareness Month in the month of June 00:14:13.770 --> 00:14:14.940 for the last four years in a row. 00:14:14.940 --> 00:14:18.330 Even with our differing political parties as governors, 00:14:18.330 --> 00:14:19.163 we've been able to maintain that, 00:14:19.163 --> 00:14:21.870 and it looks like we'll be able to continue to do that. 00:14:21.870 --> 00:14:22.830 Limitations of our studies. 00:14:22.830 --> 00:14:23.970 This is a small sample size. 00:14:23.970 --> 00:14:25.710 Obviously, this doesn't give us a lot of information 00:14:25.710 --> 00:14:27.234 about incidence in our state. 00:14:27.234 --> 00:14:29.850 This is more of a proof of concept study. 00:14:29.850 --> 00:14:32.010 So we also screened only healthy infants. 00:14:32.010 --> 00:14:33.510 So we need to adapt our protocol 00:14:33.510 --> 00:14:35.250 if we're gonna include NICU babies, 00:14:35.250 --> 00:14:36.540 as you heard some of those challenges 00:14:36.540 --> 00:14:38.040 in the previous presentation. 00:14:38.040 --> 00:14:39.240 And then this was a convenient sample. 00:14:39.240 --> 00:14:42.360 That is, we did not test every single baby that was born, 00:14:42.360 --> 00:14:44.700 in part because of the financial resources. 00:14:44.700 --> 00:14:46.991 So in order to pay someone to do this on the weekends, 00:14:46.991 --> 00:14:49.140 we would need to pick up some extra money. 00:14:49.140 --> 00:14:51.990 So we only collected babies that were born 00:14:51.990 --> 00:14:53.400 and available during the week. 00:14:53.400 --> 00:14:56.220 So that all needs to be adapted for a larger project. 00:14:56.220 --> 00:14:58.500 So where we go now is to expand that testing 00:14:58.500 --> 00:15:01.230 to additional sites in our network and then eventually 00:15:01.230 --> 00:15:03.450 outside our network to become a statewide project. 00:15:03.450 --> 00:15:05.760 We're gonna need to adapt our protocol, and ultimately 00:15:05.760 --> 00:15:08.940 we hope to have enough data to be able to present this 00:15:08.940 --> 00:15:11.850 to healthcare and legislative leaders 00:15:11.850 --> 00:15:14.163 in our state to make some changes. 00:15:15.330 --> 00:15:16.470 That is our website. 00:15:16.470 --> 00:15:18.900 You're welcome to scan that code or talk to any of us 00:15:18.900 --> 00:15:19.795 about what we're doing. 00:15:19.795 --> 00:15:20.820 We welcome that. 00:15:20.820 --> 00:15:22.231 Thank you for the opportunity to present. 00:15:22.231 --> 00:15:25.398 (audience applauding) 00:15:30.570 --> 00:15:31.710 - [Dr. Rosebrock] Hello, everyone. 00:15:31.710 --> 00:15:33.540 Thank you to the organizers for having me today. 00:15:33.540 --> 00:15:36.750 My name is Tracy Rosebrock, and I'm a professor of biology 00:15:36.750 --> 00:15:39.180 and health sciences at Stonehill College. 00:15:39.180 --> 00:15:41.190 I'm new to the CMV community. 00:15:41.190 --> 00:15:43.770 I've been a microbiologist for 20 years working on 00:15:43.770 --> 00:15:47.529 basic biology of how bacteria and viruses infect people. 00:15:47.529 --> 00:15:51.480 I came to CMV in 2020 is when I first became aware of it. 00:15:51.480 --> 00:15:54.060 I had never heard of it before, and I have been pregnant. 00:15:54.060 --> 00:15:55.170 Never heard of it. 00:15:55.170 --> 00:15:58.170 And I was floored that this was a thing. 00:15:58.170 --> 00:16:00.390 Like I was absolutely flabbergasted. 00:16:00.390 --> 00:16:02.220 So I shifted my research. 00:16:02.220 --> 00:16:04.650 I now work on CMV in the lab. 00:16:04.650 --> 00:16:08.340 And I also decided, "Okay, lab is fun, I love lab," 00:16:08.340 --> 00:16:10.620 but I really wanted to have some skills in public health, 00:16:10.620 --> 00:16:11.820 especially around advocacy. 00:16:11.820 --> 00:16:14.910 So I started an MPH, Master's in Public Health. 00:16:14.910 --> 00:16:16.590 This summer I was finishing my MPH, 00:16:16.590 --> 00:16:18.210 I needed a practicum experience. 00:16:18.210 --> 00:16:22.200 I had just come across in my feed a paper by Karen Fowler? 00:16:22.200 --> 00:16:23.460 This is amazing! 00:16:23.460 --> 00:16:26.370 So I thought, "I'll just email her and that'll work." 00:16:26.370 --> 00:16:28.471 And it did, she wrote me back. 00:16:28.471 --> 00:16:30.360 She was truly the kindest person, 00:16:30.360 --> 00:16:32.010 has been a wonderful mentor. 00:16:32.010 --> 00:16:34.860 So we've come up with this project to evaluate the digital 00:16:34.860 --> 00:16:37.020 impact of National CMV Awareness Month, 00:16:37.020 --> 00:16:39.947 which basically we ask what's happening on social media. 00:16:39.947 --> 00:16:42.510 (chuckles) So just to anchor us a little bit, 00:16:42.510 --> 00:16:44.940 what is National CMV Awareness month? 00:16:44.940 --> 00:16:49.940 It is, in 2011, this was actually mandated by the US Senate 00:16:49.980 --> 00:16:51.390 that June would be recognized 00:16:51.390 --> 00:16:53.280 as National CMV Awareness Month, 00:16:53.280 --> 00:16:54.720 and it would be an annual event. 00:16:54.720 --> 00:16:57.371 And they explicitly state, "To raise awareness 00:16:57.371 --> 00:16:59.767 "of the dangers of cytomegalovirus 00:16:59.767 --> 00:17:03.987 "and to reduce the occurrence of congenital CMV infection." 00:17:05.400 --> 00:17:06.480 So how did we do this? 00:17:06.480 --> 00:17:08.490 Really, I'm gonna walk you through two study questions. 00:17:08.490 --> 00:17:12.293 The first one was, did CMV messaging on social media, 00:17:12.293 --> 00:17:15.510 did it change due to National CMV Awareness Month? 00:17:15.510 --> 00:17:16.706 And how do we do this? 00:17:16.706 --> 00:17:18.769 So we looked at social media because there 00:17:18.769 --> 00:17:23.430 are 5 billion users of social media across the globe. 00:17:23.430 --> 00:17:27.180 90% of US adults use social media an average 00:17:27.180 --> 00:17:29.400 of 2.5 hours per day. 00:17:29.400 --> 00:17:33.330 That makes this a powerful public health platform. 00:17:33.330 --> 00:17:37.740 It is used widely, it is democratic, and it is free. 00:17:37.740 --> 00:17:38.640 It's amazing. 00:17:38.640 --> 00:17:41.970 So we used social listening, which is a, 00:17:41.970 --> 00:17:44.100 I could tell you all about that in my poster tomorrow, 00:17:44.100 --> 00:17:45.450 but we used social media listening. 00:17:45.450 --> 00:17:47.700 We looked at three different platforms. 00:17:47.700 --> 00:17:49.413 So what's on Twitter, or X, whatever you wanna call it, 00:17:49.413 --> 00:17:52.320 Instagram and TikTok. 00:17:52.320 --> 00:17:55.110 We then evaluated, pulled all those posts 00:17:55.110 --> 00:17:58.560 using five hashtags that were used that we kind of 00:17:58.560 --> 00:18:01.080 figured out were used by a bunch of different stakeholders. 00:18:01.080 --> 00:18:05.075 So we used the hashtag StopCMV, cCMV, CMV, 00:18:05.075 --> 00:18:07.473 CMVAwareness, or #Cytomegalovirus. 00:18:08.370 --> 00:18:12.630 We pulled those for June, which was CMV Awareness Month. 00:18:12.630 --> 00:18:14.783 And then we also looked just before in May 00:18:14.783 --> 00:18:16.770 and just after in July. 00:18:16.770 --> 00:18:20.010 So before in May to ask, did things change from May to June? 00:18:20.010 --> 00:18:22.064 And then did, if we did have a change, 00:18:22.064 --> 00:18:24.978 were we able to maintain that change through July? 00:18:24.978 --> 00:18:27.660 So we collected those posts, we indexed by author, 00:18:27.660 --> 00:18:30.240 and then we also evaluated by post intent, 00:18:30.240 --> 00:18:32.040 which I'll get to in a second. 00:18:32.040 --> 00:18:33.870 So I'm only gonna show you a little bit of this data 00:18:33.870 --> 00:18:36.990 because it is a lot of data and this is how far I've gotten. 00:18:36.990 --> 00:18:40.140 So, so far I've looked at Twitter/X posts. 00:18:40.140 --> 00:18:42.291 We asked, "Is there a change in the number of posts 00:18:42.291 --> 00:18:45.930 "that were posted, increase, decrease or no change?" 00:18:45.930 --> 00:18:48.630 And then we also asked about the change in intent. 00:18:48.630 --> 00:18:51.030 So the CDC lists on their website 00:18:51.030 --> 00:18:54.060 for National CMV Awareness Month three objectives. 00:18:54.060 --> 00:18:57.660 One, to increase awareness of congenital CMV. 00:18:57.660 --> 00:19:01.050 So to be specific, congenital CMV. 00:19:01.050 --> 00:19:03.210 To increase education, public education 00:19:03.210 --> 00:19:05.199 around congenital CMV, and to increase 00:19:05.199 --> 00:19:08.550 healthcare provider education on early signs and symptoms 00:19:08.550 --> 00:19:12.410 of congenital CMV to get to early inventions, to create, 00:19:12.410 --> 00:19:15.930 or to get to earlier, to get to interventions earlier. 00:19:15.930 --> 00:19:19.590 So first, first question, did the number of tweets change? 00:19:19.590 --> 00:19:20.940 CMV-related tweets change. 00:19:20.940 --> 00:19:22.830 Yes, so these are all five hashtags 00:19:22.830 --> 00:19:24.390 you can see are grouped as columns. 00:19:24.390 --> 00:19:27.510 And then they're color coded by month: May, June and July. 00:19:27.510 --> 00:19:29.340 And you can see for each of the hashtags 00:19:29.340 --> 00:19:30.480 we do see an increase. 00:19:30.480 --> 00:19:32.130 That orange dotted line kind of helps 00:19:32.130 --> 00:19:33.933 you show the difference from May to June. 00:19:33.933 --> 00:19:35.612 That's fantastic. 00:19:35.612 --> 00:19:38.640 The bad news is that this wasn't maintained. 00:19:38.640 --> 00:19:40.470 So once we get to July, we see a dip. 00:19:40.470 --> 00:19:42.155 Now, this could be everybody went on vacation. 00:19:42.155 --> 00:19:44.850 This could be Elon Musk twittering around 00:19:44.850 --> 00:19:46.470 and doing X-ing and whatever he was doing. 00:19:46.470 --> 00:19:47.940 So we're not exactly sure. 00:19:47.940 --> 00:19:50.520 But we, I'm pretty sure we didn't maintain that momentum. 00:19:50.520 --> 00:19:52.700 But the good news is we did have some momentum. 00:19:52.700 --> 00:19:54.674 Okay, so did the intent change. 00:19:54.674 --> 00:19:58.200 I've only been able to dig through the StopCMV hashtag 00:19:58.200 --> 00:20:00.480 so far, of which there were very, very many. 00:20:00.480 --> 00:20:02.310 And it's manual work. 00:20:02.310 --> 00:20:06.000 You have to read the tweets, which takes a long time. 00:20:06.000 --> 00:20:07.200 So reading the tweets, 00:20:07.200 --> 00:20:09.810 I can say of the StopCMV in hashtags, 00:20:09.810 --> 00:20:12.840 only about half of them actually explicitly talk 00:20:12.840 --> 00:20:15.180 about congenital CMV. 00:20:15.180 --> 00:20:16.560 So of those half we did see, 00:20:16.560 --> 00:20:19.740 we went from 40% in May to 50% of those, 00:20:19.740 --> 00:20:23.220 50% of those tweets actually talking about congenital CMV. 00:20:23.220 --> 00:20:26.460 So we increased congenital CMV, which was fabulous. 00:20:26.460 --> 00:20:30.005 And then most of those do a great job of showing awareness. 00:20:30.005 --> 00:20:33.900 Alerting people to the fact that congenital CMV does exist. 00:20:33.900 --> 00:20:37.350 However, most of them don't have anything to do 00:20:37.350 --> 00:20:39.420 with education, and we don't do anything 00:20:39.420 --> 00:20:42.540 to educate healthcare providers with that hashtag. 00:20:42.540 --> 00:20:44.460 The other thing I wanted to look at was sentiment. 00:20:44.460 --> 00:20:47.280 Are these posts happy, sad, neutral? 00:20:47.280 --> 00:20:48.750 What would the audience feel? 00:20:48.750 --> 00:20:51.500 We can say that posts that have education or awareness 00:20:51.500 --> 00:20:54.734 in them are more likely to be scored negative by algorithms, 00:20:54.734 --> 00:20:57.083 but they're also more likely to induce engagement 00:20:57.083 --> 00:20:58.260 with the audience. 00:20:58.260 --> 00:21:00.300 So don't be afraid to add education. 00:21:00.300 --> 00:21:01.939 It may feel dry, it may feel boring, 00:21:01.939 --> 00:21:05.162 but you'll get more likes and you'll get more retweets. 00:21:05.162 --> 00:21:07.147 Then we also asked, "Did public interest 00:21:07.147 --> 00:21:08.850 "in congenital CMV change?" 00:21:08.850 --> 00:21:11.167 And so we don't, can't really go ask everybody, 00:21:11.167 --> 00:21:12.990 "Did your interest change, did your interest change?" 00:21:12.990 --> 00:21:16.530 So instead what we did was we looked at Google searches. 00:21:16.530 --> 00:21:18.450 90% of US adults use Google. 00:21:18.450 --> 00:21:20.790 75% of US adults use the internet 00:21:20.790 --> 00:21:22.260 to look for healthcare information. 00:21:22.260 --> 00:21:23.460 So I looked for Google searches 00:21:23.460 --> 00:21:25.110 using a tool called Google Trends. 00:21:25.110 --> 00:21:25.943 Same thing. 00:21:25.943 --> 00:21:27.360 We looked at the three months. 00:21:27.360 --> 00:21:30.330 Google indexes searches based on their topical categories 00:21:30.330 --> 00:21:31.560 of which there were two. 00:21:31.560 --> 00:21:33.450 I looked at cytomegalovirus infection, 00:21:33.450 --> 00:21:34.590 which is all the way to the right, 00:21:34.590 --> 00:21:36.870 and then congenital cytomegalovirus infection, 00:21:36.870 --> 00:21:38.250 which is all the way to the left. 00:21:38.250 --> 00:21:40.710 And so we can see with the little orange stars 00:21:40.710 --> 00:21:42.330 that we did have a significant increase 00:21:42.330 --> 00:21:46.781 in public interest in or searches for CMV infection. 00:21:46.781 --> 00:21:51.150 But we had no meaningful change in congenital CMV infection. 00:21:51.150 --> 00:21:52.927 So conclusions, we have more tweets. 00:21:52.927 --> 00:21:55.650 We have more tweets that show awareness, 00:21:55.650 --> 00:21:57.017 more tweets that show education. 00:21:57.017 --> 00:22:00.450 We are not doing anything to educate providers necessarily 00:22:00.450 --> 00:22:04.140 with this #StopCMV, and public interest did change 00:22:04.140 --> 00:22:05.730 for cytomegalovirus infection, 00:22:05.730 --> 00:22:08.820 but not congenital cytomegalovirus infection. 00:22:08.820 --> 00:22:10.492 Thanks, hope to see you at my poster. 00:22:10.492 --> 00:22:11.510 Take care. 00:22:11.510 --> 00:22:14.677 (audience applauding) 00:22:23.310 --> 00:22:25.470 - [Dr. Piper] Good afternoon. 00:22:25.470 --> 00:22:27.397 So here's a quote from Lincoln. 00:22:27.397 --> 00:22:29.467 "If we could first know where we are 00:22:29.467 --> 00:22:31.177 "and whither we are tending, 00:22:31.177 --> 00:22:34.590 "we could then better judge what to do and how to do it." 00:22:34.590 --> 00:22:37.066 So this is, who knew Lincoln was an epidemiologist 00:22:37.066 --> 00:22:39.540 first of all. (audience chuckles) 00:22:39.540 --> 00:22:42.570 And this is a much more elegant way of saying 00:22:42.570 --> 00:22:45.920 that we need information before we can best know what to do, 00:22:45.920 --> 00:22:47.790 how to proceed. 00:22:47.790 --> 00:22:50.220 And isn't it kind of jarring to see a picture 00:22:50.220 --> 00:22:51.240 of him in color? 00:22:51.240 --> 00:22:53.550 I just think it's kind of almost creepy, 00:22:53.550 --> 00:22:56.793 just to see what he probably looked like otherwise. 00:22:59.340 --> 00:23:01.680 So we need information about the incidence and occurrence 00:23:01.680 --> 00:23:04.440 of congenital CMV in Iowa so we can know the best way 00:23:04.440 --> 00:23:08.100 to develop and implement prevention and treatment efforts. 00:23:08.100 --> 00:23:10.950 And our aim is to understand the impact of cCMV 00:23:10.950 --> 00:23:13.650 on Iowa families and to build comprehensive prevention 00:23:13.650 --> 00:23:15.540 and intervention efforts. 00:23:15.540 --> 00:23:17.250 And you're not gonna see a lot of stuff on my slides 00:23:17.250 --> 00:23:19.710 'cause I want you to go look at my poster. 00:23:19.710 --> 00:23:22.653 Number 22. (chuckles) 00:23:24.360 --> 00:23:28.200 Currently, Iowa law requires newborn care providers 00:23:28.200 --> 00:23:30.570 to test newborns that fail their newborn hearing screening 00:23:30.570 --> 00:23:31.680 for cCMV. 00:23:31.680 --> 00:23:34.290 So we do targeted screening in Iowa. 00:23:34.290 --> 00:23:37.440 And the Iowa Department of Health and Human Services, 00:23:37.440 --> 00:23:39.574 formerly the Iowa Department of Public Health, 00:23:39.574 --> 00:23:42.750 we don't have any authority to collect information 00:23:42.750 --> 00:23:45.600 about cCMV testing that is done by the provider. 00:23:45.600 --> 00:23:49.170 So there's no reporting mechanism that we can follow up 00:23:49.170 --> 00:23:51.270 and see what's going on with this testing. 00:23:55.050 --> 00:23:58.500 So how do we get the cCMV data? 00:23:58.500 --> 00:24:01.740 One way that we thought to gather data about CMV occurrence 00:24:01.740 --> 00:24:06.300 in Iowa was to see if the Director of Iowa HHS would 00:24:06.300 --> 00:24:10.890 issue a temporary reporting order for CMV test results, 00:24:10.890 --> 00:24:13.590 similar to what was issued in probably most states 00:24:13.590 --> 00:24:16.053 and jurisdictions for COVID-19 reporting. 00:24:23.310 --> 00:24:24.143 There we go. 00:24:24.143 --> 00:24:25.230 And our plan worked. 00:24:25.230 --> 00:24:27.210 We approached her, and she agreed to do this. 00:24:27.210 --> 00:24:30.817 And her order says, in part, 00:24:30.817 --> 00:24:32.677 "As the Director of the Iowa Department of Health 00:24:32.677 --> 00:24:35.347 "and Human Services, I temporarily designate 00:24:35.347 --> 00:24:37.496 "laboratory results for CMV testing, 00:24:37.496 --> 00:24:40.837 "including but not limited to testing conducted on saliva, 00:24:40.837 --> 00:24:44.820 "urine, blood, or blood spots as reportable in Iowa." 00:24:44.820 --> 00:24:45.757 And then it further says, 00:24:45.757 --> 00:24:47.827 "All Iowa healthcare providers and public, 00:24:47.827 --> 00:24:50.497 "private, and hospital laboratories are required 00:24:50.497 --> 00:24:52.834 "to report all laboratory CMV testing results 00:24:52.834 --> 00:24:55.207 "to the Department within three days 00:24:55.207 --> 00:24:58.027 "of the test being resulted. 00:24:58.027 --> 00:25:00.037 "And reports must be made electronically 00:25:00.037 --> 00:25:02.587 "through the Iowa Disease Surveillance System 00:25:02.587 --> 00:25:06.180 "or other electronic means as directed by the Department." 00:25:06.180 --> 00:25:09.840 So starting in September 1st, this was enacted, 00:25:09.840 --> 00:25:12.649 and it requires all CMV test results. 00:25:12.649 --> 00:25:13.482 The mic? 00:25:14.700 --> 00:25:16.860 Short people problems. (audience chuckles) 00:25:16.860 --> 00:25:17.693 Okay. 00:25:18.870 --> 00:25:21.090 So we started September 1st, and it requires 00:25:21.090 --> 00:25:25.531 all CMV test results, positive and negative for all ages. 00:25:25.531 --> 00:25:28.500 And we know we might be careful what we wish for 00:25:28.500 --> 00:25:31.953 when we're getting reports from all ages. 00:25:33.669 --> 00:25:35.970 The epidemiologist will sort through, 00:25:35.970 --> 00:25:38.670 will parse out those records for us so we can narrow it 00:25:38.670 --> 00:25:39.810 down to something that, 00:25:39.810 --> 00:25:42.600 a little more interested in for cCMV. 00:25:42.600 --> 00:25:45.090 And right now we're just requesting PCR results. 00:25:45.090 --> 00:25:48.003 We're not looking at antibody testing results. 00:25:49.770 --> 00:25:51.180 So the disease are reported 00:25:51.180 --> 00:25:53.970 to our disease surveillance system. 00:25:53.970 --> 00:25:56.460 They have an application called Smart Lab. 00:25:56.460 --> 00:25:58.050 And similar to how labs 00:25:58.050 --> 00:26:01.080 report other infectious disease results like tuberculosis 00:26:01.080 --> 00:26:02.520 to the health department. 00:26:02.520 --> 00:26:05.190 And then the Smart Lab epidemiologist will create a file 00:26:05.190 --> 00:26:08.100 to be picked up via secure file transfer protocol 00:26:08.100 --> 00:26:11.220 by the Iowa Registry for Congenital and Inherited Disorders. 00:26:11.220 --> 00:26:13.320 And I gotta give a shout out to Dr. Paul Romitti. 00:26:13.320 --> 00:26:15.690 He's our director of our registry, 00:26:15.690 --> 00:26:18.750 and he leads the team on that effort. 00:26:18.750 --> 00:26:21.120 And then that is one of our surveillance systems 00:26:21.120 --> 00:26:22.620 for reportable conditions. 00:26:22.620 --> 00:26:25.050 And then the data will also be made available for matching 00:26:25.050 --> 00:26:27.300 with our Iowa Newborn Screening Information System, 00:26:27.300 --> 00:26:29.940 which is our EHDI hearing screening data system. 00:26:29.940 --> 00:26:32.177 And another shout out to Tammy up in the nosebleeds, 00:26:32.177 --> 00:26:36.153 our EHDI coordinator or director of our EDHI program, so. 00:26:40.140 --> 00:26:42.810 So what do we plan to do with the information? 00:26:42.810 --> 00:26:46.050 Well, the registry will abstract the data to develop reports 00:26:46.050 --> 00:26:47.900 about the incidence and occurrence of CMV 00:26:47.900 --> 00:26:50.520 in the Iowa population with special attention 00:26:50.520 --> 00:26:52.890 to potential cCMV cases. 00:26:52.890 --> 00:26:55.230 And then the EDHI program can also use the information 00:26:55.230 --> 00:26:57.060 to follow up on those newborns who received the 00:26:57.060 --> 00:27:00.330 required CMV testing and those that did not. 00:27:00.330 --> 00:27:02.160 And we hope to have some initial outcomes data 00:27:02.160 --> 00:27:05.977 through the surveillance follow up process as we get going. 00:27:05.977 --> 00:27:10.050 I do have some current info, very just basic information. 00:27:10.050 --> 00:27:12.920 So we started this in September, September 1st, 00:27:12.920 --> 00:27:17.760 and we have 54 tests on women ages 15 to 49, 00:27:17.760 --> 00:27:19.290 so reproductive years. 00:27:19.290 --> 00:27:23.130 So 54 women's were tested in September for CMV. 00:27:23.130 --> 00:27:26.910 And then 92 infants less than one year of age 00:27:26.910 --> 00:27:29.400 were tested for CMV in September. 00:27:29.400 --> 00:27:33.870 So we will further dissect that information 00:27:33.870 --> 00:27:36.018 and look to see what those results were 00:27:36.018 --> 00:27:39.360 and if we can match them to refer babies 00:27:39.360 --> 00:27:41.340 that referred on the hearing screening 00:27:41.340 --> 00:27:46.340 and give us some more information, make Lincoln happy, so. 00:27:46.920 --> 00:27:49.230 And again, a plug for poster number 22. 00:27:49.230 --> 00:27:52.620 It's around the corner outside out here on the ramp. 00:27:52.620 --> 00:27:53.673 Thank you. 00:27:53.673 --> 00:27:56.840 (audience applauding) 00:28:01.978 --> 00:28:05.145 (panelist chattering) 00:28:06.210 --> 00:28:07.740 - [Speaker] Good afternoon. 00:28:07.740 --> 00:28:10.870 I do not have any slides to share just the poster 00:28:10.870 --> 00:28:13.810 that is gonna be put up tomorrow. 00:28:13.810 --> 00:28:17.602 And this is, I'm going to give some background 00:28:17.602 --> 00:28:18.963 about the poster. 00:28:19.800 --> 00:28:24.800 Last year, Suresh and Karen convened a working group 00:28:26.280 --> 00:28:31.280 for WHO to do a evidence review on the burden 00:28:31.390 --> 00:28:34.320 of congenital CMV and the opportunities 00:28:34.320 --> 00:28:36.690 for vaccines for low and middle income countries 00:28:36.690 --> 00:28:38.790 for the World Health Organization. 00:28:38.790 --> 00:28:41.895 And they recruited an international panel. 00:28:41.895 --> 00:28:46.895 Tatiana and I, Soren, were also part of that panel. 00:28:46.920 --> 00:28:49.020 The report was just published. 00:28:49.020 --> 00:28:53.700 It's now available online in the journal's vaccines, 00:28:53.700 --> 00:28:55.740 the vaccine value profile for congenital, 00:28:55.740 --> 00:28:58.098 for cytomegalovirus. 00:28:58.098 --> 00:29:02.103 Part of that, we were supposed to assess the burden. 00:29:03.120 --> 00:29:07.200 One of the questions was how many deaths are caused by CMV. 00:29:07.200 --> 00:29:08.550 And reviewing the evidence, 00:29:08.550 --> 00:29:11.760 it's really hard to come up with a good estimate 00:29:11.760 --> 00:29:15.813 of the number of deaths caused by congenital CMV infection. 00:29:16.800 --> 00:29:18.033 There have been a number of estimates 00:29:18.033 --> 00:29:20.460 that have been published over the years. 00:29:20.460 --> 00:29:24.334 It's very common to say five to 10% of infants 00:29:24.334 --> 00:29:26.970 with symptomatic, moderately to severe 00:29:26.970 --> 00:29:31.970 symptomatic congenital CMV die in the neonatal period. 00:29:32.850 --> 00:29:35.880 But the problem, there are multiple problems. 00:29:35.880 --> 00:29:39.690 One is that a lot of studies report no infant deaths, 00:29:39.690 --> 00:29:42.480 a lot of prospective studies. 00:29:42.480 --> 00:29:45.690 And so I decided we need to do a systematic review, 00:29:45.690 --> 00:29:48.600 a comprehensive review of all the published studies. 00:29:48.600 --> 00:29:52.290 And when you review estimates, it's not just the numbers, 00:29:52.290 --> 00:29:55.560 but you have to understand what are the potential threats 00:29:55.560 --> 00:29:57.420 to validity of those estimates. 00:29:57.420 --> 00:29:59.550 What are the potential biases? 00:29:59.550 --> 00:30:04.550 And I use the word bias not as a criticism of studies, 00:30:04.740 --> 00:30:07.477 but to acknowledge the inherent limitations 00:30:07.477 --> 00:30:11.259 of different data sources and study designs 00:30:11.259 --> 00:30:14.820 for coming up with estimates. 00:30:14.820 --> 00:30:18.233 So you can see there's, okay, 00:30:19.320 --> 00:30:21.303 I should mention I have my co-authors. 00:30:22.650 --> 00:30:27.650 So there's Patrick Fleming and Bill Rawlinson. 00:30:27.840 --> 00:30:30.150 So I originally reached out to Dr. Rawlinson 00:30:30.150 --> 00:30:32.883 who is also a member of this working group. 00:30:34.140 --> 00:30:36.570 And she's an expert in perinatal mortality 00:30:36.570 --> 00:30:38.823 and congenital CMV, well known. 00:30:40.890 --> 00:30:45.890 And then recruited Megan Pesch and one of her students, 00:30:47.220 --> 00:30:49.980 or someone she had worked with, Patrick Fleming. 00:30:49.980 --> 00:30:51.780 And we put together this poster. 00:30:51.780 --> 00:30:55.357 Megan is responsible for the two figures that you see, 00:30:56.273 --> 00:30:58.050 and Patrick created the tables. 00:30:58.050 --> 00:31:00.270 There's a manuscript that we're, 00:31:00.270 --> 00:31:01.950 I'm gonna be submitting the revised version 00:31:01.950 --> 00:31:04.020 to the journal next week. 00:31:04.020 --> 00:31:05.790 Hopefully, it'll be published soon 00:31:05.790 --> 00:31:08.700 with tables listing all of the studies. 00:31:08.700 --> 00:31:11.952 But if you look at the top figure, 00:31:11.952 --> 00:31:15.584 you'll see that there's potential biases 00:31:15.584 --> 00:31:20.430 that can cause underestimation of mortality. 00:31:20.430 --> 00:31:24.730 There's left truncation bias, is caused 00:31:24.730 --> 00:31:29.730 when you have the events occur before you begin observing. 00:31:31.080 --> 00:31:33.030 Roughly half of all infant deaths 00:31:33.030 --> 00:31:34.863 occur in the first week of life. 00:31:35.902 --> 00:31:38.610 And generally you do not get a diagnosis 00:31:38.610 --> 00:31:41.640 of congenital CMV until after that. 00:31:41.640 --> 00:31:44.799 So infants who die in the first days after life 00:31:44.799 --> 00:31:48.480 who had congenital CMV infection will not get, 00:31:48.480 --> 00:31:51.630 will not have the diagnosis of congenital CMV 00:31:51.630 --> 00:31:54.240 and those deaths will not be counted. 00:31:54.240 --> 00:31:57.540 And a related bias that's in epidemiology referred 00:31:57.540 --> 00:32:00.270 to immortal time bias 00:32:00.270 --> 00:32:03.014 is when you're comparing the death rate 00:32:03.014 --> 00:32:05.877 in an exposed group such as congenital CMV 00:32:05.877 --> 00:32:09.540 to other infants who do not have that exposure. 00:32:09.540 --> 00:32:11.670 And when you have left truncation bias, 00:32:11.670 --> 00:32:16.670 that causes the relative mortality to be reduced 00:32:17.850 --> 00:32:19.137 in your exposed group. 00:32:19.137 --> 00:32:21.480 And so there's a previous study I was involved with 00:32:21.480 --> 00:32:26.130 on sickle cell disease where the phenomena was infants 00:32:26.130 --> 00:32:31.130 with sickle cell disease had a lower infant mortality rate 00:32:31.530 --> 00:32:34.530 than other infants of the same racial ethnic background, 00:32:34.530 --> 00:32:36.120 specifically African Americans. 00:32:36.120 --> 00:32:40.447 And people would say, "Oh, that's because there's such good 00:32:40.447 --> 00:32:43.807 "clinical care for the infants with sickle cell disease. 00:32:43.807 --> 00:32:45.667 "They're getting such close clinical attention, 00:32:45.667 --> 00:32:48.300 "that's why their infant mortality rate is lower." 00:32:48.300 --> 00:32:51.270 But it turned out, no, it was immortal time bias. 00:32:51.270 --> 00:32:54.120 When we excluded the neonatal deaths, 00:32:54.120 --> 00:32:56.280 the mortality rate for the infants 00:32:56.280 --> 00:32:59.751 with sickle cell anemia was substantially higher. 00:32:59.751 --> 00:33:04.380 So it's important to be aware of left truncation bias 00:33:04.380 --> 00:33:08.073 and immortal time bias when estimating infant mortality. 00:33:09.570 --> 00:33:13.320 The other biases can go in the other direction is you can 00:33:13.320 --> 00:33:16.904 have ascertainment bias and referral bias 00:33:16.904 --> 00:33:20.280 where the infants who are most severely affected 00:33:20.280 --> 00:33:22.680 are the ones who are most likely either to come 00:33:22.680 --> 00:33:26.730 to clinical attention or be reported. 00:33:26.730 --> 00:33:29.370 And so these offsetting biases, 00:33:29.370 --> 00:33:32.310 but bottom line there does appear 00:33:32.310 --> 00:33:35.310 to be an appreciable burden of infant mortality. 00:33:35.310 --> 00:33:37.529 Not just infant mortality. 00:33:37.529 --> 00:33:40.890 Fetal mortality is also elevated. 00:33:40.890 --> 00:33:45.270 And child mortality is not just neonatal or infancy, 00:33:45.270 --> 00:33:47.820 that other, children older ages 00:33:47.820 --> 00:33:50.613 are also at greater risk of dying. 00:33:52.380 --> 00:33:55.019 So this, I don't have any definite answers, 00:33:55.019 --> 00:33:59.430 but this is, so stay tuned for the publication when you can 00:33:59.430 --> 00:34:01.470 see all of the studies we've reviewed. 00:34:01.470 --> 00:34:04.301 And we need additional studies 00:34:04.301 --> 00:34:08.010 that could get better answers for this question. 00:34:08.010 --> 00:34:09.369 Thank you. 00:34:09.369 --> 00:34:12.536 (audience applauding) 00:34:19.620 --> 00:34:20.928 - [Dr. Moriuchi] Good afternoon. 00:34:20.928 --> 00:34:24.600 I'm sorry, I have brain fog, not COVID 00:34:24.600 --> 00:34:28.470 because of the jet lag between here and Japan, 00:34:28.470 --> 00:34:31.680 but I will represent public health achievement 00:34:31.680 --> 00:34:35.910 by the Japanese Congenital CMV Study Group as well as a 00:34:35.910 --> 00:34:39.393 contribution by the Patient Family Association in Japan. 00:34:46.800 --> 00:34:47.853 I declare no COI. 00:34:50.340 --> 00:34:52.290 The TORCH Association or Association 00:34:52.290 --> 00:34:55.110 for Congenital Toxoplasmosis and CMV 00:34:55.110 --> 00:34:57.690 was established in 2012. 00:34:57.690 --> 00:35:02.490 Dr. Tomomi Watanabe is a founder and a representative, 00:35:02.490 --> 00:35:04.983 and I am a co-founder and a counselor. 00:35:06.990 --> 00:35:11.220 My talk will review these issues, and our association 00:35:11.220 --> 00:35:13.953 has been deeply involved in the last three. 00:35:16.590 --> 00:35:20.629 First, a nationwide retrospective study between 2006 00:35:20.629 --> 00:35:25.629 and 2008 identified 140 cases of symptomatic CMV, 00:35:26.477 --> 00:35:30.540 congenital CMV, accounting for zero point, I'm sorry, 00:35:30.540 --> 00:35:33.990 0.0044% of all live births. 00:35:33.990 --> 00:35:38.760 But we are sure that that was an underestimate. 00:35:38.760 --> 00:35:42.303 So we conducted a multicenter prospective study. 00:35:46.230 --> 00:35:47.063 Oh. 00:35:49.140 --> 00:35:52.200 More than 21,000 urine specimens were collected 00:35:52.200 --> 00:35:56.617 into filter paper and tested for CMV DNA by realtime PCR. 00:36:03.335 --> 00:36:08.335 And 66 were confirmed to be congenital CMV, 00:36:08.760 --> 00:36:11.823 accounting for 0.31% of all live births. 00:36:14.190 --> 00:36:19.190 And 30% among them had either typical clinical manifestation 00:36:19.890 --> 00:36:23.160 or abnormal brain imaging or both. 00:36:23.160 --> 00:36:28.020 So we calculated that 95% of symptomatic cases 00:36:28.020 --> 00:36:30.483 had been left undiagnosed in Japan. 00:36:32.100 --> 00:36:35.417 A follow-up study found, revealed that 12% 00:36:35.417 --> 00:36:38.220 of initially asymptomatic children 00:36:38.220 --> 00:36:41.193 had late-onset neurological deficit. 00:36:44.700 --> 00:36:46.970 So this is a summary of our clinical 00:36:46.970 --> 00:36:48.690 and developmental neurological studies. 00:36:48.690 --> 00:36:51.907 0.31% of all live births had congenital CMV. 00:36:55.507 --> 00:36:56.817 And 32% of them had some kind of clinical problems, 00:36:58.980 --> 00:37:02.373 accounting for 0.1% of all live births. 00:37:05.400 --> 00:37:09.153 The next task was development of in vitro diagnostics. 00:37:10.260 --> 00:37:12.930 The Industry Academia Collaboration 00:37:12.930 --> 00:37:16.980 developed the isothermal nucleic acid amplification test 00:37:16.980 --> 00:37:21.497 using the urine specimens collected within 21 days of life. 00:37:23.040 --> 00:37:25.500 And that was approved for the definite diagnosis 00:37:25.500 --> 00:37:30.033 of congenital CMV in 2018 by the Ministry of Health. 00:37:32.100 --> 00:37:35.520 For retrospective diagnosis of congenital CMV, 00:37:35.520 --> 00:37:39.750 we can use either a dried umbilical cord or a Guthrie card, 00:37:39.750 --> 00:37:42.303 and the former is easily available in Japan. 00:37:43.590 --> 00:37:47.220 So the study group offers the diagnosis services 00:37:47.220 --> 00:37:52.140 using dried umbilical cord specimens for children 00:37:52.140 --> 00:37:56.430 beyond 21 days of life suspected of congenital CMV 00:37:56.430 --> 00:37:57.543 free of charge. 00:37:59.490 --> 00:38:04.490 The next task was approval for antiviral treatment. 00:38:06.350 --> 00:38:07.980 In this famous study, 00:38:07.980 --> 00:38:11.373 Valganciclovir started within one month of age. 00:38:14.880 --> 00:38:17.850 We aimed to get approval for Valganciclovir 00:38:17.850 --> 00:38:19.233 by the Ministry of Health. 00:38:23.327 --> 00:38:27.810 And we recruited the infant aged two months or younger. 00:38:27.810 --> 00:38:31.890 And we observed no differences in hearing efficacy 00:38:31.890 --> 00:38:36.630 between the younger, the first months of age and the, 00:38:36.630 --> 00:38:39.333 oh, the older, the second month of age group. 00:38:40.889 --> 00:38:44.400 Sorry for such a big slide, but efficacy was similar 00:38:44.400 --> 00:38:46.980 between the first month age group 00:38:46.980 --> 00:38:48.300 and the second month age group. 00:38:48.300 --> 00:38:51.990 So we are confident that we can start Valganciclovir 00:38:51.990 --> 00:38:56.990 beyond 30 days of life, but by six days of life. 00:38:59.400 --> 00:39:03.903 We are also encouraging the targeted neonatal CMV screening. 00:39:06.450 --> 00:39:09.150 CMV antibody screening among pregnant women 00:39:09.150 --> 00:39:11.080 is not very common, but 00:39:13.080 --> 00:39:16.410 CMV test for babies who could not pass neonatal 00:39:16.410 --> 00:39:18.603 hearing screening is spreading in Japan. 00:39:20.640 --> 00:39:21.473 Oops. 00:39:26.730 --> 00:39:28.680 So our society has been deeply involved 00:39:28.680 --> 00:39:31.443 in these two activities. 00:39:33.256 --> 00:39:35.763 Awareness of congenital CMV is lowest. 00:39:36.720 --> 00:39:37.553 Sorry. 00:39:42.474 --> 00:39:45.960 Awareness of congenital CMV is lowest among those congenital 00:39:45.960 --> 00:39:47.973 and perinatal infections in Japan. 00:39:49.440 --> 00:39:50.273 Oops. 00:39:50.273 --> 00:39:53.640 So we established the TORCH Association for patient 00:39:53.640 --> 00:39:56.283 with congenital toxoplasmosis or CMV. 00:39:59.760 --> 00:40:01.653 I'm sorry, automatically moving. 00:40:02.490 --> 00:40:03.783 In 2012. 00:40:04.890 --> 00:40:07.890 We have been doing a lot of peer support activities 00:40:07.890 --> 00:40:09.063 in various ways. 00:40:10.530 --> 00:40:13.530 We are also doing a lot of awareness raising activities 00:40:13.530 --> 00:40:15.120 through internet or mass media, 00:40:15.120 --> 00:40:17.790 production and distribution of educational brochures, 00:40:17.790 --> 00:40:20.793 booths at academic meetings, and giving lectures. 00:40:25.440 --> 00:40:28.290 These are educational posters for congenital toxoplasmosis 00:40:28.290 --> 00:40:29.123 and CMV. 00:40:29.123 --> 00:40:31.740 This is another educational posters 00:40:31.740 --> 00:40:33.840 illustrating the transmission route 00:40:33.840 --> 00:40:36.217 and how to prevent infection. 00:40:36.217 --> 00:40:39.957 These educational brochures for congenital toxoplasmosis 00:40:39.957 --> 00:40:43.808 and CMV, easy to read and understand. 00:40:43.808 --> 00:40:45.960 (speakers chattering) 00:40:45.960 --> 00:40:47.556 And in this brochure, 00:40:47.556 --> 00:40:51.420 we listed 11 notes important for the prevention 00:40:51.420 --> 00:40:55.083 of the various infection during pregnancy. 00:41:00.361 --> 00:41:03.510 And they are not only for the prevention of CMV infection 00:41:03.510 --> 00:41:06.840 but also for many other maternal and fetal infections. 00:41:06.840 --> 00:41:09.510 We used brain words and the friendly registrations, 00:41:09.510 --> 00:41:10.895 and more detailed information 00:41:10.895 --> 00:41:14.493 is available by reading the QR code. 00:41:15.780 --> 00:41:18.252 And we also published a picture book 00:41:18.252 --> 00:41:21.480 for friendly awareness-raising activities. 00:41:21.480 --> 00:41:25.290 This was originally contributed by Ms. Lisa Sanders, 00:41:25.290 --> 00:41:26.123 of course. 00:41:28.110 --> 00:41:29.113 And the study group also 00:41:29.113 --> 00:41:31.680 started awareness-raising activities. 00:41:31.680 --> 00:41:36.360 Critical management manual were prepared for obstetricians, 00:41:36.360 --> 00:41:38.220 and the educational poster and brochure 00:41:38.220 --> 00:41:39.933 were made for pregnant women. 00:41:41.073 --> 00:41:46.073 This brochure has, oh, okay, detailed the seven preventive 00:41:47.430 --> 00:41:50.943 measures that is specific and easy to understand. 00:41:52.170 --> 00:41:54.480 And finally we have just published a guideline 00:41:54.480 --> 00:41:56.880 for clinical management of congenital CMV. 00:41:56.880 --> 00:41:59.460 Based on the algorithm of clinical management, 00:41:59.460 --> 00:42:01.620 we picked up 20 clinical questions 00:42:01.620 --> 00:42:04.473 and described the answers with evidence levels. 00:42:06.090 --> 00:42:09.213 And they were reviewed by several academic societies. 00:42:10.860 --> 00:42:14.190 And these are the cover and the table of content. 00:42:14.190 --> 00:42:16.680 And one chapter is for patient family association 00:42:16.680 --> 00:42:20.373 and the support written by our representative. 00:42:21.540 --> 00:42:22.713 And this is the text. 00:42:24.327 --> 00:42:28.623 The study group deeply acknowledged our association 00:42:28.623 --> 00:42:31.077 in the preface of the guideline. 00:42:33.115 --> 00:42:34.050 I'm sorry. 00:42:34.050 --> 00:42:35.310 Okay, thank you. 00:42:35.310 --> 00:42:36.150 Thank you for your attention, 00:42:36.150 --> 00:42:38.149 and please visit my poster tomorrow. 00:42:38.149 --> 00:42:41.149 (audience applauds) 00:42:45.086 --> 00:42:47.030 - [Colin] If I use this, would this work? 00:42:49.380 --> 00:42:51.060 Perfect, I'm gonna push this, can you all hear me? 00:42:51.060 --> 00:42:52.710 Perfect, I first wanna recognize. 00:43:00.360 --> 00:43:02.010 Well, either way, all these presenters are basically-- 00:43:02.010 --> 00:43:04.230 - [Speaker] I suggest we should let go. 00:43:13.671 --> 00:43:16.115 - [Colin] All these presenters are doing this basically 00:43:16.115 --> 00:43:18.780 from memory 'cause this screen is kind of flapping around. 00:43:18.780 --> 00:43:21.029 So very cool. 00:43:21.029 --> 00:43:23.713 (laughs) Ah, perfect. 00:43:23.713 --> 00:43:24.930 - Thank you. - Thank you. 00:43:24.930 --> 00:43:26.340 I just wanted to recognize these presenters 00:43:26.340 --> 00:43:27.720 for their excellent jobs today. 00:43:27.720 --> 00:43:30.300 All of these presentations are basically from memory. 00:43:30.300 --> 00:43:31.590 I don't have that great of a mind. 00:43:31.590 --> 00:43:33.030 I need to read some numbers up on mine, 00:43:33.030 --> 00:43:34.230 so I'm gonna stand over here. 00:43:34.230 --> 00:43:36.090 Plus, you don't need to see me in the front of you. 00:43:36.090 --> 00:43:38.070 I also recognize I'm the last person standing 00:43:38.070 --> 00:43:40.890 between you and a raffle, so I'll try and be quick. 00:43:40.890 --> 00:43:43.800 I'm here on behalf of co-authors, 00:43:43.800 --> 00:43:45.420 one of whom is in the room, John Diaz-Decaro. 00:43:45.420 --> 00:43:47.340 So if you see him, go ahead and ask him questions 00:43:47.340 --> 00:43:48.510 about this study as well. 00:43:48.510 --> 00:43:49.567 But I'm here to present a study on the 00:43:49.567 --> 00:43:52.110 "Modeled Seroprevalence of CMV in North America 00:43:52.110 --> 00:43:52.943 by Age and Sex." 00:43:52.943 --> 00:43:55.673 That's for North, that's for the United States and Canada. 00:43:58.050 --> 00:44:00.030 I guess I have to come a little closer. 00:44:00.030 --> 00:44:03.390 There we go, these are our disclosures and acknowledgements. 00:44:03.390 --> 00:44:04.920 I'm not gonna spend much time on this slide 00:44:04.920 --> 00:44:07.140 as I think everyone in the room here is very familiar 00:44:07.140 --> 00:44:08.250 with cCMV. 00:44:08.250 --> 00:44:11.010 However, again, CMV is a common lifelong latent virus. 00:44:11.010 --> 00:44:15.000 It's transmitted during pregnancy from mother to fetus. 00:44:15.000 --> 00:44:16.950 For all the Minnesota epidemiologists in the house, 00:44:16.950 --> 00:44:19.560 I'm going to cite the one in 200 babies 00:44:19.560 --> 00:44:21.000 are born in the United States and Canada. 00:44:21.000 --> 00:44:24.270 Although your exciting data are actually kind of maybe 00:44:24.270 --> 00:44:26.220 leading to question that now. 00:44:26.220 --> 00:44:28.260 Signs and symptoms are present at birth, however, 00:44:28.260 --> 00:44:31.290 they might not also appear until a couple years later 00:44:31.290 --> 00:44:32.460 or several years later. 00:44:32.460 --> 00:44:34.860 And they are multi-system in nature. 00:44:34.860 --> 00:44:37.710 And then we also know that there are higher rates of cCMV 00:44:37.710 --> 00:44:41.160 that are associated with higher maternal seroprevalence. 00:44:41.160 --> 00:44:43.650 As additional context to then this analysis, 00:44:43.650 --> 00:44:46.020 we know the global CMV seroprevalence ranges 00:44:46.020 --> 00:44:48.300 from 45% to 100%. 00:44:48.300 --> 00:44:49.620 It's a rather broad range. 00:44:49.620 --> 00:44:51.060 However, when the question comes 00:44:51.060 --> 00:44:51.990 what's the CMV seroprevalence 00:44:51.990 --> 00:44:54.570 for a specific geographic setting, 00:44:54.570 --> 00:44:57.690 we often turn to then population-level data. 00:44:57.690 --> 00:45:00.900 Those data need to be contemporary as well as comprehensive. 00:45:00.900 --> 00:45:03.180 And however, that's also problematic 00:45:03.180 --> 00:45:05.330 for many geographic settings in the United States. 00:45:05.330 --> 00:45:07.170 In this analysis, for example, 00:45:07.170 --> 00:45:10.050 data were reported relatively recently for children. 00:45:10.050 --> 00:45:13.440 However, in adults the most recent sampling was in 2004. 00:45:13.440 --> 00:45:17.370 In Canada, the sampling is even more distant, 00:45:17.370 --> 00:45:19.080 and it's also sparser as well. 00:45:19.080 --> 00:45:21.510 So we conducted a systematic literature review, 00:45:21.510 --> 00:45:24.030 and we developed a mathematical model to extract data 00:45:24.030 --> 00:45:28.200 and estimate CMV seroprevalence for a broad age category. 00:45:28.200 --> 00:45:30.000 The spectrum of age from one to 89 years 00:45:30.000 --> 00:45:31.380 in the United States, for example. 00:45:31.380 --> 00:45:32.823 By two years age groups. 00:45:34.620 --> 00:45:36.133 We conducted our lit search in PubMed 00:45:36.133 --> 00:45:38.160 and Embase electronic databases. 00:45:38.160 --> 00:45:40.080 We restricted our data to publications 00:45:40.080 --> 00:45:42.270 that were published in 2005 to 2022 00:45:42.270 --> 00:45:43.560 when the search was conducted. 00:45:43.560 --> 00:45:45.060 We restricted to the English language. 00:45:45.060 --> 00:45:47.580 In the United States, we identified seven studies 00:45:47.580 --> 00:45:50.116 all of whom examined data from NHANES, 00:45:50.116 --> 00:45:52.408 which is a representative population sample 00:45:52.408 --> 00:45:55.695 of males and females, ages one to 89 years. 00:45:55.695 --> 00:45:59.070 As I said, the last year of sampling for adults was in 2004 00:45:59.070 --> 00:46:03.120 in this dataset in these publications in 2024 children. 00:46:03.120 --> 00:46:05.340 In Canada, we identified three publications. 00:46:05.340 --> 00:46:07.350 However, they were all based in academic hospitals 00:46:07.350 --> 00:46:10.860 among pregnant women, ages 17 to 47 years. 00:46:10.860 --> 00:46:13.503 And the most recent sampling year was in 2013. 00:46:15.780 --> 00:46:18.450 Another slide about our methods real quick. 00:46:18.450 --> 00:46:20.880 We used a random effects meta regression model to account 00:46:20.880 --> 00:46:22.440 for the between study heterogeneity 00:46:22.440 --> 00:46:24.630 that we identified in our search results. 00:46:24.630 --> 00:46:27.390 I'm gonna talk about Canada a little bit more specifically. 00:46:27.390 --> 00:46:29.430 Given the sparseness of the data in the three studies 00:46:29.430 --> 00:46:31.470 only in pregnant women, we had to do two levels 00:46:31.470 --> 00:46:33.870 of extrapolation to go from pregnant women 00:46:33.870 --> 00:46:36.060 to then the general population of females. 00:46:36.060 --> 00:46:38.100 So we used data from the UK, France, 00:46:38.100 --> 00:46:40.800 and Japan to make that estimation. 00:46:40.800 --> 00:46:42.450 And then we also then had to extrapolate 00:46:42.450 --> 00:46:44.430 from the general population of females 00:46:44.430 --> 00:46:46.415 to then the general population of males to then get 00:46:46.415 --> 00:46:48.360 that estimate that we were after. 00:46:48.360 --> 00:46:50.070 And that was used on NHANES data 00:46:50.070 --> 00:46:52.500 for the sex-specific differences that we observed, 00:46:52.500 --> 00:46:55.230 which was approximately 10%. 00:46:55.230 --> 00:46:56.670 We then modeled our seroprevalence 00:46:56.670 --> 00:46:57.960 for two years age intervals. 00:46:57.960 --> 00:47:00.390 And I will get to those right now. 00:47:00.390 --> 00:47:03.090 So here in this slide and in the following slides, 00:47:03.090 --> 00:47:05.610 females are represented in red, males in blue. 00:47:05.610 --> 00:47:07.170 Observed data from publications 00:47:07.170 --> 00:47:09.184 are in the lighter circled dots. 00:47:09.184 --> 00:47:12.948 The more intense darker dockets are the model estimates. 00:47:12.948 --> 00:47:16.140 As we can see on both the female and male charts there, 00:47:16.140 --> 00:47:18.600 we see that the overlap between the observed 00:47:18.600 --> 00:47:20.760 and the fitted data are actually quite tight. 00:47:20.760 --> 00:47:23.100 The confidence intervals in the gray 00:47:23.100 --> 00:47:25.500 are actually quite narrow, indicating relatively good 00:47:25.500 --> 00:47:27.813 agreement and fit for our data and our model. 00:47:29.551 --> 00:47:30.873 Oh, too far? 00:47:31.860 --> 00:47:33.030 Still too far. 00:47:33.030 --> 00:47:34.200 One more time, there we go. 00:47:34.200 --> 00:47:36.150 I'm so sorry, it's the end of the day. 00:47:36.150 --> 00:47:38.340 This is our slide then demonstrating 00:47:38.340 --> 00:47:39.990 that the estimated CMV seroprevalence 00:47:39.990 --> 00:47:42.000 for males and females in the United States. 00:47:42.000 --> 00:47:43.920 We see a few trends here pulling out of the data. 00:47:43.920 --> 00:47:46.860 One we see rather expectedly an increase 00:47:46.860 --> 00:47:48.816 in seroprevalence with increasing age. 00:47:48.816 --> 00:47:51.210 We also then see a gender disparity where 00:47:51.210 --> 00:47:52.898 at every age the prevalence of CMV 00:47:52.898 --> 00:47:54.990 is greater in females than in males. 00:47:54.990 --> 00:47:57.390 And then we also see a slight increase in this disparity 00:47:57.390 --> 00:47:59.520 then as age increases. 00:47:59.520 --> 00:48:01.590 We look at then on the table on the right here. 00:48:01.590 --> 00:48:03.620 When we're looking at then the seroprevalence 00:48:03.620 --> 00:48:05.520 as women enter their reproductive years, 00:48:05.520 --> 00:48:08.130 we see that by 20 to 22 years of age 00:48:08.130 --> 00:48:11.490 women already have a CMV seroprevalence of 50.3%. 00:48:11.490 --> 00:48:14.700 Males then at 42.8%. 00:48:14.700 --> 00:48:16.380 Moving to Canada, a similar graph, 00:48:16.380 --> 00:48:17.370 however, there's less data. 00:48:17.370 --> 00:48:19.230 You'll also notice the age range at the bottom 00:48:19.230 --> 00:48:21.240 on the X-axis is also quite short. 00:48:21.240 --> 00:48:24.720 Again, it was in pregnant women 17 to 47 years of age. 00:48:24.720 --> 00:48:25.788 However, we fit our model. 00:48:25.788 --> 00:48:29.490 The fit and the overlap is a little less tight. 00:48:29.490 --> 00:48:31.680 There is a little more wobble in these data points. 00:48:31.680 --> 00:48:34.320 The confidence interval is actually quite wide. 00:48:34.320 --> 00:48:38.680 So this represents a difficulty in modeling these data 00:48:39.900 --> 00:48:41.490 with a sparseness of the evidence 00:48:41.490 --> 00:48:42.940 that we are able to identify. 00:48:43.800 --> 00:48:45.150 However, looking at the trend, again, 00:48:45.150 --> 00:48:46.590 we do see that same trend, 00:48:46.590 --> 00:48:49.027 increasing CMV seroprevalence with increasing age. 00:48:49.027 --> 00:48:51.210 We see that a gender disparity as well. 00:48:51.210 --> 00:48:52.470 But that's by manufacturer. 00:48:52.470 --> 00:48:53.970 That's an artifact of our methods. 00:48:53.970 --> 00:48:57.450 Again, that was an extrapolation from the sex difference 00:48:57.450 --> 00:48:59.190 between female general population 00:48:59.190 --> 00:49:01.380 to male general population, and its 10%. 00:49:01.380 --> 00:49:03.480 However, when we're looking at the burden in females then 00:49:03.480 --> 00:49:05.756 as they're entering their reproductive ages 18 to 20 years, 00:49:05.756 --> 00:49:09.923 the prevalence of CMV is already 23.7%. 00:49:09.923 --> 00:49:11.640 This is my last slide, I promise, 00:49:11.640 --> 00:49:13.553 and I think I can get through it pretty quick. 00:49:13.553 --> 00:49:15.990 First, we had three kind of important 00:49:15.990 --> 00:49:17.880 contributions from this study. 00:49:17.880 --> 00:49:20.250 The first being that we updated the estimate 00:49:20.250 --> 00:49:23.038 of CMV seroprevalence for the United States for adults. 00:49:23.038 --> 00:49:26.400 That hadn't been updated since 2004, for example. 00:49:26.400 --> 00:49:28.260 In Canada, this is a first effort. 00:49:28.260 --> 00:49:30.724 However, you know, limited the methods may be 00:49:30.724 --> 00:49:32.730 for estimating CMV seroprevalence 00:49:32.730 --> 00:49:35.490 in the female and male general population as well. 00:49:35.490 --> 00:49:37.050 We identified clear differences 00:49:37.050 --> 00:49:39.030 between the Canadian and the United States data, 00:49:39.030 --> 00:49:40.530 both in terms of the number of studies 00:49:40.530 --> 00:49:42.360 as well as then trends. 00:49:42.360 --> 00:49:44.604 However, we did identify substantial seroprevalence burden 00:49:44.604 --> 00:49:47.760 in females in particular in both the United States 00:49:47.760 --> 00:49:49.139 and the Canadian setting. 00:49:49.139 --> 00:49:52.410 So much though that by reproductive age half 00:49:52.410 --> 00:49:54.099 of the female population in the United States 00:49:54.099 --> 00:49:57.630 and three-quarters of the female population in Canada 00:49:57.630 --> 00:49:58.980 are immunologically naive 00:49:58.980 --> 00:50:00.570 as they enter the reproductive years, 00:50:00.570 --> 00:50:02.700 therefore at risk of primary seroconversion 00:50:02.700 --> 00:50:04.260 during pregnancy. 00:50:04.260 --> 00:50:08.130 Again, I think this study also really underscores the need 00:50:08.130 --> 00:50:11.010 for robust national epidemiologic data, 00:50:11.010 --> 00:50:12.510 and that'll better inform our understanding 00:50:12.510 --> 00:50:14.190 of CMV seroprevalence. 00:50:14.190 --> 00:50:16.110 With that, I thank you very much for your attention, 00:50:16.110 --> 00:50:17.951 and I look forward to any questions. 00:50:17.951 --> 00:50:20.951 (audience applauds) 00:50:24.389 --> 00:50:26.890 - [Moderator] Okay, it's easier if you come down here 00:50:26.890 --> 00:50:29.280 for questions, but if you need me to, 00:50:29.280 --> 00:50:31.410 I will run the mic to you. 00:50:31.410 --> 00:50:33.570 Any questions so far? 00:50:33.570 --> 00:50:34.403 All right. 00:50:39.090 --> 00:50:42.090 - [Audience Member] Thanks, I really enjoyed all the talks. 00:50:42.090 --> 00:50:44.904 First, I just, while I remember, Colin, 00:50:44.904 --> 00:50:49.904 we have population-based data in Canada, in infants, 00:50:50.844 --> 00:50:55.844 so I can send you 13% at three months and 20% at one year. 00:50:56.850 --> 00:50:58.290 Yeah. 00:50:58.290 --> 00:51:02.130 Scott, a very nice presentation. 00:51:02.130 --> 00:51:07.130 My question is, do any of the studies that you found account 00:51:09.000 --> 00:51:11.700 for a termination of pregnancies 00:51:11.700 --> 00:51:16.700 because of severe ultrasound anomalies? 00:51:18.150 --> 00:51:19.590 Do we know how often that happens 00:51:19.590 --> 00:51:21.140 or how do you account for that? 00:51:22.134 --> 00:51:24.390 - A number of the European studies 00:51:24.390 --> 00:51:28.424 do report the termination of pregnancy 00:51:28.424 --> 00:51:33.093 due to positive CMV and abnormalities. 00:51:34.471 --> 00:51:37.260 We don't have many infant mortality estimates 00:51:37.260 --> 00:51:39.123 from those European studies. 00:51:40.560 --> 00:51:44.040 There is, that is one of the limitations. 00:51:44.040 --> 00:51:48.210 I don't think there are many terminations 00:51:48.210 --> 00:51:52.890 in this country due to CMV-caused abnormalities. 00:51:52.890 --> 00:51:56.223 But if anyone has information on that, I would love to know. 00:52:01.530 --> 00:52:02.880 - [Audience Member] Hi, thank you all for your talks. 00:52:02.880 --> 00:52:04.520 My question is for Dr. Page. 00:52:04.520 --> 00:52:06.870 First, congratulations on all of your successes. 00:52:06.870 --> 00:52:09.090 It sounds like it's gonna be a really exciting 00:52:09.090 --> 00:52:10.560 program for you guys. 00:52:10.560 --> 00:52:11.790 My question is two parts. 00:52:11.790 --> 00:52:14.880 Recognizing that Arizona has a much larger 00:52:14.880 --> 00:52:17.610 Indigenous population than some of the other states, 00:52:17.610 --> 00:52:20.790 one, will you or did you collect 00:52:20.790 --> 00:52:23.010 specific tribal affiliation data? 00:52:23.010 --> 00:52:26.010 And then also recognizing that many Indigenous persons 00:52:26.010 --> 00:52:28.752 who live on tribal lands often have to be med-evaced out 00:52:28.752 --> 00:52:31.470 for higher levels of care, such as the NICU, 00:52:31.470 --> 00:52:33.810 will you collect residency data 00:52:33.810 --> 00:52:36.450 to better inform those potential disparities? 00:52:36.450 --> 00:52:37.680 - Oh, these are great questions. 00:52:37.680 --> 00:52:40.260 So the, yes, I mean, partly we think 00:52:40.260 --> 00:52:43.170 that we have a really unique population in Arizona, 00:52:43.170 --> 00:52:47.370 and so there's a great deal of value in obtaining the kind 00:52:47.370 --> 00:52:49.800 of data that we're looking for because we think we can't 00:52:49.800 --> 00:52:51.480 just extrapolate from other states 00:52:51.480 --> 00:52:54.330 and feel like we're getting the right answer. 00:52:54.330 --> 00:52:56.697 We did not gather tribal affiliation. 00:52:56.697 --> 00:53:01.110 So what we hope that we could do is take race data 00:53:01.110 --> 00:53:03.810 and geographic data and be able to put those together. 00:53:03.810 --> 00:53:05.003 But one of the questions that came up as part 00:53:05.003 --> 00:53:08.310 of the project is about birthing center, for example. 00:53:08.310 --> 00:53:12.417 And so if you're, we have to collect the home zip code 00:53:12.417 --> 00:53:14.100 as well as the birthing zip code. 00:53:14.100 --> 00:53:16.080 If we only use birthing zip code, 00:53:16.080 --> 00:53:18.210 then all of these patients were born in Downtown Phoenix 00:53:18.210 --> 00:53:20.430 and it doesn't tell us much about where they come from. 00:53:20.430 --> 00:53:23.130 So we're hoping to use their home information 00:53:23.130 --> 00:53:24.600 to give us geographic data. 00:53:24.600 --> 00:53:25.704 Again, if you saw these numbers, 00:53:25.704 --> 00:53:28.410 we had a surprisingly small number of Native Americans 00:53:28.410 --> 00:53:30.810 on this study, given our population in the state. 00:53:30.810 --> 00:53:32.010 And again that, we have, 00:53:32.010 --> 00:53:33.900 this is a very limited sample from what we had. 00:53:33.900 --> 00:53:36.330 We know that once we see that we'll have a much wider number 00:53:36.330 --> 00:53:38.100 and a broader area. 00:53:38.100 --> 00:53:38.977 That answer your question? - Yes, thank you. 00:53:38.977 --> 00:53:40.627 - Thank you for bringing that up. 00:53:43.747 --> 00:53:46.249 - [Audience Member] For Dr. Moriuchi. 00:53:46.249 --> 00:53:48.690 Thank you for coming to the meeting. 00:53:48.690 --> 00:53:51.930 We're honored that you came here all this distance. 00:53:51.930 --> 00:53:55.500 I wanted to ask you, I mean, and it's tremendous work 00:53:55.500 --> 00:53:57.531 that you've done with this organization. 00:53:57.531 --> 00:54:00.420 I wanted to ask you about the seroprevalence 00:54:00.420 --> 00:54:03.960 of CMV antibodies in women of reproductive age. 00:54:03.960 --> 00:54:07.470 I may have missed it, but is it your sense 00:54:07.470 --> 00:54:09.480 that most congenital CMV infections 00:54:09.480 --> 00:54:13.530 are in women with preconception immunity in Japan? 00:54:13.530 --> 00:54:15.989 Or do you have any data on that? 00:54:15.989 --> 00:54:19.773 Are they primary infections or reactivation reinfections? 00:54:20.910 --> 00:54:22.857 - So first of all, the seroprevalence among, 00:54:22.857 --> 00:54:25.770 CMV seroprevalence among pregnant women 00:54:25.770 --> 00:54:28.890 is currently 60 to 70%. 00:54:28.890 --> 00:54:30.870 But several decades ago, 00:54:30.870 --> 00:54:34.200 the seroprevalence was more than 90%. 00:54:34.200 --> 00:54:36.540 So it has been decreasing. 00:54:36.540 --> 00:54:40.387 And you know, 00:54:40.387 --> 00:54:45.260 the incidence of congenital CMV in Japan is 0.31%. 00:54:45.260 --> 00:54:49.101 So not very high, but we are not sure, you know, 00:54:49.101 --> 00:54:53.550 if it's going up or down, or steady. 00:54:53.550 --> 00:54:55.080 - [Audience Member] And do you know if the infections 00:54:55.080 --> 00:54:57.470 are in seropositive women, seronegative women. 00:54:57.470 --> 00:54:58.570 Do you have some data? - Yeah. 00:54:58.570 --> 00:55:00.960 - Probably half and half. - Okay. 00:55:00.960 --> 00:55:02.347 - Yeah. - Thank you. 00:55:03.330 --> 00:55:06.330 - [Audience Member] Another question for my Japanese friend. 00:55:07.230 --> 00:55:09.570 What's this, what's the lay of the land 00:55:09.570 --> 00:55:11.909 with respect to parent advocacy groups in Japan? 00:55:11.909 --> 00:55:13.851 I don't know what's happening there. 00:55:13.851 --> 00:55:15.831 Are you working with? 00:55:15.831 --> 00:55:19.380 Like what, yeah, what's the lay of the land, and who's, 00:55:19.380 --> 00:55:21.960 are you having success with the parents? 00:55:21.960 --> 00:55:24.330 - Excuse me, could you please repeat again? 00:55:24.330 --> 00:55:26.383 - [Audience Member] Parent advocacy groups, so. 00:55:26.383 --> 00:55:27.720 - Yes. 00:55:27.720 --> 00:55:28.620 - [Audience Member] Are you working with any 00:55:28.620 --> 00:55:29.580 parent advocacy groups? 00:55:29.580 --> 00:55:31.200 Are they lobbying for change? 00:55:31.200 --> 00:55:33.450 Are there, is anyone working kind of doing 00:55:33.450 --> 00:55:35.154 what I'm doing out there? 00:55:35.154 --> 00:55:37.830 - Well, our association, the TORCH Association, 00:55:37.830 --> 00:55:41.130 has been working together with that study group, 00:55:41.130 --> 00:55:46.130 but we are not doing very political activities, 00:55:47.340 --> 00:55:51.060 but we have some negotiation with the statement 00:55:51.060 --> 00:55:56.060 and also some, the local government, the officers. 00:55:57.330 --> 00:56:00.720 And so our major activities, 00:56:00.720 --> 00:56:03.810 awareness-raising activities and peer support. 00:56:03.810 --> 00:56:08.810 However, we would like to, you know, 00:56:08.940 --> 00:56:11.160 appeal to the local government 00:56:11.160 --> 00:56:13.083 and also the Ministry of Health. 00:56:16.530 --> 00:56:18.018 - [Audience Member] Hi, I have, I also have a question 00:56:18.018 --> 00:56:19.113 for you, sir. 00:56:20.452 --> 00:56:23.730 I noticed when you, you were talking 00:56:23.730 --> 00:56:28.290 about the umbilical cord, and so the women in Japan, 00:56:28.290 --> 00:56:32.520 they bring that home to their family after the birth, 00:56:32.520 --> 00:56:33.780 is that correct? 00:56:33.780 --> 00:56:34.860 - Excuse me. 00:56:34.860 --> 00:56:37.770 - [Audience Member] The women bring their umbilical cord 00:56:37.770 --> 00:56:42.770 home after the birth, is that correct, what? 00:56:43.380 --> 00:56:48.270 - Yes, we keep the umbilical cord as a symbol 00:56:48.270 --> 00:56:52.230 of mother to child bonding, so it is always available. 00:56:52.230 --> 00:56:57.230 So, and we have two advantage for dried umbilical code. 00:56:57.900 --> 00:57:02.160 So, first of all, the detection rate is higher 00:57:02.160 --> 00:57:06.240 when we use the umbilical cord than the Guthrie card. 00:57:06.240 --> 00:57:10.740 And the second advantage is the, as I said, 00:57:10.740 --> 00:57:13.351 it is always available in Japan. 00:57:13.351 --> 00:57:16.110 - [Audience Member] And then how long of course 00:57:16.110 --> 00:57:17.973 could that be good for? 00:57:19.980 --> 00:57:23.850 - Well, a year ago I have detected, 00:57:23.850 --> 00:57:28.850 I could detect CMV DNA from the 23-year-old girl. 00:57:29.460 --> 00:57:30.660 I mean, the women. 00:57:30.660 --> 00:57:34.866 So we can detect the CMV DNA even after decades. 00:57:34.866 --> 00:57:37.080 - [Audience Member] That's cool. 00:57:37.080 --> 00:57:38.293 - [Audience Member] That's unreal. 00:57:38.293 --> 00:57:42.660 (audience members chattering) 00:57:42.660 --> 00:57:44.010 - [Audience Member] One question in regards 00:57:44.010 --> 00:57:47.133 to the National CMV month. 00:57:48.480 --> 00:57:51.870 I thought your work was very interesting. 00:57:51.870 --> 00:57:55.720 Do you think that it would be better to rename it 00:57:56.790 --> 00:58:00.660 with an extra small C in front of CMV 00:58:00.660 --> 00:58:05.660 or is my interpretation that the advocacy month 00:58:07.530 --> 00:58:10.323 is not for congenital CMV? 00:58:11.310 --> 00:58:13.460 - That's a great question and I, oh, sorry. 00:58:15.835 --> 00:58:17.550 Got it, I think. 00:58:17.550 --> 00:58:18.383 It's a great question. 00:58:18.383 --> 00:58:20.970 I had this, I mean I'm, as I said, I'm new to the area so, 00:58:20.970 --> 00:58:22.020 or to this field. 00:58:22.020 --> 00:58:24.000 So I have, would really defer to people 00:58:24.000 --> 00:58:25.080 who know much more than me. 00:58:25.080 --> 00:58:29.280 But I was quite confused, like because the mandate 00:58:29.280 --> 00:58:32.880 from the Senate explicitly is talking about congenital CMV. 00:58:32.880 --> 00:58:35.970 The CDC is explicitly talking about congenital CMV. 00:58:35.970 --> 00:58:37.080 And then when I'm reading tweets, 00:58:37.080 --> 00:58:38.820 which is how I learned all of you, 00:58:38.820 --> 00:58:42.780 which was pretty cool, I was just lost as 00:58:42.780 --> 00:58:45.120 to why we're not talking about congenital CMV. 00:58:45.120 --> 00:58:47.565 So if that's the goal, I'm with you. 00:58:47.565 --> 00:58:50.370 We should be talking about congenital CMV. 00:58:50.370 --> 00:58:51.570 Thank you. - Thank you. 00:58:55.740 --> 00:58:57.973 (audience members chattering) 00:58:57.973 --> 00:58:59.250 - [Audience Member] I have another question. 00:58:59.250 --> 00:59:04.250 Sunil, do you think, or do you know 00:59:04.410 --> 00:59:06.180 what those false positives were from? 00:59:06.180 --> 00:59:11.180 Is it something specific to the Alethea assay or? 00:59:11.460 --> 00:59:15.748 - So, I don't know, that's the only assay that we have used. 00:59:15.748 --> 00:59:20.070 There seems to be two possibilities. 00:59:20.070 --> 00:59:23.310 Surface contamination during the few weeks 00:59:23.310 --> 00:59:26.280 that it occurred in March, which has cleaned up. 00:59:26.280 --> 00:59:30.480 But we do continue to see some indeterminants, 00:59:30.480 --> 00:59:32.460 even a false positive even after that. 00:59:32.460 --> 00:59:35.280 And the other, from my molecular lab director, 00:59:35.280 --> 00:59:37.950 is the setting, and this is like completely 00:59:37.950 --> 00:59:40.920 out of my league, the setting of the software setting 00:59:40.920 --> 00:59:42.300 to make it more sensitive. 00:59:42.300 --> 00:59:45.540 So the software settings is all I can say 00:59:45.540 --> 00:59:46.710 is what he told me. 00:59:46.710 --> 00:59:49.050 So I don't know the technical details of that. 00:59:49.050 --> 00:59:50.970 And those need to be tweaked. 00:59:50.970 --> 00:59:52.650 - [Audience Member] Because I think there was a paper 00:59:52.650 --> 00:59:55.980 just published showing like unexpected levels 00:59:55.980 --> 00:59:57.990 of false positives with that assay. 00:59:57.990 --> 00:59:58.823 - Oh, okay. 00:59:58.823 --> 00:59:59.763 So thank you. 01:00:03.330 --> 01:00:05.070 - [Audience Member] This is more of a shout out 01:00:05.070 --> 01:00:09.843 not a question for the Arizona gentleman. 01:00:10.920 --> 01:00:14.520 No, so when I saw you're from Phoenix Children's, 01:00:14.520 --> 01:00:17.061 my best friend from college actually works at the lab, 01:00:17.061 --> 01:00:19.200 and I asked him like, "Well, are you testing for CMV?" 01:00:19.200 --> 01:00:20.790 She said, "Yes." 01:00:20.790 --> 01:00:23.430 They have plenty of cases and she works third shift. 01:00:23.430 --> 01:00:24.330 But I thought that was pretty cool 01:00:24.330 --> 01:00:25.770 that the connection was there, 01:00:25.770 --> 01:00:28.980 and she's doing the work for you and all that. 01:00:28.980 --> 01:00:29.940 So I thought that was pretty cool. 01:00:29.940 --> 01:00:30.773 That's all. 01:00:30.773 --> 01:00:32.100 - We better talk about her so we find out 01:00:32.100 --> 01:00:33.502 where she's running those. 01:00:33.502 --> 01:00:37.110 - [Audience Member] Oh, I would love to have a conversation. 01:00:37.110 --> 01:00:38.874 We could even FaceTime. 01:00:38.874 --> 01:00:41.050 (audience members laugh) 01:00:41.050 --> 01:00:44.190 - [Moderator] Okay, so remember that all of these presenters 01:00:44.190 --> 01:00:48.630 will be giving poster presentations during lunch tomorrow. 01:00:48.630 --> 01:00:50.460 So, you have one more question? 01:00:50.460 --> 01:00:52.230 - One more question. - One more question, okay. 01:00:52.230 --> 01:00:54.241 I actually have a question too, darn it. 01:00:54.241 --> 01:00:55.200 (audience members laughing) 01:00:55.200 --> 01:00:56.033 - [Audience Member] Hi, and thank you all 01:00:56.033 --> 01:00:56.880 for your presentations. 01:00:56.880 --> 01:00:58.650 Really, really excellent. 01:00:58.650 --> 01:01:01.290 Tracy, I have a question for you actually. 01:01:01.290 --> 01:01:03.240 So in terms of the social media tracking, 01:01:03.240 --> 01:01:05.580 have you considered LinkedIn, 01:01:05.580 --> 01:01:08.700 not just because of the connection with the providers, 01:01:08.700 --> 01:01:11.434 but also for tracking the sustained awareness 01:01:11.434 --> 01:01:13.710 that happens amongst that community? 01:01:13.710 --> 01:01:14.543 - I think you're absolutely right. 01:01:14.543 --> 01:01:16.050 I mean, I think that's where we're gonna find 01:01:16.050 --> 01:01:17.670 more providers who are talking about it. 01:01:17.670 --> 01:01:19.620 I'm just at capacity 'cause it's me, 01:01:19.620 --> 01:01:22.770 but if anybody wants to help, I would love help. 01:01:22.770 --> 01:01:25.200 And then we have another CMV awareness month coming up. 01:01:25.200 --> 01:01:27.193 So that would be fabulous, I agree. 01:01:27.193 --> 01:01:28.950 That is where providers are. 01:01:28.950 --> 01:01:30.250 - Thank you. - Thank you. 01:01:31.787 --> 01:01:35.850 - [Audience Member] Okay, so my question is for Scott. 01:01:35.850 --> 01:01:39.557 Have you thought about looking at the Fetal 01:01:39.557 --> 01:01:42.420 and Infant Mortality Review? 01:01:42.420 --> 01:01:46.464 Is there any information around CMV in that review? 01:01:46.464 --> 01:01:47.733 - I have not. 01:01:51.000 --> 01:01:51.833 Yeah. 01:01:52.710 --> 01:01:55.020 The problem with the death records, 01:01:55.020 --> 01:01:57.990 CMV is not very often recorded, 01:01:57.990 --> 01:01:59.940 for the reasons I already mentioned. 01:01:59.940 --> 01:02:00.773 - [Audience Member] Mm-hm, okay. 01:02:00.773 --> 01:02:03.540 - And in terms of fetal mortality, 01:02:03.540 --> 01:02:05.220 there have been a number of published studies. 01:02:05.220 --> 01:02:08.490 Dr. Rawlinson published some of the earliest ones, 01:02:08.490 --> 01:02:11.550 which have documented, when you do the pathology, 01:02:11.550 --> 01:02:16.550 you'll find CMV infections very common in fetal deaths, 01:02:18.360 --> 01:02:21.988 but they're not routinely tested for CMV. 01:02:21.988 --> 01:02:23.160 - [Audience Member] Okay. 01:02:23.160 --> 01:02:24.540 Okay, thank you so much. 01:02:24.540 --> 01:02:26.730 And Colin, I have one little question for you. 01:02:26.730 --> 01:02:28.200 I'm hoping it's little. 01:02:28.200 --> 01:02:31.530 So just what is your hypothesis 01:02:31.530 --> 01:02:35.677 around the gender differences of seroprevalence? 01:02:35.677 --> 01:02:37.710 - Well, so for Canada it was manufactured, right, 01:02:37.710 --> 01:02:38.543 because there was no data. 01:02:38.543 --> 01:02:41.047 So we had to make that extrapolation, that assumption. 01:02:41.047 --> 01:02:44.463 For the United States, I'm not entirely sure other than, 01:02:45.360 --> 01:02:47.580 you know, potential increased contact 01:02:47.580 --> 01:02:50.569 between mothers and potentially with children. 01:02:50.569 --> 01:02:55.569 I think that might be maybe one of the most logical tests. 01:02:55.590 --> 01:02:57.450 We can't test it in our data unfortunately, 01:02:57.450 --> 01:02:59.043 but other studies will. 01:03:00.760 --> 01:03:02.890 - Okay, let's give them a round of applause. 01:03:02.890 --> 01:03:06.057 (audience applauding)