Real-world Effectiveness and Causal Mediation Study of BNT162b2 on Long COVID Risks in Children and Adolescents (preprint)

Research Square

Racial/ethnic differences are associated with the potential symptoms and conditions of post-acute sequelae SARS-CoV-2 infection (PASC) in adults. These differences may exist among children and warrant further exploration. We conducted a retrospective cohort study for children and adolescents under the age of 21 from the thirteen institutions in the RECOVER Initiative. The cohort is 225,723 patients with SARS-CoV-2 infection or COVID-19 diagnosis and 677,448 patients without SARS-CoV-2 infection or COVID-19 diagnosis between March 2020 and October 2022. The study compared minor racial/ethnic groups to Non-Hispanic White (NHW) individuals, stratified by severity during the acute phase of COVID-19. Within the severe group, Asian American/Pacific Islanders (AAPI) had a higher prevalence of fever/chills and respiratory symptoms, Hispanic patients showed greater hair loss prevalence in severe COVID-19 cases, while Non-Hispanic Black (NHB) patients had fewer skin symptoms in comparison to NHW patients. Within the non-severe group, AAPI patients had increased POTS/dysautonomia and respiratory symptoms, and NHB patients showed more cognitive symptoms than NHW patients. In conclusion, racial/ethnic differences related to COVID-19 exist among specific PASC symptoms and conditions in pediatrics, and these differences are associated with the severity of illness during acute COVID-19.

medRxiv

INTRODUCTION Alzheimer's Disease (AD) are often misclassified in electronic health records (EHRs) when relying solely on diagnostic codes. This study aims to develop a more accurate, computable phenotype (CP) for identifying AD patients by using both structured and unstructured EHR data. METHODS We used EHRs from the University of Florida Health (UF Health) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UT Health) and the University of Minnesota (UMN). RESULTS Our best-performing CP is "patient has at least 2 AD diagnoses and AD-related keywords" with an F1-score of 0.817 at UF, and 0.961 and 0.623 at UT Health and UMN, respectively. DISCUSSION We developed and validated rule-based CPs for AD identification with good performance, crucial for studies that aim to use real-world data like EHRs.

Annals of Internal Medicine

Background The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant’s emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited. Objective To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents. Design Comparative effectiveness research accounting for underreported vaccination in 3 study cohorts: adolescents (12 to 20 years) during the Delta phase and children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. Setting A national collaboration of pediatric health systems (PEDSnet). Participants 77 392 …

Research Square

Racial/ethnic differences are associated with the potential symptoms and conditions of post-acute sequelae SARS-CoV-2 infection (PASC) in adults. These differences may exist among children and warrant further exploration. We conducted a retrospective cohort study for children and adolescents under the age of 21 from the thirteen institutions in the RECOVER Initiative. The cohort is 225,723 patients with SARS-CoV-2 infection or COVID-19 diagnosis and 677,448 patients without SARS-CoV-2 infection or COVID-19 diagnosis between March 2020 and October 2022. The study compared minor racial/ethnic groups to Non-Hispanic White (NHW) individuals, stratified by severity during the acute phase of COVID-19. Within the severe group, Asian American/Pacific Islanders (AAPI) had a higher prevalence of fever/chills and respiratory symptoms, Hispanic patients showed greater hair loss prevalence in severe COVID-19 cases, while Non-Hispanic Black (NHB) patients had fewer skin symptoms in comparison to NHW patients. Within the non-severe group, AAPI patients had increased POTS/dysautonomia and respiratory symptoms, and NHB patients showed more cognitive symptoms than NHW patients. In conclusion, racial/ethnic differences related to COVID-19 exist among specific PASC symptoms and conditions in pediatrics, and these differences are associated with the severity of illness during acute COVID-19.

JAMA Network Open

ImportanceA first step toward understanding whether pediatric medical subspecialists are meeting the needs of the nation’s children is describing rates of use and trends over time.ObjectivesTo quantify rates of outpatient pediatric medical subspecialty use.Design, Setting, and ParticipantsThis repeated cross-sectional study of annual subspecialist use examined 3 complementary data sources: electronic health records from PEDSnet (8 large academic medical centers [January 1, 2010, to December 31, 2021]); administrative data from the Healthcare Integrated Research Database (HIRD) (14 commercial health plans [January 1, 2011, to December 31, 2021]); and administrative data from the Transformed Medicaid Statistical Information System (T-MSIS) (44 state Medicaid programs [January 1, 2016, to December 31, 2019]). Annual denominators included 493 628 to 858 551 patients younger than 21 years with a …

arXiv preprint arXiv:2402.15060

Finite sample inference for Cox models is an important problem in many settings, such as clinical trials. Bayesian procedures provide a means for finite sample inference and incorporation of prior information if MCMC algorithms and posteriors are well behaved. On the other hand, estimation procedures should also retain inferential properties in high dimensional settings. In addition, estimation procedures should be able to incorporate constraints and multilevel modeling such as cure models and frailty models in a straightforward manner. In order to tackle these modeling challenges, we propose a uniformly ergodic Gibbs sampler for a broad class of convex set constrained multilevel Cox models. We develop two key strategies. First, we exploit a connection between Cox models and negative binomial processes through the Poisson process to reduce Bayesian computation to iterative Gaussian sampling. Next, we appeal to sufficient dimension reduction to address the difficult computation of nonparametric baseline hazards, allowing for the collapse of the Markov transition operator within the Gibbs sampler based on sufficient statistics. We demonstrate our approach using open source data and simulations.

Journal of Biomedical Informatics

ObjectiveTo characterize the interplay between multiple medical conditions across sites and account for the heterogeneity in patient population characteristics across sites within a distributed research network, we develop a one-shot algorithm that can efficiently utilize summary-level data from various institutions. By applying our proposed algorithm to a large pediatric cohort across four national Children’s hospitals, we replicated a recently published prospective cohort, the RISK study, and quantified the impact of the risk factors associated with the penetrating or stricturing behaviors of pediatric Crohn's disease (PCD).MethodsIn this study, we introduce the ODACoRH algorithm, a one-shot distributed algorithm designed for the competing risks model with heterogeneity. Our approach considers the variability in baseline hazard functions of multiple endpoints of interest across different sites. To accomplish this, we …

LGBT health

Purpose: The goal of this article was to identify demographic differences in receipt of gender dysphoria (GD) diagnosis and access to gender-affirming care (GAC) among adolescents whose gender identity and/or pronouns differed from their sex assigned at birth. Methods: Data were from 2444 patients who were 13–17 years old and had a documented gender identity and/or pronouns that differed from their sex assigned at birth in the electronic health record. Adjusted logistic regression models explored associations between demographic characteristics (sex assigned at birth, gender identity, race and ethnicity, language, insurance type, rural status) and presence of GD diagnosis and having accessed GAC. Results: The average predicted probability (Pr) of having received a GD diagnosis was 0.62 (95% confidence interval [CI] = 0.60–0.63) and of having accessed GAC was 0.48 (95% CI = 0.46–0.50 …

International Journal of Pediatric Otorhinolaryngology

ObjectivesTo determine rates and risk factors of pediatric otitis media (OM) using real-world electronic health record (PEDSnet) data from January 2009 through May 2021.Study designRetrospective cohort study.SettingSeven pediatric academic health systems that participate in PEDSnet.MethodsChildren <6 months-old at time of first outpatient, Emergency Department, or inpatient visit were included and followed longitudinally. A time-to-event analysis was performed using a Cox proportional hazards model to estimate hazard ratios for OM incidence based on sociodemographic factors and specific health conditions.ResultsThe PEDSnet cohort included 910,265 children, 54.3% male, mean age (months) 1.3 [standard deviation (SD) 1.6] and mean follow up (years) 4.3 (SD 3.2). By age 3 years, 39.6% of children had evidence of one OM episode. OM rates decreased following pneumococcal-13 vaccination (PCV-13 …

medRxiv

BackgroundMultisystem inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection. The highly diverse clinical features of MIS-C necessities characterizing its features by subphenotypes for improved recognition and treatment. However, jointly identifying subphenotypes in multi-site settings can be challenging. We propose a distributed multi-site latent class analysis (dMLCA) approach to jointly learn MIS-C subphenotypes using data across multiple institutions.MethodsWe used data from the electronic health records (EHR) systems across nine US children’s hospitals. Among the 3,549,894 patients, we extracted 864 patients< 21 years of age who had received a diagnosis of MIS-C during an inpatient stay or up to one day before admission. Using MIS-C conditions, laboratory results, and procedure information as input features for the patients, we applied our dMLCA …

Pediatrics

OBJECTIVES Vaccination reduces the risk of acute coronavirus disease 2019 (COVID-19) in children, but it is less clear whether it protects against long COVID. We estimated vaccine effectiveness (VE) against long COVID in children aged 5 to 17 years. METHODS This retrospective cohort study used data from 17 health systems in the RECOVER PCORnet electronic health record program for visits after vaccine availability. We examined both probable (symptom-based) and diagnosed long COVID after vaccination. RESULTS The vaccination rate was 67% in the cohort of 1 037 936 children. The incidence of probable long COVID was 4.5% among patients with COVID-19, whereas diagnosed long COVID was 0.8%. Adjusted vaccine effectiveness within 12 months was 35.4% (95 CI 24.5–44.7) against probable long COVID and 41.7% (15.0–60.0) against …

Journal of Biomedical Informatics

ObjectiveTo characterize the interplay between multiple medical conditions across sites and account for the heterogeneity in patient population characteristics across sites within a distributed research network, we develop a one-shot algorithm that can efficiently utilize summary-level data from various institutions. By applying our proposed algorithm to a large pediatric cohort across four national Children’s hospitals, we replicated a recently published prospective cohort, the RISK study, and quantified the impact of the risk factors associated with the penetrating or stricturing behaviors of pediatric Crohn's disease (PCD).MethodsIn this study, we introduce the ODACoRH algorithm, a one-shot distributed algorithm designed for the competing risks model with heterogeneity. Our approach considers the variability in baseline hazard functions of multiple endpoints of interest across different sites. To accomplish this, we …

Journal of the American Medical Informatics Association

Objectives To characterize the complex interplay between multiple clinical conditions in a time-to-event analysis framework using data from multiple hospitals, we developed two novel one-shot distributed algorithms for competing risk models (ODACoR). By applying our algorithms to the EHR data from eight national children’s hospitals, we quantified the impacts of a wide range of risk factors on the risk of post-acute sequelae of SARS-COV-2 (PASC) among children and adolescents. Materials and Methods Our ODACoR algorithms are effectively executed due to their devised simplicity and communication efficiency. We evaluated our algorithms via extensive simulation studies as applications to quantification of the impacts of risk factors for PASC among children and adolescents using data from eight children’s hospitals including the Children’s Hospital of Philadelphia …

Annals of Internal Medicine

Background The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant’s emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited. Objective To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents. Design Comparative effectiveness research accounting for underreported vaccination in 3 study cohorts: adolescents (12 to 20 years) during the Delta phase and children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. Setting A national collaboration of pediatric health systems (PEDSnet). Participants 77 392 …

Research Square

Racial/ethnic differences are associated with the potential symptoms and conditions of post-acute sequelae SARS-CoV-2 infection (PASC) in adults. These differences may exist among children and warrant further exploration. We conducted a retrospective cohort study for children and adolescents under the age of 21 from the thirteen institutions in the RECOVER Initiative. The cohort is 225,723 patients with SARS-CoV-2 infection or COVID-19 diagnosis and 677,448 patients without SARS-CoV-2 infection or COVID-19 diagnosis between March 2020 and October 2022. The study compared minor racial/ethnic groups to Non-Hispanic White (NHW) individuals, stratified by severity during the acute phase of COVID-19. Within the severe group, Asian American/Pacific Islanders (AAPI) had a higher prevalence of fever/chills and respiratory symptoms, Hispanic patients showed greater hair loss prevalence in severe COVID-19 cases, while Non-Hispanic Black (NHB) patients had fewer skin symptoms in comparison to NHW patients. Within the non-severe group, AAPI patients had increased POTS/dysautonomia and respiratory symptoms, and NHB patients showed more cognitive symptoms than NHW patients. In conclusion, racial/ethnic differences related to COVID-19 exist among specific PASC symptoms and conditions in pediatrics, and these differences are associated with the severity of illness during acute COVID-19.

Journal of Pediatric Urology

BackgroundPrimary hyperoxaluria type 1 (PH1) is an autosomal recessive inborn error of metabolism that causes oxalate deposition, leading to recurrent calcium oxalate kidney stones, chronic kidney disease and systemic oxalosis, which produces a broad range of serious life-threatening complications. Patients with PH1 have delayed diagnosis due to the rarity of the disease and the overlap with early-onset kidney stone disease not due to primary hyperoxaluria.ObjectiveThe objective of this study was to determine the clinical features of individuals <21 years of age with PH1 that precede its diagnosis. We hypothesized that a parsimonious set of features could be identified that differentiate patients with PH1 from patients with non-primary hyperoxaluria-associated causes of early-onset kidney stone disease.Study designWe determined the association between clinical characteristics and PH1 diagnosis in a case …

Telemedicine and e-Health

Purpose: To explore transgender and nonbinary (TNB) young adults' (1) interest in receiving gender-affirming medications through telemedicine before age 18 years and (2) willingness to initiate this care with primary care providers (PCPs). Methods: Data were from a survey of TNB young adults who had not received gender-affirming medications before age 18 years. Chi-square and Wald tests identified demographic differences in telemedicine interest and willingness to initiate medications with their PCP as minors. Results: Among 280 respondents, 82.5% indicated interest in telemedicine and 42.0% were willing to initiate medications with their PCP. Black/African American respondents were more likely to indicate interest in telemedicine than White and multiracial respondents. Respondents from rural areas were more likely to indicate willingness to initiate medications with their PCP than those from urban areas …

medRxiv

Chronic pain is a multifactorial condition presenting significant diagnostic and prognostic challenges. Biomarkers for the classification and the prediction of chronic pain are therefore critically needed. In this multi-dataset study of over 523,000 participants, we applied machine learning to multi-dimensional biological data from the UK Biobank to identify biomarkers for 35 medical conditions associated with pain (e.g., clinical diagnosis of rheumatoid arthritis, fibromyalgia, stroke, gout, etc.) or self-reported chronic pain (e.g., back pain, knee pain, etc). Biomarkers derived from blood immunoassays, brain and bone imaging, and genetics were effective in predicting medical conditions associated with chronic pain (area under the curve (AUC) 0.62-0.87) but not self-reported pain (AUC 0.50-0.62). Among the biomarkers identified was a composite blood-based signature that predicted the onset of various medical conditions approximately nine years in advance (AUC 0.59-0.72). Notably, all biomarkers worked in synergy with psychosocial factors, accurately predicting both medical conditions (AUC 0.69-0.91) and self-report pain (AUC 0.71-0.92). Over a period of 15 years, individuals scoring high on both biomarkers and psychosocial risk factors had twice the cumulative incidence of diagnoses for pain-associated medical conditions (Hazard Ratio (HR): 2.26) compared to individuals scoring high on biomarkers but low on psychosocial risk factors (HR: 1.06). In summary, we identified various biomarkers for chronic pain conditions and showed that their predictive efficacy heavily depended on psychological and social influences. These findings underscore …

medRxiv

ImportanceChildren prenatally exposed to maternal diabetes have a higher risk of developing obesity and metabolic disorders. Alterations in the brain development is hypothesized as a potential mechanism underlying this relationship but has not been fully tested in humans.ObjectivesTo examine the mediating role of child brain structure in the relationships between prenatal exposure to maternal diabetes and child adiposity.Design, setting and participantsThis was a cross-sectional study of children (ages 9-to-10-years-old) from the baseline assessment of the Adolescent Brain and Cognitive Development (ABCD) Study® (N=11,875).ExposuresPrenatal exposure to maternal diabetes was determined via self-reported questionnaire.Main outcomes and measuresChild adiposity markers included age- and sex-specific body mass index (BMI z-scores), waist circumference, and waist-to-height ratio (WHtR). T1-weighted magnetic resonance imaging (MRI) was used to assess brain structure. Linear mixed effects models examined associations of prenatal exposure to maternal diabetes with child adiposity markers and brain structure controlling for sociodemographic covariates. Mediation models were performed to investigate the mediating role of brain structure on the association between maternal diabetes exposure and child adiposity markers.ResultsThe sample consisted of 8,521 children (agem: 9.92±0.63 years; sex: 51.4% males; 7% exposed to maternal diabetes). Children prenatally exposed vs. unexposed to maternal diabetes had greater BMI z-scores (β (95% CI) = 0.175 (0.093, 0.256; FDR corrected P<0.001), waist circumference (β (95% CI …

medRxiv

Background Physical activity has been associated with preventing the development of type 2 diabetes and atherosclerotic cardiovascular disease. However, our understanding of the precise molecular mechanisms underlying these effects remains incomplete and good biomarkers to objectively assess physical activity are lacking. Methods We analyzed 3072 serum proteins in 26 men, normal weight or overweight, undergoing 12 weeks of a combined strength and endurance exercise intervention. We estimated insulin sensitivity with hyperinsulinemic euglycemic clamp, maximum oxygen uptake, muscle strength, and used MRI/MRS to evaluate body composition and organ fat depots. Muscle and subcutaneous adipose tissue biopsies were used for mRNA sequencing. Additional association analyses were performed in samples from up to 47,747 individuals in the UK Biobank, as well as using 2-sample Mendelian randomization and mice models. Results Following 12 weeks of exercise intervention, we observed significant changes in 283 serum proteins. Notably, 66 of these proteins were elevated in overweight men and positively associated with liver fat before the exercise regimen, but were normalized after exercise. Furthermore, for 19.7% and 12.1% of the exercise-responsive proteins, corresponding changes in mRNA expression levels in muscle and fat, respectively, were shown. The protein CD300LG displayed consistent alterations in blood, muscle, and fat. Serum CD300LG exhibited positive associations with insulin sensitivity, and to angiogenesis-related gene expression in both muscle and fat. Furthermore, serum CD300LG was …

medRxiv

Digital health technologies offer valuable advantages to dementia researchers and clinicians as screening tools, diagnostic aids, and monitoring instruments. To support the use and advancement of these resources, a comprehensive overview of the current technological landscape is essential. A multi-stakeholder working group, convened by the Digital Medicine Society (DiMe), conducted a landscape review to identify digital health technologies for Alzheimers disease and related dementia populations. We searched studies indexed in PubMed, Embase, and APA PsycInfo to identify manuscripts published between May 2003 to May 2023 reporting analytical validation, clinical validation, or usability/feasibility results for relevant digital health technologies. Additional technologies were identified through community outreach. We collated 172 peer-reviewed manuscripts, poster presentations, or regulatory documents for 106 different technologies for Alzheimers disease and related dementia assessment covering diverse populations such as Lewy Body, vascular dementias, frontotemporal dementias, and all severities of Alzheimers disease. Wearable sensors represent 32% of included technologies, non-wearables 61%, and technologies with components of both account for the remaining 7%. Neurocognition is the most prevalent concept of interest, followed by physical activity and sleep. Clinical validation is reported in 69% of evidence, analytical validation in 34%, and usability/feasibility in 20% (not mutually exclusive). These findings provide a landscape overview for clinicians and researchers to appraise the clinical utility and relative maturity of …

medRxiv

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating …

medRxiv

Background: The impact of pre-infection vaccination on the risk of long COVID remains unclear in the pediatric population. Further, it is unknown if such pre-infection vaccination can mitigate the risk of long COVID beyond its established protective benefits against SARS-CoV-2 infection. Objective: To assess the effectiveness of BNT162b2 on long COVID risks with various strains of the SARS-CoV-2 virus in children and adolescents, using comparative effectiveness methods. To disentangle the overall effectiveness of the vaccine on long COVID outcomes into its independent impact and indirect impact via prevention of SARS-CoV-2 infections, using causal mediation analysis. Design: Real-world vaccine effectiveness study and mediation analysis in three independent cohorts: adolescents (12 to 20 years) during the Delta phase, children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. Setting: Twenty health systems in the RECOVER PCORnet electronic health record (EHR) Program. Participants: 112,590 adolescents (88,811 vaccinated) in the Delta period, 188,894 children (101,277 vaccinated), and 84,735 adolescents (37,724 vaccinated) in the Omicron period. Exposures: First dose of the BNT162b2 vaccine vs. no receipt of COVID-19 vaccine. Measurements: Outcomes of interest include conclusive or probable diagnosis of long COVID following a documented SARS-CoV-2 infection, and body-system-specific condition clusters of post-acute sequelae of SARS-CoV-2 infection (PASC), such as cardiac, gastrointestinal, musculoskeletal, respiratory, and syndromic categories. The effectiveness was reported as (1 …

medRxiv

Background Cytokine storm syndromes (CSS), including hemophagocytic lymphohistiocytosis (HLH), are increasingly recognized as hyper-inflammatory states leading to multi-organ failure and death. Familial HLH (FHL) in infancy results from homozygous genetic defects in perforin-mediated cytolysis by CD8 T-lymphocytes and natural killer (NK) cells. Later onset CSS are frequently associated with heterozygous defects in FHL genes, but genetic etiologies for most are unknown. We identified rare DOCK8 variants in CSS patients. Objective We explore the role of CSS patient derived DOCK8 mutations on cytolytic activity in NK cells. We further study effects of Dock8-/- in murine models of CSS. Methods DOCK8 cDNA from 2 unrelated CSS patients with different missense mutations were introduced into human NK-92 NK cells by foamy virus transduction. NK cell degranulation (CD107a), cytolytic activity against K562 target cells, and interferon-gamma (IFNlower case Greek gamma) production were explored by flow cytometry (FCM). A third CSS patient DOCK8 mRNA splice acceptor site variant was explored by exon trapping. Dock8-/- mice were assessed for features of CSS (weight loss, splenomegaly, hepatic inflammation, cytopenias, and IFNlower case Greek gamma levels) upon challenge with lymphochoriomeningitic virus (LCMV) and excess IL-18. Results Both patient DOCK8 missense mutations decreased cytolytic function in NK cells in a partial dominant-negative fashion in vitro. The patient DOCK8 splice variant disrupted mRNA splicing in vitro. Dock8-/- mice tolerated excess IL-18 but developed features of CSS upon LCMV infection …

medRxiv

Background and Objectives Cohort studies investigating respiratory disease pathogenesis aim to pair mechanistic investigations with longitudinal virus detection but are limited by the burden of methods tracking illness over time. In this study, we explored the utility of a smartphone app to robustly identify symptomatic respiratory illnesses, while reducing burden and facilitating real-time data collection and adherence monitoring. Methods The AERIAL TempTracker smartphone app was assessed in the AERIAL and COCOON birth cohort studies. Participants recorded daily temperatures and associated symptoms/medications in TempTracker for 6 months, with daily use adherence measured over this period. Regular participant feedback was collected at quarterly study visits. Symptomatic respiratory illnesses meeting study criteria prompted an automated app alert and collection of a nose/throat swab for testing of eight respiratory viruses. Results In total, 32,764 daily TempTracker entries from 348 AERIAL participants and 30,542 entries from 361 COCOON participants were recorded. This corresponded to an adherence median of 67.0% (range 1.9$[ndash]100%) and 55.4% (range 1.1–100%) of each participants study period, respectively. Feedback was positive, with 75.5% of responding families reporting no barriers to use. A total of 648 symptomatic respiratory illness events from 249/709 participants were identified with significant variability between individuals in the frequency (0–16 events per participant), duration (1–13 days), and virus detected (rhinovirus in 42.7%). Conclusions A smartphone app provides a reliable method to capture the …

medRxiv

Importance Masks reduce transmission of SARS-CoV2 and other respiratory pathogens. Comparative studies of the fitted filtration efficiency of different types of masks of are few.   Objective To describe the fitted filtration efficiency against small aerosols (0.02 – 1 µm) of medical and non-medical masks and respirators when worn, and how this is affected by user modifications (hacks) and by overmasking with a cloth mask.   Design We tested a 2-layer woven-cotton cloth mask of a consensus design, ASTM-certified level 1 and level 3 masks, a non-certified mask, KF94s, KN95s, an N95 and a CaN99.   Setting Closed rooms with ambient particles supplemented by salt particles.   Participants 12 total participants; 21 – 55 years, 68% female, 77% white, NIOSH 1 to 10.   Main Outcome and Measure Using standard methods and a PortaCount 8038, we counted 0.02–1µm particles inside and outside masks and respirators, expressing results as the percentage filtered by each mask. We also studied level 1 and level 3 masks with earguards, scrub caps, the knot-and-tuck method, and the effects of braces or overmasking with a cloth mask.   Results Filtration efficiency for the cloth mask was 47-55%, for level 1 masks 52-60%, for level 3 masks 60-77%. A non-certified KN95 look-alike, two KF94s, and three KN95s filtered 57-77%, and the N95 and CaN99 97-98% without fit testing. External braces and overmasking with a well-fitting cloth mask increased filtration, but earguards, scrub caps, and the knot-and-tuck method did not.   Limitations Limited number of masks of each type sampled; no adjustment for multiple comparisons.   Conclusions and Relevance …

medRxiv

Objectives Prevention of fetal growth restriction/small for gestational age is adequate if screening is accurate. Ultrasound and biomarkers can achieve this goal; however, both are often inaccessible. This study aimed to develop, validate, and deploy a prognostic prediction model for screening fetal growth restriction/small for gestational age using only medical history. Methods From a nationwide health insurance database (n=1,697,452), we retrospectively selected visits of 12-to-55-year-old females to 22,024 healthcare providers of primary, secondary, and tertiary care. This study used machine learning (including deep learning) to develop prediction models using 54 medical-history predictors. After evaluating model calibration, clinical utility, and explainability, we selected the best by discrimination ability. We also externally validated and compared the models with those from previous studies, which were rigorously selected by a systematic review of Pubmed, Scopus, and Web of Science. Results We selected 169,746 subjects with 507,319 visits for predictive modeling. The best prediction model was a deep-insight visible neural network. It had an area under the receiver operating characteristics curve of 0.742 (95% confidence interval 0.734 to 0.750) and a sensitivity of 49.09% (95% confidence interval 47.60% to 50.58% using a threshold with 95% specificity). The model was competitive against the previous models in a systematic review of 30 eligible studies of 381 records, including those using either ultrasound or biomarker measurements. We deployed a web application to apply the model. Conclusions Our model used only medical history …

medRxiv

Young-onset Alzheimer's Disease(AD) is a rare form of AD characterized by early symptom onset (< 65 years) and heterogeneous clinical phenotypes. Previous studies have consistently shown that patients with late-onset AD exhibit alterations in the default mode network-a large-scale brain network associated with self-related processing and autobiographical memory. However, the functional organization of the default-mode network is far less clear in young-onset AD. Here, we assessed default-mode network effective connectivity in two common young-onset AD variants (i.e., typical amnestic variant and posterior cortical atrophy) and healthy participants to identify disease- and variant-specific differences in the default-mode network. This case-control study was conducted with thirty-nine young-onset AD patients, including typical amnestic (n = 26, 15 females, mean age = 61) and posterior cortical atrophy (n = 13; 8 females, mean age = 61.8), and 24 age-matched healthy participants (13 females, mean age=60.1). All participants underwent resting-state functional MRI and extensive neuropsychological testing. Spectral dynamic causal modelling was performed to quantify resting-state effective connectivity between default-mode network regions. Parametric empirical Bayes analysis was then performed to characterise group differences in effective connectivity. Our results showed that patients with typical AD variant showed increased connectivity from medial prefrontal cortex to posterior default-mode network nodes as well as reduced inhibitory connectivity from hippocampus to other default-mode network nodes, relative to healthy controls …

medRxiv

Background Treatment with monoclonal antibodies against amyloid-beta; slowed cognitive decline in recent randomized clinical trials in patients with mild cognitive impairment (MCI) and early dementia due to Alzheimers disease (AD). However, stringent trial eligibility criteria may affect generalizability of these findings to clinical practice. Methods We extracted eligibility criteria for trials of aducanumab, lecanemab and donanemab from published reports, and applied these to participants with MCI or early clinical AD dementia from the population-based Rotterdam Study. Participants underwent questionnaires, genotyping, brain MRI, cognitive testing, and cardiovascular assessment. We had continuous linkage with medical records and pharmacy dispensary data. We determined amyloid status using an established and validated prediction model based on age and APOE genotype. We assessed progression to dementia within 5 years among participants with MCI, stratified for eligibility. Results Of 968 participants (mean age: 75 years, 56% women), 779 had MCI and 189 early clinical AD dementia. Across the three drug trials, around 40% of participants would be ineligible because of predicted amyloid negativity. At least one clinical exclusion criterion was present in 76.3% (95% CI; 73.3-79.3) of participants for aducanumab, 75.8% (73.0-78.7) for lecanemab, and 59.8% (56.4-63.3) for donanemab. Criteria that most often led to exclusion were a history of cardiovascular disease (35.2%), use of anticoagulant (31.2%), use of psychotropic or immunological medications (20.4%), history of anxiety or depression (15.9%), or lack of social support (15 …

medRxiv

INTRODUCTION Gene carriers of frontotemporal dementia can remain cognitively well despite neurodegeneration. A better understanding of brain structural, perfusion and functional patterns in pre-symptomatic stage could inform accurate staging and potential mechanisms. METHODS We included 207 pre-symptomatic carriers and 188 relatives without mutations. The grey matter volume, cerebral perfusion, and resting-state functional network maps were co-analyzed using linked independent component analysis (LICA). Multiple regression analysis was used to investigate the relationship of LICA components to genetic status and cognition. RESULTS Pre-symptomatic carriers showed an age-related decrease in the left frontoparietal network integrity while non-carriers did not. Executive functions of pre-symptomatic carriers dissociated from the level of atrophy and cerebrovascular dysfunction, but became dependent on the left frontoparietal network integrity in older age. DISCUSSION The frontoparietal network integrity of pre-symptomatic carriers showed a distinctive relationship to age and cognition compared to non-carriers, despite atrophy and hypoperfusion. Functional network integrity may contribute to brain resilience in pre-symptomatic frontotemporal dementia, mitigating the effects of atrophy and hypoperfusion.

medRxiv

INTRODUCTION Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular health and its signature in hereditary frontotemporal dementia (FTD) remains unknown. We investigated CVR in genetic FTD and its relationship to cognition. METHODS CVR differences were assessed between 284 pre-symptomatic and 124 symptomatic mutation carriers, and 265 non-carriers, using resting-state fluctuation amplitudes (RSFA) on component-based and voxel-level RSFA maps. Associations and interactions between RSFA, age, genetic status, and cognition were examined using generalised linear models. RESULTS Compared to non-carriers, mutation carriers exhibited greater RSFA reductions, predominantly in frontal cortex. These reductions increased with age. The RSFA in these regions correlated with cognitive function in symptomatic and, to a lesser extent, pre-symptomatic individuals, independent of disease stage. DISCUSSION CVR impairment in genetic FTD predominantly affects frontal cortical areas, and its preservation may yield cognitive benefits for at-risk individuals. Cerebrovascular health may be a potential target for biomarker identification and disease-modifying efforts.

medRxiv

Human papillomavirus-associated oropharyngeal squamous cell carcinomas (HPV+OPSCC) release circulating tumor HPV DNA (ctHPVDNA) into the blood which we, and others, have shown is an accurate real-time biomarker of disease status. In a prior prospective observational trial of 34 patients with AJCC 8 stage I-II HPV+OPSCC treated with surgery, we reported that ctHPVDNA was rapidly cleared within hours of surgery in patients who underwent complete cancer extirpation, yet remained elevated in those with macroscopic residual disease. The primary outcomes of this study were to assess 2-year OS and RFS between patients with and without molecular residual disease (MRD) following completion of treatment in this prospective cohort. MRD was defined as persistent elevation of ctHPVDNA at two consecutive time points, without clinical evidence of disease. The secondary outcomes were 2-year OS and RFS between patients with and without detectable MRD after surgery. We observed that patients with MRD after treatment completion were more likely to recur compared to patients without MRD, while there was no difference in recurrence rates between patients with MRD and without MRD on postoperative day 1. OS did not significantly differ between patients with MRD after surgery or treatment completion compared to patients without MRD; however, time to death was significantly different between the groups in both settings, suggesting that with a larger sample size OS would differ significantly between the groups or that the impact of MRD detection on survival is time dependent.

medrxiv

The adaptive immune response is physiologically regulated by the circadian rhythm. Data in lung and melanoma malignancies suggests immunotherapy infusions earlier in the day may be associated with improved response; however, the optimal time of administration for patients with head and neck squamous cell carcinoma (HNSCC) is not known. We aimed to evaluate the association of immunotherapy infusion time with overall survival (OS) and progression free survival (PFS) in patients with HNSCC in an Institutional Review Board-approved, retrospective cohort study. 113 patients met study inclusion criteria and 98 patients were included in a propensity score-matched cohort. In the full unmatched cohort (N = 113), each additional 20 % of infusions received after 1500 h conferred an OS hazard ratio (HR) of 1.35 (95 % C.I.1.2–1.6; p-value = 0.0003) and a PFS HR of 1.34 (95 % C.I.1.2–1.6; p-value < 0.0001). A …

medRxiv

Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011–2012 to 2018–2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A (H3N2)(OR= 1.11, 95% CI: 1.02–1.21) but not for influenza B or A (H1N1). We found that clinical infection influences individuals’ decision to vaccinate in the following season while protecting against clinical infection of the same (sub) type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical …

medRxiv

Collaborative efforts in artificial intelligence (AI) are increasingly common between high-income countries (HICs) and low- to middle-income countries (LMICs). Given the resource limitations often encountered by LMICs, collaboration becomes crucial for pooling resources, expertise, and knowledge. Despite the apparent advantages, ensuring the fairness and equity of these collaborative models is essential, especially considering the distinct differences between LMIC and HIC hospitals. In this study, we show that collaborative AI approaches can lead to divergent performance outcomes across HIC and LMIC settings, particularly in the presence of data imbalances. Through a real-world COVID-19 screening case study, we demonstrate that implementing algorithmic-level bias mitigation methods significantly improves outcome fairness between HIC and LMIC sites while maintaining high diagnostic sensitivity. We compare our results against previous benchmarks, utilizing datasets from four independent United Kingdom Hospitals and one Vietnamese hospital, representing HIC and LMIC settings, respectively.

medRxiv

Retinal fundus imaging is a powerful tool for disease screening and diagnosis in opthalmology. With the advent of machine learning and artificial intelligence, in particular modern computer vision classification algorithms, there is broad scope for technology to improve accuracy, increase accessibility and reduce cost in these processes. In this paper we present the first deep learning model trained on the first Brazilian multi-label opthalmological datatset. We train a multi-label classifier using over 16,000 clinically-labelled fundus images. Across a range of 13 retinal diseases, we obtain frequency-weighted AUC and F1 scores of 0.92 and 0.70 respectively. Our work establishes a baseline model on this new dataset and furthermore demonstrates the applicability and power of artificial intelligence approaches to retinal fundus disease diagnosis in under-represented populations.

medRxiv

The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering task with answer options for evaluation. However, in real clinical settings, many clinical decisions, such as treatment recommendations, involve answering open-ended questions without pre-set options. Meanwhile, existing studies mainly use accuracy to assess model performance. In this paper, we comprehensively benchmark diverse LLMs in healthcare, to clearly understand their strengths and weaknesses. Our benchmark contains seven tasks and thirteen datasets across medical language generation, understanding, and reasoning. We conduct a detailed evaluation of existing sixteen LLMs in healthcare under both zero-shot and few-shot (i.e., 1,3,5-shot) learning settings. We report the results on five metrics (i.e. matching, faithfulness, comprehensiveness, generalizability, and robustness) that are critical in achieving trust from clinical users. We further invite medical experts to conduct human evaluation.