UMass Center for Clinical and Translational Science Supported Publications
ABOUT THIS COLLECTION
The University of Massachusetts Center for Clinical and Translational Science (UMCCTS) was founded in 2006 to enhance clinical and translational research across the five University of Massachusetts campuses and our clinical partners, UMass Memorial Health Care and Baystate Medical Center. The UMCCTS is part of the Clinical and Translational Science Award (CTSA) program, funded by the National Center for Advancing Translational Sciences (Grant # UL1-TR001453) at the National Institutes of Health (NIH). This collection showcases publications that are the result of UMCCTS supported research.
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Recently Published
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Performance of Rapid Antigen Tests Based on Symptom Onset and Close Contact Exposure: A secondary analysis from the Test Us At Home prospective cohort study [preprint]Background: The performance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) in temporal relation to symptom onset or exposure is unknown, as is the impact of vaccination on this relationship. Objective: To evaluate the performance of Ag-RDT compared with RT-PCR based on day after symptom onset or exposure in order to decide on 'when to test'. Design setting and participants: The Test Us at Home study was a longitudinal cohort study that enrolled participants over 2 years old across the United States between October 18, 2021 and February 4, 2022. All participants were asked to conduct Ag-RDT and RT-PCR testing every 48 hours over a 15-day period. Participants with one or more symptoms during the study period were included in the Day Post Symptom Onset (DPSO) analyses, while those who reported a COVID-19 exposure were included in the Day Post Exposure (DPE) analysis. Exposure: Participants were asked to self-report any symptoms or known exposures to SARS-CoV-2 every 48-hours, immediately prior to conducting Ag-RDT and RT-PCR testing. The first day a participant reported one or more symptoms was termed DPSO 0, and the day of exposure was DPE 0. Vaccination status was self-reported. Main outcome and measures: Results of Ag-RDT were self-reported (positive, negative, or invalid) and RT-PCR results were analyzed by a central laboratory. Percent positivity of SARS-CoV-2 and sensitivity of Ag-RDT and RT-PCR by DPSO and DPE were stratified by vaccination status and calculated with 95% confidence intervals. Results: A total of 7,361 participants enrolled in the study. Among them, 2,086 (28.3%) and 546 (7.4%) participants were eligible for the DPSO and DPE analyses, respectively. Unvaccinated participants were nearly twice as likely to test positive for SARS-CoV-2 than vaccinated participants in event of symptoms (PCR+: 27.6% vs 10.1%) or exposure (PCR+: 43.8% vs. 22.2%). The highest proportion of vaccinated and unvaccinated individuals tested positive on DPSO 2 and DPE 5-8. Performance of RT-PCR and Ag-RDT did not differ by vaccination status. Ag-RDT detected 78.0% (95% Confidence Interval: 72.56-82.61) of PCR-confirmed infections by DPSO 4. For exposed participants, Ag-RDT detected 84.9% (95% CI: 75.0-91.4) of PCR-confirmed infections by day five post-exposure (DPE 5). Conclusions and relevance: Performance of Ag-RDT and RT-PCR was highest on DPSO 0-2 and DPE 5 and did not differ by vaccination status. These data suggests that serial testing remains integral to enhancing the performance of Ag-RDT.
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CRISPR-induced exon skipping of β-catenin reveals tumorigenic mutants driving distinct subtypes of liver cancerCRISPR/Cas9-driven cancer modeling studies are based on the disruption of tumor suppressor genes by small insertions or deletions (indels) that lead to frame-shift mutations. In addition, CRISPR/Cas9 is widely used to define the significance of cancer oncogenes and genetic dependencies in loss-of-function studies. However, how CRISPR/Cas9 influences gain-of-function oncogenic mutations is elusive. Here, we demonstrate that single guide RNA targeting exon 3 of Ctnnb1 (encoding β-catenin) results in exon skipping and generates gain-of-function isoforms in vivo. CRISPR/Cas9-mediated exon skipping of Ctnnb1 induces liver tumor formation in synergy with YAPS127A in mice. We define two distinct exon skipping-induced tumor subtypes with different histological and transcriptional features. Notably, ectopic expression of two exon-skipped β-catenin transcript isoforms together with YAPS127A phenocopies the two distinct subtypes of liver cancer. Moreover, we identify similar CTNNB1 exon-skipping events in patients with hepatocellular carcinoma. Collectively, our findings advance our understanding of β-catenin-related tumorigenesis and reveal that CRISPR/Cas9 can be repurposed, in vivo, to study gain-of-function mutations of oncogenes in cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Anti-SOD1 Nanobodies That Stabilize Misfolded SOD1 Proteins Also Promote Neurite Outgrowth in Mutant SOD1 Human NeuronsALS-linked mutations induce aberrant conformations within the SOD1 protein that are thought to underlie the pathogenic mechanism of SOD1-mediated ALS. Although clinical trials are underway for gene silencing of SOD1, these approaches reduce both wild-type and mutated forms of SOD1. Here, we sought to develop anti-SOD1 nanobodies with selectivity for mutant and misfolded forms of human SOD1 over wild-type SOD1. Characterization of two anti-SOD1 nanobodies revealed that these biologics stabilize mutant SOD1 in vitro. Further, SOD1 expression levels were enhanced and the physiological subcellular localization of mutant SOD1 was restored upon co-expression of anti-SOD1 nanobodies in immortalized cells. In human motor neurons harboring the SOD1 A4V mutation, anti-SOD1 nanobody expression promoted neurite outgrowth, demonstrating a protective effect of anti-SOD1 nanobodies in otherwise unhealthy cells. In vitro assays revealed that an anti-SOD1 nanobody exhibited selectivity for human mutant SOD1 over endogenous murine SOD1, thus supporting the preclinical utility of anti-SOD1 nanobodies for testing in animal models of ALS. In sum, the anti-SOD1 nanobodies developed and presented herein represent viable biologics for further preclinical testing in human and mouse models of ALS.
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Profiling genome-wide recombination in Epstein Barr virus reveals type-specific patterns and associations with endemic-Burkitt lymphomaBackground: Endemic Burkitt lymphoma (eBL) is potentiated through the interplay of Epstein Barr virus (EBV) and holoendemic Plasmodium falciparum malaria. To better understand EBV's biology and role in eBL, we characterized genome-wide recombination sites and patterns as a source of genetic diversity in EBV genomes in our well-defined population of eBL cases and controls from Western Kenya. Methods: EBV genomes representing 54 eBL cases and 32 healthy children from the same geographic region in Western Kenya that we previously sequenced were analyzed. Whole-genome multiple sequence alignment, recombination analyses, and phylogenetic inference were made using multiple alignment with fast Fourier transform, recombination detection program 4, and molecular evolutionary genetics analysis. Results: We identified 28 different recombination events and 71 (82.6%) of the 86 EBV genomes analyzed contained evidence of one or more recombinant segments. Associated recombination breakpoints were found to occur in a total of 42 different genes, with only 7 (16.67%) being latent genes. Recombination events were major drivers of clustering within genome-wide phylogenetic trees. The occurrence of recombination segments was comparable between genomes from male and female participants and across age groups. More recombinant segments were found in EBV type 1 genomes (p = 6.4e - 06) and the genomes from the eBLs (p = 0.037). Two recombination events were enriched in the eBLs; event 47 (OR = 4.07, p = 0.038) and event 50 (OR = 14.24, p = 0.012). Conclusions: EBV genomes have extensive evidence of recombination likely acquired progressively and cumulatively over time. Recombination patterns display a heterogeneous occurrence rate across the genome with enrichment in lytic genes. Overall, recombination appears to be a major evolutionary force impacting EBV diversity and genome structure with evidence of the association of specific recombinants with eBL.
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Development and Beta-Testing of the CONFIDENCE Intervention to Increase Pediatric COVID-19 VaccinationIntroduction: Innovative strategies are needed to improve pediatric COVID-19 vaccination rates. We describe the process for developing a clinic-based intervention, CONFIDENCE, to improve pediatric COVID-19 vaccine uptake and present results of our beta-test for feasibility and acceptability. Method: CONFIDENCE included communication training with providers, a poster campaign, and parent-facing educational materials. We assessed feasibility and acceptability through interviews and measured preliminary vaccine intention outcomes with a pre-post parent survey. Interviews were analyzed using rapid qualitative methods. We generated descriptive statistics for variables on the parent survey and used Fisher's exact test to assess pre-post differences. Results: Participating providers (n = 4) reported high levels of feasibility and acceptability. We observed positive trends in parents' (n = 69) reports of discussing vaccination with their provider and the parental decision to accept COVID-19 vaccination. Discussion: Our next steps will be to use more rigorous methods to establish the efficacy and effectiveness of the CONFIDENCE intervention.
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Evaluation of mRNA-1273 Vaccine in Children 6 Months to 5 Years of AgeBackground: The safety, reactogenicity, immunogenicity, and efficacy of the mRNA-1273 coronavirus disease 2019 (Covid-19) vaccine in young children are unknown. Methods: Part 1 of this ongoing phase 2-3 trial was open label for dose selection; part 2 was an observer-blinded, placebo-controlled evaluation of the selected dose. In part 2, we randomly assigned young children (6 months to 5 years of age) in a 3:1 ratio to receive two 25-μg injections of mRNA-1273 or placebo, administered 28 days apart. The primary objectives were to evaluate the safety and reactogenicity of the vaccine and to determine whether the immune response in these children was noninferior to that in young adults (18 to 25 years of age) in a related phase 3 trial. Secondary objectives were to determine the incidences of Covid-19 and severe acute respiratory syndrome coronavirus 2 infection after administration of mRNA-1273 or placebo. Results: On the basis of safety and immunogenicity results in part 1 of the trial, the 25-μg dose was evaluated in part 2. In part 2, 3040 children 2 to 5 years of age and 1762 children 6 to 23 months of age were randomly assigned to receive two 25-μg injections of mRNA-1273; 1008 children 2 to 5 years of age and 593 children 6 to 23 months of age were randomly assigned to receive placebo. The median duration of follow-up after the second injection was 71 days in the 2-to-5-year-old cohort and 68 days in the 6-to-23-month-old cohort. Adverse events were mainly low-grade and transient, and no new safety concerns were identified. At day 57, neutralizing antibody geometric mean concentrations were 1410 (95% confidence interval [CI], 1272 to 1563) among 2-to-5-year-olds and 1781 (95% CI, 1616 to 1962) among 6-to-23-month-olds, as compared with 1391 (95% CI, 1263 to 1531) among young adults, who had received 100-μg injections of mRNA-1273, findings that met the noninferiority criteria for immune responses for both age cohorts. The estimated vaccine efficacy against Covid-19 was 36.8% (95% CI, 12.5 to 54.0) among 2-to-5-year-olds and 50.6% (95% CI, 21.4 to 68.6) among 6-to-23-month-olds, at a time when B.1.1.529 (omicron) was the predominant circulating variant. Conclusions: Two 25-μg doses of the mRNA-1273 vaccine were found to be safe in children 6 months to 5 years of age and elicited immune responses that were noninferior to those in young adults. (Funded by the Biomedical Advanced Research and Development Authority and National Institute of Allergy and Infectious Diseases; KidCOVE ClinicalTrials.gov number, NCT04796896.).
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A prospective analysis of red blood cell membrane polyunsaturated fatty acid levels and risk of non-Hodgkin lymphomaPublished studies report inconsistent associations of polyunsaturated fatty acid (PUFA) intake with non-Hodgkin lymphoma (NHL) risk. We conducted a nested case-control study in Nurses' Health Study and Health Professionals Follow-Up Study participants to evaluate a hypothesis of inverse association of pre-diagnosis red blood cell (RBC) membrane PUFA levels with risk of NHL endpoints. We confirmed 583 NHL cases and matched 583 controls by cohort/sex, age, race and blood draw date/time. We estimated odds ratios (OR) and 95% confidence intervals (CI) for risk of NHL endpoints using logistic regression. RBC PUFA levels were not associated with all NHL risk; cis 20:2n-6 was associated with follicular lymphoma risk (OR [95% CI] per one standard deviation increase: 1.35 [1.03-1.77]), and the omega-6/omega-3 PUFA ratio was associated with diffuse large B-cell lymphoma risk (2.33 [1.23-4.43]). Overall, PUFA did not demonstrate a role in NHL etiology; the two unexpected positive associations lack clear biologic explanations.
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Established Outpatient Care and Follow-Up After Acute Psychiatric Service Use Among Youths and Young AdultsObjective: This study explored follow-up after hospitalization and emergency room (ER) use for mental health among youths and young adults with private insurance. Methods: The IBM MarketScan commercial database (2013-2018) was used to identify people ages 12-27 with a mental health hospitalization (N=95,153) or ER use (N=108,576). Factors associated with outpatient mental health follow-up within 7 and 30 days of discharge were determined via logistic models with generalized estimating equations that accounted for state variation. Results: Of those hospitalized, 42.7% received follow-up within 7 days (67.4% within 30 days). Of those with ER use, 28.6% received follow-up within 7 days (46.4% within 30 days). Type of established outpatient care predicted follow-up after hospitalization and ER use. Compared with people with no established care, the likelihood of receiving follow-up within 7 days was highest among those with mental health and primary care (hospitalization, adjusted odds ratio [AOR]=2.81, 95% confidence interval [CI]=2.68-2.94; ER use, AOR=4.06, 95% CI=3.72-4.42), followed by those with mental health care only (hospitalization, AOR=2.57, 95% CI=2.45-2.70; ER use, AOR=3.48, 95% CI=3.17-3.82) and those with primary care only (hospitalization, AOR=1.20, 95% CI=1.15-1.26; ER use, AOR=1.22, 95% CI=1.16-1.28). Similar trends were observed within 30 days of discharge. Conclusions: Follow-up rates after acute mental health service use among youths and young adults were suboptimal. Having established mental health care more strongly predicted receiving follow-up than did having established primary care. Improving engagement with outpatient mental health care providers may increase follow-up rates.
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Comparison of Rapid Antigen Tests' Performance Between Delta and Omicron Variants of SARS-CoV-2 : A Secondary Analysis From a Serial Home Self-testing StudyBackground: It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants. Objective: To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2. Design: Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days. Setting: The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory. Participants: Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy. Measurements: Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result. Results: A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day: Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours: Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity: Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs. Limitation: A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report. Conclusion: The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity. Primary funding source: National Heart, Lung, and Blood Institute of the National Institutes of Health.
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Distinct HIV-1 Population Structure across Meningeal and Peripheral T Cells and Macrophage Lineage CellsHIV-1 sequence population structure among brain and nonbrain cellular compartments is incompletely understood. Here, we compared proviral pol and env high-quality consensus single-molecule real-time (SMRT) sequences derived from CD3+ T cells and CD14+ macrophage lineage cells from meningeal or peripheral (spleen, blood) tissues obtained at autopsy from two individuals with viral suppression on antiretroviral therapy (ART). Phylogenetic analyses showed strong evidence of population structure between CD3+ and CD14+ virus populations. Distinct env variable-region characteristics were also found between CD3+ and CD14+ viruses. Furthermore, shared macrophage-tropic amino acid residues (env) and drug resistance mutations (pol) between meningeal and peripheral virus populations were consistent with the meninges playing a role in viral gene flow across the blood-brain barrier. Overall, our results point toward potential functional differences among meningeal and peripheral CD3+ and CD14+ virus populations and a complex evolutionary history driven by distinct selection pressures and/or viral gene flow. IMPORTANCE Different cell types and/or tissues may serve as a reservoir for HIV-1 during ART-induced viral suppression. We compared proviral pol and env sequences from CD3+ T cells and CD14+ macrophage lineage cells from brain and nonbrain tissues from two virally suppressed individuals. We found strong evidence of viral population structure among cells/tissues, which may result from distinct selective pressures across cell types and anatomic sites.
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Metformin is Associated with Reduced COVID-19 Severity in Patients with Prediabetes [preprint]Background: With the continuing COVID-19 pandemic, identifying medications that improve COVID-19 outcomes is crucial. Studies suggest that use of metformin, an oral antihyperglycemic, is associated with reduced COVID-19 severity in individuals with diabetes compared to other antihyperglycemic medications. Some patients without diabetes, including those with polycystic ovary syndrome (PCOS) and prediabetes, are prescribed metformin for off-label use, which provides an opportunity to further investigate the effect of metformin on COVID-19. Participants: In this observational, retrospective analysis, we leveraged the harmonized electronic health record data from 53 hospitals to construct cohorts of COVID-19 positive, metformin users without diabetes and propensity-weighted control users of levothyroxine (a medication for hypothyroidism that is not known to affect COVID-19 outcome) who had either PCOS (n = 282) or prediabetes (n = 3136). The primary outcome of interest was COVID-19 severity, which was classified as: mild, mild ED (emergency department), moderate, severe, or mortality/hospice. Results: In the prediabetes cohort, metformin use was associated with a lower rate of COVID-19 with severity of mild ED or worse (OR: 0.630, 95% CI 0.450 - 0.882, p < 0.05) and a lower rate of COVID-19 with severity of moderate or worse (OR: 0.490, 95% CI 0.336 - 0.715, p < 0.001). In patients with PCOS, we found no significant association between metformin use and COVID-19 severity, although the number of patients was relatively small. Conclusions: Metformin was associated with less severe COVID-19 in patients with prediabetes, as seen in previous studies of patients with diabetes. This is an important finding, since prediabetes affects between 19 and 38% of the US population, and COVID-19 is an ongoing public health emergency. Further observational and prospective studies will clarify the relationship between metformin and COVID-19 severity in patients with prediabetes, and whether metformin usage may reduce COVID-19 severity.
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Lay Beliefs About Doctors' Knowledge of and Reasons for Recommending COVID-19 VaccinesCommonly cited as the most trusted source of information about COVID-19 vaccines, healthcare providers have an important role in promoting COVID-19 vaccination While a healthcare provider recommendation is associated with greater likelihood of being vaccinated against COVID-193, there is limited understanding of lay beliefs about providers’ knowledge of COVID-19 vaccines and reasons for promoting vaccination.
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Trends in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seroprevalence in Massachusetts Estimated from Newborn Screening SpecimensBackground: Estimating the cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for setting public health policies. We leveraged deidentified Massachusetts newborn screening specimens as an accessible, retrospective source of maternal antibodies for estimating statewide seroprevalence in a nontest-seeking population. Methods: We analyzed 72 117 newborn specimens collected from November 2019 through December 2020, representing 337 towns and cities across Massachusetts. Seroprevalence was estimated for the Massachusetts population after correcting for imperfect test specificity and nonrepresentative sampling using Bayesian multilevel regression and poststratification. Results: Statewide seroprevalence was estimated to be 0.03% (90% credible interval [CI], 0.00-0.11) in November 2019 and rose to 1.47% (90% CI: 1.00-2.13) by May 2020, following sustained SARS-CoV-2 transmission in the spring. Seroprevalence plateaued from May onward, reaching 2.15% (90% CI: 1.56-2.98) in December 2020. Seroprevalence varied substantially by community and was particularly associated with community percent non-Hispanic Black (β = .024; 90% CI: 0.004-0.044); i.e., a 10% increase in community percent non-Hispanic Black was associated with 27% higher odds of seropositivity. Seroprevalence estimates had good concordance with reported case counts and wastewater surveillance for most of 2020, prior to the resurgence of transmission in winter. Conclusions: Cumulative incidence of SARS-CoV-2 protective antibody in Massachusetts was low as of December 2020, indicating that a substantial fraction of the population was still susceptible. Maternal seroprevalence data from newborn screening can inform longitudinal trends and identify cities and towns at highest risk, particularly in settings where widespread diagnostic testing is unavailable.
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Impact of individual and treatment characteristics on wearable sensor-based digital biomarkers of opioid useOpioid use disorder is one of the most pressing public health problems of our time. Mobile health tools, including wearable sensors, have great potential in this space, but have been underutilized. Of specific interest are digital biomarkers, or end-user generated physiologic or behavioral measurements that correlate with health or pathology. The current manuscript describes a longitudinal, observational study of adult patients receiving opioid analgesics for acute painful conditions. Participants in the study are monitored with a wrist-worn E4 sensor, during which time physiologic parameters (heart rate/variability, electrodermal activity, skin temperature, and accelerometry) are collected continuously. Opioid use events are recorded via electronic medical record and self-report. Three-hundred thirty-nine discreet dose opioid events from 36 participant are analyzed among 2070 h of sensor data. Fifty-one features are extracted from the data and initially compared pre- and post-opioid administration, and subsequently are used to generate machine learning models. Model performance is compared based on individual and treatment characteristics. The best performing machine learning model to detect opioid administration is a Channel-Temporal Attention-Temporal Convolutional Network (CTA-TCN) model using raw data from the wearable sensor. History of intravenous drug use is associated with better model performance, while middle age, and co-administration of non-narcotic analgesia or sedative drugs are associated with worse model performance. These characteristics may be candidate input features for future opioid detection model iterations. Once mature, this technology could provide clinicians with actionable data on opioid use patterns in real-world settings, and predictive analytics for early identification of opioid use disorder risk.
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Strategies to improve the recruitment and retention of underserved children and families in clinical trials: A case example of a school-supervised asthma therapy pilotBackground: Due to underrepresentation of racial/ethnic minority and low-income groups in clinical studies, there is a call to improve the recruitment and retention of these populations in research. Pilot studies can test recruitment and retention practices for better inclusion of medically underserved children and families in subsequent clinical trials. We examined this using a school-based asthma intervention, in preparation for a larger clinical trial in which our goal is to include an underserved study population. Methods: We recruited children with poorly controlled asthma in a two-site pilot cluster randomized controlled trial of school-supervised asthma therapy versus enhanced usual care (receipt of an educational asthma workbook). We sought a study population with a high percentage of children and families from racial/ethnic minority and low-income groups. The primary outcome of the pilot trial was recruitment/retention over 12 months. Strategies used to facilitate recruitment/retention of this study population included engaging pre-trial multi-level stakeholders, selecting trial sites with high percentages of underserved children and families, training diverse medical providers to recruit participants, conducting remote trial assessments, and providing multi-lingual study materials. Results: Twenty-six children [42.3% female, 11.5% Black, 30.8% Multiracial (Black & other), 76.9% Hispanic, and 92.3% with family income below $40,000] and their caregivers were enrolled in the study, which represents 55.3% of those initially referred by their provider, with 96.2%, 92.3%, and 96.2% retention at 3-, 6-, and 12-month follow-up, respectively. Conclusion: Targeted strategies facilitated the inclusion of a medically underserved population of children and families in our pilot study, prior to expanding to a larger trial.
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Risk Factors Associated with Post-Acute Sequelae of SARS-CoV-2 in an EHR Cohort: A National COVID Cohort Collaborative (N3C) Analysis as part of the NIH RECOVER program [preprint]Background: More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). Objective: To identify risk factors associated with PASC/long-COVID. Design: Retrospective case-control study. Setting: 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). Patients: 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system. Measurements: Risk factors included demographics, comorbidities, and treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC. Results: Among 8,325 individuals with PASC, the majority were >50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33-1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05-4.73), long (8-30 days, OR 1.69, 95% CI 1.31-2.17) or extended hospital stay (30+ days, OR 3.38, 95% CI 2.45-4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18-1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40-1.60), chronic lung disease (OR 1.63, 95% CI 1.53-1.74), and obesity (OR 1.23, 95% CI 1.16-1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls. Conclusions: This national study identified important risk factors for PASC such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.
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MedML: Fusing medical knowledge and machine learning models for early pediatric COVID-19 hospitalization and severity predictionThe COVID-19 pandemic has caused devastating economic and social disruption. This has led to a nationwide call for models to predict hospitalization and severe illness in patients with COVID-19 to inform the distribution of limited healthcare resources. To address this challenge, we propose a machine learning model, MedML, to conduct the hospitalization and severity prediction for the pediatric population using electronic health records. MedML extracts the most predictive features based on medical knowledge and propensity scores from over 6 million medical concepts and incorporates the inter-feature relationships in medical knowledge graphs via graph neural networks. We evaluate MedML on the National Cohort Collaborative (N3C) dataset. MedML achieves up to a 7% higher AUROC and 14% higher AUPRC compared to the best baseline machine learning models. MedML is a new machine learnig framework to incorporate clinical domain knowledge and is more predictive and explainable than current data-driven methods.
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Association Between Patient Portal Use and Perceived Patient-Centered Communication Among Adults With Cancer: Cross-sectional Survey StudyBackground: Patient-centered communication (PCC) plays a vital role in effective cancer management and care. Patient portals are increasingly available to patients and hold potential as a valuable tool to facilitate PCC. However, whether more frequent use of patient portals is associated with increased perceived PCC and which mechanisms might mediate this relationship have not been fully studied. Objective: The goal of this study was to investigate the association between the frequency of access of patient portals and perceived PCC in patients diagnosed with cancer. We further sought to examine whether this association was mediated by patients' self-efficacy in health information-seeking. Methods: We used data from the Health Information National Trend Survey 5 (HINTS 5) cycle 3 (2019) and cycle 4 (2020). This analysis includes 1222 individuals who self-reported having a current or past diagnosis of cancer. Perceived PCC was measured with a 7-item HINTS 5-derived scale and classified as low, medium, or high. Patient portal use was measured by a single item assessing the frequency of use. Self-efficacy about health information-seeking was assessed with a 1-item measure assessing confidence in obtaining health information. We used adjusted multinomial logistic regression models to estimate relative risk ratios (RRRs)/effect sizes of the association between patient portal use and perceived PCC. Mediation by health information self-efficacy was investigated using the Baron and Kenny and Karlson-Holm-Breen methods. Results: A total of 54.5% of the sample reported that they had not accessed their patient portals in the past 12 months, 12.6% accessed it 1 to 2 times, 24.8% accessed it 3 to 9 times, and 8.2% accessed it 10 or more times. Overall, the frequency of accessing the patient portal was marginally associated (P=.06) with perceived PCC in an adjusted multinominal logistic regression model. Patients who accessed their patient portal 10 or more times in the previous 12 months were almost 4 times more likely (RRR 3.8, 95% CI 1.6-9.0) to report high perceived PCC. In mediation analysis, the association between patient portal use and perceived PCC was attenuated adjusting for health information-seeking self-efficacy, but those with the most frequent patient portal use (10 or more times in the previous 12 months) were still almost 2.5 times more likely to report high perceived PCC (RRR 2.4, 95% CI 1.1-5.6) compared to those with no portal use. Conclusions: Increased frequency of patient portal use was associated with higher PCC, and an individual's health information-seeking self-efficacy partially mediated this association. These findings emphasize the importance of encouraging patients and providers to use patient portals to assist in patient-centeredness of cancer care. Interventions to promote the adoption and use of patient portals could incorporate strategies to improve health information self-efficacy.
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Who is pregnant? defining real-world data-based pregnancy episodes in the National COVID Cohort Collaborative (N3C) [preprint]Objective: To define pregnancy episodes and estimate gestational aging within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C). Materials and methods: We developed a comprehensive approach, named H ierarchy and rule-based pregnancy episode I nference integrated with P regnancy P rogression S ignatures (HIPPS) and applied it to EHR data in the N3C from 1 January 2018 to 7 April 2022. HIPPS combines: 1) an extension of a previously published pregnancy episode algorithm, 2) a novel algorithm to detect gestational aging-specific signatures of a progressing pregnancy for further episode support, and 3) pregnancy start date inference. Clinicians performed validation of HIPPS on a subset of episodes. We then generated three types of pregnancy cohorts based on the level of precision for gestational aging and pregnancy outcomes for comparison of COVID-19 and other characteristics. Results: We identified 628,165 pregnant persons with 816,471 pregnancy episodes, of which 52.3% were live births, 24.4% were other outcomes (stillbirth, ectopic pregnancy, spontaneous abortions), and 23.3% had unknown outcomes. We were able to estimate start dates within one week of precision for 431,173 (52.8%) episodes. 66,019 (8.1%) episodes had incident COVID-19 during pregnancy. Across varying COVID-19 cohorts, patient characteristics were generally similar though pregnancy outcomes differed. Discussion: HIPPS provides support for pregnancy-related variables based on EHR data for researchers to define pregnancy cohorts. Our approach performed well based on clinician validation. Conclusion: We have developed a novel and robust approach for inferring pregnancy episodes and gestational aging that addresses data inconsistency and missingness in EHR data.