Sarah E. Maidlow
A5082523862- COVID-19 Clinical Research Studies
- Long-Term Effects of COVID-19
- COVID-19 and healthcare impacts
- Advanced Causal Inference Techniques
- Statistical Methods and Bayesian Inference
- Thermal Regulation in Medicine
- Chronic Disease Management Strategies
- Statistical Methods and Inference
- Intensive Care Unit Cognitive Disorders
- Kawasaki Disease and Coronary Complications
- Biomedical Text Mining and Ontologies
- Medical Coding and Health Information
- Healthcare Systems and Reforms
- Childhood Cancer Survivors' Quality of Life
- Inflammasome and immune disorders
- COVID-19 Digital Contact Tracing
- Adolescent and Pediatric Healthcare
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Acute Kidney Injury Research
- Mechanical Circulatory Support Devices
- Global Cancer Incidence and Screening
- Psychosomatic Disorders and Their Treatments
- COVID-19 diagnosis using AI
- Genomics and Rare Diseases
- Sepsis Diagnosis and Treatment
University of Michigan
2021-2023
Collaborative Research Group
2021
Cohort (United Kingdom)
2021
The National COVID Cohort Collaborative (N3C) is a centralized, harmonized, high-granularity electronic health record repository that the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools inform clinical care policy.
Abstract Objective In response to COVID-19, the informatics community united aggregate as much clinical data possible characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now largest publicly available HIPAA limited dataset in US history with over 6.4 million patients a testament partnership of 100 organizations. Materials Methods We developed pipeline for ingesting, harmonizing, centralizing from 56...
While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI function recovery and the clinical factors associated with poor lacking.
Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across variants. We aimed to investigate clinical characteristics and outcomes eras.
The risk profiles of post-acute sequelae COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients COVID-19, 2.3 million control without the inpatient and outpatient settings, over 221 diagnosis codes to systematically identify new-onset conditions enriched among during period. Compared controls, cases were at significant for angina...
Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories patients hospitalized in separate pandemic enables further understanding evolving epidemiology, pathophysiology, and health care dynamics COVID-19 pandemic. In this retrospective cohort study, we analyzed electronic record (EHR) data from with SARS-CoV-2 infections participating systems representing 315 hospitals across 6 countries. We compared hospitalization rates,...
Abstract Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated transportability a mortality algorithm using multi-national network healthcare systems. We predicted baseline commonly measured laboratory values and standard demographic clinical covariates across systems, countries, continents. Specifically, trained Cox regression model with nine test values, demographics at admission, comorbidity burden pre-admission. These models were compared...
Objective To assess changes in international mortality rates and laboratory recovery during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) second July 2020 31 January 2021) of COVID-19 pandemic. Design, setting participants This is a retrospective cohort study 83 178 admitted 7 days before or 14 after PCR-confirmed infection within Consortium Clinical Characterization by Electronic Health Record, an multihealthcare system...
Abstract Objective For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from set of health care centers without sharing patient-level information. Materials Methods each which want borrow improve prediction performance population, penalized is fitted center. Using estimated covariance matrix then...
<sec> <title>BACKGROUND</title> Many countries have experienced 2 predominant waves of COVID-19–related hospitalizations. Comparing the clinical trajectories patients hospitalized in separate pandemic enables further understanding evolving epidemiology, pathophysiology, and health care dynamics COVID-19 pandemic. </sec> <title>OBJECTIVE</title> In this retrospective cohort study, we analyzed electronic record (EHR) data from with SARS-CoV-2 infections participating systems representing 315...
Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across variants. We aimed to investigate clinical characteristics and outcomes eras.Methods: performed multicenter observational retrospective study including seven pediatric hospitals four countries. All consecutive confirmed patients hospitalized between February 2020 May 2022 were included. Electronic Health Records (EHR) data...
<sec> <title>UNSTRUCTURED</title> Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study In “International Study” (J Med Internet Res 2021 Oct 11;23(10):e31400. doi: 10.2196/31400), two errors were noted. Due to a system error, the equal contribution of last three authors was not To correct this under JMIR parameters allowing only one footnote, we are implementing following changes. originally published...