ImportanceThe COVID-19 pandemic has been associated with an increase in mental health diagnoses a... more ImportanceThe COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents.ObjectiveTo estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic.Design, Setting, and ParticipantsThis retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children’s hospitals in the US and France.Main Outcomes and MeasuresChange in the mo...
Background. In electronic health records, patterns of missing laboratory test results could captu... more Background. In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to characterize the patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. Methods. We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. Results. With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. Conclusion. This work elucidates how missing data patterns in EHRs can be leveraged to identify quality control issues and relationships between laboratory measurements. Missing data patterns will allow sites to attain better quality data for subsequent analyses and help researchers identify which sites are better poised to study particular questions. Our results could also provide insight into some of the biological relationships between labs in EHR data for COVID-19 patients. .
International Journal of Scientific Reports, Nov 22, 2022
INTRODUCTION Guillain-Barré syndrome (GBS), an acute, immunemediated paralysing, inflammatory per... more INTRODUCTION Guillain-Barré syndrome (GBS), an acute, immunemediated paralysing, inflammatory peripheral nerve disease, is an uncommon disease of the nerves outside the brain and spinal cord. 1,2 It is characterized by weakness and numbness of the limbs, facial and respiratory muscles. The common pathogenesis includes multifocal inflammation of spinal roots and peripheral nerves, especially their myelin sheaths. 2-4 GBS has a global median annual incidence of 1.11 (range: 0.81-1.89) cases per 100,000 persons. 5 The GBS has been traditionally used interchangeably with acute inflammatory demyelinating polyradiculoneuropathy (AIDP) for several years, until the recent evidence suggested that AIDP is a subtype of GBS among others. The GBS is considered as group of several immune polyneuropathies that leads to generalized weakness with different etiopathogenesis. Among these, the axonal subtypes of GBS include acute motor axonal neuropathy (AMAN) and acute motor-sensory axonal neuropathy (AMSAN). Furthermore, several other subtypes of GBS, have been reported. 6 The AIDP subtype of GBS is predominantly observed in Europe and North America whereas in Asian countries, AMAN is the most common subtype. 7
Background While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI... more Background While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (
International Journal Of Community Medicine And Public Health
Background: Objectives of the study was to describe the utilization pattern of systemic antifunga... more Background: Objectives of the study was to describe the utilization pattern of systemic antifungal agents in Indian patients with invasive fungal infections (IFIs).Methods: This real-world, multicenter (127 centers), retrospective analysis included data of patients receiving systemic antifungal medications at various centers across India. The study data was collected between April 2021 and March 2022.Results: Data of a total of 323 patients was analyzed. The mean age of patients was 54±13.52 years. There was male preponderance seen in this study (72.4%). Diabetes was the most common comorbidity (36.8%) followed by concomitant diabetes and hypertension (31.9%), hypertension (9.6%) and hematological malignancies (9.6%). The most common indication occurring in >10% of the patients and for whom systemic antifungals were used included pulmonary mucormycosis (33.1%) followed by invasive candidiasis (16.1%), sepsis (13.3%) and fungal pneumonia (11.8%). In total 323 patients, the most co...
Background: The objectives of the study were to describe the demographics and utilization pattern... more Background: The objectives of the study were to describe the demographics and utilization pattern of tacrolimus (TAC)-based immunosuppressive regimens in recipients with solid organ transplant in India.Methods: This real-world, multicenter (134 centers), retrospective analysis included data of solid organ transplant recipients between 2010 and 2022 who had received TAC-based immunosuppressive therapy. The study data was collected between April 2021 and March 2022.Results: Data of a total of 1022 recipients with kidney transplant (KT, n=899) or liver transplant (LT, n=123) who received TAC-based immunosuppression was analyzed. The mean age of recipients among KT and LT was 41.04±10.62 and 42.88±11.32 years, respectively. The most common diseases leading to end stage organ failure were diabetes (24.7%), hypertension (15.8%), concomitant diabetes and hypertension (14.9%), chronic kidney disease (9.2%), nephrotic syndrome (5%), and end stage renal disease (ESRD, 4.4%) in KT recipients, ...
BackgroundIn electronic health records, patterns of missing laboratory test results could capture... more BackgroundIn electronic health records, patterns of missing laboratory test results could capture patients’ course of disease as well as reflect clinician’s concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to characterize the patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients.MethodsWe collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern.ResultsWith these analyses, we identified mapping issues faced in seven out of 15 s...
ObjectiveTo assess changes in international mortality rates and laboratory recovery rates during ... more ObjectiveTo assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic.Design, setting and participantsThis is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic.Primary and secondary outcome measuresThe primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the avera...
Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we eva... more Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size ...
Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress s... more Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. Methods : A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. Results : Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS ( 7.8% of young hospitalized adults). Their ...
ObjectiveFor multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and hig... more ObjectiveFor 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 a set of health care centers without sharing patient-level information.Materials and MethodsFor each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or can be a single center, corresponding to transfer learning.ResultsSimulation studies and a real-world international electronic health re...
Journal of the American Medical Informatics Association, 2021
Objective The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Network... more Objective The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Networks capture healthcare utilization within their health systems. Here, we describe a reusable environment (GPC Reusable Observable Unified Study Environment [GROUSE]) that integrates hospital and electronic health records (EHRs) data with state-wide Medicare and Medicaid claims and assess how claims and clinical data complement each other to identify obesity and related comorbidities in a patient sample. Materials and Methods EHR, billing, and tumor registry data from 7 healthcare systems were integrated with Center for Medicare (2011–2016) and Medicaid (2011–2012) services insurance claims to create deidentified databases in Informatics for Integrating Biology & the Bedside and PCORnet Common Data Model formats. We describe technical details of how this federally compliant, cloud-based data environment was built. As a use case, trends in obesity rates for different age groups are reported,...
UNSTRUCTURED Authorship Correction: International Changes in COVID-19 Clinical Trajectories Acros... more UNSTRUCTURED Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study In “International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort 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 the last three authors was not noted. To correct this under the JMIR parameters allowing only one equal contribution footnote, we are implementing the following changes. In the originally published paper, equal contribution was noted as: “Griffin M Weber MD, PhD1*, Harrison G Zhang1*, Sehi L'Yi PhD1*,… *These authors contributed equally” This has been corrected to: “Griffin M Weber MD, PhD1*, Harrison G Zhang1*, Sehi L'Yi PhD1*,… Tianxi Cai ScD1*‡, Andrew M South MD, MS36*, Gabriel A Brat MD, MPH1*… *These authors contributed equally” Additionally, the Authors...
Clinical data networks that leverage large volumes of data in electronic health records (EHRs) ar... more Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that are critical to COVID-19 research. The ontology contains over 50 000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for severe acute respiratory syndrome coronavirus 2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of 9 academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community...
Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological ... more Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalizat...
IMPORTANCE Additional sources of pediatric epidemiological and clinical data are needed to effici... more IMPORTANCE Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. OBJECTIVE To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. MAIN OUTCOMES AND MEASURES Patient characteristics, clinical features, and medication use. RESULTS There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0-to 2-year (199 patients [30%]) and 12-to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. CONCLUSIONS AND RELEVANCE This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and (continued) Key Points Question What are international trends in hospitalizations for children and youth with SARS-CoV-2, and what are the epidemiological and clinical features of these patients? Findings This cohort study of 671 children and youth found discrete surges in hospitalizations with variable trends and timing across countries. Common complications included cardiac arrhythmias and viral pneumonia, and laboratory findings included elevations in markers of inflammation and abnormalities of coagulation; few children and youth were treated with medications directed specifically at SARS-CoV-2. Meaning These findings suggest largescale informatics-based approaches used to incorporate electronic health record data across health care systems can provide an efficient source of information to monitor disease activity and define epidemiological and clinical features of pediatric patients hospitalized with SARS-CoV-2 infections.
Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been... more Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. Methods In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3–6 and 6–9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in...
ImportanceThe COVID-19 pandemic has been associated with an increase in mental health diagnoses a... more ImportanceThe COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents.ObjectiveTo estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic.Design, Setting, and ParticipantsThis retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children’s hospitals in the US and France.Main Outcomes and MeasuresChange in the mo...
Background. In electronic health records, patterns of missing laboratory test results could captu... more Background. In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to characterize the patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. Methods. We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. Results. With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. Conclusion. This work elucidates how missing data patterns in EHRs can be leveraged to identify quality control issues and relationships between laboratory measurements. Missing data patterns will allow sites to attain better quality data for subsequent analyses and help researchers identify which sites are better poised to study particular questions. Our results could also provide insight into some of the biological relationships between labs in EHR data for COVID-19 patients. .
International Journal of Scientific Reports, Nov 22, 2022
INTRODUCTION Guillain-Barré syndrome (GBS), an acute, immunemediated paralysing, inflammatory per... more INTRODUCTION Guillain-Barré syndrome (GBS), an acute, immunemediated paralysing, inflammatory peripheral nerve disease, is an uncommon disease of the nerves outside the brain and spinal cord. 1,2 It is characterized by weakness and numbness of the limbs, facial and respiratory muscles. The common pathogenesis includes multifocal inflammation of spinal roots and peripheral nerves, especially their myelin sheaths. 2-4 GBS has a global median annual incidence of 1.11 (range: 0.81-1.89) cases per 100,000 persons. 5 The GBS has been traditionally used interchangeably with acute inflammatory demyelinating polyradiculoneuropathy (AIDP) for several years, until the recent evidence suggested that AIDP is a subtype of GBS among others. The GBS is considered as group of several immune polyneuropathies that leads to generalized weakness with different etiopathogenesis. Among these, the axonal subtypes of GBS include acute motor axonal neuropathy (AMAN) and acute motor-sensory axonal neuropathy (AMSAN). Furthermore, several other subtypes of GBS, have been reported. 6 The AIDP subtype of GBS is predominantly observed in Europe and North America whereas in Asian countries, AMAN is the most common subtype. 7
Background While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI... more Background While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (
International Journal Of Community Medicine And Public Health
Background: Objectives of the study was to describe the utilization pattern of systemic antifunga... more Background: Objectives of the study was to describe the utilization pattern of systemic antifungal agents in Indian patients with invasive fungal infections (IFIs).Methods: This real-world, multicenter (127 centers), retrospective analysis included data of patients receiving systemic antifungal medications at various centers across India. The study data was collected between April 2021 and March 2022.Results: Data of a total of 323 patients was analyzed. The mean age of patients was 54±13.52 years. There was male preponderance seen in this study (72.4%). Diabetes was the most common comorbidity (36.8%) followed by concomitant diabetes and hypertension (31.9%), hypertension (9.6%) and hematological malignancies (9.6%). The most common indication occurring in >10% of the patients and for whom systemic antifungals were used included pulmonary mucormycosis (33.1%) followed by invasive candidiasis (16.1%), sepsis (13.3%) and fungal pneumonia (11.8%). In total 323 patients, the most co...
Background: The objectives of the study were to describe the demographics and utilization pattern... more Background: The objectives of the study were to describe the demographics and utilization pattern of tacrolimus (TAC)-based immunosuppressive regimens in recipients with solid organ transplant in India.Methods: This real-world, multicenter (134 centers), retrospective analysis included data of solid organ transplant recipients between 2010 and 2022 who had received TAC-based immunosuppressive therapy. The study data was collected between April 2021 and March 2022.Results: Data of a total of 1022 recipients with kidney transplant (KT, n=899) or liver transplant (LT, n=123) who received TAC-based immunosuppression was analyzed. The mean age of recipients among KT and LT was 41.04±10.62 and 42.88±11.32 years, respectively. The most common diseases leading to end stage organ failure were diabetes (24.7%), hypertension (15.8%), concomitant diabetes and hypertension (14.9%), chronic kidney disease (9.2%), nephrotic syndrome (5%), and end stage renal disease (ESRD, 4.4%) in KT recipients, ...
BackgroundIn electronic health records, patterns of missing laboratory test results could capture... more BackgroundIn electronic health records, patterns of missing laboratory test results could capture patients’ course of disease as well as reflect clinician’s concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to characterize the patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients.MethodsWe collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern.ResultsWith these analyses, we identified mapping issues faced in seven out of 15 s...
ObjectiveTo assess changes in international mortality rates and laboratory recovery rates during ... more ObjectiveTo assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic.Design, setting and participantsThis is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic.Primary and secondary outcome measuresThe primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the avera...
Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we eva... more Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size ...
Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress s... more Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. Methods : A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. Results : Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS ( 7.8% of young hospitalized adults). Their ...
ObjectiveFor multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and hig... more ObjectiveFor 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 a set of health care centers without sharing patient-level information.Materials and MethodsFor each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or can be a single center, corresponding to transfer learning.ResultsSimulation studies and a real-world international electronic health re...
Journal of the American Medical Informatics Association, 2021
Objective The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Network... more Objective The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Networks capture healthcare utilization within their health systems. Here, we describe a reusable environment (GPC Reusable Observable Unified Study Environment [GROUSE]) that integrates hospital and electronic health records (EHRs) data with state-wide Medicare and Medicaid claims and assess how claims and clinical data complement each other to identify obesity and related comorbidities in a patient sample. Materials and Methods EHR, billing, and tumor registry data from 7 healthcare systems were integrated with Center for Medicare (2011–2016) and Medicaid (2011–2012) services insurance claims to create deidentified databases in Informatics for Integrating Biology & the Bedside and PCORnet Common Data Model formats. We describe technical details of how this federally compliant, cloud-based data environment was built. As a use case, trends in obesity rates for different age groups are reported,...
UNSTRUCTURED Authorship Correction: International Changes in COVID-19 Clinical Trajectories Acros... more UNSTRUCTURED Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study In “International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort 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 the last three authors was not noted. To correct this under the JMIR parameters allowing only one equal contribution footnote, we are implementing the following changes. In the originally published paper, equal contribution was noted as: “Griffin M Weber MD, PhD1*, Harrison G Zhang1*, Sehi L'Yi PhD1*,… *These authors contributed equally” This has been corrected to: “Griffin M Weber MD, PhD1*, Harrison G Zhang1*, Sehi L'Yi PhD1*,… Tianxi Cai ScD1*‡, Andrew M South MD, MS36*, Gabriel A Brat MD, MPH1*… *These authors contributed equally” Additionally, the Authors...
Clinical data networks that leverage large volumes of data in electronic health records (EHRs) ar... more Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that are critical to COVID-19 research. The ontology contains over 50 000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for severe acute respiratory syndrome coronavirus 2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of 9 academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community...
Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological ... more Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalizat...
IMPORTANCE Additional sources of pediatric epidemiological and clinical data are needed to effici... more IMPORTANCE Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. OBJECTIVE To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. MAIN OUTCOMES AND MEASURES Patient characteristics, clinical features, and medication use. RESULTS There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0-to 2-year (199 patients [30%]) and 12-to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. CONCLUSIONS AND RELEVANCE This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and (continued) Key Points Question What are international trends in hospitalizations for children and youth with SARS-CoV-2, and what are the epidemiological and clinical features of these patients? Findings This cohort study of 671 children and youth found discrete surges in hospitalizations with variable trends and timing across countries. Common complications included cardiac arrhythmias and viral pneumonia, and laboratory findings included elevations in markers of inflammation and abnormalities of coagulation; few children and youth were treated with medications directed specifically at SARS-CoV-2. Meaning These findings suggest largescale informatics-based approaches used to incorporate electronic health record data across health care systems can provide an efficient source of information to monitor disease activity and define epidemiological and clinical features of pediatric patients hospitalized with SARS-CoV-2 infections.
Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been... more Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. Methods In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3–6 and 6–9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in...
Uploads
Papers by Lav Patel