Publications by authors named "Kevin Coppa"
Background: COVID-19 is a challenging disease to characterize given its wide-ranging heterogeneous symptomatology. Several studies have attempted to extract clinical phenotypes but often relied on data from small patient cohorts, usually limited to only one viral variant and utilizing a static snapshot of patient data.
Objective: This study aimed to identify clinical phenotypes of hospitalized COVID-19 patients and investigate their longitudinal dynamics throughout the pandemic, with the goal to relate these phenotypes to clinical outcomes and treatment strategies.
Background: Non-arrivals to scheduled ambulatory visits are common and lead to a discontinuity of care, poor health outcomes, and increased subsequent healthcare utilization. Reducing non-arrivals is important given their association with poorer health outcomes and cost to health systems.
Objective: To develop and validate a prediction model for ambulatory non-arrivals.
Clinical prognostic models can assist patient care decisions. However, their performance can drift over time and location, necessitating model monitoring and updating. Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for these drifts.
View Article and Find Full Text PDFBackground: Neutralizing monoclonal antibody (MAB) therapies may benefit patients with mild to moderate COVID-19 at high risk for progressing to severe COVID-19 or hospitalization. Studies documenting approaches to deliver MAB infusions and demonstrating their efficacy are lacking.
Objective: We describe our experience and the outcomes of almost 3000 patients who received MAB infusion therapy at Northwell Health, a large integrated health care system in New York.
There is a need to discriminate which COVID-19 inpatients are at higher risk for venous thromboembolism (VTE) to inform prophylaxis strategies. The IMPROVE-DD VTE risk assessment model (RAM) has previously demonstrated good discrimination in non-COVID populations. We aimed to externally validate the IMPROVE-DD VTE RAM in medical patients hospitalized with COVID-19.
View Article and Find Full Text PDFArticle Synopsis
- The study aims to validate the IMPROVE-DD risk assessment model for identifying venous thromboembolism (VTE) risk in hospitalized COVID-19 patients in a multihospital system.
- Researchers evaluated data from 9,407 hospitalized COVID-19 patients, finding that the VTE rate increased with higher IMPROVE-DD scores, indicating a good correlation between the risk scores and actual VTE occurrence.
- The findings suggest that the IMPROVE-DD model effectively categorizes patients into low, moderate, and high VTE risk, which could help customize thromboprophylactic strategies in clinical settings.
Article Synopsis
- Venous thromboembolism (VTE) has become a significant concern for COVID-19 patients, prompting a study to determine its incidence and mortality rates in a large health system.
- The retrospective analysis involved 10,871 adults diagnosed with COVID-19 from March 1 to April 27, 2020, revealing a 1.09% incidence of symptomatic VTE and a 0.26% mortality rate during initial assessment.
- Factors such as male gender, age, BMI, and certain comorbidities were noted, with the study indicating that statin and antiplatelet medications appeared to lower VTE and mortality risk, suggesting further research on antithrombotic use in high-risk COVID
Objective: To describe the pattern of hydroxychloroquine use and examine the association between hydroxychloroquine use and clinical outcomes arising from changes in the US Food and Drug Administration (FDA)'s recommendation during the coronavirus disease 2019 (COVID-19) pandemic.
Design: A retrospective cross-sectional analysis.
Setting And Participants: We included hospitalised adult patients at Northwell Health hospitals with confirmed COVID-19 infections between 1 March 2020 and 11 May 2020.
Background: We aimed to identify the prevalence and predictors of venous thromboembolism (VTE) or mortality in hospitalized coronavirus disease 2019 (COVID-19) patients.
Methods: A retrospective cohort study of hospitalized adult patients admitted to an integrated health care network in the New York metropolitan region between March 1, 2020 and April 27, 2020. The final analysis included 9,407 patients with an overall VTE rate of 2.
Background: Post-hospital discharge follow-up appointments are intended to evaluate patients' recovery following a hospitalization, but it is unclear how appointment statuses are associated with readmissions.
Objective: To examine the association between post-discharge ambulatory follow-up status, (1) having a scheduled appointment and (2) arriving to said appointment, and 30-day readmission.
Design And Setting: A retrospective cohort study of patients hospitalized at 12 hospitals in an Integrated Delivery Network and their ambulatory appointments in that same network.
Background And Aims: Gastrointestinal (GI) bleeding has been observed amongst patients hospitalized with COVID-19. Recently, anticoagulation has shown to decrease mortality, but it is unclear whether this contributes to increased GI bleeding. The aims of this study are: (i) to examine whether there are risk factors for GI bleeding in COVID-19 patients and (ii) to study whether there is a mortality difference between hospitalized patients with COVID-19 with and without GI bleeding.
View Article and Find Full Text PDFBackground: The number of cases from the coronavirus disease 2019 (COVID-19) global pandemic has overwhelmed existing medical facilities and forced clinicians, patients, and families to make pivotal decisions with limited time and information.
Main Body: While machine learning (ML) methods have been previously used to augment clinical decisions, there is now a demand for "Emergency ML." Throughout the patient care pathway, there are opportunities for ML-supported decisions based on collected vitals, laboratory results, medication orders, and comorbidities.
Background: Chinese studies reported predictors of severe disease and mortality associated with coronavirus disease 2019 (COVID-19). A generalizable and simple survival calculator based on data from US patients hospitalized with COVID-19 has not yet been introduced.
Objective: Develop and validate a clinical tool to predict 7-day survival in patients hospitalized with COVID-19.
Importance: There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).
Objective: To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system.
Design, Setting, And Participants: Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system.