Dataset Information

3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19.

ABSTRACT: Hypercoagulability is a recognized feature in SARS-CoV-2 infection. There exists a need for a dedicated risk assessment model (RAM) that can risk-stratify hospitalized COVID-19 patients for venous thromboembolism (VTE) and guide anticoagulation. We aimed to build a simple clinical model to predict VTE in COVID-19 patients. This large-cohort, retrospective study included adult patients admitted to four hospitals with PCR-confirmed SARS-CoV-2 infection. Model training was performed on 3531 patients hospitalized between March and December 2020 and validated on 2508 patients hospitalized between January and September 2021. Diagnosis of VTE was defined as acute deep vein thrombosis (DVT) or pulmonary embolism (PE). The novel RAM was based on commonly available parameters at hospital admission. LASSO regression and logistic regression were performed, risk scores were assigned to the significant variables, and cutoffs were derived. Seven variables with assigned scores were delineated as: DVT History = 2; High D-Dimer (>500-2000 ng/mL) = 2; Very High D-Dimer (>2000 ng/mL) = 5; PE History = 2; Low Albumin (<3.5 g/dL) = 1; Systolic Blood Pressure <120 mmHg = 1, Tachycardia (heart rate >100 bpm) = 1. The model had a sensitivity of 83% and specificity of 53%. This simple, robust clinical tool can help individualize thromboprophylaxis for COVID-19 patients based on their VTE risk category.

SUBMITTER: Lee Y

PROVIDER: S-EPMC9325096 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19.

Lee Yi Y Jehangir Qasim Q Lin Chun-Hui CH Li Pin P Sule Anupam A AA Poisson Laila L Balijepally Venugopal V Halabi Abdul R AR Patel Kiritkumar K Krishnamoorthy Geetha G Nair Girish B GB

Journal of clinical medicine 20220707 14

Hypercoagulability is a recognized feature in SARS-CoV-2 infection. There exists a need for a dedicated risk assessment model (RAM) that can risk-stratify hospitalized COVID-19 patients for venous thromboembolism (VTE) and guide anticoagulation. We aimed to build a simple clinical model to predict VTE in COVID-19 patients. This large-cohort, retrospective study included adult patients admitted to four hospitals with PCR-confirmed SARS-CoV-2 infection. Model training was performed on 3531 patient ...[more]

PMID: 35887713

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Project description:ImportancePatients hospitalized with COVID-19 have higher rates of venous thromboembolism (VTE), but the risk and predictors of VTE among individuals with less severe COVID-19 managed in outpatient settings are less well understood.ObjectivesTo assess the risk of VTE among outpatients with COVID-19 and identify independent predictors of VTE.Design, setting, and participantsA retrospective cohort study was conducted at 2 integrated health care delivery systems in Northern and Southern California. Data for this study were obtained from the Kaiser Permanente Virtual Data Warehouse and electronic health records. Participants included nonhospitalized adults aged 18 years or older with COVID-19 diagnosed between January 1, 2020, and January 31, 2021, with follow-up through February 28, 2021.ExposuresPatient demographic and clinical characteristics identified from integrated electronic health records.Main outcomes and measuresThe primary outcome was the rate per 100 person-years of diagnosed VTE, which was identified using an algorithm based on encounter diagnosis codes and natural language processing. Multivariable regression using a Fine-Gray subdistribution hazard model was used to identify variables independently associated with VTE risk. Multiple imputation was used to address missing data.ResultsA total of 398 530 outpatients with COVID-19 were identified. The mean (SD) age was 43.8 (15.8) years, 53.7% were women, and 54.3% were of self-reported Hispanic ethnicity. There were 292 (0.1%) VTE events identified over the follow-up period, for an overall rate of 0.26 (95% CI, 0.24-0.30) per 100 person-years. The sharpest increase in VTE risk was observed during the first 30 days after COVID-19 diagnosis (unadjusted rate, 0.58; 95% CI, 0.51-0.67 per 100 person-years vs 0.09; 95% CI, 0.08-0.11 per 100 person-years after 30 days). In multivariable models, the following variables were associated with a higher risk for VTE in the setting of nonhospitalized COVID-19: age 55 to 64 years (HR 1.85 [95% CI, 1.26-2.72]), 65 to 74 years (3.43 [95% CI, 2.18-5.39]), 75 to 84 years (5.46 [95% CI, 3.20-9.34]), greater than or equal to 85 years (6.51 [95% CI, 3.05-13.86]), male gender (1.49 [95% CI, 1.15-1.96]), prior VTE (7.49 [95% CI, 4.29-13.07]), thrombophilia (2.52 [95% CI, 1.04-6.14]), inflammatory bowel disease (2.43 [95% CI, 1.02-5.80]), body mass index 30.0-39.9 (1.57 [95% CI, 1.06-2.34]), and body mass index greater than or equal to 40.0 (3.07 [1.95-4.83]).Conclusions and relevanceIn this cohort study of outpatients with COVID-19, the absolute risk of VTE was low. Several patient-level factors were associated with higher VTE risk; these findings may help identify subsets of patients with COVID-19 who may benefit from more intensive surveillance or VTE preventive strategies.

Dataset Information

3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19.

Publications

3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19.

Similar Datasets

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