Development and Validation of a Two-Step Predictive Risk Stratification Model for Coronavirus Disease 2019 In-hospital Mortality: A Multicenter Retrospective Cohort Study.

MedStar author(s):
Citation: Frontiers in Medicine. 9:827261, 2022.PMID: 35463024Institution: MedStar Washington Hospital CenterDepartment: Emergency MedicineForm of publication: Journal ArticleMedline article type(s): Journal ArticleYear: 2022ISSN:
  • 2296-858X
Name of journal: Frontiers in medicineAbstract: Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice. Copyright © 2022 Li, Kong, Ebell, Martinez, Cai, Lennon, Tarn, Mainous, Zgierska, Barrett, Tuan, Maloy, Goyal, Krist, Gal, Sung, Li, Jin and Shen.Design: Multicenter retrospective observational cohort study.Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate >=30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score.Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information.Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients.Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles.All authors: Li Y, Kong Y, Ebell MH, Martinez L, Cai X, Lennon RP, Tarn DM, Mainous AG, Zgierska AE, Barrett B, Tuan WJ, Maloy K, Goyal M, Krist AH, Gal TS, Sung MH, Li C, Jin Y, Shen YFiscal year: FY2022Digital Object Identifier: Date added to catalog: 2023-06-26
No physical items for this record

Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice. Copyright © 2022 Li, Kong, Ebell, Martinez, Cai, Lennon, Tarn, Mainous, Zgierska, Barrett, Tuan, Maloy, Goyal, Krist, Gal, Sung, Li, Jin and Shen.

Design: Multicenter retrospective observational cohort study.

Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate >=30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score.

Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information.

Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients.

Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles.

English

Powered by Koha