High Systolic Blood Pressure at Hospital Admission Is an Important Risk Factor in Models Predicting Outcome of COVID-19 Patients.


Journal

American journal of hypertension
ISSN: 1941-7225
Titre abrégé: Am J Hypertens
Pays: United States
ID NLM: 8803676

Informations de publication

Date de publication:
02 04 2021
Historique:
received: 25 11 2020
revised: 23 12 2020
accepted: 28 12 2020
pubmed: 3 1 2021
medline: 23 4 2021
entrez: 2 1 2021
Statut: ppublish

Résumé

The risk that coronavirus disease 2019 (COVID-19) patients develop critical illness that can be fatal depends on their age and immune status and may also be affected by comorbidities like hypertension. The goal of this study was to develop models that predict outcome using parameters collected at admission to the hospital. This is a retrospective single-center cohort study of COVID-19 patients at the Seventh Hospital of Wuhan City, China. Forty-three demographic, clinical, and laboratory parameters collected at admission plus discharge/death status, days from COVID-19 symptoms onset, and days of hospitalization were analyzed. From 157 patients, 120 were discharged and 37 died. Pearson correlations showed that hypertension and systolic blood pressure (SBP) were associated with death and respiratory distress parameters. A penalized logistic regression model efficiently predicts the probability of death with 13 of 43 variables. A regularized Cox regression model predicts the probability of survival with 7 of above 13 variables. SBP but not hypertension was a covariate in both mortality and survival prediction models. SBP was elevated in deceased compared with discharged COVID-19 patients. Using an unbiased approach, we developed models predicting outcome of COVID-19 patients based on data available at hospital admission. This can contribute to evidence-based risk prediction and appropriate decision-making at hospital triage to provide the most appropriate care and ensure the best patient outcome. High SBP, a cause of end-organ damage and an important comorbid factor, was identified as a covariate in both mortality and survival prediction models.

Sections du résumé

BACKGROUND
The risk that coronavirus disease 2019 (COVID-19) patients develop critical illness that can be fatal depends on their age and immune status and may also be affected by comorbidities like hypertension. The goal of this study was to develop models that predict outcome using parameters collected at admission to the hospital.
METHODS AND RESULTS
This is a retrospective single-center cohort study of COVID-19 patients at the Seventh Hospital of Wuhan City, China. Forty-three demographic, clinical, and laboratory parameters collected at admission plus discharge/death status, days from COVID-19 symptoms onset, and days of hospitalization were analyzed. From 157 patients, 120 were discharged and 37 died. Pearson correlations showed that hypertension and systolic blood pressure (SBP) were associated with death and respiratory distress parameters. A penalized logistic regression model efficiently predicts the probability of death with 13 of 43 variables. A regularized Cox regression model predicts the probability of survival with 7 of above 13 variables. SBP but not hypertension was a covariate in both mortality and survival prediction models. SBP was elevated in deceased compared with discharged COVID-19 patients.
CONCLUSIONS
Using an unbiased approach, we developed models predicting outcome of COVID-19 patients based on data available at hospital admission. This can contribute to evidence-based risk prediction and appropriate decision-making at hospital triage to provide the most appropriate care and ensure the best patient outcome. High SBP, a cause of end-organ damage and an important comorbid factor, was identified as a covariate in both mortality and survival prediction models.

Identifiants

pubmed: 33386395
pii: 6056792
doi: 10.1093/ajh/hpaa225
pmc: PMC7799245
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

282-290

Informations de copyright

© American Journal of Hypertension, Ltd 2021. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Auteurs

Antoine Caillon (A)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.

Kaiqiong Zhao (K)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.

Kathleen Oros Klein (KO)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.

Celia M T Greenwood (CMT)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.
Department of Oncology, McGill University, Montréal, Québec, Canada.
Department of Human Genetics, McGill University, Montréal, Québec, Canada.
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.

Zhibing Lu (Z)

Department of Cardiology, Zhongnan Hospital of Wuhan University, Hubei, China.

Pierre Paradis (P)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.

Ernesto L Schiffrin (EL)

Lady Davis Institute for Medical Research, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.
Department of Medicine, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montréal, Québec, Canada.

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Classifications MeSH