Cargando…

Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study

BACKGROUND: Several laboratory data have been identified as predictors of disease severity or mortality in COVID-19 patients. However, the relative strength of laboratory data for the prediction of health outcomes in COVID-19 patients has not been fully explored. This meta-analytical study aimed to...

Descripción completa

Detalles Bibliográficos
Autores principales: Lai, Kuan-Lang, Hu, Fu-Chang, Wen, Fang-Yu, Chen, Ju-Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Society of Global Health 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480861/
https://www.ncbi.nlm.nih.gov/pubmed/36112520
http://dx.doi.org/10.7189/jogh.12.05041
_version_ 1784791136778321920
author Lai, Kuan-Lang
Hu, Fu-Chang
Wen, Fang-Yu
Chen, Ju-Ju
author_facet Lai, Kuan-Lang
Hu, Fu-Chang
Wen, Fang-Yu
Chen, Ju-Ju
author_sort Lai, Kuan-Lang
collection PubMed
description BACKGROUND: Several laboratory data have been identified as predictors of disease severity or mortality in COVID-19 patients. However, the relative strength of laboratory data for the prediction of health outcomes in COVID-19 patients has not been fully explored. This meta-analytical study aimed to evaluate the prediction capabilities of laboratory data on the prognosis of COVID-19 patients during 2020 while mass vaccination has not started yet. METHODS: Two electronic databases, MEDLINE and EMBASE, from inception to October 10, 2020 were searched. Observational studies of laboratory-confirmed COVID-19 patients with well-defined severity or survival status, and with the desired laboratory data at initial hospital administrations, were selected. Meta-regression analysis with the generalized estimating equations (GEE) method for clustered data was performed sequentially. Primary outcome measures were to compare the level of laboratory data and their impact on different health outcomes (severe vs non-severe, critically severe vs non-critically severe, and dead vs alive). RESULTS: Meta-data of 13 clinical laboratory items at initial hospital presentations were extracted from 76 selected studies with a total of 26 627 COVID-19 patients in 16 countries. After adjusting for the effect of age, 1.03 <lymphocyte count mean or median ( × 10(9)/L) ≤2.06 (estimated odds ratio (OR) = 0.0216; 95% confidence interval (CI) = 0.0041-0.1131; P < 0.0001), higher lymphocyte count mean or median ( × 10(9)/L) (OR <0.0001; 95% CI: <0.0001-0.0386; P = 0.0284), and lymphocyte count mean or median ( × 10(9)/L) >0.87 (OR = 0.0576; 95% CI = 0.0043-0.4726; P = 0.0079) had a much lower risk of severity, critical severity, and mortality from COVID-19, respectively. CONCLUSIONS: Lymphocyte count was the most powerful predictor among the 13 common laboratory variables explored from COVID-19 patients to differentiate disease severity and to predict mortality. Lymphocyte count should be monitored for the prognoses of COVID-19 patients in clinical settings in particular for patients not fully vaccinated.
format Online
Article
Text
id pubmed-9480861
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher International Society of Global Health
record_format MEDLINE/PubMed
spelling pubmed-94808612022-09-20 Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study Lai, Kuan-Lang Hu, Fu-Chang Wen, Fang-Yu Chen, Ju-Ju J Glob Health Research Theme 1: COVID-19 Pandemic BACKGROUND: Several laboratory data have been identified as predictors of disease severity or mortality in COVID-19 patients. However, the relative strength of laboratory data for the prediction of health outcomes in COVID-19 patients has not been fully explored. This meta-analytical study aimed to evaluate the prediction capabilities of laboratory data on the prognosis of COVID-19 patients during 2020 while mass vaccination has not started yet. METHODS: Two electronic databases, MEDLINE and EMBASE, from inception to October 10, 2020 were searched. Observational studies of laboratory-confirmed COVID-19 patients with well-defined severity or survival status, and with the desired laboratory data at initial hospital administrations, were selected. Meta-regression analysis with the generalized estimating equations (GEE) method for clustered data was performed sequentially. Primary outcome measures were to compare the level of laboratory data and their impact on different health outcomes (severe vs non-severe, critically severe vs non-critically severe, and dead vs alive). RESULTS: Meta-data of 13 clinical laboratory items at initial hospital presentations were extracted from 76 selected studies with a total of 26 627 COVID-19 patients in 16 countries. After adjusting for the effect of age, 1.03 <lymphocyte count mean or median ( × 10(9)/L) ≤2.06 (estimated odds ratio (OR) = 0.0216; 95% confidence interval (CI) = 0.0041-0.1131; P < 0.0001), higher lymphocyte count mean or median ( × 10(9)/L) (OR <0.0001; 95% CI: <0.0001-0.0386; P = 0.0284), and lymphocyte count mean or median ( × 10(9)/L) >0.87 (OR = 0.0576; 95% CI = 0.0043-0.4726; P = 0.0079) had a much lower risk of severity, critical severity, and mortality from COVID-19, respectively. CONCLUSIONS: Lymphocyte count was the most powerful predictor among the 13 common laboratory variables explored from COVID-19 patients to differentiate disease severity and to predict mortality. Lymphocyte count should be monitored for the prognoses of COVID-19 patients in clinical settings in particular for patients not fully vaccinated. International Society of Global Health 2022-09-17 /pmc/articles/PMC9480861/ /pubmed/36112520 http://dx.doi.org/10.7189/jogh.12.05041 Text en Copyright © 2022 by the Journal of Global Health. All rights reserved. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Research Theme 1: COVID-19 Pandemic
Lai, Kuan-Lang
Hu, Fu-Chang
Wen, Fang-Yu
Chen, Ju-Ju
Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title_full Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title_fullStr Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title_full_unstemmed Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title_short Lymphocyte count is a universal predictor of health outcomes in COVID-19 patients before mass vaccination: A meta-analytical study
title_sort lymphocyte count is a universal predictor of health outcomes in covid-19 patients before mass vaccination: a meta-analytical study
topic Research Theme 1: COVID-19 Pandemic
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480861/
https://www.ncbi.nlm.nih.gov/pubmed/36112520
http://dx.doi.org/10.7189/jogh.12.05041
work_keys_str_mv AT laikuanlang lymphocytecountisauniversalpredictorofhealthoutcomesincovid19patientsbeforemassvaccinationametaanalyticalstudy
AT hufuchang lymphocytecountisauniversalpredictorofhealthoutcomesincovid19patientsbeforemassvaccinationametaanalyticalstudy
AT wenfangyu lymphocytecountisauniversalpredictorofhealthoutcomesincovid19patientsbeforemassvaccinationametaanalyticalstudy
AT chenjuju lymphocytecountisauniversalpredictorofhealthoutcomesincovid19patientsbeforemassvaccinationametaanalyticalstudy