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Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit

Sigwadhi, LN; Tamuzi, JL; Zemlin, AE; Chapanduka, ZC; Allwood, BW; Koegelenberg, CF; Irusen, EM; ... Nyasulu, PS; + view all (2022) Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit. IJID Regions , 5 pp. 154-162. 10.1016/j.ijregi.2022.10.004. Green open access

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Abstract

Objective: The aim of this study was to identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (ICU) at Tygerberg Hospital, Cape Town. Methods and results: A latent class analysis (LCA) model was applied in a prospective, observational cohort study. Data from 343 COVID-19 patients were analysed. Two distinct phenotypes (1 and 2) were identified, comprising 68.46% and 31.54% of patients, respectively. The phenotype 2 patients were characterized by increased coagulopathy markers (D-dimer, median value 1.73 ng/L vs 0.94 ng/L; p < 0.001), end-organ dysfunction (creatinine, median value 79 µmol/L vs 69.5 µmol/L; p < 0.003), under-perfusion markers (lactate, median value 1.60 mmol/L vs 1.20 mmol/L; p < 0.001), abnormal cardiac function markers (median N‐terminal pro‐brain natriuretic peptide (NT-proBNP) 314 pg/ml vs 63.5 pg/ml; p < 0.001 and median high‐sensitivity cardiac troponin (Hs-TropT) 39 ng/L vs 12 ng/L; p < 0.001), and acute inflammatory syndrome (median neutrophil-to-lymphocyte ratio 15.08 vs 8.68; p < 0.001 and median monocyte value 0.68 × 109/L vs 0.45 × 109/L; p < 0.001). Conclusion: The identification of COVID-19 phenotypes and sub-phenotypes in ICU patients could help as a prognostic marker in the day-to-day management of COVID-19 patients admitted to the ICU.

Type: Article
Title: Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ijregi.2022.10.004
Publisher version: https://doi.org/10.1016/j.ijregi.2022.10.004
Language: English
Additional information: © 2022 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases under a Creative Commons license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Infection and Immunity
URI: https://discovery.ucl.ac.uk/id/eprint/10168294
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