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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
INTRO: Evidence about the phenotypic profile of COVID-19 ICU patients in sub- Saharan Africa remains insufficient. Our study aimed to identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10186906/ http://dx.doi.org/10.1016/j.ijid.2023.04.375 |
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author | Nyasulu, P. Sigwadi, L. Zemlin, A. Tamuzi, J. |
author_facet | Nyasulu, P. Sigwadi, L. Zemlin, A. Tamuzi, J. |
author_sort | Nyasulu, P. |
collection | PubMed |
description | INTRO: Evidence about the phenotypic profile of COVID-19 ICU patients in sub- Saharan Africa remains insufficient. Our study aimed 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) in South Africa. METHODS: We used a latent class analysis (LCA) model in a prospective cohort study of clinical and laboratory data collected from 343 COVID-19 patients between 27 March 2020 and 10 February 2021. A sub-analysis was performed to determine sub-phenotypes associated with clinical outcomes among COVID-19 patients and their impact on survival. FINDINGS: Data from 343 COVID-19 patients were analysed. Two distinct phenotypes 1 and 2, comprising 68.46 % and 31.54% patients respectively, were identified. 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 79 umol/L vs 69.5 umol/L, p <0.003), under-perfusion marker (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 value 8.68, p <0.001 and monocyte, median value 0.68 × 109/L vs 0.45 × 109/L, p <0.001). Females in class 2 had lower mean haemoglobin levels than females in class 1 (11.88g/dL vs 12.67g/dL, p = 0.014). In a sub-analysis, mortality and survival were characterized in two sub-phenotypes with increased acute inflammatory syndrome, under-perfusion, end-organ dysfunction, and cardiac function markers in sub-phenotype 2. CONCLUSION: The identification of COVID-19 phenotypes and sub-phenotypes among ICU patients could be used as prognostic markers in day-to-day management of patients. Future studies are required in sub-Sahara Africa to elucidate pathophysiological mechanisms underlying these phenotypes. |
format | Online Article Text |
id | pubmed-10186906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101869062023-05-16 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 Nyasulu, P. Sigwadi, L. Zemlin, A. Tamuzi, J. Int J Infect Dis Article INTRO: Evidence about the phenotypic profile of COVID-19 ICU patients in sub- Saharan Africa remains insufficient. Our study aimed 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) in South Africa. METHODS: We used a latent class analysis (LCA) model in a prospective cohort study of clinical and laboratory data collected from 343 COVID-19 patients between 27 March 2020 and 10 February 2021. A sub-analysis was performed to determine sub-phenotypes associated with clinical outcomes among COVID-19 patients and their impact on survival. FINDINGS: Data from 343 COVID-19 patients were analysed. Two distinct phenotypes 1 and 2, comprising 68.46 % and 31.54% patients respectively, were identified. 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 79 umol/L vs 69.5 umol/L, p <0.003), under-perfusion marker (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 value 8.68, p <0.001 and monocyte, median value 0.68 × 109/L vs 0.45 × 109/L, p <0.001). Females in class 2 had lower mean haemoglobin levels than females in class 1 (11.88g/dL vs 12.67g/dL, p = 0.014). In a sub-analysis, mortality and survival were characterized in two sub-phenotypes with increased acute inflammatory syndrome, under-perfusion, end-organ dysfunction, and cardiac function markers in sub-phenotype 2. CONCLUSION: The identification of COVID-19 phenotypes and sub-phenotypes among ICU patients could be used as prognostic markers in day-to-day management of patients. Future studies are required in sub-Sahara Africa to elucidate pathophysiological mechanisms underlying these phenotypes. Published by Elsevier Ltd. 2023-05 2023-05-16 /pmc/articles/PMC10186906/ http://dx.doi.org/10.1016/j.ijid.2023.04.375 Text en Copyright © 2023 Published by Elsevier Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Nyasulu, P. Sigwadi, L. Zemlin, A. Tamuzi, J. 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 |
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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10186906/ http://dx.doi.org/10.1016/j.ijid.2023.04.375 |
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