Please use this identifier to cite or link to this item:
http://hdl.handle.net/11189/9536| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Allwood, Brian W. | en_US |
| dc.contributor.author | Koegelenberg, Coenraad F. | en_US |
| dc.contributor.author | Ngah, Veranyuy D. | en_US |
| dc.contributor.author | Sigwadhi, Lovemore Nyasha | en_US |
| dc.contributor.author | Irusen, Elvis M. | en_US |
| dc.contributor.author | Lalla, Usha | en_US |
| dc.contributor.author | Yalew, Anteneh | en_US |
| dc.contributor.author | Tamuzi, Jacques L. | en_US |
| dc.contributor.author | McAllister, Marli | en_US |
| dc.contributor.author | Zemlin, Annalise E. | en_US |
| dc.contributor.author | Jalavu, Thumeka P. | en_US |
| dc.contributor.author | Erasmus, Rajiv | en_US |
| dc.contributor.author | Chapanduka, Zivanai Cuthbert | en_US |
| dc.contributor.author | Matsha, Tandi Edith | en_US |
| dc.contributor.author | Fwemba, Isaac | en_US |
| dc.contributor.author | Zumla, Alimuddin | en_US |
| dc.contributor.author | Nyasulu, Peter S. | en_US |
| dc.date.accessioned | 2023-12-01T10:57:47Z | - |
| dc.date.available | 2023-12-01T10:57:47Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Allwood, B. W., Koegelenberg, C. F., Ngah, V. D. et al. 2022. Predicting COVID-19 outcomes from clinical and laboratory parameters in an intensive care facility during the second wave of the pandemic in South Africa. IJID Regions, 3: 242–247. [https://doi.org/10.1016/j.ijregi.2022.03.024] | en_US |
| dc.identifier.issn | 2772-7076 | - |
| dc.identifier.uri | http://hdl.handle.net/11189/9536 | - |
| dc.description.abstract | Background: The second wave of coronavirus disease 2019 (COVID-19) in South Africa was caused by the Beta variant of severe acute respiratory syndrome coronavirurus-2. This study aimed to explore clinical and biochemical parameters that could predict outcome in patients with COVID-19. Methods: A prospective study was conducted between 5 November 2020 and 30 April 2021 among patients with confirmed COVID-19 admitted to the intensive care unit (ICU) of a tertiary hospital. The Cox proportional hazards model in Stata 16 was used to assess risk factors associated with survival or death. Factors with P<0.05 were considered significant. Results: Patients who died were found to have significantly lower median pH (P<0.001), higher median arterial partial pressure of carbon dioxide (P<0.001), higher D-dimer levels (P=0.001), higher troponin T levels (P=0.001), higher N-terminal-prohormone B-type natriuretic peptide levels (P=0.007) and higher C-reactive protein levels (P=0.010) compared with patients who survived. Increased standard bicarbonate (HCO3std) was associated with lower risk of death (hazard ratio 0.96, 95% confidence interval 0.93–0.99). Conclusions: The mortality of patients with COVID-19 admitted to the ICU was associated with elevated D-dimer and a low HCO3std level. Large studies are warranted to increase the identification of patients at risk of poor prognosis, and to improve the clinical approach. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.relation.ispartof | IJID Regions | en_US |
| dc.subject | COVID-19 | en_US |
| dc.subject | SARS-CoV-2 | en_US |
| dc.subject | Mortality | en_US |
| dc.subject | ICU | en_US |
| dc.subject | Second wave | en_US |
| dc.subject | Biomarkers | en_US |
| dc.title | Predicting COVID-19 outcomes from clinical and laboratory parameters in an intensive care facility during the second wave of the pandemic in South Africa | en_US |
| dc.identifier.doi | https://doi.org/10.1016/j.ijregi.2022.03.024 | - |
| dc.type | Article | en_US |
| Appears in Collections: | HWSci - Journal Articles (DHET subsidised) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Predicting_COVID-19_outcomes.pdf | Article | 349.78 kB | Adobe PDF | View/Open |
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