Dataset Information

Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa.

ABSTRACT:

Background

Studies from Asia, Europe and the USA indicate that widely available haematological parameters could be used to determine the clinical severity of Coronavirus disease 2019 (COVID-19) and predict management outcome. There is limited data from Africa on their usefulness in patients admitted to Intensive Care Units (ICUs). We performed an evaluation of baseline haematological parameters as prognostic biomarkers in ICU COVID-19 patients.

Methods

Demographic, clinical and laboratory data were collected prospectively on patients with confirmed COVID-19, admitted to the adult ICU in a tertiary hospital in Cape Town, South Africa, between March 2020 and February 2021. Robust Poisson regression methods and receiver operating characteristic (ROC) curves were used to explore the association of haematological parameters with COVID-19 severity and mortality.

Results

A total of 490 patients (median age 54.1 years) were included, of whom 237 (48%) were female. The median duration of ICU stay was 6 days and 309/490 (63%) patients died. Raised neutrophil count and neutrophil/lymphocyte ratio (NLR) were associated with worse outcome. Independent risk factors associated with mortality were age (ARR 1.01, 95%CI 1.0-1.02; p = 0.002); female sex (ARR 1.23, 95%CI 1.05-1.42; p = 0.008) and D-dimer levels (ARR 1.01, 95%CI 1.002-1.03; p = 0.016).

Conclusions

Our study showed that raised neutrophil count, NLR and D-dimer at the time of ICU admission were associated with higher mortality. Contrary to what has previously been reported, our study revealed females admitted to the ICU had a higher risk of mortality.

SUBMITTER: Chapanduka ZC

PROVIDER: S-EPMC9635707 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa.

Chapanduka Zivanai C ZC Abdullah Ibtisam I Allwood Brian B Koegelenberg Coenraad F CF Irusen Elvis E Lalla Usha U Zemlin Annalise E AE Masha Tandi E TE Erasmus Rajiv T RT Jalavu Thumeka P TP Ngah Veranyuy D VD Yalew Anteneh A Sigwadhi Lovemore N LN Baines Nicola N Tamuzi Jacques L JL McAllister Marli M Barasa Anne K AK Magutu Valerie K VK Njeru Caroline C Amayo Angela A Wanjiru Mureithi Marianne W MW Mungania Mary M Sono-Setati Musa M Zumla Alimuddin A Nyasulu Peter S PS

PloS one 20221104 11

<h4>Background</h4>Studies from Asia, Europe and the USA indicate that widely available haematological parameters could be used to determine the clinical severity of Coronavirus disease 2019 (COVID-19) and predict management outcome. There is limited data from Africa on their usefulness in patients admitted to Intensive Care Units (ICUs). We performed an evaluation of baseline haematological parameters as prognostic biomarkers in ICU COVID-19 patients.<h4>Methods</h4>Demographic, clinical and la ...[more]

PMID: 36331976

Similar Datasets

Project description:BackgroundOver 130 million people have been diagnosed with Coronavirus disease 2019 (COVID-19), and more than one million fatalities have been reported worldwide. South Africa is unique in having a quadruple disease burden of type 2 diabetes, hypertension, human immunodeficiency virus (HIV) and tuberculosis, making COVID-19-related mortality of particular interest in the country. The aim of this study was to investigate the clinical characteristics and associated mortality of COVID-19 patients admitted to an intensive care unit (ICU) in a South African setting.Methods and findingsWe performed a prospective observational study of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection admitted to the ICU of a South African tertiary hospital in Cape Town. The mortality and discharge rates were the primary outcomes. Demographic, clinical and laboratory data were analysed, and multivariable robust Poisson regression model was used to identify risk factors for mortality. Furthermore, Cox proportional hazards regression model was performed to assess the association between time to death and the predictor variables. Factors associated with death (time to death) at p-value < 0.05 were considered statistically significant. Of the 402 patients admitted to the ICU, 250 (62%) died, and another 12 (3%) died in the hospital after being discharged from the ICU. The median age of the study population was 54.1 years (IQR: 46.0-61.6). The mortality rate among those who were intubated was significantly higher at 201/221 (91%). After adjusting for confounding, multivariable robust Poisson regression analysis revealed that age more than 48 years, requiring invasive mechanical ventilation, HIV status, procalcitonin (PCT), Troponin T, Aspartate Aminotransferase (AST), and a low pH on admission all significantly predicted mortality. Three main risk factors predictive of mortality were identified in the analysis using Cox regression Cox proportional hazards regression model. HIV positive status, myalgia, and intubated in the ICU were identified as independent prognostic factors.ConclusionsIn this study, the mortality rate in COVID-19 patients admitted to the ICU was high. Older age, the need for invasive mechanical ventilation, HIV status, and metabolic acidosis were found to be significant predictors of mortality in patients admitted to the ICU.

Project description:Acute Physiology and Chronic Health Evaluation (APACHE) III score has been widely used for prediction of clinical outcomes in mixed critically ill patients. However, it has not been validated in patients with sepsis-associated acute lung injury (ALI). The aim of the study was to explore the calibration and predictive value of APACHE III in patients with sepsis-associated ALI.The study was a secondary analysis of a prospective randomized controlled trial investigating the efficacy of rosuvastatin in sepsis-associated ALI (Statins for Acutely Injured Lungs from Sepsis, SAILS). The study population was sepsis-related ALI patients. The primary outcome of the current study was the same as in the original trial, 60-day in-hospital mortality, defined as death before hospital discharge, censored 60 days after enrollment. Discrimination of APACHE III was assessed by calculating the area under the receiver operating characteristic (ROC) curve (AUC) with its 95% CI. Hosmer-Lemeshow goodness-of-fit statistic was used to assess the calibration of APACHE III. The Brier score was reported to represent the overall performance of APACHE III in predicting outcome.A total of 745 patients were included in the study, including 540 survivors and 205 non-survivors. Non-survivors were significantly older than survivors (59.71 ± 16.17 vs 52.00 ± 15.92 years, p < 0.001). The primary causes of ALI were also different between survivors and non-survivors (p = 0.017). Survivors were more likely to have the cause of sepsis than non-survivors (21.2% vs. 15.1%). APACHE III score was higher in non-survivors than in survivors (106.72 ± 27.30 vs. 88.42 ± 26.86; p < 0.001). Discrimination of APACHE III to predict mortality in ALI patients was moderate with an AUC of 0.68 (95% confidence interval: 0.64-0.73).this study for the first time validated the discrimination of APACHE III in sepsis associated ALI patients. The result shows that APACHE III score has moderate predictive value for in-hospital mortality among adults with sepsis-associated acute lung injury.

Dataset Information

Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa.

Background

Methods

Results

Conclusions

Publications

Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets