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IntroductionWhile the CURB-65 score predicts mortality in community-acquired pneumonia (CAP), its performance in COVID-19 CAP is suboptimal. Hyperglycaemia correlates with an increased mortality in COVID-19. This analysis aims to enhance predictive accuracy for in-hospital mortality among COVID-19 patients by augmenting the CURB-65 score with objective variables, including markers of dysglycaemia.DesignA single-centre retrospective observational analysis assessed the effectiveness of the CURB-65 score in predicting in-hospital mortality among adult patients with moderate to severe COVID-19 from March to September 2020. Using a binary logistic regression model, two extended CURB-65 scores which include markers of dysglycemia are proposed to enhance the predictive capability of the CURB-65 score for in-hospital mortality.ResultsAmong 517 patients admitted, 117 (22.6%) died. Using the CURB-65 score, 393 patients (76%) were classified as low risk, 91 (17.6%) as medium risk and 33 (6.4%) as high risk. 37 patients were diagnosed with new-onset dysglycaemia, of which 22 (59.5%) died (p<0.001). Of those with dysglycaemia who died, 41% and 23% were classified as low risk and high risk using the CURB-65 score. The CURB-65 score demonstrated a modest area under the receiver operator characteristic curve (AUC) of 0.75 (95% CI 0.70 to 0.81) for in-hospital mortality in COVID-19 CAP. An Extended CURB-65 Score 1, incorporating an admission of fasting plasma glucose (FPG) and neutrophil to lymphocyte ratio, showed improved prognostic performance with an AUC of 0.80 (95% CI 0.76 to 0.85). When lactate and lactate dehydrogenase were added to these parameters (Extended CURB-65 Score 2), the AUC was 0.82 (95% CI 0.78 to 0.86). The integrated discrimination index showed an 11% and 24% higher discrimination slope when using the Extended CURB-65 Scores 1 and 2, respectively.ConclusionsThe addition of common biochemical parameters including an admission FPG enhances the prognostic performance of CURB-65 for in-hospital mortality among patients with COVID-19.
IntroductionWhile the CURB-65 score predicts mortality in community-acquired pneumonia (CAP), its performance in COVID-19 CAP is suboptimal. Hyperglycaemia correlates with an increased mortality in COVID-19. This analysis aims to enhance predictive accuracy for in-hospital mortality among COVID-19 patients by augmenting the CURB-65 score with objective variables, including markers of dysglycaemia.DesignA single-centre retrospective observational analysis assessed the effectiveness of the CURB-65 score in predicting in-hospital mortality among adult patients with moderate to severe COVID-19 from March to September 2020. Using a binary logistic regression model, two extended CURB-65 scores which include markers of dysglycemia are proposed to enhance the predictive capability of the CURB-65 score for in-hospital mortality.ResultsAmong 517 patients admitted, 117 (22.6%) died. Using the CURB-65 score, 393 patients (76%) were classified as low risk, 91 (17.6%) as medium risk and 33 (6.4%) as high risk. 37 patients were diagnosed with new-onset dysglycaemia, of which 22 (59.5%) died (p<0.001). Of those with dysglycaemia who died, 41% and 23% were classified as low risk and high risk using the CURB-65 score. The CURB-65 score demonstrated a modest area under the receiver operator characteristic curve (AUC) of 0.75 (95% CI 0.70 to 0.81) for in-hospital mortality in COVID-19 CAP. An Extended CURB-65 Score 1, incorporating an admission of fasting plasma glucose (FPG) and neutrophil to lymphocyte ratio, showed improved prognostic performance with an AUC of 0.80 (95% CI 0.76 to 0.85). When lactate and lactate dehydrogenase were added to these parameters (Extended CURB-65 Score 2), the AUC was 0.82 (95% CI 0.78 to 0.86). The integrated discrimination index showed an 11% and 24% higher discrimination slope when using the Extended CURB-65 Scores 1 and 2, respectively.ConclusionsThe addition of common biochemical parameters including an admission FPG enhances the prognostic performance of CURB-65 for in-hospital mortality among patients with COVID-19.
There are few data regarding clinical outcomes from COVD-19 from low-income countries (LICs) including Rwanda. Accordingly, we aimed to determine 1) outcomes of patients admitted to hospital with COVID-19 in Rwanda, and 2) the ability of the Universal Vital Assessment (UVA) score to predict mortality in patients with COVID-19 compared to sequential organ failure assessment (SOFA) and quick (qSOFA) scores. We conducted a retrospective study of patients aged ≥18 years hospitalized with laboratory-confirmed COVID-19 at the University Teaching Hospital of Butare (CHUB), Rwanda, April 2021-January 2022. For each participant, we calculated UVA, SOFA, and qSOFA risk scores and determined their area under the receive operating characteristic curve (AUC). We used logistic regression to determine predictors of mortality. Of the 150 patients included, 83 (55%) were female and the median (IQR) age was 61 (43–73) years. The median (IQR) length of hospital stay was 6 (3–10) days. Respiratory failure occurred in 69 (46%) including 34 (23%) who had ARDS. The case fatality rate was 44%. Factors independently associated with mortality included acute kidney injury (adjusted odds ratio [aOR] 7.99, 95% confidence interval [CI] 1.47–43.22, p = 0.016), severe COVID-19 (aOR 3.42, 95% CI 1.06–11.01, p = 0.039), and a UVA score >4 (aOR 7.15, 95% CI 1.56–32.79, p = 0.011). The AUCs for UVA, qSOFA, and SOFA scores were 0.86 (95% CI 0.79–0.92), 0.81 (95% CI 0.74–0.88), and 0.84 (95% CI 0.78–0.91), respectively, which were not statistically significantly different from each other. At a UVA score cut-off of 4, the sensitivity, specificity, positive predictive value, and negative predictive value for mortality were 0.58, 0.93, 0.86, and 0.74, respectively. Patients hospitalized with COVID-19 in CHUB had high mortality, which was accurately predicted by the UVA score. Calculation of the UVA score in patients with COVID-19 in LICs may assist clinicians with triage and other management decisions.
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