Performance of pneumonia severity index and CURB-65 in predicting 30-day mortality in patients with COVID-19

Satıcı, Celal; Demirkol, Mustafa Asım; Altunok, Elif Sargın; Gürsoy, Bengül; Alkan, Mustafa; Kamat, Sadettin; Demirok, Berna; Sürmeli, Cemile Dilşah; Çalık, Mustafa; Çavuş, Zuhal; Esatoğlu, Sinem Nihal

doi:10.1016/j.ijid.2020.06.038

Cited by 159 publications

(178 citation statements)

References 22 publications

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“…In contrast, CURB-65, consisting of only five easily obtained parameters (mainly derived from vital signs), has been validated in different populations [14,16,17] and regarded as a strong predictor for mortality in CAP patients [8]. Celal Satici et al also found an excellent discrimination ability of CURB-65 for prediction of 30-day mortality in hospitalised patients, although it was outperformed by the more complex score system PSI [18]. In our study, CURB-65 demonstrated a good performance (AUC 0.81) and had a relatively large effect size (OR 4.11, 95% CI 2.10-8.02) for in-hospital death in univariate analysis.…”

Section: Discussionmentioning

confidence: 99%

CURB-65 may serve as a useful prognostic marker in COVID-19 patients within Wuhan, China: a retrospective cohort study

et al. 2020

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A recently developed pneumonia caused by SARS-CoV-2 has quickly spread across the world. Unfortunately, a simplified risk score that could easily be used in primary care or general practice settings has not been developed. The objective of this study is to identify a simplified risk score that could easily be used to quickly triage severe COVID-19 patients. All severe and critical adult patients with laboratory-confirmed COVID-19 on the West campus of Union Hospital, Wuhan, China, from 28 January 2020 to 29 February 2020 were included in this study. Clinical data and laboratory results were obtained. CURB-65 pneumonia score was calculated. Univariate logistic regressions were applied to explore risk factors associated with in-hospital death. We used the receiver operating characteristic curve and multivariate COX-PH model to analyse risk factors for in-hospital death. A total of 74 patients (31 died, 43 survived) were finally included in the study. We observed that compared with survivors, non-survivors were older and illustrated higher respiratory rate, neutrophil-to-lymphocyte ratio, D-dimer and lactate dehydrogenase (LDH), but lower SpO2 as well as impaired liver function, especially synthesis function. CURB-65 showed good performance for predicting in-hospital death (area under curve 0.81, 95% confidence interval (CI) 0.71–0.91). CURB-65 ⩾ 2 may serve as a cut-off value for prediction of in-hospital death in severe patients with COVID-19 (sensitivity 68%, specificity 81%, F1 score 0.7). CURB-65 (hazard ratio (HR) 1.61; 95% CI 1.05–2.46), LDH (HR 1.003; 95% CI 1.001–1.004) and albumin (HR 0.9; 95% CI 0.81–1) were risk factors for in-hospital death in severe patients with COVID-19. Our study indicates CURB-65 may serve as a useful prognostic marker in COVID-19 patients, which could be used to quickly triage severe patients in primary care or general practice settings.

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Section: Discussionmentioning

confidence: 99%

CURB-65 may serve as a useful prognostic marker in COVID-19 patients within Wuhan, China: a retrospective cohort study

et al. 2020

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“…Various comorbidities were assessed and compared between two groups, except Medetalibeyoglu et al and Zheng et al studies which did not assess comorbidities of the subjects (12,13). The comorbidities that were more significantly common in the severe groups included cardiovascular diseases (i.e., coronary artery disease, heart failure) in ten studies (14-24), hypertension in nine studies (14, 16-19, 21, 22, 24, 25), chronic respiratory diseases in nine studies (17,19,20,(23)(24)(25)(26)(27)(28), diabetes mellitus in seven studies (11,16,18,21,22,25,29), cerebrovascular diseases in five studies (15,16,18,21,24), chronic kidney disease in four studies (18,(22)(23)(24), cancer in one study (25), and immunosuppression in one study (17). Four studies did not find significant association between the infection severity and the patients' comorbidities (30)(31)(32)(33).…”

Section: Study Characteristicsmentioning

confidence: 99%

Assessing the Elevation of Cardiac Biomarkers and the Severity of COVID-19 Infection: A Meta-analysis

Walker

Deb²,

Ling³

et al. 2020

J Pharm Pharm Sci

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- Purpose: Since December 2019, coronavirus disease 2019 infection has become a global pandemic. The cases of Coronavirus Disease 2019 (COVID-19)-related acute cardiac injury with unknown pathophysiologic mechanism has become increasingly prevalent. However, it is not yet understood how the extent of cardiac injury differs with the intensity of viral infection. In the current study, we aimed to assess the association between elevated cardiac biomarkers and the severity of COVID-19 infection. Methods: A systematic literature search was performed across PubMed and Embase databases from December 1, 2019 to July 10, 2020, to identify studies that reported cardiac biomarkers of troponin (TnI) and creatine kinase-myocardial band (CK-MB) in patients with COVID-19. These studies compared non-severe patients with severe patients, or survivors with non-survivors or medical patients with critically ill patients. The data were extracted for TnI, CK-MB, N-terminal-brain natriuretic peptide (NT-BNP), D-dimer, and lactate dehydrogenase (LDH), C-reactive protein (CRP), and interleukin 6 (IL-6). Wherever possible, the data were pooled for meta-analysis (Review Manager, RevMan. version 5.3) with standard or weighted mean or median difference and corresponding 95% confidence intervals (95% CI). Results: A total of 25 studies involving 5,626 patients were included in the present analysis. More severe COVID-19 infection was found to be associated with higher mean values of TnI (-0.54 [-0.72, -0.36]) (ng/mL), CK-MB (-1.55 [-2.23, -0.88]) (ng/mL) and (-4.75 [-13.31, 3.82]) (units/L), NT-BNP (-815.7 [-1073.97, -557.42]) (pg/mL), D-dimer (-1.4 [-2.04, -0.77]) (mcg/mL), and LDH (-176.59 [-224.11, -129.06]) (units/L), as well as CRP (-64.03 [-68.88, -59.19]) (mg/L) and IL-6 (-22.59 [-29.39, -15.79]) (pg/mL). Conclusions: There is significant association between elevated cardiac biomarkers and the severity of COVID-19, which underlines the increased risk of acute cardiac injury with more severe viral infection. This highlights the need to understand the cardiac history among the COVID-19 patients during initial assessment and for monitoring.

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“…Their score yielded an AUC of 0.74 for predicting ICU admission, and 0.82 for predicting mortality [8]. The well-known CURB-65 (C = Confusion, U = blood Urea nitrogen, R = Respiratory rate, 65 = age 65 or older) score and the Pneumonia Severity Index (PSI) have also been used on 681 laboratory-confirmed Turkish patients to predict mortality of COVID-19 related pneumonia with an AUC of 0.88 and 0.91, respectively [9]. All these scores were designed using multivariate regression models.…”

Section: Introductionmentioning

confidence: 99%

Predictive Accuracy of COVID-19 World Health Organization (WHO) Severity Classification and Comparison with a Bayesian-Method-Based Severity Score (EPI-SCORE)

Terwangne

Laouni

Jouffe³

et al. 2020

Pathogens

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Assess the predictive accuracy of the WHO COVID-19 severity classification on COVID-19 hospitalized patients. The secondary aim was to compare its predictive power with a new prediction model, named COVID-19 EPI-SCORE, based on a Bayesian network analysis. Methods: We retrospectively analyzed a population of 295 COVID-19 RT-PCR positive patients hospitalized at Epicura Hospital Center, Belgium, admitted between March 1st and April 30th, 2020. Results: Our cohort’s median age was 73 (62–83) years, and the female proportion was 43%. All patients were classified following WHO severity classification at admission. In total, 125 (42.4%) were classified as Moderate, 69 (23.4%) as Severe, and 101 (34.2%) as Critical. Death proportions through these three classes were 11.2%, 33.3%, and 67.3%, respectively, and the proportions of critically ill patients (dead or needed Invasive Mechanical Ventilation) were 11.2%, 34.8%, and 83.2%, respectively. A Bayesian network analysis was used to create a model to analyze predictive accuracy of the WHO severity classification and to create the EPI-SCORE. The six variables that have been automatically selected by our machine learning algorithm were the WHO severity classification, acute kidney injury, age, Lactate Dehydrogenase Levels (LDH), lymphocytes and activated prothrombin time (aPTT). Receiver Operation Characteristic (ROC) curve indexes hereby obtained were 83.8% and 91% for the models based on WHO classification only and our EPI-SCORE, respectively. Conclusions: Our study shows that the WHO severity classification is reliable in predicting a severe outcome among COVID-19 patients. The addition to this classification of a few clinical and laboratory variables as per our COVID-19 EPI-SCORE has demonstrated to significantly increase its accuracy.

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Performance of pneumonia severity index and CURB-65 in predicting 30-day mortality in patients with COVID-19

Cited by 159 publications

References 22 publications

CURB-65 may serve as a useful prognostic marker in COVID-19 patients within Wuhan, China: a retrospective cohort study

CURB-65 may serve as a useful prognostic marker in COVID-19 patients within Wuhan, China: a retrospective cohort study

Assessing the Elevation of Cardiac Biomarkers and the Severity of COVID-19 Infection: A Meta-analysis

Predictive Accuracy of COVID-19 World Health Organization (WHO) Severity Classification and Comparison with a Bayesian-Method-Based Severity Score (EPI-SCORE)

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