Development of a scoring system for the prediction of in-hospital mortality among COVID-19 patients

Aghajani, Mohammad Haji; Sistanizad, Mohammad; Pourhoseingholi, Asma; Asadpoordezaki, Ziba; Taherpour, Niloufar

doi:10.1016/j.cegh.2021.100871

Cited by 11 publications

(9 citation statements)

References 23 publications

(31 reference statements)

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“…Despite the fact that many studies have pointed to the importance of male sex and associated comorbidity in poor prognosis [45][46][47][48][49] , our study did not find that link after multiple filtration of logistic regression modeling, and a recent study supported that 50 . Furthermore, the severity level of lesion in HRCT was one of the most reliable predictors; thus, it was associated with a poor prognosis, despite the fact that a few studies used that factor to predict in-hospital mortality outcome [50][51][52] .…”

Section: Discussioncontrasting

confidence: 99%

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Development and validation of a predictive scoring system for in-hospital mortality in COVID-19 Egyptian patients: a retrospective study

Elgohary

Ali

El‐Masry

et al. 2022

Sci Rep

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SARS-CoV-2 virus has rapidly spread worldwide since December 2019, causing COVID-19 disease. In-hospital mortality is a common indicator for evaluating treatment outcomes. Therefore, the developing and validating a simple score system from observational data could assist in modulating the management procedures. A retrospective cohort study included all data records of patients with positive PCR for SARS-CoV-2. The factors that associated with mortality were analyzed, then allocation of potential predictors of mortality was executed using different logistic regression modeling, subsequently scoring system was developed from the most weighted predictors. The mortality rate of patients with COVID-19 pneumonia was 28.5% and 28.74%, respectively. The most significant factors that affected in-hospital mortality were old age (> 60 years), delay in hospital admission (> 4 days), high neutrophil/lymphocyte ratio “NLR” (> 3); higher computed tomography severity score; and CT-SS (> 20), in addition to using remdesivir and tocilizumab in the treatment protocol (P < 0.001 for all). The validity of the newly performed score was significant; the AUC was 85%, P < 0.001, and its prognostic utility was good; the AUC was 75%, P < 0.001. The prognostic utility of newly developed score system (EGY.Score) was excellent and could be used to adjust the treatment strategy of highly at-risk patients with COVID-19 pneumonia.

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Section: Discussioncontrasting

confidence: 99%

“…reported that a shorter time from symptom onset to hospitalization is associated with a more serious disease and higher mortality 40 . On the other hand, old age was correlated with bad prognosis, which came in consistence with other reports 41 – 46 .…”

Section: Discussionsupporting

confidence: 90%

Development and validation of a predictive scoring system for in-hospital mortality in COVID-19 Egyptian patients: a retrospective study

Elgohary

Ali

El‐Masry

et al. 2022

Sci Rep

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“…Prediction models for severity and disease outcome in COVID-19 patients have been reported in the previous studies. [11][12][13] However, most of these studies were done in the upper-middle to high-income countries such as China, the UK, and the US with vastly different health profiles and disease burdens than those in the lower-middle income country (LMIC) counterpart. 6,[14][15][16] Like many other LMIC, Indonesia is still struggling with several communicable diseases, namely tuberculosis, HIV/AIDS, and malaria.…”

Section: Discussionmentioning

confidence: 99%

Laboratory risk factors for mortality in severe and critical COVID-19 patients admitted to the ICU

Bestari

Suharjo²,

Nuari³

et al. 2022

F1000Res

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Background: Several studies have reported clinical characteristics and risk factors for predicting adverse outcomes in COVID-19.4–6 However, data exclusively from the ICU especially in the low- and middle-income countries (LMIC) remain lacking. This study aimed to explore risk factors associated with mortality based on laboratory parameters at hospital admission in severe and critical COVID-19 patients admitted to the ICU. Methods: This study is a retrospective cohort study. Data from the electronic medical records were collected retrospectively from all severe and critical COVID-19 patients requiring ICU admission in two designated COVID-19 hospitals in Jakarta, Indonesia. A multivariate logistic regression analysis was used to identify the predictors associated with ICU mortality. The model performance was evaluated by the area under curve (AUC) from the receiver operating characteristic (ROC) analysis. Results: There were 334 patients admitted to the ICU with COVID-19 included in the statistical analysis. The ICU mortality rate was 75.1%, with 251 patients died in the hospital. Independent risk factors associated mortality including white blood cell count >13.9 x109/L (OR=2.41; 95% CI, 1.15-5.06, p=0.02), neutrophil to lymphocyte ratio >10.7 (OR=2.20; 95% CI, 1.20 – 4.03, p=0.011), and creatinine >0.8 mg/dL (OR=3.55; 95% CI, 2.05 – 6.17, p<0.001). The model yielded an AUC of 0.72 (95% CI, 0.659-0.780, p<0.0001) for predicting ICU mortality in severe and critical COVID-19 patients. Conclusions: White blood cell, neutrophil to lymphocyte ratio, and serum creatinine on hospital admission are significant predictors of mortality in severe and critical COVID-19 patients admitted to the ICU. The ICU mortality rate during the second wave of the pandemic in this study was high.

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“…The equation for mortality had a poorer discriminatory value (AUC=0.73). Multiple studies conducted to determine a scoring system to predict the need for oxygen and mortality have also consistently included NLR and other biomarkers that we have explored [18][19][20][21][22][23].…”

Section: Predictors and Scoring Equation To Determine Mortalitymentioning

confidence: 99%

Novel Scoring Systems to Predict the Need for Oxygenation and ICU Care, and Mortality in Hospitalized COVID-19 Patients: A Risk Stratification Tool

Keri¹,

Jorwal²,

Verma³

et al. 2022

Cureus

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Introduction: A rapid surge in cases during the COVID-19 pandemic can overwhelm any healthcare system. It is imperative to triage patients who would require oxygen and ICU care, and predict mortality. Specific parameters at admission may help in identifying them.Methodology: A prospective observational study was undertaken in a COVID-19 ward of a tertiary care center. All baseline clinical and laboratory data were captured. Patients were followed till death or discharge. Univariable and multivariable logistic regression was used to find predictors of the need for oxygen, need for ICU care, and mortality. Objective scoring systems were developed for the same using the predictors.Results: The study included 209 patients. Disease severity was mild, moderate, and severe in 98 (46.9%), 74 (35.4%), and 37 (17.7%) patients, respectively. The neutrophil-to-lymphocyte ratio (NLR) >4 was a common independent predictor of the need for oxygen (p<0.001), need for ICU transfer (p=0.04), and mortality (p=0.06). Clinical risk scores were developed (10*c-reactive protein (CRP) + 14.8*NLR + 12*urea), (10*aspartate transaminase (AST) + 15.7*NLR + 14.28*CRP), (10*NLR + 10.1*creatinine) which, if ≥14.8, ≥25.7, ≥10.1 predicted need for oxygenation, need for ICU transfer and mortality with a sensitivity and specificity (81.6%, 70%), (73.3%, 75.7%), (61.1%, 75%), respectively. Conclusion:The NLR, CRP, urea, creatinine, and AST are independent predictors in identifying patients with poor outcomes. An objective scoring system can be used at the bedside for appropriate triaging of patients and utilization of resources.

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Development of a scoring system for the prediction of in-hospital mortality among COVID-19 patients

Cited by 11 publications

References 23 publications

Development and validation of a predictive scoring system for in-hospital mortality in COVID-19 Egyptian patients: a retrospective study

Development and validation of a predictive scoring system for in-hospital mortality in COVID-19 Egyptian patients: a retrospective study

Laboratory risk factors for mortality in severe and critical COVID-19 patients admitted to the ICU

Novel Scoring Systems to Predict the Need for Oxygenation and ICU Care, and Mortality in Hospitalized COVID-19 Patients: A Risk Stratification Tool

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