Comparison of prognostic scores for inpatients with COVID-19: a retrospective monocentric cohort study

Abstract

BackgroundThe SARS-CoV-2 pandemic led to a steep increase in hospital and intensive care unit (ICU) admissions for acute respiratory failure worldwide. Early identification of patients at risk of clinical deterioration is crucial in terms of appropriate care delivery and resource allocation. We aimed to evaluate and compare the prognostic performance of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Uraemia, Respiratory Rate, Blood Pressure and Age ≥65 (CURB-65), Respiratory Rate and Oxygenation (ROX) index and Coronavirus Clinical Characterisation Consortium (4C) score to predict death and ICU admission among patients admitted to the hospital for acute COVID-19 infection.Methods and analysisConsecutive adult patients admitted to the Geneva University Hospitals during two successive COVID-19 flares in spring and autumn 2020 were included. Discriminative performance of these prediction rules, obtained during the first 24 hours of hospital admission, were computed to predict death or ICU admission. We further exluded patients with therapeutic limitations and reported areas under the curve (AUCs) for 30-day mortality and ICU admission in sensitivity analyses.ResultsA total of 2122 patients were included. 216 patients (10.2%) required ICU admission and 303 (14.3%) died within 30 days post admission. 4C score had the best discriminatory performance to predict 30-day mortality (AUC 0.82, 95% CI 0.80 to 0.85), compared with SOFA (AUC 0.75, 95% CI 0.72 to 0.78), qSOFA (AUC 0.59, 95% CI 0.56 to 0.62), CURB-65 (AUC 0.75, 95% CI 0.72 to 0.78) and ROX index (AUC 0.68, 95% CI 0.65 to 0.72). ROX index had the greatest discriminatory performance (AUC 0.79, 95% CI 0.76 to 0.83) to predict ICU admission compared with 4C score (AUC 0.62, 95% CI 0.59 to 0.66), CURB-65 (AUC 0.60, 95% CI 0.56 to 0.64), SOFA (AUC 0.74, 95% CI 0.71 to 0.77) and qSOFA (AUC 0.59, 95% CI 0.55 to 0.62).ConclusionScores including age and/or comorbidities (4C and CURB-65) have the best discriminatory performance to predict mortality among inpatients with COVID-19, while scores including quantitative assessment of hypoxaemia (SOFA and ROX index) perform best to predict ICU admission. Exclusion of patients with therapeutic limitations improved the discriminatory performance of prognostic scores relying on age and/or comorbidities to predict ICU admission.

Validation of the qSOFA and CRB-65 in SARS-CoV-2-infected community-acquired pneumonia

“…Such differences also have been described by others [16,17], however for direct comparison of CAP patients with and without SARS-CoV-2 infection hospitalized within the same period we found surprisingly few data. Mortality rate in our cohort of hospitalized CAP and COVID-19 was high compared to previous prospective studies [8,16,18], but closely resembled that of other European population-based cohorts for hospitalized CAP [19][20][21] and COVID-19 [9,10,12,22]. Additionally, the median age of our cohorts was high with 72 years in SARS-CoV-2 positive and 78 years in SARS-CoV-2 negative patients, respectively.…”

“…The current German CAP guideline [7] recommends initial risk screening including the CRB-65 score and evaluation of potential sepsis with the qSOFA. Both scores only partially have been validated for initial assessment of SARS-CoV-2 CAP with conflicting results in recent studies [5,[8][9][10][11][12]. Additionally, prediction models show heterogeneous results according to the specified outcome (mortality vs. severe disease / mechanical ventilation).…”

High-flow nasal oxygen in acute hypoxemic respiratory failure: A narrative review of the evidence before and after the COVID-19 pandemic

“…For these reasons, early recognition of patients failing to respond to non-invasive respiratory support is crucial, so that the use of HFNO and NIV should, to pour opinion, be restricted to settings such as intermediate/respiratory care units or intensive care units, where the response to treatment can be closely monitored and treatment strategies quickly adapted (76). The ROX index [(SpO 2 /FiO 2 )/respiratory rate] has been validated as a simple predictor of failure in patients with AHRF receiving HFNO and might be helpful to evaluate patient response, guiding therapy adaptation and to avoid potential risks associated with delayed intubation (77,78). Given its ease of use, excellent tolerance, and the potential benefits compared to COT, HFNO could arguably be the first option for patients with AHRF and may constitute an adequate comparator to evaluate the benefits of alternative or additional strategies such as CPAP or BiPAP in future trials.…”

Machine learning models for predicting severe COVID-19 outcomes in hospitals

“…Our models use standard clinical laboratory data from hospitals of medium level of care measured during clinical routine in combination with biological sex and age as covariates. Our purely data-driven approach avoids potential bias or the pure reproduction of well-known results [ 9 ] and is an important addition to the landscape of expert knowledge-based Covid-19 risk scores [ [10] , [11] , [12] , [13] ]. In contrast to previous approaches [ 14 ], we explored a large space of potential predictors.…”