Prospective predictive performance comparison between Clinical Gestalt and validated COVID-19 mortality scores

Abstract

Background: Most COVID-19 mortality scores were developed in the early months of the pandemic and now available evidence-based interventions have helped reduce its lethality. It has not been evaluated if the original predictive performance of these scores holds true nor compared it against Clinical Gestalt predictions. We tested the current predictive accuracy of six COVID-19 scores and compared it with Clinical Gestalt predictions. Methods: 200 COVID-19 patients were enrolled in a tertiary hospital in Mexico City between September and December 2020. Clinical Gestalt predictions of death (as a percentage) and LOW-HARM, qSOFA, MSL-COVID-19, NUTRI-CoV and NEWS2 were obtained at admission. We calculated the AUC of each score and compared it against Clinical Gestalt predictions and against their respective originally reported value. Results: 106 men and 60 women aged 56+/-9 and with confirmed COVID-19 were included in the analysis. The observed AUC of all scores was significantly lower than originally reported; LOW-HARM 0.96 (0.94-0.98) vs 0.76 (0.69-0.84), qSOFA 0.74 (0.65-0.81) vs 0.61 (0.53-0.69), MSL-COVID-19 0.72 (0.69-0.75) vs 0.64 (0.55-0.73) NUTRI-CoV 0.79 (0.76-0.82) vs 0.60 (0.51-0.69), NEWS2 0.84 (0.79-0.90) vs 0.65 (0.56-0.75), Neutrophil-Lymphocyte ratio 0.74 (0.62-0.85) vs 0.65 (0.57-0.73). Clinical Gestalt predictions were non-inferior to mortality scores (AUC=0.68 (0.59-0.77)). Adjusting the LOW-HARM score with locally derived likelihood ratios did not improve its performance. However, some scores performed better than Clinical Gestalt predictions when clinician's confidence of prediction was <80%. Conclusion: No score was significantly better than Clinical Gestalt predictions. Despite its subjective nature, Clinical Gestalt has relevant advantages for predicting COVID-19 clinical outcomes.

Which is better in predicting mortality in patients hospitalized for COVID-19: CURB-65 score versus physicians' gestalt

“…[12] In another study, several mortality scores (LOW-HARM, qSOFA, MSL-COVID-19, NUTRI-CoV and NEWS2) were compared according to physician's gestalt, and no score was found to be superior to the physician's gestalt. [13] In this study, physicians were found to be as successful as gestalt, and the CURB-65 score that every emergency medicine physician is familiar with consists of only five parameters that can be easily obtained (mainly obtained from vital signs). This has been confirmed in different populations and has been acknowledged as a strong predictor of mortality in pneumonia patients.…”

Deep Learning for Identification of Acute Illness and Facial Cues of Illness

“…The value of the clinical gestalt as a diagnostic tool has been studied in different health conditions (10)(11)(12)(13). In acute coronary syndrome, heart failure, pneumonia, and COVID-19, the clinical gestalt registered by doctors was comparable to clinical scores in "ruling in" or "ruling out" patients with certain symptoms presenting to the ED (10)(11)(12)(13)(14). For sepsis, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) advocates clinicians should, in addition to systemic inflammatory response syndrome (SIRS) criteria, use clinical gestalt in screening, treating and risk-stratifying patients with infection (15).…”