Objectives: Early identification of patients with the novel coronavirus induced-disease 2019 (COVID-19) and pneumonia is currently challenging. Few data are available on validated scores predictive of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection. The Portuguese Society of Intensive Care (PSIC) proposed a risk score whose main goals were to predict a higher probability of COVID-19 and optimize hospital resources, adjusting patients' intervention. This study aimed to validate the PSIC risk score applied to inpatients with pneumonia. Methods: A retrospective analysis of 207 patients with pneumonia admitted to a suspected/confirmed SARS-CoV-2 infection specialized ward (20/03 to 20/05/2020) was performed. Score variables were analyzed to determine the significance of the independent predictive variables on the probability of a positive SARS-CoV-2 rRT-PCR test. The binary logistic regression modeling approach was selected. The best cut-off value was obtained with the Receiver Operating Characteristic (ROC) curve together with the evaluation of the discriminatory power through the Area Under the Curve (AUC). Results: The validation cohort included 145 patients. Typical chest computed-tomography features (OR, 12.16; 95% CI, 3.32 -44.50) and contact with a positive SARS-CoV-2 patient (OR, 6.56; 95% CI, 1.33 -32.30) were the most significant independent predictive variables. A score ≥ 10 increased suspicion for SARS-CoV-2 pneumonia. The AUC was 0.82 (95% CI, 0.73 -0.91) demonstrating the good discriminating power for COVID-19 probability stratification in inpatients with pneumonia. Conclusions: The application of the PSIC score to inpatients with pneumonia may be of value in predicting the risk of COVID-19. Further studies from other centers are needed to validate this score widely.

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Background Coronavirus disease 2019 (COVID-19) has been associated with significant morbidity and mortality, with cardiovascular involvement being usual. Elevations in cardiac Troponin-I level has proposed as an independent biomarker for mortality among patients with COVID-19. Aim To evaluate the role of high sensivity Troponin-I (hs-TnI) level at hospital admission in predicting 30 day in-hospital mortality and 6-month mortality in patients hospitalized with a COVID-19 diagnosis. Methods We performed a retrospective single-center cohort study including consecutive patients aged 18 years and older who were admitted for COVID-19, during a 1-year period (n=818). We excluded patients with acute coronary syndrome (n=23), patients with acute heart failure (n=42), and patients in which hs-TnI level was not dosed at admission (n=163). Patients were divided into two groups according to hs-TnI levels: hs-TnI <19.8 vs hs-TnI ≥19.8 pg/mL. Primary outcomes were 30-day in-hospital mortality and 6-months mortality. According to the data distribution, appropriate statistical tests were conducted to compare independent samples. Multivariable logistic regression was used to analyze mortality risk. Receiver operator characteristics (ROC) curve and area under the curve (AUC) were obtained to determine the discriminative power of hs-TnI as a predictor of mortality. (Figure 1). Results This cohort included 590 patients. Mean age was 71 ≥±15 years and 52.4% were men. Overall, 209 patients (35.4%) had elevated hs-TnI levels and 381 patients had normal hs-TnI levels. Individuals in the hs-TnI ≥19.8 pg/mL group were older (80±11 vs 66±14 years, p<0.001) and presented higher prevalence of chronic heart failure (24.9% vs 7.1%, p<0.001), hypertension (77.0% vs 57.5%, p<0.001), atrial fibrillation/flutter (19.1% vs 5.5%, p<0.001), prior stroke (12.4% vs 5.2%, p=0.001) and ischemic heart disease (12.4% vs 3.7%, p<0.001). There was no difference in length of hospital stay between the groups (8.0 [IQR 9.6] in hs-TnI 19.8 pg/mL group vs 9.0 [IQR 8.0] normal hs-TnI group, p=0.669). Troponin-I was the only independent predictor of in-hospital mortality (OR 3.80, CI 95%: 2.44–5.93, p<0.001), see Table 1. The troponin levels had the highest area under the receiver operating characteristic curv (AUC) with an AUC of 0.705 (95% CI: 0.667–0.742, p<0.001) for association with the in-hospital mortality (figure 1). There was no difference in 6-months mortality between the two groups. Conclusion Acute myocardial injury is common in patients hospitalized with COVID-19. In the present study a TnI level ≥19.8 pg/mL was predictor of 30 days in-hospital mortality, suggesting that raised levels of this biomarker is associated with adverse prognosis. This tool might be useful for COVID-19 patient risk stratification. Further studies are needed to provide robust data and reliable recommendations on this theme. Funding Acknowledgement Type of funding sources: None.

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