Internal and emergency medicine
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Multicenter Study Observational Study
Correlation of SpO2/FiO2 and PaO2/FiO2 in patients with symptomatic COVID-19: An observational, retrospective study.
Some patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) experience acute hypoxemic respiratory failure progressing toward atypical acute respiratory distress syndrome (ARDS). The aim of the study is to evaluate whether a correlation between ratio of peripheral saturation of oxygen (SpO2) and fraction of inspired oxygen (S/F) and ratio of arterial partial pressure of oxygen and fraction of inspired oxygen (P/F) exists in COVID-19-related ARDS as already known in classical ARDS. In this multicenter, retrospective, observational study, consecutive, adult (≥ 18 years) patients with symptomatic coronavirus disease 2019 (COVID-19) admitted to different COVID-19 divisions in Italy between March and December 2020 were included. ⋯ S/F was also tested against P/F values ≤ 200 and ≤ 100 mmHg (suggestive for moderate and severe ARDS, respectively), the latter showing great accuracy for S/F ≤ 178%. S/F was accurate in predicting ARDS for SpO2 ≥ 92%. In conclusion, our findings support the routine use of S/F as a reliable surrogate of P/F in patients with COVID-19-related ARDS.
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Multicenter Study
Fibrosis-4 (FIB-4) Index and mortality in COVID-19 patients admitted to the emergency department.
Liver damage worsens the prognosis of coronavirus 19 disease (COVID-19). However, the best strategy to stratify mortality risk according to liver damage has not been established. The aim of this study is to test the predictive value of the validated Fibrosis-4 (FIB-4) Index and compared it to liver transaminases and to the AST-to-Platelet ratio index (APRI). ⋯ FIB-4 was also associated with high-flow oxygen use (n = 255, HR 1.69, 95% CI 1.25-2.28, p = 0.001) and mechanical ventilation (n = 39, HR 2.07, 95% CI 1.03-4.19, p = 0.043). FIB-4 score predicts mortality better than liver transaminases and APRI score. FIB-4 score may be an easy tool to identify COVID-19 patients at worse prognosis in the emergency department.
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Multicenter Study
Machine learning versus traditional methods for the development of risk stratification scores: a case study using original Canadian Syncope Risk Score data.
Artificial Intelligence and machine learning (ML) methods are promising for risk-stratification, but the added benefit over traditional statistical methods remains unclear. We compared predictive models developed using machine learning (ML) methods to the Canadian Syncope Risk Score (CSRS), a risk-tool developed with logistic regression for predicting serious adverse events (SAE) after emergency department (ED) disposition for syncope. We used the prospective multicenter cohort data collected for CSRS development at 11 Canadian EDs over an 8-year period to develop four ML models to predict 30-day SAE (death, arrhythmias, MI, structural heart disease, pulmonary embolism, hemorrhage) after ED disposition. ⋯ The AUCs and calibration slopes for the ML models and CSRS were similar. Two ML models used fewer predictors than the CSRS but matched its performance. Overall, the ML models matched the CSRS in performance, with some models using fewer predictors.
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Multicenter Study Observational Study
Low in-hospital mortality rate in patients with COVID-19 receiving thromboprophylaxis: data from the multicentre observational START-COVID Register.
COVID-19 infection causes respiratory pathology with severe interstitial pneumonia and extra-pulmonary complications; in particular, it may predispose to thromboembolic disease. The current guidelines recommend the use of thromboprophylaxis in patients with COVID-19, however, the optimal heparin dosage treatment is not well-established. We conducted a multicentre, Italian, retrospective, observational study on COVID-19 patients admitted to ordinary wards, to describe clinical characteristic of patients at admission, bleeding and thrombotic events occurring during hospital stay. The strategies used for thromboprophylaxis and its role on patient outcome were, also, described. 1091 patients hospitalized were included in the START-COVID-19 Register. ⋯ All patients were treated with antithrombotic drugs; 5.4%, had venous thromboembolism [30.5% deep vein thrombosis (DVT), 66.1% pulmonary embolism (PE), and 3.4% patients had DVT + PE]. In our cohort the mortality rate was 18.3%. Heparin use was independently associated with survival in patients aged ≥ 59 years at multivariable analysis. We confirmed the high mortality rate of COVID-19 in hospitalized patients in ordinary wards. Treatment with antithrombotic drugs is significantly associated with a reduction of mortality rates especially in patients older than 59 years.