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BACKGROUND AND AIM: The nature of the association between obesity and poor prognosis of COVID-19 without the evaluation of other co-pathologies associated has not yet been clearly evaluated. The aim of the present pair-matched case-control study was to investigate the outcome of patients with SARS-CoV-2 infection in obese and non-obese patients matched considering gender, age, number of comorbidities, and Charlson Comorbidity Index. METHODS: All the adults hospitalized for SARS-CoV-2 infection and with BMI ≥ 30 kg/m2 were included (Cases). For each Case, two patients with BMI < 30 kg/m2 pair matched for gender, age (±5 years), number of comorbidities (excluding obesity), and Charlson Comorbidity Index (±1) were enrolled (Controls). RESULTS: Of the 1282 patients with SARS-CoV-2 infection followed during the study period, 141 patients with obesity and 282 patients without were enrolled in the case and control groups, respectively. Considering matching variables, there was no statistical difference between the two groups. Patients in the Control group developed more frequently a mild-moderate disease (67% vs. 46.1%, respectively), whereas obese patients were more prone to need intensive care treatment (41.8% vs. 26.6%, respectively; p = 0.001). Moreover, the prevalence of death during hospitalization was higher in the Case group than in the Control group (12.1% vs. 6.4%, p = 0.046). DISCUSSION: We confirmed an association between obesity and severe outcome of patients with COVID-19, also considering other factors associated with a severe outcome of COVID-19. Thus, in the case of SARS-CoV-2 infection, the subjects with BMI ≥ 30 kg/m2 should be evaluated for early antiviral treatment to avoid the development of a severe course.
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INTRODUCTION: Since the beginning of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic an important tool for patients with Coronavirus Disease 2019 (COVID-19) has been the computed tomography (CT) scan, but not always available in some settings The aim was to find a cut-off that can predict worsening in patients with COVID-19 assessed with a computed tomography (CT) scan and to find laboratory, clinical or demographic parameters that may correlate with a higher CT score. METHODS: We performed a multi-center, observational, retrospective study involving seventeen COVID-19 Units in southern Italy, including all 321 adult patients hospitalized with a diagnosis of COVID-19 who underwent at admission a CT evaluated using Pan score. RESULTS: Considering the clinical outcome and Pan score, the best cut-off point to discriminate a severe outcome was 12.5. High lactate dehydrogenase (LDH) serum value and low PaO2/FiO2 ratio (P/F) resulted independently associated with a high CT score. The Area Under Curve (AUC) analysis showed that the best cut-off point for LDH was 367.5 U/L and for P/F 164.5. Moreover, the patients with LDH> 367.5 U/L and P/F < 164.5 showed more frequently a severe CT score than those with LDH< 367.5 U/L and P/F> 164.5, 83.4%, vs 20%, respectively. CONCLUSIONS: A direct correlation was observed between CT score value and outcome of COVID-19, such as CT score and high LDH levels and low P/F ratio at admission. Clinical or laboratory tools that predict the outcome at admission to hospital are useful to avoiding the overload of hospital facilities.
