ABSTRACT
Introduction: Several studies have shown that diabetes mellitus (DM) is a risk factor for in hospital mortality due to COVID-19. The aim of our study was to analyze if prior clinical characteristics among DM patients affected the risk of in hospital mortality compared with nondiabetic patients hospitalized with COVID-19. Material and Methods: The study was based on a retrospective, observational design and was conducted at two hospitals located in Albacete (Spain). All patients hospitalized with COVID-19 since the start of the pandemic until 7 July 2020 were included. Results: During the study period, 1468 patients were hospitalized due to COVID-19;402 of them had DM prior to hospitalization. DM was associated with higher in hospital mortality (28.6% versus 17.5%) in the univariate analysis. But, in a multivariate logistic regression analysis, after adjusting for age, presence of hypertension, smoking, presence of COPD, ACEI, ARB, antiplatelet, or anticoagulant therapy, DM was not a significant risk factor for death. Patients with DM2 receiving insulin treatment had a higher risk of in hospital death than nondiabetic patients (OR 1.78 [1.13-2.81], p=0.0126) after age was considered. The age-associated relative risk was 1.06 (1.05-1.07, p<0.001) per year, whereas the relative risk associated with DM2 treated with insulin compared with no DM was 1.57 (1.11-2.23, p=0.0111) suggesting that DM2 treated with insulin entails a risk of in hospital COVID-19 death equivalent to being 9 years older. When previous logistic regression models included other variables related to personal history and prior nondiabetic treatments, the risks described showed no change. Conclusion: This study confirms that pre-admission need for insulin therapy before hospitalization in patients with DM2 are associated with higher in hospital mortality due to COVID-19 in a large sample of DM inpatients with COVID-19.
ABSTRACT
BACKGROUND: COVID-19 has a wide range of symptoms reported, which may vary from very mild cases (even asymptomatic) to deadly infections. Identifying high mortality risk individuals infected with the SARS-CoV-2 virus through a prediction instrument that uses simple clinical and analytical parameters at admission can help clinicians to focus on treatment efforts in this group of patients. METHODS: Data was obtained retrospectively from the electronic medical record of all COVID-19 patients hospitalized in the Albacete University Hospital Complex until July 2020. Patients were split into two: a generating and a validating cohort. Clinical, demographical and laboratory variables were included. A multivariate logistic regression model was used to select variables associated with in-hospital mortality in the generating cohort. A numerical and subsequently a categorical score according to mortality were constructed (A: mortality from 0% to 5%; B: from 5% to 15%; C: from 15% to 30%; D: from 30% to 50%; E: greater than 50%). These scores were validated with the validation cohort. RESULTS: Variables independently related to mortality during hospitalization were age, diabetes mellitus, confusion, SaFiO2, heart rate and lactate dehydrogenase (LDH) at admission. The numerical score defined ranges from 0 to 13 points. Scores included are: age ≥71 years (3 points), diabetes mellitus (1 point), confusion (2 points), onco-hematologic disease (1 point), SaFiO2 ≤ 419 (3 points), heart rate ≥ 100 bpm (1 point) and LDH ≥ 390 IU/L (2 points). The area under the curve (AUC) for the numerical and categorical scores from the generating cohort were 0.8625 and 0.848, respectively. In the validating cohort, AUCs were 0.8505 for the numerical score and 0.8313 for the categorical score. CONCLUSIONS: Data analysis found a correlation between clinical admission parameters and in-hospital mortality for COVID-19 patients. This correlation is used to develop a model to assist physicians in the emergency department in the COVID-19 treatment decision-making process.