The current outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread across the world. No specific antiviral agents have been adequately evidenced for the treatment of coronavirus disease 2019 (COVID-19). Although metformin has been recommended as a host-directed therapy for COVID-19, there are some opposite views. The effects of metformin on the disease severity of patients with COVID-19 with diabetes during hospitalization remains unclear. This study aimed to determine the effect of metformin on disease severity. We enrolled 110 hospitalized patients with COVID-19 with diabetes prescribed either metformin or non-metformin hypoglycemic treatment for a case-control study. The primary outcome was the occurrence of life-threatening complications. There were no differences between the two groups in age, sex, comorbidities, and clinical severity at admission. Blood glucose and lactate dehydrogenase levels of the metformin group were higher than those of the non-metformin group at admission. Other laboratory parameters at admission and treatments after admission were not different between the two groups. Strikingly, the percentage of patients who experienced life-threatening complications was significantly higher in the metformin group (28.6% (16/56) vs. 7.4% (4/54), P = 0.004). Antidiabetic therapy with metformin was associated with a higher risk of disease progression in patients with COVID-19 with diabetes during hospitalization (adjusted odds ratio = 3.964, 95% confidence interval 1.034-15.194, P = 0.045). This retrospective analysis suggested a potential safety signal for metformin, the use of which was associated with a higher risk of severe COVID-19. We propose that metformin withdrawal in patients with COVID-19 be considered to prevent disease progression. The current outbreak of coronavirus disease 2019 (COVID-19) by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread quickly through human-to-human transmission, 1 and has been declared as "Public Health Emergency of International Concern" by the World Health Organization (WHO). As both SARS-CoV 2 and Middle East respiratory syndrome coronavirus (MERS-CoV), 3 the SARS-CoV-2 outbreak has caused a large number of human deaths
Aim Shortening the length of stay (LOS) is a potential and sustainable way to relieve the pressure that type 2 diabetes mellitus (T2DM) patients placed on the public health system. Method Multi-stage random sampling was used to obtain qualified hospitals and electronic medical records for patients discharged with T2DM in 2018. A box-cox transformation was adopted to normalize LOS. Multilevel model was used to verify hospital cluster effect on LOS variations and screen potential factors for LOS variations from both individual and hospital levels. Result 50 hospitals and a total of 12,888 T2DM patients were included. Significant differences in LOS variations between hospitals, and a hospital cluster effect on LOS variations (t = 92.188, P<0.001) was detected. The results showed that female patients, patients with new rural cooperative’ medical insurance, hospitals with more beds, and hospitals with faster bed turnovers had shorter LOS. Conversely, elderly patients, patients with urban workers’ medical insurance, patients requiring surgery, patients with the International Classification of Diseases coded complication types E11.1, E11.2, E11.4, E11.5, and other complications cardiovascular diseases, grade III hospitals, hospitals with a lower doctor-to-nurse ratio, and hospitals with more daily visits per doctor had longer LOS. Conclusions The evidence proved that hospital cluster effect on LOS variation did exist. Complications and patients features at individual level, as well as organization and resource characteristics at hospital level, had impacted LOS variations to varying degrees. To shorten LOS and better meet the medical demand for T2DM patients, limited health resources must be allocated and utilized rationally at hospital level, and the patients with the characteristics of longer LOS risk must be identified in time. More influencing factors on LOS variations at different levels are still worth of comprehensive exploration in the future.
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