Background: Study of factors/predictors leading to the disease severity is important. They help us for the early identification of the patients who are susceptible to develop severe form of disease. Cases with a set of unfavorable factors can be given priority attention for the management thereby it may be possible to reduce the mortality rates. Objective: The objective of this study was to study the patient-related risk factors for predicting severity of coronavirus disease 2019 (COVID-19) infection admitted to a tertiary care hospital. Methods: A hospital-based retrospective study was carried out among 305 cases of COVID-19. Hospital records of these cases were studied. Sociodemographic variables and presence of comorbidities were noted. Disease severity was classified as per the standard guidelines. It was classified as mild, moderate, and severe. Univariate and multivariate analysis was carried out. Results: Majority, i.e., 42.3% had severe disease. On univariate analysis, advanced age, coming from rural area, preexisting hypertension, being obese were significant risk factors for severe disease (P < 0.05). Those with severe disease had total risk factors score of 3.36 ± 1.68 compared to 2.48 ± 1.67 for mild or moderate disease, and this difference was statistically significant (P < 0.05). In the final model, coming from rural area and advanced age were the significant predictors of severe disease in the present study (P < 0.05). Conclusion: Advanced age and being from rural area were the significant predictors of severe disease in the present study.

Background: Type 2 diabetes and insomnia are common health issues which have a detrimental relationship with each other. Clinical management of diabetes in patients with poor sleep quality is a challenge. Therefore, understanding the correlation between the diabetic status, the presence of diabetes-related complications, and poor sleep quality among diabetic patients can help physicians in the better management of such cases. Objective: The objective of this study was to study the sleep quality among patients with type 2 diabetes. Materials and Methods: A cross-sectional study was carried out among 200 patients with type 2 diabetes. “The Pittsburgh Sleep Quality Index (PSQI)” questionnaire was used to document the quality of sleep. HbA1c and fasting blood sugar were estimated. Complications of diabetes were assessed using investigations such as electrocardiography, urine albumin, and other relevant investigations as and when indicated. Type of treatment was recorded from the preexisting prescription. Binary logistic regression analysis was used to calculate the adjusted odds ratio. Results: The mean age was 55.08 ± 13.02 years. Forty-five percent reported fairly good subjective sleep quality. 26.5% had 31–60 min sleep latency. Fifty-one percent had sleep duration of more than 7 h. Habitual sleep efficiency was >85% in 82.5% of study participants. 58.5% had sleep disturbances for less than a week. Ninety-five percent did not use any sleep medication and 62% had no daytime dysfunction during the past month. The prevalence of poor sleep quality was 52%. Among all the factors studied for association with poor sleep quality, only the presence of complications of diabetes were found to be significantly associated with poor sleep quality after adjusting for other factors (adjusted odds ratio = 4.33; 95% confidence interval = 2.13–8.78; P = 0.000). Conclusion: The prevalence of poor sleep quality among diabetics in the present study was high. This association was noted only with the presence of complications of diabetes. Hence, efforts to prevent complications of diabetes by regular follow-up and appropriate treatment along with regular screening for complications can prevent complications associated with diabetes and hence prevent poor sleep quality.