As surgeries are performed around the clock, the time of surgery might have an impact on outcomes. Our aim is to investigate the impact of daytime and nighttime shifts on surgeons and their performance. We believe that such studies are important to enhance the quality of surgeries and their outcomes and help understand the effects of time of the day on surgeons and the surgeries they perform. A retrospective cohort study was conducted using the database from the King Abdulaziz Medical City trauma center. We selected 330 cases of patients between 2015 and 2018, who underwent a trauma intervention surgery within 24 hours after admission. Patients were aged 15 years and above who underwent 1 or more of the following trauma interventions: neurosurgery, general surgery, plastic surgery, vascular surgery, orthopedics, ophthalmology, and/or otolaryngology. We divided the work hours into 3 shifts: 8 am to 3:59 pm , 4 pm to 11:59 pm , and midnight to 7:59 am . Participants’ mean age was 31.4 (standard deviation ± 13) years. Most surgeries occurred on weekdays (68.4%). Complications were one and a half times more on weekends, with 5 complicated cases on weekends (1.55%) and 3 (0.9%) on weekdays. Half of all surgeries were performed in the morning (152 cases, 53.15%); 73 surgeries (25.5%) were performed in the evening and 61 (21.3%) were performed late at night. Surgeries performed during late-night shifts were marginally better. Complications occurred in 4 out of 152 morning surgeries (2.6%), 2 out of 73 evening surgeries (2.7%), and only 1 out of 61 late-night surgeries (1.6%). The earlier comparison scored a P -value of >.99, suggesting that patients in morning and evening surgeries were twice more likely to experience complications than late-night surgeries. This study may support previous research that there is little difference in outcomes between daytime and nighttime surgeries. The popular belief that rested physicians are better physicians requires further assessment and research.

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This epidemiological cross-sectional data-based study aimed to explore the morbidity and mortality patterns of novel coronavirus infections (COVID-19) among the worst affected regions of the world. The data on the worldwide pandemic of COVID-19 were obtained from World Health Organization (WHO), John Hopkin’s University research center, Worldometer, Centers for Disease Control and Prevention (CDC), since its outbreak until August 5, 2020. The evidences were also recorded from research papers published in international scientific journals indexed in Pub Med and Institute of Scientific Information (ISI) Web of Science. The findings show that the average of COVID-19 cases in Europe is 154754 cases per million of the population, in America (both north and south) is 47982 cases per million of the population and in Asia is 13280 cases per million of the population. The mean value of mortality rate in Europe, America (both north and south) and Asia is 2436 deaths per million of population, 2158 deaths per million of population, and 181 deaths per million people, respectively. The study broadly concludes that the infection rate and mortality are higher in developed countries than in developing or underdeveloped countries. The perceptible causes of increase in infection rate and mortality in developed European and American countries may be the difference in individual and herd immunity in the population due to less exposure to similar viruses. The lack of exposure may be attributed to better economic conditions leading to relatively good hygienic practices as compared to the developing and underdeveloped countries of the Asian region.