Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

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Not AvailableCoronavirus disease, COVID-19 is the deadliest pandemic, which has affected most of the countries worldwide. Disease outbreak analysis has become a priority for the Government to take healthcare measures in reducing the impact of this pandemic. In this study, we attempt to analyse the disease outbreak data collected from 4th March 2020 to 26th May 2020 in India. Auto Regressive Integrated Moving Average (ARIMA) and Periodic Regression models were employed to predict the epidemiological trend of the incidence and probable number of new cases for the next ninety days for COVID-19 in India. The total number of probable daily new cases would be increased in the future as predicted by both ARIMA and Periodic regression models. Both ARIMA and Periodic regression models are best fitted to the observed data on daily incidence of COVID-19 in India. Incidence of COVID-19 expected to increase in next ninety days allowing to employ the stringent infection control measures such as public awareness and social distancing for effective mitigation and spread of disease in India.Not Availabl

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Not AvailableCOVID-19 is the deadliest pandemic, with over 18.2 million people infected with the SARS-CoV-2 virus by August 2, 2021 resulting in human deaths and economic losses. A number of countries have formulated control measures in order to prevent the spread of the virus. However, it is unknown when the outbreak will subside in different countries around the world. The role of predicting the COVID-19 trend is extremely difficult. Indian government has made disease outbreak analysis a priority in order to implement necessary healthcare measures to reduce the impact of this deadly pandemic on human health and country’s economics. The time series data for COVID-19 disease was collected from the website www.covid19india.org and were analyzed using a periodic regression model using the data from 22nd Janaury March 2020 to 01st Febraury 2021 the estimated number of cases until 27 July, 2021 was predicted to develop a stochastic model using periodic regression and were documented in top 10 highly infected states in India. The analysis revealed a increasing pattern for the number of reporting cases in the early days of prediction and decreasing trend for the number of reporting cases in the later days of prediction, which could decrease in future days in Karnataka, West Bengal, Uttar Pradesh, Telangana, Bihar and Haryana states. However, in Madhya Pradesh, Andhra Pradesh, Maharashtra and Tamil Nadu states showed a rapid phase of rise in disease incidence, which is likely to infect a larger population and suggests the disease's pandemic existence over a duration. Our model emphasizes the importance of ongoing and continuous efforts that are in place in all states to minimize occurrence of new cases of infections, so as to potentially improving India's economic wealth with the available resourcesNot Availabl