Designing an Isolation Center for Respiratory Diseases

 This scientific paper is focused on designing an isolation center for respiratory diseases that meets high standards of patient care while minimizing the risk of transmission of infectious viruses. The paper is based on a mixed-methods approach that includes a comprehensive review of existing literature on isolation centers and respiratory diseases, as well as visits to different facilities to gather data on best practices and equipment requirements. The resulting design incorporates feedback from experts in infection control and patient care to ensure that it meets high standards of patient care while minimizing the risk of transmission of infectious viruses. Key protocols for infection control were identified based on findings from the literature review and expert consultation. The paper provides valuable insights into best practices for designing and operating isolation centers treating respiratory diseases, and can help improve patient outcomes and reduce the spread of respiratory viruses in both high- and low-resource settings. The sources for this paper include a variety of references, including Bjørg Marit Andersen's Background Information on Isolation Routines, the World Health Organization's Infection Advice Center, the Centers for Disease Control and Prevention, the Royal College of Nursing's Standards for Assessing, Measuring and Monitoring Vital Signs in Infants, Children and Young People, and the Design Guideline for COVID-19 Isolation Center Institute of Architects Bangladesh. </p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population. The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous

Is perioperative COVID-19 really associated with worse surgical outcomes? A nationwide COVIDSurg propensity-matched analysis

BACKGROUND: Patients undergoing surgery with perioperative COVID-19 are suggested to have worse outcomes, but whether this is COVID-related or due to selection bias remains unclear. We aimed to compare the postoperative outcomes of patients with and without perioperative COVID-19. METHODS: Patients with perioperative COVID-19 diagnosed within 7 days before or 30 days after surgery between February and July 2020 from 68 US hospitals in COVIDSurg, an international multicenter database, were 1:1 propensity score matched to patients without COVID-19 undergoing similar procedures in the 2012 American College of Surgeons National Surgical Quality Improvement Program database. The matching criteria included demographics (e.g., age, sex), comorbidities (e.g., diabetes, chronic obstructive pulmonary disease, chronic kidney disease), and operation characteristics (e.g., type, urgency, complexity). The primary outcome was 30-day hospital mortality. Secondary outcomes included hospital length of stay and 13 postoperative complications (e.g., pneumonia, renal failure, surgical site infection). RESULTS: A total of 97,936 patients were included, 1,054 with and 96,882 without COVID-19. Prematching, COVID-19 patients more often underwent emergency surgery (76.1% vs. 10.3%, p &lt; 0.001). A total of 843 COVID-19 and 843 non-COVID-19 patients were successfully matched based on demographics, comorbidities, and operative characteristics. Postmatching, COVID-19 patients had a higher mortality (12.0% vs. 8.1%, p = 0.007), longer length of stay (6 [2-15] vs. 5 [1-12] days), and higher rates of acute renal failure (19.3% vs. 3.0%, p &lt; 0.001), sepsis (13.5% vs. 9.0%, p = 0.003), and septic shock (11.8% vs. 6.0%, p &lt; 0.001). They also had higher rates of thromboembolic complications such as deep vein thrombosis (4.4% vs. 1.5%, p &lt; 0.001) and pulmonary embolism (2.5% vs. 0.4%, p &lt; 0.001) but lower rates of bleeding (11.6% vs. 26.1%, p &lt; 0.001). CONCLUSION: Patients undergoing surgery with perioperative COVID-19 have higher rates of 30-day mortality and postoperative complications, especially thromboembolic, compared with similar patients without COVID-19 undergoing similar surgeries. Such information is crucial for the complex surgical decision making and counseling of these patients. (J Trauma Acute Care Surg. 2023;94: 513-524. Copyright (C) 2023 American Association for the Surgery of Trauma.)LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level IV

Outcomes and Their State-level Variation in Patients Undergoing Surgery With Perioperative SARS-CoV-2 Infection in the USA. A Prospective Multicenter Study

Objective: To report the 30-day outcomes of patients with perioperative SARS-CoV-2 infection undergoing surgery in the USA. Background: Uncertainty regarding the postoperative risks of patients with SARS-CoV-2 exists. Methods: As part of the COVIDSurg multicenter study, all patients aged ≥17 years undergoing surgery between January 1 and June 30, 2020 with perioperative SARS-CoV-2 infection in 70 hospitals across 27 states were included. The primary outcomes were 30-day mortality and pulmonary complications. Multivariable analyses (adjusting for demographics, comorbidities, and procedure characteristics) were performed to identify predictors of mortality. Results: A total of 1581 patients were included; more than half of them were males (n = 822, 52.0%) and older than 50 years (n = 835, 52.8%). Most procedures (n = 1261, 79.8%) were emergent, and laparotomies (n = 538, 34.1%). The mortality and pulmonary complication rates were 11.0 and 39.5%, respectively. Independent predictors of mortality included age ≥70 years (odds ratio 2.46, 95% confidence interval [1.65-3.69]), male sex (2.26 [1.53-3.35]), ASA grades 3-5 (3.08 [1.60-5.95]), emergent surgery (2.44 [1.31-4.54]), malignancy (2.97 [1.58-5.57]), respiratory comorbidities (2.08 [1.30-3.32]), and higher Revised Cardiac Risk Index (1.20 [1.02-1.41]). While statewide elective cancelation orders were not associated with a lower mortality, a sub-analysis showed it to be associated with lower mortality in those who underwent elective surgery (0.14 [0.03-0.61]). Conclusions: Patients with perioperative SARS-CoV-2 infection have a significantly high risk for postoperative complications, especially elderly males. Postponing elective surgery and adopting non-operative management, when reasonable, should be considered in the USA during the pandemic peaks

Y Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients

Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.</jats:p