External validation of a cardiovascular risk model for Omani patients with type 2 diabetes mellitus: a retrospective cohort study

Objectives To externally validate a recently developed cardiovascular disease (CVD) risk model for Omanis with type 2 diabetes mellitus (T2DM).Design Retrospective cohort study.Setting Nine primary care centres in Muscat Governorate, Oman.Participants A total of 809 male and female adult Omani patients with T2DM free of CVD at baseline were selected using a systematic random sampling strategy.Outcome measures Data regarding CVD risk factors and outcomes were collected from the patients’ electronic medical records between 29 August 2020 and 2 May 2021. The ability of the model to discriminate CVD risk was assessed by calculating the area under the curve (AUC) of the receiver-operating characteristic curve. Calibration of the model was evaluated using a Hosmer-Lemeshow χ2 test and the Brier score.Results The incidence of CVD events over the 5-year follow-up period was 4.6%, with myocardial infarction being most frequent (48.6%), followed by peripheral arterial disease (27%) and non-fatal stroke (21.6%). A cut-off risk value of 11.8% demonstrated good sensitivity (67.6%) and specificity (66.5%). The area under the curve (AUC) was 0.7 (95% CI 0.60 to 0.78) and the Brier score was 0.01. However, the overall mean predicted risk was greater than the overall observed risk (11.8% vs 4.6%) and the calibration graph showed a relatively significant difference between predicted and observed risk levels in different subgroups.Conclusions Although the model slightly overestimated the CVD risk, it demonstrated good discrimination. Recalibration of the model is required, after which it has the potential to be applied to patients presenting to diabetic care centres elsewhere in Oman

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