Determining the impact of an artificial intelligence tool on the management of pulmonary nodules detected incidentally on CT (DOLCE) study protocol: a prospective, non-interventional multicentre UK study.

INTRODUCTION: In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models. METHODS AND ANALYSIS: This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness. ETHICS AND DISSEMINATION: This study has been reviewed and given a favourable opinion by the South Central-Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities. TRIAL REGISTRATION NUMBER: NCT05389774.

Risk of Mortality Following Surgery in Patients With a Previous Cardiovascular Event.

Importance: There is a lack of consensus regarding the interval of time-dependent postoperative mortality risk following acute coronary syndrome or stroke. Objective: To determine the magnitude and duration of risk associated with the time interval between a preoperative cardiovascular event and 30-day postoperative mortality. Design, Setting, and Participants: This is a longitudinal retrospective population-based cohort study. This study linked data from the Hospital Episode Statistics for National Health Service England, Myocardial Ischaemia National Audit Project and the Office for National Statistics mortality registry. All adults undergoing a National Health Service-funded noncardiac, nonneurologic surgery in England between April 1, 2007, and March 31, 2018, registered in Hospital Episode Statistics Admitted Patient Care were included. Data were analyzed from July 2021 to July 2022. Exposure: The time interval between a previous cardiovascular event (acute coronary syndrome or stroke) and surgery. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. Secondary outcomes were postoperative mortality at 60, 90, and 365 days. Multivariable logistic regression models with restricted cubic splines were used to estimate adjusted odds ratios. Results: There were 877 430 patients with and 20 582 717 without a prior cardiovascular event (overall mean [SD] age, 53.4 [19.4] years; 11 577 157 [54%] female). Among patients with a previous cardiovascular event, the time interval associated with increased risk of postoperative mortality was surgery within 11.3 months (95% CI, 10.8-11.7), with subgroup risks of 14.2 months before elective surgery (95% CI, 13.3-15.3) and 7.3 months for emergency surgery (95% CI, 6.8-7.8). Heterogeneity in these timings was noted across many surgical specialties. The time-dependent risk intervals following stroke and myocardial infarction were similar, but the absolute risk was greater following a stroke. Regarding surgical urgency, the risk of 30-day mortality was higher in those with a prior cardiovascular event for emergency surgery (adjusted hazard ratio, 1.35; 95% CI, 1.34-1.37) and an elective procedure (adjusted hazard ratio, 1.83; 95% CI, 1.78-1.89) than those without a prior cardiovascular event. Conclusions and Relevance: In this study, surgery within 1 year of an acute coronary syndrome or stroke was associated with increased postoperative mortality before reaching a new baseline, particularly for elective surgery. This information may help clinicians and patients balance deferring the potential benefits of the surgery against the desire to avoid increased mortality from overly expeditious surgery after a recent cardiovascular event.

Investigating modifiable pathways in psoriasis: A Mendelian randomization study.

BACKGROUND: Potentially modifiable risk factors have previously been investigated only in conventional observational studies. OBJECTIVE: To assess whether genetically predicted exposures to modifiable factors are associated with the risk of psoriasis. METHODS: Two-sample Mendelian randomization (MR) analysis. RESULTS: An increased risk of psoriasis was noted for genetically predicted lifetime smoking index (odds ratio [OR]MR-IVW = 2.11; 95% confidence interval [CI], 1.28-3.51), childhood (OR MR-IVW = 1.40; 95% CI, 1.14-1.71) and adult body mass index (OR MR-IVW = 1.63; 95% CI, 1.32-2), waist (OR IVW = 1.86; 95% CI, 1.31-2.64), and hip circumference (OR MR-IVW = 1.55; 95% CI, 1.15-2.07). Protective association was also reported between genetically predicted longer sleep duration (OR MR-IVW = 0.56; 95% CI 0.37-0.84) and increased years of education (OR MR-IVW = 0.78; 95% CI, 0.62-0.98). This effect of education persisted in multivariable MR after adjusting for genetic predictors of smoking and adult body mass index (ORMVMR-IVW = 0.72; 95% CI, 0.56-0.92). LIMITATIONS: It was not possible to stratify for psoriasis severity. CONCLUSION: Smoking cessation and prevention of obesity are important strategies for decreasing the incidence of psoriasis. Similarly, targeting education inequality is expected to lead further to reductions in cases of psoriasis.