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Objective: To describe and critique tools used to assess frailty in vascular surgery patients, and investigate its associations with patient factors and outcomes. Background: Increasing evidence shows negative impacts of frailty on outcomes in surgical patients, but little investigation of its associations with patient factors has been undertaken. Methods: Systematic review and meta-analysis of studies reporting frailty in vascular surgery patients (PROSPERO registration: CRD42018116253) searching Medline, Embase, CINAHL, PsycINFO, and Scopus. Quality of studies was assessed using Newcastle–Ottawa scores (NOS) and quality of evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria. Associations of frailty with patient factors were investigated by difference in means (MD) or expressed as risk ratios (RRs), and associations with outcomes expressed as odds ratios (ORs) or hazard ratios (HRs). Data were pooled using random-effects models. Results: Fifty-three studies were included in the review and only 8 (15%) were both good quality (NOS ≥ 7) and used a well-validated frailty measure. Eighteen studies (62,976 patients) provided data for the meta-analysis. Frailty was associated with increased age [MD 4.05 years; 95% confidence interval (CI) 3.35, 4.75], female sex (RR 1.32; 95% CI 1.14, 1.54), and lower body mass index (MD −1.81; 95% CI −2.94, −0.68). Frailty was associated with 30-day mortality [adjusted OR (AOR) 2.77; 95% CI 2.01–3.81), postoperative complications (AOR 2.16; 95% CI 1.55, 3.02), and long-term mortality (HR 1.85; 95% CI 1.31, 2.62). Sarcopenia was not associated with any outcomes. Conclusion: Frailty, but not sarcopenia, is associated with worse outcomes in vascular surgery patients. Well-validated frailty assessment tools should be preferred clinically, and in future research.

This systematic review evaluated the knowledge and awareness of peripheral artery disease (PAD) within the general public (including patients with peripheral vascular disease), nonspecialist healthcare professionals (nsHCP), and trainees (medical students and trainee doctors). Relevant articles were identified from electronic databases using key search terms: ‘peripheral artery disease’; ‘limb ischaemia’; ‘intermittent claudication’; ‘knowledge’; ‘understanding’; ‘public’; ‘medical professional’. The heterogeneous results were described narratively. A lack of knowledge and understanding of PAD (disease awareness) were identified in all groups. Among nsHCPs, factors which affect knowledge include the level of training, early clinical exposure and the presence of family members with cardiovascular/vascular disease. Within the general public, knowledge and awareness was improved if a family member/friend had a diagnosis, or following a patient-centred consultation with any HCP. Public campaigns are proven effective in improving disease knowledge/awareness in conditions such as stroke alongside sustained patient education. These may provide future avenues to improve PAD knowledge and awareness, in order to effectively manage risk factors and minimise delayed or missed diagnosis of PAD. (PROSPERO registration number: CRD42018117304)

Aims Most patients who receive implantable cardioverter defibrillators (ICDs) for primary prevention do not receive therapy during the lifespan of the ICD, whilst up to 50% of sudden cardiac death (SCD) occur in individuals who are considered low risk by conventional criteria. Machine learning offers a novel approach to risk stratification for ICD assignment. Methods and results Systematic search was performed in MEDLINE, Embase, Emcare, CINAHL, Cochrane Library, OpenGrey, MedrXiv, arXiv, Scopus, and Web of Science. Studies modelling SCD risk prediction within days to years using machine learning were eligible for inclusion. Transparency and quality of reporting (TRIPOD) and risk of bias (PROBAST) were assessed. A total of 4356 studies were screened with 11 meeting the inclusion criteria with heterogeneous populations, methods, and outcome measures preventing meta-analysis. The study size ranged from 122 to 124 097 participants. Input data sources included demographic, clinical, electrocardiogram, electrophysiological, imaging, and genetic data ranging from 4 to 72 variables per model. The most common outcome metric reported was the area under the receiver operator characteristic (n = 7) ranging between 0.71 and 0.96. In six studies comparing machine learning models and regression, machine learning improved performance in five. No studies adhered to a reporting standard. Five of the papers were at high risk of bias. Conclusion Machine learning for SCD prediction has been under-applied and incorrectly implemented but is ripe for future investigation. It may have some incremental utility in predicting SCD over traditional models. The development of reporting standards for machine learning is required to improve the quality of evidence reporting in the field.

Scope: There is extensive pre-clinical evidence for utility of curcuminoids across many diseases with a particular focus on cancer prevention, yet there remains a paucity of clinical evidence for its approved use. To assess current knowledge on the broader potential for clinical efficacy of curcumin and in particular, in cancer prevention strategies, this study undertook a systematic review determining the number and quality of randomized controlled trials (RCTs) undertaken across any pathology. Methods and Results: Search strategies for RCTs using a quantifiable amount of curcuminoids, are applied across Medline (Medical Literature Analysis and Retrieval System Online), Embase (Excerpta Medica dataBASE), Cochrane and clinicaltrials.gov. There are 314 curcuminoid-based RCTs, with 100 of these revealing significant within-and between-group changes relating to the primary outcome. Twenty three studies are conducted in a setting where there is an increased risk of cancer. Fifteen of these meet all prescribed quality criteria, and 10 reveal positive outcomes. Conclusions: A substantial number of studies reveal positive outcomes following curcumin use. However, despite the vast array of preclinical data, there are relatively few RCTs conducted in the prevention setting. Future approaches to trials must deliver improved robustness and credibility of curcumin-related research to facilitate approvals for use in clinical settings.