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BackgroundThere is increasing evidence to suggest vitamin D plays a role in immune and vascular function; hence, it may be of biological and clinical relevance for patients undergoing major surgery. With a greater number of randomised studies being conducted evaluating the impact of vitamin D supplementation on surgical patients, it is an opportune time to conduct further analysis of the impact of vitamin D on surgical outcomes.MethodsMEDLINE, EMBASE and the Cochrane Trials Register were interrogated up to December 2023 to identify randomised controlled trials of vitamin D supplementation in surgery. The risk of bias in the included studies was assessed using the Cochrane Risk of Bias tool. A narrative synthesis was conducted for all studies. The primary outcome assessed was overall postoperative survival.ResultsWe screened 4883 unique studies, assessed 236 full-text articles and included 14 articles in the qualitative synthesis, comprising 1982 patients. The included studies were highly heterogeneous with respect to patient conditions, ranging from open heart surgery to cancer operations to orthopaedic conditions, and also with respect to the timing and equivalent daily dose of vitamin D supplementation (range: 0.5–7500 mcg; 20–300 000 IU). No studies reported significant differences in overall survival or postoperative mortality with vitamin D supplementation. There was also no clear evidence of benefit with respect to overall or intensive care unit length of stay.DiscussionNumerous studies have reported the benefits of vitamin D supplementation in different surgical settings without any consistency. However, this systematic review found no clear evidence of benefit, which warrants the supposition that a single biological effect of vitamin D supplementation does not exist. The observed improvement in outcomes in low vitamin D groups has not been convincingly proven beyond chance findings.Trial registration numberCRD42021232067.

A 77-year-old man was admitted for aortic valve replacement and combined coronary bypass grafting. Grossly, labile arterial pressures were demonstrated on anesthetic induction prompting cancellation and Intensive Care Unit transfer. Urine analysis identified high normetadrenaline/creatinine ratio, plasma metanephrine, and plasma normetanephrine. A left adrenal lesion on computed tomography scan collectively indicated pheochromocytoma. Laparoscopic adrenalectomy was prioritized at multidisciplinary team before cardiac surgery. Vague symptoms of pheochromocytoma pose a diagnostic problem, being often attributed to common/co-existing pathology. The blood pressure instability on anesthetic required precise control, multidisciplinary input, and awareness of possible diagnosis as a routine intervention for hypotension may have been fatal in view of underlying cardiac pathology.

A best evidence topic in cardiac surgery was written according to a structured protocol. The question addressed was ‘in the first 3-months after mitral valve repair (MVRep) which antiplatelet and/or anticoagulant strategy should be instigated in patients who remain in normal sinus rhythm’. Altogether 77 papers were found using the reported search, of which 8 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. We conclude that there remains a lack of high-quality randomized studies, controlling for postoperative cardiac rhythm, comparing vitamin K antagonists (VKA) and antiplatelet therapy in the early postoperative period following isolated MVRep. Current guidelines are based on limited evidence or expert consensus alone. Based on the currently available evidence, the authors conclude that antiplatelet therapy (e.g. aspirin) is safe and appropriate to use in the 3-month postoperative period following isolated MVRep, in those without preoperative, or postoperative atrial fibrillation. Rates of thromboembolic events are comparable between these patient groups (i.e. VKA versus aspirin), whilst VKA therapy is associated with increased rates of major bleeding events and mortality.

Prehabilitation prior to surgery has been shown to reduce postoperative complications, reduce length of hospital stay and improve quality of life after cancer and limb reconstruction surgery. However, there are minimal data on the impact of prehabilitation in patients undergoing cardiac surgery, despite the fact these patients are generally older and have more comorbidities and frailty. This trial will assess the feasibility and impact of a prehabilitation intervention consisting of exercise and inspiratory muscle training on preoperative functional exercise capacity in adult patients awaiting elective cardiac surgery, and determine any impact on clinical outcomes after surgery. PrEPS is a randomised controlled single-centre trial recruiting 180 participants undergoing elective cardiac surgery. Participants will be randomised in a 1:1 ratio to standard presurgical care or standard care plus a prehabilitation intervention. The primary outcome will be change in functional exercise capacity measured as change in the 6 min walk test distance from baseline. Secondary outcomes will evaluate the impact of prehabilitation on preoperative and postoperative outcomes including; respiratory function, health-related quality of life, anxiety and depression, frailty, and postoperative complications and resource use. This trial will evaluate if a prehabilitation intervention can improve preoperative physical function, inspiratory muscle function, frailty and quality of life prior to surgery in elective patients awaiting cardiac surgery, and impact postoperative outcomes. A favourable opinion was given by the Sheffield Research Ethics Committee in 2019. Trial findings will be disseminated to patients, clinicians, commissioning groups and through peer-reviewed publication. ISRCTN13860094.

A 77-year-old man was admitted for aortic valve replacement and combined coronary bypass grafting. Grossly, labile arterial pressures were demonstrated on anesthetic induction prompting cancellation and Intensive Care Unit transfer. Urine analysis identified high normetadrenaline/creatinine ratio, plasma metanephrine, and plasma normetanephrine. A left adrenal lesion on computed tomography scan collectively indicated pheochromocytoma. Laparoscopic adrenalectomy was prioritized at multidisciplinary team before cardiac surgery. Vague symptoms of pheochromocytoma pose a diagnostic problem, being often attributed to common/co-existing pathology. The blood pressure instability on anesthetic required precise control, multidisciplinary input, and awareness of possible diagnosis as a routine intervention for hypotension may have been fatal in view of underlying cardiac pathology.

Timeseries data captured by unoccupied aircraft systems (UASs) are increasingly used for agricultural applications requiring accurate prediction of plant phenotypes from remotely sensed imagery. However, prediction models often fail to generalize well from one year to the next or to new environments. Here, we investigate the ability of various machine learning (ML) approaches to improve yield prediction accuracy in new environments from multispectral timeseries imagery acquired on a set of rice (Oryza sativa L.) experiments with different management treatments and varieties. We also trained deep learning models that perform automated feature extraction and compared these against a suite of other approaches. We observed similar performance on a held‐out growing season for a spatiotemporal model (a three‐dimensional convolutional neural network) trained on raw images compared to simpler workflows using dimension reduction of manually extracted features from temporal imagery (i.e., vegetation indices and image texture properties). Manifold learning on raw imagery was better suited for the prediction of phenological traits due to the preservation of local structure in image embeddings at some time points. Together, these results highlight the competitiveness of classical ML approaches for UAS image analysis alongside computationally expensive deep learning models. Along with a new benchmark dataset for rice, our results help extend the toolkit for UAS image analysis, contributing to improved phenotype prediction in plant breeding and precision agriculture applications. Core Ideas Linear yield prediction models based on multitemporal drone imagery transfer poorly to new growing seasons. Workflows using nonlinear models improve generalization to new growing seasons. Manifold learning shows promise for developmental trajectory inference and phenological traits. A new public benchmark dataset of multitemporal UAS imagery for rice is made available.