For clinical follow-up, features of SDHB mutation-associated disease include a later age of onset, extraadrenal (abdominal or thoracic) tumors, and a higher rate of malignancy. In contrast, SDHD mutation carriers, in addition to head and neck paragangliomas, should be observed for multifocal tumors, infrequent malignancy, and the possibility of extraadrenal pheochromocytoma.

Background Surgical audit, sometimes including public reporting, is an important foundation of high quality health care. We aimed to assess the validity of a novel outcome metric, days at home up to 30 days after surgery , as a surgical outcome measure in clinical trials and quality assurance. Methods This was a multicentre, registry-based cohort study. We used prospectively collected hospital and national healthcare registry data obtained from patients aged 18 years or older undergoing a broad range of surgeries in Sweden over a 10-year period. The association between days at home up to 30 days after surgery and patient (older age, poorer physical status, comorbidity) and surgical (elective or non-elective, complexity, duration) risk factors, process of care outcomes (re-admissions, discharge destination), clinical outcomes (major complications, 30-day mortality) and death up to 1 year after surgery were measured. Findings From January, 2005, to December, 2014, we obtained demographic and perioperative data on 636,885 patients from 21 Swedish hospitals. Mortality at 30 days and one year was 1.8% and 7.3%, respectively. The median (IQR) days at home up to 30 days after surgery was 27 (23–29), being significantly lower among high-risk patients, those recovering from more complex surgical procedures, and suffering serious postoperative complications (all p < 0.0001). Patients with 8 days or less at home up to 30 days after surgery had a nearly 7-fold higher risk of death up to 1 year postoperatively when compared with those with 29 or 30 days at home (adjusted HR 6.78 [95% CI: 6.44–7.13]). Interpretation Days at home up to 30 days after surgery is a valid, easy to measure patient-centred outcome metric. It is highly sensitive to changes in surgical risk and impact of complications, and has prognostic importance; it is therefore a valuable endpoint for perioperative clinical trials and quality assurance. Funding Swedish National Research Council Medicine and Stockholm County Council ALF-project grant (LE), and the Australian National Health and Medical Research Council (PM).

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Background Risk prediction tools can be used in the perioperative setting to identify high‐risk patients who may benefit from increased surveillance and monitoring in the postoperative period, to aid shared decision‐making, and to benchmark risk‐adjusted hospital performance. We evaluated perioperative risk prediction tools relevant to an Australian context. Methods A systematic review of perioperative mortality risk prediction tools used for adults undergoing inpatient noncardiac surgery, published between 2011 and 2019 (following an earlier systematic review). We searched Medline via OVID using medical subject headings consistent with the three main areas of risk, surgery and mortality/morbidity. A similar search was conducted in Embase. Tools predicting morbidity but not mortality were excluded, as were those predicting a composite outcome that did not report predictive performance for mortality separately. Tools were also excluded if they were specifically designed for use in cardiac or other highly specialized surgery, emergency surgery, paediatrics or elderly patients. Results Literature search identified 2568 studies for screening, of which 19 studies identified 21 risk prediction tools for inclusion. Conclusion Four tools are candidates for adapting in the Australian context, including the Surgical Mortality Probability Model (SMPM), Preoperative Score to Predict Postoperative Mortality (POSPOM), Surgical Outcome Risk Tool (SORT) and NZRISK. SORT has similar predictive performance to POSPOM, using only six variables instead of 17, contains all variables of the SMPM, and the original model developed in the UK has already been successfully adapted in New Zealand as NZRISK. Collecting the SORT and NZRISK variables in a national surgical outcomes study in Australia would present an opportunity to simultaneously investigate three of our four shortlisted models and to develop a locally valid perioperative mortality risk prediction model with high predictive performance.

Accurately measuring the incidence of major postoperative complications is essential for funding and reimbursement of healthcare providers, for internal and external benchmarking of hospital performance and for valid and reliable public reporting of outcomes. Actual or surrogate outcomes data are typically obtained by one of three methods: clinical quality registries, clinical audit, or administrative data. In 2017 a perioperative registry was developed at the Alfred Hospital and mapped to administrative and clinical data. This study investigated the statistical agreement between administrative data (International Statistical Classification of Diseases and Related Health Problems (10th edition) Australian Modification codes) and clinical audit by anaesthetists in identifying major postoperative complications. The study population included 482 high-risk surgical patients referred to the Alfred Hospital anaesthesia postoperative service over two years. Clinical audit was conducted to determine the presence of major complications and these data were compared to administrative data. The main outcome was statistical agreement between the two methods, as defined by Cohen’s kappa statistic. Substantial agreement was observed for five major complications, moderate agreement for three, fair agreement for six and poor agreement for two. Sensitivity and positive predictive value ranged from 0 to 100%. Specificity was above 90% for all complications. There was important variation in inter-rater agreement. For four of the five complications with substantial agreement between administrative data and clinical audit, sensitivity was only moderate (61.5%–75%). Using International Statistical Classification of Diseases and Related Health Problems (10th edition) Australian Modification codes to identify postoperative complications at our hospital has high specificity but is likely to underestimate the incidence compared to clinical audit. Further, retrospective clinical audit itself is not a highly reliable method of identifying complications. We believe a perioperative clinical quality registry is necessary to validly and reliably measure major postoperative complications in Australia for benchmarking of hospital performance and before public reporting of outcomes should be considered.

Prolonged fasting leads to a shift from carbohydrate to fat as the primary energy source, resulting in the production of ketones such as beta-hydroxybutyrate. Hyperketonaemia and ketoacidosis have been observed in young children fasting for surgery. The aim of this study was to investigate ketonaemia in adults fasted for surgery. One hundred non-diabetic adults presenting for elective or emergency surgery were assessed for the presence of hyperketonaemia (beta-hydroxybutyrate levels more than 1 mmol/l), and the relationship between beta-hydroxybutyrate, blood glucose and fasting duration was investigated. Three of 100 patients demonstrated hyperketonaemia, one of whom had ingested a ketogenic supplement the evening prior to surgery. No patient demonstrated beta-hydroxybutyrate levels suggestive of ketoacidosis (above 3 mmol/l). No relationship between fasting duration and ketone or glucose levels was observed. We found no evidence that prolonged preoperative fasting led to beta-hydroxybutyrate levels consistent with ketoacidosis.

Registry randomised clinical trials (RRCTs) have the potential to provide pragmatic answers to important clinical questions. RRCTs can be embedded into large population-based registries or smaller single site registries to provide timely answers at a reduced cost compared with traditional randomised controlled trials. RRCTs can take a number of forms in addition to the traditional individual-level randomised trial, including parallel group trials, platform or adaptive trials, cluster randomised trials and cluster randomised stepped-wedge trials. From an implementation perspective, initially it is advantageous to embed RRCT into well-established registries as these have typically already overcome any issues with end point validation and adjudication. With advances in data linkage and data quality, RRCTs can play an important role in answering clinical questions in a pragmatic, cost-effective way.

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