The PREDICT study aimed to determine how the COVID-19 pandemic affected surgical services and surgical patients and to identify predictors of outcomes in this cohort. Background: High mortality rates were reported for surgical patients with COVID-19 in the early stages of the pandemic. However, the indirect impact of the pandemic on this cohort is not understood, and risk predictors are yet to be identified. Methods: PREDICT is an international longitudinal cohort study comprising surgical patients presenting to hospital between March and August 2020, conducted alongside a survey of staff redeployment and departmental restructuring. A subgroup analysis of 3176 adult emergency patients, recruited by 55 teams across 18 countries is presented. Results: Among adult emergency surgical patients, all-cause in-hospital mortality (IHM) was 3.6%, compared to 15.5% for those with COVID-19. However, only 14.1% received a COVID-19 test on admission in March, increasing to 76.5% by July. Higher Clinical Frailty Scale scores (CFS >7 aOR 18 87), ASA grade above 2 (aOR 4.29), and COVID-19 infection (aOR 5.12) were independently associated with significantly increased IHM. The peak months of the first wave were independently associated with significantly higher IHM (March aOR 4.34; April aOR 4.25; May aOR 3.97), compared to non-peak months.During the study, UK operating theatre capacity decreased by a mean of 63.6% with a concomitant 27.3% reduction in surgical staffing. Conclusion:The first wave of the COVID-19 pandemic significantly impacted surgical patients, both directly through co-morbid infection and indirectly as shown by increasing mortality in peak months, irrespective of COVID-19 status. Higher CFS scores and ASA grades strongly predict outcomes in surgical patients and are an important risk assessment tool during the pandemic.

The baby was born full term via spontaneous vaginal delivery to non-consanguineous parents (Table 1). He was breastfed every 3-4 h. At 57 h-of-life, he missed a feed stretching to a 6-h feeding interval. He was then noted to be hypothermic, pale and lethargic with a weak cry. He was also hypotonic and had hepatomegaly. He was transferred to the special care nursery. Investigations showed hypoglycaemia (1.5 mmol/L) and transaminitis (Table 1). He was treated with a 10% dextrose bolus (2 mL/kg) and maintained on Solution 120 (dextrose containing fluids) at 120 mL/kg/day. Within 24 h, the patient's lethargy, hypothermia and hypoglycaemia resolved but abnormal transaminases persisted. The metabolic service was consulted on day 4 of life and the differential diagnosis included fatty-acid oxidation and glycogen storage disorders. The patient was transferred to the tertiary hospital for management. Septic work-up was negative. The laboratory findings of rhabdomyolysis and transaminitis especially AST which is present in high concentrations in skeletal muscles were more in keeping with a fattyacid oxidation disorder. The abnormal acylcarnitine species (particularly C14:1 and its ratio to C10) in the dried blood spot, increased C4:1 species on qualitative analysis of the plasma carnitine and results of the genetic and enzymatic tests supported the diagnosis of VLCAD deficiency (Table 1). With low long-chain fat diet supplemented with medium-chain fats, the creatine kinase gradually decreased. Our patient had a severe and early clinical presentation with significant hypoglycaemia and rhabdomyolysis with no cardiac involvement. Management of the patient included a low long-chain fat diet supplemented with medium-chain fats and avoidance of prolonged fasting or dehydration to prevent complications such as hypoglycaemia and rhabdomyolysis. 2 When the patient is unwell, especially with poor oral intake, the parents have been advised to call the metabolic service and present early to an emergency department for prompt assessment and intravenous glucose therapy. This case highlights that: (i) a fatty acid oxidation disorder should be suspected in newborns/infants with unexplained hypoglycaemia and/or acute liver disease, rhabdomyolysis and cardiac arrhythmias/ cardiomyopathy; (ii) glucose-containing fluids should be started; (iii) newborns with a fatty-acid oxidation disorder can become symptomatic even before newborn bloodspot screening can be done; and (iv) Prompt referral to a metabolic service is recommended.

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Background In the midst of the COVID-19 pandemic, patients have continued to present with endocrine (surgical) pathology in an environment depleted of resources. This study investigated how the pandemic affected endocrine surgery practice. Methods PanSurg-PREDICT is an international, multicentre, prospective, observational cohort study of emergency and elective surgical patients in secondary/tertiary care during the pandemic. PREDICT-Endocrine collected endocrine-specific data alongside demographics, COVID-19 and outcome data from 11–3-2020 to 13–9-2020. Results A total of 380 endocrine surgery patients (19 centres, 12 countries) were analysed (224 thyroidectomies, 116 parathyroidectomies, 40 adrenalectomies). Ninety-seven percent were elective, and 63% needed surgery within 4 weeks. Eight percent were initially deferred but had surgery during the pandemic; less than 1% percent was deferred for more than 6 months. Decision-making was affected by capacity, COVID-19 status or the pandemic in 17%, 5% and 7% of cases. Indication was cancer/worrying lesion in 61% of thyroidectomies and 73% of adrenalectomies and calcium 2.80 mmol/l or greater in 50% of parathyroidectomies. COVID-19 status was unknown at presentation in 92% and remained unknown before surgery in 30%. Two-thirds were asked to self-isolate before surgery. There was one COVID-19-related ICU admission and no mortalities. Consultant-delivered care occurred in a majority (anaesthetist 96%, primary surgeon 76%). Post-operative vocal cord check was reported in only 14% of neck endocrine operations. Both of these observations are likely to reflect modification of practice due to the pandemic. Conclusion The COVID-19 pandemic has affected endocrine surgical decision-making, case mix and personnel delivering care. Significant variation was seen in COVID-19 risk mitigation measures. COVID-19-related complications were uncommon. This analysis demonstrates the safety of endocrine surgery during this pandemic.

Background

Objective: To develop prediction models to predict long-term survival and time-to-recurrence following surgery for esophageal cancer. Background: Long-term survival after esophagectomy remains poor, with recurrence common. Prediction tools can identify high-risk patients and optimize treatment decisions based on their prognostic factors. Methods: Patients undergoing curative surgery from the European iNvestigation of SUrveillance After Resection for Esophageal Cancer study were included. Prediction models were developed for overall survival (OS) and disease-free survival (DFS) using Cox proportional hazards (CPH) and random survival forest (RSF). Model performance was evaluated using discrimination [time-dependent area under the curve (tAUC)] and calibration (visual comparison of predicted and observed survival probabilities). Results: This study included 4719 patients with an OS of 47.7% and DFS of 40.9% at 5 years. Sixteen variables were included. CPH and RSF demonstrated good discrimination with a tAUC of 78.2% [95% confidence interval (CI): 77.4%–79.1%] and 77.1% (95% CI: 76.1%–78.1%) for OS and a tAUC of 79.4% (95% CI: 78.5%–80.2%) and 78.6% (95% CI: 77.5%–79.5%), respectively for DFS at 5 years. CPH showed good agreement between predicted and observed probabilities in all quintiles. RSF showed good agreement for patients with survival probabilities between 20% and 80%. Conclusions: This study demonstrated that a statistical model can accurately predict long-term survival and time-to-recurrence after esophagectomy. Identification of patient groups at risk of recurrence and poor long-term survival can improve patient outcomes by optimizing treatment methods and surveillance strategies. Future work evaluating prediction-based decisions against standard decision-making is required to understand the clinical utility derived from prognostic model use.

A correction to this paper has been published: https://doi.org/10.1007/s00268‐021‐06171‐8

Background Integrated Care Systems (ICSs) are being introduced into the National Health Service (NHS) in England to replace Sustainability and Transformation Partnerships (STPs). They aim to improve care through place-based collaboration between primary, secondary and community providers. It is important that new organisational configurations adequately reflect existing patterns of patient care to minimise disruption resulting from patients crossing between ICSs. Methods All planned outpatient hospital clinic appointments from 1st April 2017 to 31st March 2018 for patients resident in England to NHS hospitals in England were identified from Hospital Episode Statistics. Markov Multiscale Community Detection (MMCD), an unsupervised network clustering technique, was used to identify natural communities of GP practices, hospitals and geographic regions according to patterns of GP practice registration and outpatient clinic referral. Two primary measures of care coverage were calculated; the proportion of patients registered to a GP practice in a different community than they reside, and the proportion of outpatient clinic appointments to hospitals in a different community to the referring GP practice. Results 109,830,647 outpatient clinic appointments were identified for 20,992,695 patients. A configuration of 42 ICSs was identified from MMCD to match the 42 STPs of the current configuration. In the current STP configuration, 534,946 patients (2.6%) were registered to a GP practice in a different STP than their residence, compared to 334,192 (1.6%) in the optimal MMCD configuration. 16,110,267 hospital clinic appointments (14.7%) occurred in a different STP to the referring GP practice, compared to 11,518,735 (10.5%) in the MMCD configuration. Conclusions Millions of hospital appointments annually occur in hospitals outside of the STP of the referring GP practice. Applying MMCD we derive spatially consistent partitions of NHS Trusts and GPs into ICSs that are more representative of existing patient flows while maintaining the intended population size and number of ICSs. The findings of this study should guide policymakers locally and nationally to determine where ICS boundaries may be redrawn and the extent to which such changes would better reflect the current needs of patients.