Mechanisms underlying between-hospital variation in mortality after emergency laparotomies in England and Wales: A structure – process analysis

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Paternal anxiety and satisfaction in elective caesarean section

Whilst the overwhelming weight of data on caesarean section (CS) concerns maternal experiences, expectant fathers have historically been underrepresented. A literature search revealed only two relevant studies conducted in the past two decades; Chan demonstrated greater paternal anxiety at CS than normal vaginal delivery [1] and Capogna showed that epidural analgesia for the partner reduces paternal stress and enhances involvement in the experience of childbirth [2]. We undertook a survey of the partners of women undergoing CS under spinal anaesthesia to assess paternal preparedness and satisfaction with the proces

Systematic development and validation of a predictive model for major postoperative complications in the Peri-operative Quality Improvement Project (PQIP) dataset

Complications are common following major surgery and are associated with increased use of healthcare resources, disability and mortality. Continued reliance on mortality estimates risks harming patients and health systems, but existing tools for predicting complications are unwieldy and inaccurate. We aimed to systematically construct an accurate pre-operative model for predicting major postoperative complications; compare its performance against existing tools; and identify sources of inaccuracy in predictive models more generally. Complete patient records from the UK Peri-operative Quality Improvement Programme dataset were analysed. Major complications were defined as Clavien–Dindo grade ≥ 2 for novel models. In a 75% train:25% test split cohort, we developed a pipeline of increasingly complex models, prioritising pre-operative predictors using Least Absolute Shrinkage and Selection Operators (LASSO). We defined the best model in the training cohort by the lowest Akaike's information criterion, balancing accuracy and simplicity. Of the 24,983 included cases, 6389 (25.6%) patients developed major complications. Potentially modifiable risk factors (pain, reduced mobility and smoking) were retained. The best-performing model was highly complex, specifying individual hospital complication rates and 11 patient covariates. This novel model showed substantially superior performance over generic and specific prediction models and scores. We have developed a novel complications model with good internal accuracy, re-prioritised predictor variables and identified hospital-level variation as an important, but overlooked, source of inaccuracy in existing tools. The complexity of the best-performing model does, however, highlight the need for a step-change in clinical risk prediction to automate the delivery of informative risk estimates in clinical systems

Appearance and management of COVID-19 laryngo-tracheitis: two case reports.

We present two cases of coronavirus disease 2019 (COVID-19)-related laryngotracheitis in good-prognosis, ventilated patients who had failed extubation. As the pandemic continues to unfold across the globe and better management of those with respiratory failure develops, this may be an increasingly common scenario. Close ENT-intensivist liaison, meticulous team preparation, early consideration of rigid endoscopy and prospective data collection and case sharing are recommended

Does the PI3K pathway promote or antagonize regulatory T cell development and function?

Regulatory T cells (Tregs) prevent autoimmunity and inflammation by suppressing the activation of other T cells and antigen presenting cells. The role of phosphoinositide 3-kinase (PI3K) signaling in Treg is controversial. Some studies suggest that inhibition of the PI3K pathway is essential for the development of Tregs whereas other studies have shown reduced Treg numbers and function when PI3K activity is suppressed. Here we attempt to reconcile the different studies that have explored PI3K and the downstream effectors Akt, Foxo, and mTOR in regulatory T cell development and function and discuss the implications for health and therapeutic intervention

Not All Piggybacks Are Equal: A Retrospective Cohort Analysis of Variation in Anhepatic Transcaval Pressure Gradient and Acute Kidney Injury During Liver Transplant

Objectives: Complete inferior vena cava clamping in caval replacement during liver transplant is associated with substantial physiological derangement and postoperative morbidity. Partial clamping in the piggyback technique may be relatively protective, but evidence is lacking. Having observed substantial variation in transhepatic inferior vena cava pressure gradient with piggyback, we hypothesized that the causative mechanism is the extent of caval clamping rather than the surgical approach. Materials and Methods: We used internal jugular and femoral catheters to estimate suprahepatic and infrahepatic inferior vena cava pressures during clamping. Pressure gradients were calculated, and distributions were compared by surgical technique. We estimated adjusted odds ratios for pressure gradient on acute kidney injury at 72 hours. Results: In 115 case records, we observed substantial variation in maximum pressure gradient; median values were 18.0 mm Hg (interquartile range, 8.0-25.0 mm Hg) with the piggyback technique and 24.0 mm Hg (interquartile range, 19.5-27.0 mm Hg) with caval replacement. Incidence of acute kidney injury was 25% (29 patients). Pressure gradient was linearly associated with probability of acute kidney injury (odds ratio, 1.06; 95% CI, 1.01-1.13). Conclusions: We report 2 novel findings. (1) Anhepatic inferior vena cava pressure gradient varied substantially in individuals undergoing piggyback, and (2) gradient was positively associated with early acute kidney injury. We hypothesize that this (unmeasured) variation explains the conflicting findings of previous studies that compared surgical techniques. Also, we propose that caval pressure gradient could be routinely assessed to optimize real-time piggyback clamp position during liver transplant surgery

Predicting Postoperative Morbidity in Adult Elective Surgical Patients using the Surgical Outcome Risk Tool (SORT)

Background: The Surgical Outcome Risk Tool (SORT) is a risk stratification tool that predicts perioperative mortality. We construct a new recalibrated model based on SORT to predict the risk of developing postoperative morbidity. Methods: We analysed prospectively collected data from a single-centre cohort of adult patients undergoing major elective surgery. The data set was split randomly into derivation and validation samples. We used logistic regression to construct a model in the derivation sample to predict postoperative morbidity as defined using the validated Postoperative Morbidity Survey (POMS) assessed at one week after surgery. Performance of this "SORT-morbidity" model was then tested in the validation sample, and compared against the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM). Results: The SORT-morbidity model was constructed using a derivation sample of 1056 patients, and validated in 527 patients. SORT-morbidity was well-calibrated in the validation sample, as assessed using calibration plots and the Hosmer-Lemeshow Test (χ² = 4.87, p = 0.77). It showed acceptable discrimination by Receiver Operator Characteristic (ROC) curve analysis (Area Under the ROC curve, AUROC = 0.72, 95% CI 0.67–0.77). This compared favourably with POSSUM (AUROC = 0.66, 95% CI 0.60–0.71), while remaining simpler to use. Linear shrinkage factors were estimated, which allow the SORT-morbidity model to predict a range of alternative morbidity outcomes with greater accuracy, including low- and high-grade morbidity, and POMS at later time-points. Conclusions: SORT-morbidity can be used preoperatively, with clinical judgement, to predict postoperative morbidity risk in major elective surgery