Comparison of major abdominal emergency surgery outcomes across organizational models of emergency surgical care: Analysis of the UK NELA national database.

BACKGROUND: Emergency general surgery (EGS) admissions account for a large proportion of surgical care and represent the majority of surgical patients who suffer in-hospital mortality. Health care systems continue to experience growing demand for emergency services: one way in which this is being increasingly addressed is dedicated subspecialty teams for emergency surgical admissions, most commonly termed "emergency general surgery" in the United Kingdom. This study aims to understand the impact of the emergency general surgery model of care on outcomes from emergency laparotomies. METHODS: Data was obtained from the National Emergency Laparotomy Audit database. Patients were dichotomized into EGS hospital or non-EGS hospital. Emergency general surgery hospital is defined as a hospital where >50% of in-hours emergency laparotomy operating is performed by an emergency general surgeon. The primary outcome was in-hospital mortality. Secondary outcomes were intensive therapy unit (ITU) length of stay and duration of hospital stay. A propensity score weighting approach was used to reduce confounding and selection bias. RESULTS: There were 115,509 patients from 175 hospitals included in the final analysis. The EGS hospital care group included 5,789 patients versus 109,720 patients in the non-EGS group. Following propensity score weighting, mean standardized mean difference reduced from 0.055 to <0.001. In-hospital mortality was similar (10.8% vs. 11.1%, p = 0.094), with mean length of stay (16.7 days vs. 16.1 days, p < 0.001) and ITU stay (2.8 days vs. 2.6 days, p < 0.001) persistently longer in patients treated in EGS systems. CONCLUSION: No significant association between the emergency surgery hospital model of care and in-hospital mortality in emergency laparotomy patients was seen. There is a significant association between the emergency surgery hospital model of care and an increased length of ITU stay and overall hospital stay. Further studies are required to examine the impact of changing models of EGS delivery in the United Kingdom. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.

Proctored adoption of robotic hiatus hernia surgery: outcomes and learning curves in a high-volume UK centre.

BACKGROUND: The adoption of new surgical technologies is inevitably accompanied by a learning curve. With the increasing adoption of robotic techniques in benign foregut surgery, it is imperative to define optimal learning pathways, to ensure a clinically safe introduction of such a technique. The aim of this study was to assess the learning curve for robotic hiatal hernia repair with a pre-defined adoption process and proctoring. METHODS: The learning curve was assessed in four surgeons in a high-volume tertiary referral centre, performing over a 100 hiatal hernia repairs annually. The robotic adoption process included simulation-based training and a multi-day wet lab-based course, followed by robotic operations proctored by robotic upper GI experts. CUSUM analysis was performed to assess changes in operating time in sequential cases. RESULTS: Each surgeon (A, B, C and D) performed between 22 and 32 cases, including a total of 109 patients. Overall, 40 cases were identified as 'complex' (36.7%), including 16 revisional cases (16/109, 14.7%). With CUSUM analysis inflection points for operating time were seen after 7 (surgeon B) to 15 cases (surgeon B). CONCLUSION: The learning curve for robotic laparoscopic fundoplication may be as little as 7-15 cases in the setting of a clearly organized learning pathway with proctoring. By integrating these organized learning pathways learning curves may be shortened, ensuring patient safety, preventing detrimental outcomes due to longer learning curves, and accelerating adoption and integration of novel surgical techniques.

Outcomes After Independent Trainee Versus Consultant-led Emergency Laparotomy: Inverse Propensity Score Population Dataset Analysis.

OBJECTIVE: We utilized a population dataset to compare outcomes for patients where surgery was independently performed by trainees to cases led by a consultant. SUMMARY OF BACKGROUND DATA: Emergency laparotomy is a common, high-risk, procedure. Although trainee involvement to improve future surgeons' experience and ability in the management of such cases is crucial, some studies have suggested this is to the detriment of patient outcomes. In the UK, appropriately skilled trainees may be entrusted to perform emergency laparotomy without supervision of a consultant (attending). METHODS: Patients who underwent emergency laparotomy between 2013 and 2018 were identified from the National Emergency Laparotomy Audit of England and Wales. To reduce selection and confounding bias, the inverse probability of treatment weighting approach was used, allowing robust comparison of trainee-led and consultant-led laparotomy cases accounting for eighteen variables, including details of patient, treatment, pathology, and preoperative mortality risk. Groups were compared for mortality and length of stay. RESULTS: A total of 111,583 patients were included in the study. The operating surgeon was a consultant in 103,462 cases (92.7%) and atrainee in 8121 cases (7.3%). Mortality at discharge was 11.6%. Trainees were less likely to operate on high-risk and colorectal cases. After weighting, mortality (12.2% vs 11.6%, P = 0.338) was equivalent between trainee- and consultant-led cases. Median length of stay was 11 (interquartile range 7, 19) versus 11 (7, 20) days ( P = 0.004), respectively. Trainee-led operations reported fewer cases of blood loss >500mL (9.1% vs 11.1%, P < 0.001). CONCLUSIONS: Major laparotomy maybe safely entrusted to appropriately skilled trainees without impacting patient outcomes.

The AUGIS Survival Predictor: Prediction of Long-Term and Conditional Survival After Esophagectomy Using Random Survival Forests.

OBJECTIVE: The aim of this study was to develop a predictive model for overall survival after esophagectomy using pre/postoperative clinical data and machine learning. SUMMARY BACKGROUND DATA: For patients with esophageal cancer, accurately predicting long-term survival after esophagectomy is challenging. This study investigated survival prediction after esophagectomy using a RandomSurvival Forest (RSF) model derived from routine data from a large, well-curated, national dataset. METHODS: Patients diagnosed with esophageal adenocarcinoma or squamous cell carcinoma between 2012 and 2018 in England and Wales who underwent an esophagectomy were included. Prediction models for overall survival were developed using the RSF method and Cox regression from 41 patient and disease characteristics. Calibration and discrimination (time-dependent area under the curve) were validated internally using bootstrap resampling. RESULTS: The study analyzed 6399 patients, with 2625 deaths during follow-up. Median follow-up was 41 months. Overall survival was 47.1% at 5 years. The final RSF model included 14 variables and had excellent discrimination with a 5-year time-dependent area under the receiver operator curve of 83.9% [95% confidence interval (CI) 82.6%-84.9%], compared to 82.3% (95% CI 81.1%-83.3%) for the Cox model. The most important variables were lymph node involvement, pT stage, circumferential resection margin involvement (tumor at < 1 mm from cut edge) and age. There was a wide range of survival estimates even within TNM staging groups, with quintiles of prediction within Stage 3b ranging from 12.2% to 44.7% survival at 5 years. CONCLUSIONS: An RSF model for long-term survival after esophagectomy exhibited excellent discrimination and well-calibrated predictions. At a patient level, it provides more accuracy than TNM staging alone and could help in the delivery of tailored treatment and follow-up.

Feasibility of laparoscopy and factors associated with conversion to open in minimally invasive emergency major abdominal surgery: population database analysis.

BACKGROUND: There is limited evidence regarding the overall feasibility and success rates of the laparoscopic approach in major emergency surgery, despite its potential to improve outcomes. This study aims to investigate the association between patient, procedural, and surgical factors and likelihood of successful laparoscopic completion in emergency major surgery and derive a predictive model to aid clinical decision-making. METHOD: All patients recorded in the NELA emergency laparotomy database 1 December 2013-31 November 2018 who underwent laparoscopically attempted surgery were included. A retrospective cohort multivariable regression analysis was conducted for the outcome of conversion to open surgery. A predictive model was developed and internally validated. RESULTS: Of 118,355 patients, 17,040 (7.7%) underwent attempted laparoscopic surgery, of which 7.915 (46.4%) were converted to open surgery. Procedure type was the strongest predictor of conversion (compared to washout as reference, small bowel resection OR 25.93 (95% CI 20.42-32.94), right colectomy OR 6.92 (5.5-8.71)). Diagnostic [free pus, blood, or blood OR 3.67 (3.29-4.1)] and surgeon [subspecialist surgeon OR 0.56 (0.52-0.61)] factors were also significant, whereas age, gender, and pre-operative mortality risk were not. A derived predictive model had high internal validity, C-index 0.758 (95% CI 0.748-0.768), and is available for free-use online. CONCLUSION: Surgical, patient, and diagnostic variables can be used to predict likelihood of laparoscopic success with a high degree of accuracy. This information can be used to inform peri-operative decision-making and patient selection.

Outcomes and survival following neoadjuvant chemotherapy versus neoadjuvant chemoradiotherapy for cancer of the esophagus: Inverse propensity score weighted analysis.

BACKGROUND: Esophageal cancer is increasingly common and carries a poor prognosis. The optimal treatment modality for locally advanced cancer is unknown, with current guidance recommending either neoadjuvant chemotherapy (CT) or chemoradiotherapy (CRT) followed by surgery. There is a lack of adequately powered trials comparing CT against CRT. We retrospectively compared CT versus CRT using a propensity score weighting approach. METHODS: Demographic, disease, treatment and outcome data were retrieved from a local database for patients who received neoadjuvant CT or CRT followed by surgery. Inverse probability of treatment weighting (IPTW) was used to balance groups using a propensity score-weighting approach. Groups were assessed for differences in postoperative outcomes and survival. Kaplan-Meier and non-parametric tests were used to compare survival and outcome data as appropriate. RESULTS: Data for 284 patients were retrieved. Following IPTW groups were well matched. No significant differences were seen for postoperative complications (CT 64.9% vs. CRT 63.3%, p = 0.807), including major complications (24.0% vs. 23.6%, p = 0.943) and anastomotic leak (7.8% vs. 5.6%, p = 0.526). Significantly higher rates of clinical regression and complete pathological response were seen following CRT (p = 0.002 for both). Rates of R0 resection were higher with CRT, CT 79.1% vs. CRT 93.1%, p = 0.006. There was no difference between groups for overall or disease-free survival. CONCLUSION: This study suggests that the significant improvements in local tumour response seen after neoadjuvant CRT compared to CT may not translate to different survival outcomes. However, it must be stressed that adequately powered prospective trials are still lacking.