Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Population‐based cohort study of outcomes following cholecystectomy for benign gallbladder diseases

Background The aim was to describe the management of benign gallbladder disease and identify characteristics associated with all‐cause 30‐day readmissions and complications in a prospective population‐based cohort. Methods Data were collected on consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing all‐cause 30‐day readmissions and complications were analysed by means of multilevel, multivariable logistic regression modelling using a two‐level hierarchical structure with patients (level 1) nested within hospitals (level 2). Results Data were collected on 8909 patients undergoing cholecystectomy from 167 hospitals. Some 1451 cholecystectomies (16·3 per cent) were performed as an emergency, 4165 (46·8 per cent) as elective operations, and 3293 patients (37·0 per cent) had had at least one previous emergency admission, but had surgery on a delayed basis. The readmission and complication rates at 30 days were 7·1 per cent (633 of 8909) and 10·8 per cent (962 of 8909) respectively. Both readmissions and complications were independently associated with increasing ASA fitness grade, duration of surgery, and increasing numbers of emergency admissions with gallbladder disease before cholecystectomy. No identifiable hospital characteristics were linked to readmissions and complications. Conclusion Readmissions and complications following cholecystectomy are common and associated with patient and disease characteristics

Effectiveness of a quality improvement collaborative in reducing time to surgery for patients requiring emergency cholecystectomy.

BACKGROUND: Acute gallstone disease is a high-volume emergency general surgery presentation with wide variations in the quality of care provided across the UK. This controlled cohort evaluation assessed whether participation in a quality improvement collaborative approach reduced time to surgery for patients with acute gallstone disease to fewer than 8 days from presentation, in line with national guidance. METHODS: Patients admitted to hospital with acute biliary conditions in England and Wales between 1 April 2014 and 31 December 2017 were identified from Hospital Episode Statistics data. Time series of quarterly activity were produced for the Cholecystectomy Quality Improvement Collaborative (Chole-QuIC) and all other acute National Health Service hospitals (control group). A negative binomial regression model was used to compare the proportion of patients having surgery within 8 days in the baseline and intervention periods. RESULTS: Of 13 sites invited to join Chole-QuIC, 12 participated throughout the collaborative, which ran from October 2016 to January 2018. Of 7944 admissions, 1160 patients had a cholecystectomy within 8 days of admission, a significant improvement (P < 0·050) from baseline performance. This represented a relative change of 1·56 (95 per cent c.i. 1·38 to 1·75), compared with 1·08 for the control group. At the individual site level, eight of the 12 Chole-QuIC sites showed a significant improvement (P < 0·050), with four sites increasing their 8-day surgery rate to over 20 per cent of all emergency admissions, well above the mean of 15·3 per cent for control hospitals. CONCLUSION: A surgeon-led quality improvement collaborative approach improved care for patients requiring emergency cholecystectomy

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

Maintenance optimization of infrastructure networks using genetic algorithms

Peer reviewed: YesNRC publication: Ye

Prediction of onset of corrosion in concrete bridge decks using neural networks and case-based reasoning

This paper proposes a methodology for predicting the time to onset of corrosion of reinforcing steel in concrete bridge decks while incorporating parameter uncertainty. It is based on the integration of artificial neural network (ANN), case-based reasoning (CBR), mechanistic model, and Monte Carlo simulation (MCS). A probabilistic mechanistic model is used to generate the distribution of the time to corrosion initiation based on statistical models of the governing parameters obtained from field data. The proposed ANN and CBR models act as universal functional mapping tools to approximate the relationship between the input and output of the mechanistic model. These tools are integrated with the MCS technique to generate the distribution of the corrosion initiation time using the distributions of the governing parameters. The proposed methodology is applied to predict the time to corrosion initiation of the top reinforcing steel in the concrete deck of the Dickson Bridge in Montreal. This study demonstrates the feasibility, adequate reliability and computational efficiency of the proposed integrated ANN-MCS and CBR-MCS approaches for preliminary project?level and also network-level analyses.Ce rapport propose une m\ue9thodologie de pr\ue9diction de l'apparition des premiers signes de corrosion des armatures des tabliers des ponts en b\ue9ton, laquelle m\ue9thodologie incorpore un param\ue8tre d'incertitude. Il est fond\ue9 sur l'int\ue9gration d'un r\ue9seau de neurones artificiels (RNA), du raisonnement automatis\ue9 \ue0 base de cas (RBC), du mod\ue8le m\ue9caniste et de la simulation Monte Carlo simulation (SMC). Un mod\ue8le m\ue9caniste probabiliste sert \ue0 g\ue9n\ue9rer le moment de l'apparition de la corrosion d'apr\ue8s des mod\ue8les statistiques des param\ue8tres dominants tir\ue9s des donn\ue9es de terrain. Les mod\ue8les RNA et RBC propos\ue9s agissent comme des outils fonctionnels universels de mappage pour approximer la relation entre les donn\ue9es d'entr\ue9e et de sortie du mod\ue8le m\ue9caniste. Ces outils sont int\ue9gr\ue9s dans la technique SMC pour g\ue9n\ue9rer la date de l'apparition initiale de la corrosion en ventilant les param\ue8tres dominants. La m\ue9thodologie propos\ue9e est appliqu\ue9e pour pr\ue9dire l'apparition de la corrosion des armatures sup\ue9rieures des tabliers en b\ue9ton du pont Dickson \ue0 Montr\ue9al. Cette \ue9tude d\ue9montre la faisabilit\ue9, la fiabilit\ue9 et l'efficacit\ue9 computationnelle des approches int\ue9gr\ue9es propos\ue9es RNA-SMC et RBC-SMC dans le cadre du projet pr\ue9liminaire et \ue9galement dans le cadre d'une analyse du r\ue9seau.Peer reviewed: YesNRC publication: Ye

Probabilistic and mechanistic deterioration models for bridge management

Peer reviewed: YesNRC publication: Ye

Integration of stochastic deterioration models with multi-criteria decision theory for maintenance optimization of bridge decks

This paper presents a new approach to optimizing the maintenance of concrete bridge decks. This approach combines a stochastic deterioration model and a multiobjective optimization model. The stochastic deterioration model is based on the first-order Markov chain, which predicts the probabilistic time variation of bridge deck conditions. The multiobjective optimization model takes into account two important and conflicting criteria: the minimization of maintenance costs and the maximization of the network condition. This approach achieves the best compromise between these competing criteria while considering the uncertainty in bridge deck deterioration. The feasibility and capability of the proposed approach are demonstrated with field data for a sample network of bridge decks obtained from the Minist\ue8re des Transports du Qu\ue9bec database. This example illustrates the effectiveness of the proposed approach in determining the optimal set of maintenance alternatives for reinforced concrete bridge decks when two or more relevant optimization criteria are taken into consideration.Cet article pr\ue9sente une nouvelle approche d'optimisation de la maintenance des tabliers de ponts en b\ue9ton qui associe un mod\ue8le stochastique de d\ue9t\ue9rioration et un mod\ue8le d'optimisation multi-objectif. Le mod\ue8le stochastique de d\ue9t\ue9rioration est bas\ue9 sur une cha\ueene de Markov de premier ordre 1 qui pr\ue9dit la variation probabiliste dans le temps de l'\ue9tat des tabliers de pont. Le mod\ue8le d'optimisation multivariable tient compte de deux crit\ue8res importants contradictoires : la minimisation des co\ufbts de maintenance et la maximisation de l'\ue9tat du r\ue9seau. La pr\ue9sente approche g\ue9n\ue8re une solution qui atteint le meilleur compromis entre ces crit\ue8res contradictoires, tout en consid\ue9rant l'incertitude de la d\ue9t\ue9rioration des tabliers de pont. La faisabilit\ue9 et la capacit\ue9 de l'approche propos\ue9e sont d\ue9montr\ue9es dans un r\ue9seau de tabliers de pont obtenu de la base de donn\ue9es du minist\ue8re des Transports du Qu\ue9bec. Cet exemple illustre l'efficacit\ue9 de l'approche propos\ue9e \ue0 d\ue9terminer l'ensemble optimal des options de maintenance des tabliers de pont en b\ue9ton arm\ue9 tout en consid\ue9rant au moins deux crit\ue8res d'optimisation pertinents.Peer reviewed: YesNRC publication: Ye