Development and internal validation of a novel risk adjustment model for adult patients undergoing emergency laparotomy surgery: the National Emergency Laparotomy Audit risk model

N Eugene; C M Oliver; M G Bassett; T E Poulton; A Kuryba; C Johnston; I D Anderson; S R Moonesinghe; M P Grocott; D M Murray; D A Cromwell; K Walker; NELA collaboration

doi:10.1016/j.bja.2018.06.026

Development and internal validation of a novel risk adjustment model for adult patients undergoing emergency laparotomy surgery: the National Emergency Laparotomy Audit risk model

Br J Anaesth. 2018 Oct;121(4):739-748. doi: 10.1016/j.bja.2018.06.026. Epub 2018 Aug 23.

Authors

N Eugene¹, C M Oliver², M G Bassett³, T E Poulton⁴, A Kuryba¹, C Johnston⁵, I D Anderson⁶, S R Moonesinghe⁷, M P Grocott⁸, D M Murray⁹, D A Cromwell¹⁰, K Walker¹¹; NELA collaboration

Collaborators

NELA collaboration:
Martin Cripps, Paul Cripps, Emma Davies, Sharon Drake, Mike Galsworthy, James Goodwin, Tom Salih, Jose Lourtie, Dimitri Papadimitriou, Carol Peden

Affiliations

¹ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK.
² National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Division of Surgery and Interventional Science, University College London, London, UK; UCLH Surgical Outcomes Research Centre, Department of Anaesthesia and Perioperative Medicine, University College London Hospitals NHS Foundation Trust, London, UK.
³ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Department of Applied Health Research, University College London, London, UK.
⁴ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Department of Applied Health Research, University College London, London, UK; Northern School of Anaesthesia and Intensive Care Medicine, Newcastle, UK.
⁵ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; St George NHS Hospital, London, UK.
⁶ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Salford Royal Foundation NHS Trust, Salford, UK.
⁷ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; UCLH Surgical Outcomes Research Centre, Department of Anaesthesia and Perioperative Medicine, University College London Hospitals NHS Foundation Trust, London, UK.
⁸ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Anaesthesia & Critical Care Research Group, NIHR Biomedical Research Centre, UK; Integrative Physiology and Critical Illness Group, Faculty of Medicine, University Hospital Southampton, UK.
⁹ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Department of Anaesthesia, James Cook University Hospital, Middlesbrough, UK.
¹⁰ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: david.cromwell@lshtm.ac.uk.
¹¹ National Emergency Laparotomy Audit, Royal College of Anaesthetists, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK; Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, UK.

PMID: 30236236
DOI: 10.1016/j.bja.2018.06.026

Abstract

Background: Among patients undergoing emergency laparotomy, 30-day postoperative mortality is around 10-15%. The risk of death among these patients, however, varies greatly because of their clinical characteristics. We developed a risk prediction model for 30-day postoperative mortality to enable better comparison of outcomes between hospitals.

Methods: We analysed data from the National Emergency Laparotomy Audit (NELA) on patients having an emergency laparotomy between December 2013 and November 2015. A prediction model was developed using multivariable logistic regression, with potential risk factors identified from existing prediction models, national guidelines, and clinical experts. Continuous risk factors were transformed if necessary to reflect their non-linear relationship with 30-day mortality. The performance of the model was assessed in terms of its calibration and discrimination. Interval validation was conducted using bootstrap resampling.

Results: There were 4458 (11.5%) deaths within 30-days among the 38 830 patients undergoing emergency laparotomy. Variables associated with death included (among others): age, blood pressure, heart rate, physiological variables, malignancy, and ASA physical status classification. The predicted risk of death among patients ranged from 1% to 50%. The model demonstrated excellent calibration and discrimination, with a C-statistic of 0.863 (95% confidence interval, 0.858-0.867). The model retained its high discrimination during internal validation, with a bootstrap derived C-statistic of 0.861.

Conclusions: The NELA risk prediction model for emergency laparotomies discriminates well between low- and high-risk patients and is suitable for producing risk-adjusted provider mortality statistics.

Keywords: emergency laparotomy; postoperative mortality; postoperative outcome; risk adjustment.

MeSH terms

Adolescent
Adult
Aged
Aged, 80 and over
Emergency Medical Services / statistics & numerical data*
Female
Forecasting
Hemodynamics
Humans
Laparotomy / adverse effects*
Laparotomy / mortality
Laparotomy / statistics & numerical data*
Male
Medical Audit
Middle Aged
Models, Statistical
Neoplasms / complications
Reproducibility of Results
Retrospective Studies
Risk Adjustment
Risk Factors
United Kingdom / epidemiology
Young Adult