N. Eugene, A. Kuryba, P. Martin, C. M. Oliver, M. Berry, I. K. Moppett, C. Johnston, S. Hare, S. Lockwood, D. Murray, K. Walker, D. A. Cromwell,

Development and validation of a prognostic model for death 30 days after adult emergency laparotomy

  • Anesthesiology and Pain Medicine
Save to CiteDrive Show PDF

SummaryThe probability of death after emergency laparotomy varies greatly between patients. Accurate pre‐operative risk prediction is fundamental to planning care and improving outcomes. We aimed to develop a model limited to a few pre‐operative factors that performed well irrespective of surgical indication: obstruction; sepsis; ischaemia; bleeding; and other. We derived a model with data from the National Emergency Laparotomy Audit for patients who had emergency laparotomy between December 2016 and November 2018. We tested the model on patients who underwent emergency laparotomy between December 2018 and November 2019. There were 4077/40,816 (10%) deaths 30 days after surgery in the derivation cohort. The final model had 13 pre‐operative variables: surgical indication; age; blood pressure; heart rate; respiratory history; urgency; biochemical markers; anticipated malignancy; anticipated peritoneal soiling; and ASA physical status. The predicted mortality probability deciles ranged from 0.1% to 47%. There were 1888/11,187 deaths in the test cohort. The scaled Brier score, integrated calibration index and concordance for the model were 20%, 0.006 and 0.86, respectively. Model metrics were similar for the five surgical indications. In conclusion, we think that this prognostic model is suitable to support decision‐making before emergency laparotomy as well as for risk adjustment for comparing organisations.

Need a simple solution for managing your BibTeX entries? Explore CiteDrive!

  • Web-based, modern reference management
  • Collaborate and share with fellow researchers
  • Integration with Overleaf
  • Comprehensive BibTeX/BibLaTeX support
  • Save articles and websites directly from your browser
  • Search for new articles from a database of tens of millions of references
Try out CiteDrive

More from our Archive