Abstract
Introduction
Postoperative pulmonary complications (PPCs) following major abdominal surgery result in substantial morbidity and mortality, yet stratifying patients for risk-modifying interventions remains challenging. This study aimed to systematically review and externally validate existing PPC risk prediction models in an international, prospective cohort.
Method
A systematic search of the MEDLINE and EMBASE databases according to PRISMA guidelines was performed to identify original risk prediction models for PPC following abdominal surgery. Subsequent external validation was performed based on a prospective dataset (REspiratory COmplications after abdomiNal surgery) which encompassed adult patients undergoing major abdominal surgery from January to April 2019 across the UK, Ireland and Australia. The primary outcome was 30-day PPC (StEP-COMPAC criteria definition), and multivariable logistic regression model discrimination were compared (with an area under the curve (AUC) ≥0.7 considered “good”).
Result
Thirty original risk prediction models were identified from 2819 records, with notable heterogeneity in risk factors considered. Within the validation dataset, the 30-day PPC rate was 7.8% (n = 903/11591), and 6 scores had all variables represented to enable external validation. No score demonstrated statistically significant “good” discrimination for identifying pulmonary complications, with no significant differences between scores. However, the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) score achieved the highest discrimination (AUC = 0.709, 95% CI = 0.692–0.727).
Conclusion
The risk of PPC for patients following major abdominal surgery in the pre-covid era is not well described by existing prediction tools. New prediction tools are required to account for additional variation introduced for patients affected by SARS-CoV-2 infection.
Take-home Message
The risk of PPC for patients following major abdominal surgery in the pre-covid era is not well described by existing prediction tools. New prediction tools are required to account for additional variation introduced for patients affected by SARS-CoV-2 infection.
702 Evaluation of Risk Prediction Models for Postoperative Pulmonary Complications in Adults Undergoing Major Abdominal Surgery: A Systematic Review and External Validation Study in The Respiratory Complications After Abdominal Surgery (RECON) Cohort
