Utilizing the intrinsic surgical risk (ISR) and the patient’s chronic and acute conditions, this study aims to develop and validate a comprehensive predictive model of perioperative morbidity in children undergoing noncardiac surgery.
Following institutional review board (IRB) approval at a tertiary care children’s hospital, data for all noncardiac surgical encounters for a derivation dataset from July 2017 to December 2018 including 16,724 cases and for a validation dataset from January 2019 to December 2019 including 9043 cases were collected retrospectively. The primary outcome was a composite morbidity score defined by unplanned transfer to an intensive care unit (ICU), acute respiratory failure requiring intubation, postoperative need for noninvasive or invasive positive pressure ventilation, or cardiac arrest. Internal model validation was performed using 1000 bootstrap resamples, and external validation was performed using the 2019 validation cohort.
A total of 1519 surgical cases (9.1%) experienced the defined composite morbidity. Using multivariable logistic regression, the Risk Assessment of Morbidity in Pediatric Surgery (RAMPS) score was developed with very good predictive ability in the derivation cohort (area under the curve [AUC] = 0.805; 95% confidence interval [CI], 0.795–0.816), very good internal validity using 1000 bootstrap resamples (bias-corrected Nagelkerke R2 = 0.21 and Brier score = 0.07), and good external validity (AUC = 0.783; 95% CI, 0.770–0.797). The included variables are age <5 years, critically ill, chronic condition indicator (CCI) ≥3, significant CCI ≥2, and ISR quartile ≥3. The RAMPS score ranges from 0 to 10, with the risk of composite morbidity ranging from 1.8% to 42.7%.
The RAMPS score provides the ability to identify a high-risk cohort of pediatric patients using a 5-component tool, and it demonstrated good internal and external validity and generalizability. It also provides an opportunity to improve perioperative planning with the intent of improving both individual-patient outcomes and the appropriate allocation of health care resources.