Abstract
A simple, objective and accurate way of grouping children undergoing surgery into clinically relevant risk groups is needed. The purpose of this study, is to develop and validate a preoperative risk classification system for postsurgical 30-day mortality for children undergoing a wide variety of operations. The National Surgical Quality Improvement Project-Pediatric participant use file data for calendar years 2012–2014 was analyzed to determine preoperative variables most associated with death within 30 days of operation (D30). Risk groups were created using classification tree analysis based on these preoperative variables. The resulting risk groups were validated using 2015 data, and applied to neonates and higher risk CPT codes to determine validity in high-risk subpopulations. A five-level risk classification was found to be most accurate. The preoperative need for ventilation, oxygen support, inotropic support, sepsis, the need for emergent surgery and a do not resuscitate order defined non-overlapping groups with observed rates of D30 that vary from 0.075% (Very Low Risk) to 38.6% (Very High Risk). When CPT codes where death was never observed are eliminated or when the system is applied to neonates, the groupings remained predictive of death in an ordinal manner.
Highlights
Over the past 30 years there has been a dramatic decline in surgical mortality for children and adults in the United States [1, 2]
It is possible that investigators from non NSQIP-Pediatrics may obtain the data at the discretion of the American College of Surgeons
The Pedi-PUF is a Health Insurance Portability and Accountability Act (HIPAA)-compliant data file containing cases submitted to NSQIP-Pediatric
Summary
Over the past 30 years there has been a dramatic decline in surgical mortality for children and adults in the United States [1, 2]. The American College of Surgeons National Surgical Quality Improvement Program-Pediatric (NSQIP-Pediatric) dataset provides information on both inpatient and outpatient operations on children from birth to 18 years of age [3]. Investigator at these institutions can access this data. The URL for the data request is: https://www.
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