کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5733526 | 1612198 | 2016 | 9 صفحه PDF | دانلود رایگان |

BackgroundThere is an increased desire among patients and families to be involved in the surgical decision-making process. A surgeon's ability to provide patients and families with patient-specific estimates of postoperative complications is critical for shared decision making and informed consent. Surgeons can also use patient-specific risk estimates to decide whether or not to operate and what options to offer patients. Our objective was to develop and evaluate a publicly available risk estimation tool that would cover many common pediatric surgical procedures across all specialties.Study DesignAmerican College of Surgeons NSQIP Pediatric standardized data from 67 hospitals were used to develop a risk estimation tool. Surgeons enter 18 preoperative variables (demographics, comorbidities, procedure) that are used in a logistic regression model to predict 9 postoperative outcomes. A surgeon adjustment score is also incorporated to adjust for any additional risk not accounted for in the 18 risk factors.ResultsA pediatric surgical risk calculator was developed based on 181,353 cases covering 382 CPT codes across all specialties. It had excellent discrimination for mortality (c-statistic = 0.98), morbidity (c-statistic = 0.81), and 7 additional complications (c-statistic > 0.77). The Hosmer-Lemeshow statistic and graphic representations also showed excellent calibration.ConclusionsThe ACS NSQIP Pediatric Surgical Risk Calculator was developed using standardized and audited multi-institutional data from the ACS NSQIP Pediatric, and it provides empirically derived, patient-specific postoperative risks. It can be used as a tool in the shared decision-making process by providing clinicians, families, and patients with useful information for many of the most common operations performed on pediatric patients in the US.
Journal: Journal of the American College of Surgeons - Volume 223, Issue 5, November 2016, Pages 685-693