Can the American College of Surgeons NSQIP surgical risk calculator identify patients at risk of complications following microsurgical breast reconstruction?

Summary Introduction The American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator is an open access online tool that estimates the risk of adverse post-operative events for a wide range of surgical procedures. This study evaluates the predictive...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of plastic, reconstructive & aesthetic surgery reconstructive & aesthetic surgery, 2016-10, Vol.69 (10), p.1356-1362
Hauptverfasser: O'Neill, Anne C, Bagher, Shaghayegh, Barandun, Marina, Hofer, Stefan O.P, Zhong, Toni
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Summary Introduction The American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator is an open access online tool that estimates the risk of adverse post-operative events for a wide range of surgical procedures. This study evaluates the predictive value of the ACS NSQIP calculator in patients undergoing microvascular breast reconstruction. Study design Details of 759 microvascular breast reconstructions in 515 patients were entered into the online calculator. The predicted rates of post-operative complications were recorded and compared to observed complications identified on chart review. The calculator was validated using three statistical measures described in the original development of the ACS NSQIP model. Results The calculator predicted that complications would occur in 11.1% of breast reconstructions while the observed rate was 10.5%. Hosmer-Lemeshow test did not find any statistical difference between these rates (p = 0.69) indicating that the calculator accurately measured what is was intended to measure. The area under the receiver operating curve or c-statistic (measure of discrimination) was found to be low at 0.548, indicating the model has random performance in this patient population. The Brier score was higher than that reported in the original ACS calculator development (0.094 vs 0.069) demonstrating poor correlation between predicted probability and actual probability. Conclusions This study demonstrates that while the ACS NSQIP Universal risk calculator can predict the proportion of patients that will develop complications it cannot effectively discriminate between patients who are at risk of complications and those who are not.
ISSN:1748-6815
1878-0539
DOI:10.1016/j.bjps.2016.05.021