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Does the ACS NSQIP Surgical Risk Calculator Accurately Predict Complications Rates After Anterior Lumbar Interbody
Ankur S Narain1, Alexander Z Kitto1, Benjamin Braun1
1Department of Orthopedic Surgery, University of Massachusetts Memorial Medical Center, Worcester MA.
Spine
|December 18, 2020
Summary
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator adequately predicts some complications after anterior lumbar interbody fusion (ALIF), but not all. Further risk stratification models are needed for ALIF patients.
Area of Science:
- Spine surgery outcomes research
- Surgical risk prediction modeling
- Health services research
Background:
- Identifying patients at high risk for complications after spine surgery is crucial for prevention.
- The ACS NSQIP surgical risk calculator aims to predict 30-day postoperative complications across various surgical procedures.
Purpose of the Study:
- To evaluate the effectiveness of the ACS NSQIP surgical risk calculator in predicting complications following anterior lumbar interbody fusion (ALIF).
Main Methods:
- Retrospective review of 253 ALIF patient medical records (2009-2019).
- Inputting demographic and comorbidity data into the ACS NSQIP calculator to predict complication incidence.
- Comparing predicted complication rates with observed rates using Area Under the Curve (AUC) analysis.
Main Results:
- The ACS NSQIP calculator showed fair predictive ability for discharge to a non-home facility (AUC 0.71) and surgical site infection (AUC 0.70).
- It demonstrated good predictive accuracy for acute kidney injury/progressive renal insufficiency (AUC 0.81).
- The calculator was inadequate for predicting pneumonia, urinary tract infections, venous thromboembolism, readmission, reoperations, and aggregate complications (AUC < 0.70).
Conclusions:
- The ACS NSQIP surgical risk calculator is a useful tool for predicting specific complications (acute kidney injury, surgical site infection, non-home discharge) after ALIF.
- Its predictive capability is limited for other complication categories, necessitating the development of improved risk stratification models for ALIF patients.
