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Updated: Jul 11, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Can Preoperative Laboratory Values Predict Short-term Postoperative Complications and Health Utilization in Patients
Anitesh Bajaj1, Rushmin Khazanchi, Joshua P Weissman
1Division of Plastic Surgery, Lurie Children's Hospital of the Northwestern University Feinberg School of Medicine, Chicago, IL.
Background:
Low hematocrit, low albumin, and high creatinine levels have been associated with postoperative morbidity. The present study intends to analyze the effects of preoperative laboratories on medical complications and postoperative health resource utilization in patients undergoing cranioplasty.
Methods:
Using data from the American College of Surgeons National Surgical Quality Improvement Program, demographic, clinical, and intraoperative characteristics were collected for each patient who had recorded albumin, hematocrit, or creatinine laboratory values within 90 days of the index cranioplasty. Outcomes analyzed were ≥1 medical complication, ≥1 wound complication, unplanned reoperation, 30-day readmission, and extended hospital stay (>30 d). Outcomes significant on bivariate analyses were evaluated using multivariate logistic regression. Significant outcomes on multivariate analyses were analyzed using receiver operating characteristic curves and Mann-Whitney U tests.
Results:
The 3 separate cohorts included 1349 patients with albumin, 2201 patients with hematocrit, and 2182 patients with creatinine levels. Upon multivariate analysis, increases in albumin and hematocrit were independently associated with decreased odds of medical complications and extended length of stay. Increases in creatinine were independently associated with increased odds of medical complications. Discriminative cutoff values were identified for albumin and hematocrit.
Conclusions:
Preoperative laboratory values were independent predictors of medical complications and health utilization following cranioplasty in this study. Surgical teams can use these findings to optimize preoperative risk stratification.
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