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Published on: October 14, 2022
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Risk stratification of patients undergoing outpatient lumbar decompression surgery
Jose A Canseco1, Brian A Karamian1, Mark J Lambrechts1
1Department of Orthopaedic Surgery, Rothman Institute, Thomas Jefferson University, 925 Chestnut St, 5th Floor, Philadelphia, PA 19107, USA.
Summary
A machine learning tool accurately predicts which lumbar decompression patients need overnight hospital stays, aiding the shift to outpatient surgery. This calculator helps surgeons select appropriate candidates for same-day procedures, reducing healthcare costs.
Area of Science:
- Neurosurgery
- Health Economics
- Machine Learning in Healthcare
Background:
- Healthcare reimbursement is shifting from fee-for-service to bundled payments.
- Surgeons are exploring outpatient lumbar decompression to minimize costs.
- Selecting appropriate patients for outpatient procedures is crucial for cost reduction.
Purpose of the Study:
- Develop a machine learning risk stratification calculator.
- Improve preoperative prediction of inpatient vs. outpatient criteria for lumbar decompression.
- Define inpatient criteria as any overnight hospital stay.
Main Methods:
- Retrospective analysis of 1656 patients undergoing lumbar decompression.
- Development of a predictive model using logistic regression and C-statistics.
- Creation of an odds ratio, nomogram, and a digital application for risk assessment.
Main Results:
- A predictive model identified older age, higher BMI, increased back pain, higher ASA score, and more decompressed levels as risk factors for overnight stay.
- Female patients and those with private insurance were less likely to be admitted overnight.
- A score over 118 accurately predicted inpatient admission with 81.4% accuracy (AUC).
Conclusions:
- A reliable machine learning calculator can predict the need for admission after lumbar decompression.
- Younger patients with lower BMI, less pain, fewer comorbidities, and private insurance are ideal candidates for outpatient surgery.
- The developed tool supports informed decision-making for outpatient lumbar decompression procedures.

