Outcome of spine surgery in the context of spinal metastatic disease: The National Surgical Quality Improvement Program

  • 0Department of Neurological Surgery, Washington University in St Louis, St. Louis, MO, USA.

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Summary

This summary is machine-generated.

Identifying perioperative risk factors for spine surgery in patients with spinal cord metastasis is crucial. Smoking, weight loss, and dependent status predict poor outcomes, aiding in better patient care and risk stratification.

Area Of Science

  • Oncology
  • Neurosurgery
  • Surgical Outcomes Research

Background

  • Spinal metastases are a common complication of cancer, affecting approximately 10% of patients.
  • While survival is often poor, advancements in therapy and surgical techniques improve surgical management options.
  • Symptomatic spine involvement necessitates careful consideration of surgical intervention.

Purpose Of The Study

  • To identify perioperative risk factors for adverse outcomes in patients undergoing spine surgery for spinal cord metastasis.
  • To analyze factors contributing to 30-day morbidity and mortality.
  • To investigate predictors of prolonged hospital stay.

Main Methods

  • Utilized the National Surgical Quality Improvement Program (NSQIP) database.
  • Identified patients with metastatic spine disease undergoing surgical procedures.
  • Employed logistic regression to analyze 30-day morbidity/mortality and prolonged hospital stay.

Main Results

  • Included 2109 patients; 19.1% experienced 30-day morbidity/mortality.
  • Significant predictors of poor outcomes included smoking, substantial weight loss, urgent surgery, dependent status, and low preoperative albumin.
  • 28.6% had prolonged hospital stays, associated with chemotherapy, urgent surgery, dependent status, preoperative hematocrit, neurological deficits, albumin levels, and surgical complexity.

Conclusions

  • Identified key risk factors for mortality, morbidity, and prolonged hospitalization in spine surgery for metastatic disease.
  • These findings aid clinicians in risk stratification, preoperative optimization, and postoperative care planning.
  • Further research is needed to validate predictive models for clinical application.