Determinants of hospital length of stay after thoracoabdominal aortic aneurysm repair

J Vasc Surg. 2002 Apr;35(4):648-53. doi: 10.1067/mva.2002.121566.

Abstract

Purpose: Extended hospital length of stay (LOS) and consequent high costs are associated with thoracic and thoracoabdominal aortic aneurysm (TAAA) surgery. In this study, we examined factors that may influence LOS after TAAA repair.

Methods: Five hundred forty thoracic and TAAA repairs were performed by one surgeon between 1990 and 1999. The data were analyzed with multiple linear regression with appropriate logarithmic transformation. The predictor variables included patient demographics, disease extent, severity indicators, intraoperative factors, and postoperative complications.

Results: The median LOS was 15 days. Postoperative creatinine level of greater than 2.9 was the most important predictor of LOS, followed by spinal cord deficit, age, and pulmonary complication (all statistically significant with P <.05). A second model constrained to preoperative risk factors showed both age and complete diaphragmatic division to be associated with increased LOS. Preservation of the diaphragm led to reduced LOS by an average of 4 days. The adjunct cerebrospinal fluid drainage and distal aortic perfusion was associated with a decrease in LOS, although it did not reach statistical significance.

Conclusion: Renal failure, spinal cord deficit, and pulmonary complication were the major determinants of LOS in patients for TAAA repair. This study shows that the preservation of diaphragmatic function and the use of the adjunct distal aortic perfusion and cerebrospinal fluid drainage may reduce hospital LOS.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aortic Aneurysm, Abdominal / epidemiology
  • Aortic Aneurysm, Abdominal / surgery*
  • Aortic Aneurysm, Thoracic / epidemiology
  • Aortic Aneurysm, Thoracic / surgery*
  • Diaphragm / physiology
  • Female
  • Hospitals, University / statistics & numerical data*
  • Humans
  • Incidence
  • Length of Stay / statistics & numerical data*
  • Linear Models
  • Male
  • Middle Aged
  • Postoperative Complications / epidemiology
  • Renal Insufficiency / epidemiology
  • Risk Factors
  • Survival Rate
  • Texas / epidemiology