Predictors of complications and hospital stay in gynecologic cancer surgery

Obstet Gynecol. 2001 May;97(5 Pt 1):721-4. doi: 10.1016/s0029-7844(00)01198-4.

Abstract

Objective: To test the hypothesis that comorbid medical conditions can predict length of hospital stay and incidence of postoperative complications.

Methods: We reviewed the medical records of 187 women who had surgery for known or suspected gynecologic malignancies during 1996 and 1997, and 179 were included in the present study. Information on each woman's comorbid medical conditions, surgical history, surgicopathologic cancer diagnosis, American Society of Anesthesiologists' classification, surgical procedures, and postoperative complications was collected and analyzed.

Results: Women with two or more comorbid medical conditions had significantly longer mean hospital stays (8.62 days) than those with none or one comorbid medical condition (6.43 days) (P <.001). Women with two or more postoperative complications had significantly longer mean hospital stays (11.88 days) than those with none or one complication (6.02 days) (P <.001). Women with two or more postoperative complications also had significantly more comorbid medical conditions (mean 2.5) than those with none or one complication (mean 1.7) (P <.001). The American Society of Anesthesiologists class also was a significant predictor of postoperative complications and length of hospitalization. Age over 60 years also was associated with statistically significant increase in comorbid medical conditions and significantly longer hospitalizations.

Conclusion: Our findings indicated that certain high-risk patients can be identified before hospital admission based on comorbid medical conditions. Certain risk indices, such as the American Society of Anesthesiologists classification score, also can predict postoperative complications and length of hospital stay. This information can be used to coordinate preoperative and postoperative hospital care and be a reference for certain future disease management systems.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Comorbidity
  • Female
  • Genital Neoplasms, Female / diagnosis
  • Genital Neoplasms, Female / epidemiology*
  • Genital Neoplasms, Female / surgery*
  • Humans
  • Incidence
  • Length of Stay / statistics & numerical data*
  • Logistic Models
  • Louisiana
  • Middle Aged
  • Multivariate Analysis
  • Postoperative Complications / diagnosis
  • Postoperative Complications / epidemiology*
  • Predictive Value of Tests
  • Probability
  • Prospective Studies
  • Risk Assessment
  • Risk Factors