title: Factors Influencing Selection of Vaginal, Open Abdominal, or Robotic Surgery to Treat Apical Vaginal Vault Prolapse.
abstract: This study aimed to determine factors influencing the selection of Mayo-McCall culdoplasty (MMC), open abdominal sacrocolpopexy (ASC), or robotic sacrocolpopexy (RSC) for posthysterectomy vaginal vault prolapse.
  
  
  
  We retrospectively searched for the records of patients undergoing posthysterectomy apical vaginal prolapse surgery between January 1, 2000, and June 30, 2012, at our institution. Baseline characteristics and explicit selection factors were abstracted from the electronic medical records. Factors were compared between groups using χ tests for categorical variables, analysis of variance for continuous variables, and Kruskal-Wallis tests for ordinal variables.
  
  
  
  Among the 512 patients identified who met inclusion criteria, the MMC group (n = 174) had more patients who were older, had American Society of Anesthesiologists class 3+ or greater, had anterior vaginal prolapse grade 3+, desired to avoid abdominal surgery, and did not desire a functional vagina. Patients in the ASC (n = 237) and RSC (n = 101) groups had more failed prolapse surgeries, suspected abdominopelvic pathologic processes, and chronic pain. Advanced prolapse was more frequently cited as an explicit selection factor for ASC than for either MMC or RSC.
  
  
  
  The most common factors that influenced the type of apical vaginal vault prolapse surgery overlapped with characteristics that differed at baseline. In general, MMC was chosen for advanced anterior vaginal prolapse and baseline characteristics that increased surgical risks, ASC for advanced apical prolapse, and ASC or RSC for recurrent prolapse, suspected abdominal pathology, and patients with chronic pain or lifestyles including heavy lifting. Thus, efforts should be made to attempt to control for selection bias when comparing these procedures.
authors.affiliation: From the Divisions of *Gynecologic Surgery and †Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN.
authors.forename: Mallika
authors.initials: M
authors.lastname: Anand
authors.forename: Amy L
authors.initials: AL
authors.lastname: Weaver
authors.forename: Kristin M
authors.initials: KM
authors.lastname: Fruth
authors.forename: John B
authors.initials: JB
authors.lastname: Gebhart
mesh_terms: D000367:Age Factors; D000368:Aged; D000704:Analysis of Variance; D000066491:Clinical Decision-Making; D005260:Female; D006801:Humans; D007044:Hysterectomy / Q000379:methods*; D008875:Middle Aged; D056887:Pelvic Organ Prolapse / Q000209:etiology / Q000601:surgery*; D012189:Retrospective Studies; D065287:Robotic Surgical Procedures; D015983:Selection Bias; D012720:Severity of Illness Index; D018709:Statistics, Nonparametric; D014621:Vagina / Q000601:surgery*