title: The impact of preoperative gonadotropin-releasing hormone agonist treatment on laparoscopic excision of ovarian endometriotic cysts.
abstract: OBJECTIVE
  To compare surgical performance and recurrence rates in patients submitted to laparoscopy for endometrioma excision following GnRH agonist (GnRH-a) treatment versus no preoperative medical treatment.
  
  
  METHODS
  Controlled clinical study.
  
  
  METHODS
  A tertiary care university hospital.
  
  
  METHODS
  Twenty patients with unilateral endometriomas underwent operative laparoscopy after 3-month GnRH-a treatment, whereas 21 patients underwent laparoscopic excision of endometriomas without preoperative medical treatment.
  
  
  METHODS
  Operative laparoscopy was performed with the stripping technique using a four-puncture approach.
  
  
  METHODS
  A blinded videotape review was undertaken to evaluate the duration and complexity of the different phases of surgery. Recurrence rates were evaluated at 1-year follow-up ultrasonography.
  
  
  RESULTS
  No significant difference was found between the two groups in total operative time, cyst excision time, time needed for cyst capsule stripping and coagulation of ovarian parenchyma, and the complexity of the latter phases; recurrence rates also were comparable.
  
  
  CONCLUSIONS
  Preoperative GnRH-a treatment for endometriomas does not seem to offer any advantage in terms of subsequent surgical performance.
authors.affiliation: Università Cattolica del Sacro Cuore, Rome, Italy.
authors.forename: L
authors.initials: L
authors.lastname: Muzii
authors.forename: R
authors.initials: R
authors.lastname: Marana
authors.forename: P
authors.initials: P
authors.lastname: Caruana
authors.forename: S
authors.initials: S
authors.lastname: Mancuso
mesh_terms: D000328:Adult; D002064:Buserelin / Q000627:therapeutic use*; D004715:Endometriosis / Q000601:surgery*; D005260:Female; D006801:Humans; D010048:Ovarian Cysts / Q000601:surgery*; D011300:Preoperative Care; D012008:Recurrence
chemical_list: D002064:Buserelin