Day-case laparoscopic Nissen fundoplication: a default pathway or is selection the key?

J Laparoendosc Adv Surg Tech A. 2012 Nov;22(9):859-63. doi: 10.1089/lap.2012.0170. Epub 2012 Oct 15.

Abstract

Background: In recent years, day-case laparoscopic Nissen fundoplication (LNF) has became popular. Our study aims to evaluate the effect of patient factors and severity of gastroesophageal reflux disease measured by DeMeester score on the success of day-case LNF.

Subjects and methods: We conducted a retrospective case series review of patient demographics (age, gender, body mass index [BMI], and smoking status) and DeMeester score over a 5-year period. Between 2005 and 2010, 112 patients had day-case LNF. Same-day discharge was achieved in 80.3%. Twenty-two patients (19.7%) required postoperative admission ("failed day-case surgery"), with a resultant mean length of stay of 1.41 days. Univariate analysis showed that female gender had a significantly higher incidence of postsurgical admission (30.76% females versus 13.69% males, P=.03 by Mann-Whitney U test). Compared with the same-day discharge group, the failed day-case group has a higher mean DeMeester score (50.89 versus 36.03, P=.021 by t test) and BMI (28.71±0.778 kg/m(2) versus 26.79±0.3737 kg/m(2), P=.023). Age and smoking status were not significant determining factors in postoperative admission rates. Using multivariable analysis and logistical regression, we derived a model based on gender, BMI, and DeMeester score to predict the probability of admission following day-case LNF.

Conclusions: We conclude that day-case LNF is a safe, feasible procedure in the appropriately selected patient population. Our novel finding of higher admission rates in females, high DeMeester score, and high BMI should be used in planning perioperative hospitalization in this cohort.

MeSH terms

  • Adult
  • Ambulatory Care / methods*
  • Body Mass Index
  • Female
  • Fundoplication / methods*
  • Gastroesophageal Reflux / surgery*
  • Humans
  • Laparoscopy / methods*
  • Length of Stay / statistics & numerical data
  • Logistic Models
  • Male
  • Patient Admission / statistics & numerical data
  • Patient Discharge / statistics & numerical data
  • Retrospective Studies
  • Sex Factors
  • Smoking / epidemiology
  • Statistics, Nonparametric
  • Treatment Outcome