The impact of frailty syndrome and risk scores on emergency cholecystectomy patients

Surg Today. 2017 Jan;47(1):74-83. doi: 10.1007/s00595-016-1361-1. Epub 2016 May 30.

Abstract

Purpose: Cholecystectomy, which is one of the most common surgical procedures, is also performed in the emergency setting. A number of risk scores have been introduced in recent studies; moreover, over the last few years literature has focused on surgical patients with frailty syndrome. The aim of the present study is to evaluate whether frailty syndrome and the risk scores are correlated with morbidity, post-operative hospital stay and the ICU admission rate following emergency cholecystectomy.

Methods: Eighty-five consecutive patients of >65 years of age who underwent cholecystectomy were selected from 2306 emergency procedures for inclusion in the present study. The patients were assessed for frailty syndrome and their scores were calculated on the basis of chart review. Univariate analyses were performed to compare severe frailty patients to intermediate frailty and robust patients. ROC and logistic regression analyses were performed with the end-points of morbidity, hospital stay and ICU admission.

Results: In addition to having worse ASA, inflammatory and risk values than robust patients, frailty syndrome patients also had higher rates of morbidity and ICU admission and longer hospitalization periods. A logistic regression analysis showed that the P-Possum was independently correlated with morbidity. Frailty and open surgery were independently correlated with longer hospitalization, whereas ICU admission was correlated with worse ASA and P-Possum values.

Conclusions: Frailty syndrome significantly impacts the length of hospitalization in patients undergoing emergency cholecystectomy. Although the ORs were limited, the P-Possum value was independently associated with the outcome.

Keywords: Charlson age-comorbidity index; Cholecystectomy; Frailty; P-Possum; SAPS-II.

MeSH terms

  • Age Factors
  • Aged
  • Cholecystectomy* / statistics & numerical data
  • Emergencies
  • Female
  • Frailty* / epidemiology
  • Humans
  • Intensive Care Units / statistics & numerical data
  • Length of Stay / statistics & numerical data*
  • Logistic Models
  • Male
  • Morbidity
  • Patient Admission / statistics & numerical data
  • Prognosis
  • ROC Curve
  • Risk