A novel model to predict the risk of readmission in patients with renal colic

J Endourol. 2014 Aug;28(8):1011-5. doi: 10.1089/end.2014.0082. Epub 2014 May 15.

Abstract

Abstract Purpose: To identify the clinical, laboratory, and imaging parameters that may increase the risk of readmission in patients with renal colic that is managed by active surveillance and to produce a novel model to predict the risk for this.

Patients and methods: We retrospectively reviewed patients with renal colic secondary to ureteral calculi admitted to our hospital from March 2009 until September 2010. The colic was managed with active surveillance for 6 weeks. Patients were divided into those who were not readmitted to the hospital within the follow-up period (group A) and those who were (group B).

Results: From the 452 studied patients, 82 (18.1%) were readmitted to the hospital. Stone size (P<0.001) and location (P<0.001) and serum white blood cell count (P=0.009) were statistically significantly different between groups. These parameters were found to be independent predictors for readmission. A predictive model was produced to calculate the risk of readmission.

Conclusions: Stone size and location and white blood cell count are independent predictors for potential readmission in patients with renal colic. Using these parameters, we may calculate the risk for readmission, and the latter may assist physicians in identifying the best treatment option.

MeSH terms

  • Adult
  • Female
  • Humans
  • Leukocyte Count
  • Male
  • Middle Aged
  • Models, Theoretical*
  • Patient Readmission* / statistics & numerical data
  • Population Surveillance
  • Renal Colic* / blood
  • Renal Colic* / etiology
  • Retrospective Studies
  • Risk Assessment
  • Ureteral Calculi* / blood
  • Ureteral Calculi* / complications
  • Ureteral Calculi* / pathology
  • Ureteral Calculi* / therapy