title: Pyelocaliceal Distribution of Kidney Stones Used as an Outcome Predictor in Percutaneous Nephrolithotomy After Being Evaluated with Preoperative and Postoperative CT Scan.
abstract: OBJECTIVE
  To identify kidney stone characteristics that will determine either success or failure of a percutaneous nephrolithotomy (PCNL) and design a classification system to predict results according to these characteristics.
  
  
  METHODS
  One hundred thirty-eight patients were assessed with multislice abdominal and pelvic CT before and after PCNL. With regard to pyelocaliceal stone distribution, we classified our patients in two groups that we called "no extra stone in middle calix" (NESMC) and "extra stone in middle calix" (ESMC), according to the difficulty in reaching the stones. We did a univariate and a multivariate analysis, as well as a receiving operating curve (ROC) of the proposed classification, based on the foreseen probabilities, to determine the diagnostic yield.
  
  
  RESULTS
  Global residual lithiasis (RL) was 26.08%. The proportion of patients with RL according to classification was NESMC 11.5% and ESMC 59.5%. In the univariate logistic regression analysis of the distribution, number, total volumetry, side, type, radio-opacity of stones, and the presence or not of preoperatory urinary tract infection, the variables related to RL were the distribution (11.3; 95% confidence interval [95% CI] 4.7, 27.4), volumetry (odds ratio [OR] 1.01; 95% CI 1.004, 1.014), and the presence of staghorn stones (OR 6.64; 95% CI 2.463, 17.905). In the multivariate analysis, distribution was statistically significant (OR 8.687; 95% CI 2.69, 28.06), whereas total volumetry and the presence of staghorn stones were not (OR 1; 95% CI 1.000, 1.000 and OR 2.7; 95% CI 0.35, 20.57, respectively). The ROC showed an area under the curve of 0.77.
  
  
  CONCLUSIONS
  In our experience, the distribution of kidney stones is the most important predictor of RL after PCNL. The results also suggest that the presence of stones in the middle calix has a direct impact on the stone-free rate. We put forward a simple and reproducible classification, easy to apply, and useful to estimate the chances of success of the procedure using preoperatory CT scans.
authors.affiliation: Urology Department, Hospital Italiano de Buenos Aires , Buenos Aires, Argentina .
authors.forename: Federico Ignacio
authors.initials: FI
authors.lastname: Tirapegui
authors.affiliation: Urology Department, Hospital Italiano de Buenos Aires , Buenos Aires, Argentina .
authors.forename: Mariano Sebastian
authors.initials: MS
authors.lastname: González
authors.affiliation: Urology Department, Hospital Italiano de Buenos Aires , Buenos Aires, Argentina .
authors.forename: Ignacio Pablo Tobía
authors.initials: IP
authors.lastname: González
authors.affiliation: Urology Department, Hospital Italiano de Buenos Aires , Buenos Aires, Argentina .
authors.forename: Francisco P
authors.initials: FP
authors.lastname: Daels
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D007669:Kidney Calculi / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009403:Nephrostomy, Percutaneous / Q000379:methods*; D016017:Odds Ratio; D011184:Postoperative Period; D011237:Predictive Value of Tests; D057234:Preoperative Period; D011379:Prognosis; D012372:ROC Curve; D012086:Reoperation; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed; D016896:Treatment Outcome; D055815:Young Adult