Which Is the Best Predictor to Achieve Trifecta in Patients Undergoing Elective Laparoscopic Partial Nephrectomy with Global Hilar Clamping? Comparative Analysis in Patients with Clinical T1a and T1b Renal Tumors

Development and Validation of a Nomogram Predicting Intraoperative Adverse Events During Robot-assisted Partial Nephrectomy

BACKGROUND

Ability to predict the risk of intraoperative adverse events (IOAEs) for patients undergoing partial nephrectomy (PN) can be of great clinical significance.

OBJECTIVE

To develop and internally validate a preoperative nomogram predicting IOAEs for robot-assisted PN (RAPN).

DESIGN, SETTING, AND PARTICIPANTS

In this observational study, data for demographic, preoperative, and postoperative variables for patients who underwent RAPN were extracted from the Vattikuti Collective Quality Initiative (VCQI) database.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

IOAEs were defined as the occurrence of intraoperative surgical complications, blood transfusion, or conversion to open surgery/radical nephrectomy. Backward stepwise logistic regression analysis was used to identify predictors of IOAEs. The nomogram was validated using bootstrapping, the area under the receiver operating characteristic curve (AUC), and the goodness of fit. Decision curve analysis (DCA) was used to determine the clinical utility of the model.

RESULTS AND LIMITATIONS

Among the 2114 patients in the study cohort, IOAEs were noted in 158 (7.5%). Multivariable analysis identified five variables as independent predictors of IOAEs: RENAL nephrometry score (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.02-1.25); clinical tumor size (OR 1.01, 95% CI 1.001-1.024); PN indication as absolute versus elective (OR 3.9, 95% CI 2.6-5.7) and relative versus elective (OR 4.2, 95% CI 2.2-8); Charlson comorbidity index (OR 1.17, 95% CI 1.05-1.30); and multifocal tumors (OR 8.8, 95% CI 5.4-14.1). A nomogram was developed using these five variables. The model was internally valid on bootstrapping and goodness of fit. The AUC estimated was 0.76 (95% CI 0.72-0.80). DCA revealed that the model was clinically useful at threshold probabilities >5%. Limitations include the lack of external validation and selection bias.

CONCLUSIONS

We developed and internally validated a nomogram predicting IOAEs during RAPN.

PATIENT SUMMARY

We developed a preoperative model than can predict complications that might occur during robotic surgery for partial removal of a kidney. Tests showed that our model is fairly accurate and it could be useful in identifying patients with kidney cancer for whom this type of surgery is suitable.

Can Aortic and Renal Arteries Calcium Scores Be New Factors to Predict Post-Operative Renal Function After Nephron Sparing Surgery?

INTRODUCTION

This study aims to investigate whether the calcification of renal arteries and aorta may be risk factors for developing chronic kidney disease (CKD) after Nephron sparing surgery (NSS).

MATERIALS AND METHODS

The patients that underwent either open or laparoscopic NSS from 2000 to 2019 in 4 different centers were retrospectively assessed. Of these patients, 328 had a non-contrast-enhanced computer tomography. Calcium scores of the renal arteries and abdominal aorta were measured in the non-contrast-enhanced images with the calcium score plugin (version 2.0) of Horos™. Univariate and multivariate logistic regression analysis was performed to determine significant risk factors for developing CKD at the last check-up. Roc curve analysis was performed to determine the optimal cut-off values of age and abdominal aorta calcium scores.

RESULTS

A total of 302 patients, of which 52 (16,6%) with CKD and 252 (83,4%) without CKD at the last check-up, were included in the analysis. The mean warm ischemia duration was significantly higher in patients with CKD (18,79±6,72 vs 16,38±5,57 minutes, p=0,016). The mean size of the tumor diameter and the number of the patients with ≥stage T1b were higher in the group with CKD (p=0,024 and 0,005, respectively). The median calcium scores of the aorta and renal arteries were higher in the group with CKD (p<0,001 and p<0,001, respectively). In multivariate analysis, age >60 years (OR:3,65, p=0,022), calcium score of the aorta (OR:4,07, p=0,029), tumor diameter (OR:1,03, p=0,026) and pre-operative CKD stage (OR:10,13, p<0,001) found the be significant factors for predicting last check-up CKD.

CONCLUSION

The calcium score of the aorta may be used as an additional risk factor to predict post-operative CKD risk after NSS with sensitivity over 80%.