External validation of Imamura nomogram as a tool to predict preoperatively laser semi-rigid ureterolithotripsy outcomes

Stone decision engine accurately predicts stone removal and treatment complications for shock wave lithotripsy and laser ureterorenoscopy patients

Kidney stones form when mineral salts crystallize in the urinary tract. While most stones exit the body in the urine stream, some can block the ureteropelvic junction or ureters, leading to severe lower back pain, blood in the urine, vomiting, and painful urination. Imaging technologies, such as X-rays or ureterorenoscopy (URS), are typically used to detect kidney stones. Subsequently, these stones are fragmented into smaller pieces using shock wave lithotripsy (SWL) or laser URS. Both treatments yield subtly different patient outcomes. To predict successful stone removal and complication outcomes, Artificial Neural Network models were trained on 15,126 SWL and 2,116 URS patient records. These records include patient metrics like Body Mass Index and age, as well as treatment outcomes obtained using various medical instruments and healthcare professionals. Due to the low number of outcome failures in the data (e.g., treatment complications), Nearest Neighbor and Synthetic Minority Oversampling Technique (SMOTE) models were implemented to improve prediction accuracies. To reduce noise in the predictions, ensemble modeling was employed. The average prediction accuracies based on Confusion Matrices for SWL stone removal and treatment complications were 84.8% and 95.0%, respectively, while those for URS were 89.0% and 92.2%, respectively. The average prediction accuracies for SWL based on Area-Under-the-Curve were 74.7% and 62.9%, respectively, while those for URS were 77.2% and 78.9%, respectively. Taken together, the approach yielded moderate to high accurate predictions, regardless of treatment or outcome. These models were incorporated into a Stone Decision Engine web application (http://peteranoble.com/webapps.html) that suggests the best interventions to healthcare providers based on individual patient metrics.

Ureteral stent encrustation: evaluation of available scores as predictors of a complex surgery

BACKGROUND

Stent encrustation is an uncommon event (13%) with a significant impact in patients' management. Aim of our study was to evaluate the available grading systems for encrusted stents.

METHODS

A retrospective analysis of encrusted stents was performed in four Italian centers between 2006 and 2020. Encrusted stents were classified according to four classifications: the Forgotten Encrusted Calcificated (FECal) Score, the Kidney Ureter Bladder (KUB) Score, the Visual Grading for Ureteral Encrusted Stent Classification and the Encrustation Burden Score (EBS). Classifications were evaluated to predict complex surgery defined as: long operative time (>60 min), need of more than one surgery, and need of a percutaneous approach. The scores were compared with receiver operating characteristic (ROC) analysis as predictors of complex surgery.

RESULTS

Seventy-seven patients were evaluated with a median age of 62 years (65/70). Overall FECal score >2 was present in 45/77 (58%) patients, median KUB score was 9 (6/14) and severe EBS was found in 47/77 (63%) patients. Patients were managed with cyst lithotripsy in 13/77 (17%), with ureteroscopy in 58/77 (75%) and with percutaneous nephrolithotomy (PCNL) in 6/77 (8%). Overall, 6/77 (8%) patients required a second intervention to remove the encrusted stent. All classifications predicted the need of complex surgery. On ROC analysis KUB score presented a better accuracy in predicting complex surgery compared to FECal, V-GUES and encrusted burden.

CONCLUSIONS

KUB score, FECal score, V-GUES score, and encrustation burden accurately predict the need of a complex surgery. KUB showed to be superior to other classifications according to our results.

Ureteral wall thickness and distal ureteral density in patients with residual fragments after Ho:YAG laser semi-rigid ureterolithotripsy

Recent data suggest that greater ureteral density distal to ureteral stones or increased ureteral wall thickness (UWT) can predict impacted stones. The aim of our study was to evaluate if patients with residual fragments present with greater ureteral density and larger UWT when compared to stone-free patients. From January onward, a consecutive series of patients undergoing semi rigid Ho:YAG laser ureterolithotripsy (ULT) for ureteral stones were enrolled. A non-contrast enhanced computed tomography (CT) scan was performed before the procedure to evaluate distal ureteral density (DUD) and wall ureteral thickness (UWT) at the site of ureteral stones. Patients with residual fragments were compared to stone-free patients using a matched-pair analysis (1:1 scenario). Cases were matched sequentially using the following criteria: age, gender, body mass index (BMI), stone length, hydronephrosis, location of stones, and mean Hounsfield unit (HU) of the stone. Overall, 160 patients were enrolled, mean age was 57.9 ± 14 years, mean BMI was 25.8 ± 4 kg/m2, mean length of the stone was 10.6 ± 4.9 mm, and mean UWT was 1.4 ± 1.6 mm. A total of 150/160 (94%) patients presented hydronephrosis; mean HU stone was 868 ± 327; mean DUD was 54 ± 17.8 HU. Ureteral distal density (51.7 vs 56.6; p = 0.535) and ureteral distal thickness (1.39 vs 1.54; p = 0.078) were similar in both groups of patients. In our study, the evaluation of distal ureteral density does not predict stone-free rate. Further studies should evaluate the role for preoperative computer tomography in predicting surgery outcome.

"VirtualBasket" ureteroscopic holmium laser lithotripsy: intraoperative and early postoperative outcomes

BACKGROUND

The "VirtualBasket" technology is the result of pulse modulation during holmium laser emission: the laser emits part of the energy to create an initial bubble, and a second pulse is emitted when the vapor bubble is at its maximum expansion, so that it can pass through the previously created vapor channel. The aim of this study is to outline the outcomes of the "VirtualBasket" technology in ureteral and renal stones.

METHODS

160 Patients were randomly assigned to holmium laser lithotripsy with or without the "VirtualBasket" technology in ureteric or renal cases (40 per 4 groups). All procedures were performed by four experienced urologists. The Quanta System Cyber Ho 100W laser generator with 365 μm fibers was used for all of the ureteral cases, whereas, 272 μm fibers were used for all of the cases in the renal pelvis. Demographic data, stone parameters, perioperative complications and success rates were compared. A statistical analysis was carried out to assess patients data and outcomes. All of the reported p-values were obtained with the two-sided exact method at the conventional 5% significance level. The degree of stone retropulsion was graded on a Likert scale from zero (no retropulsion) to 3 (maximum retropulsion).

RESULTS

All groups were comparable in terms of age, and pre-operative stone size (ureter stone size: 1.2 vs. 1.1 cm; renal pelvis stone size: 1.55 vs. 1.62 cm). Compared to the regular mode, the "VirtualBasket" technology was associated with significantly lower fragmentation time (mean time for ureteral stones: 20.4 vs. 16.1 minutes, p<0.05; mean time for renal stones: 28.7 vs. 19.8 minutes, p<0.05) and total procedural time (mean time for ureteral stones 49 vs. 35.7 minutes; mean time for renal stones 67.1 vs. 52.4 minutes). There were no significant differences in terms of energy delivered to the stones, intraoperative complications and success rate at 1 month. The "VirtualBasket" technology was associated with significantly lower retropulsion.

CONCLUSIONS

The "VirtualBasket" technology is associated with significantly lower fragmentation and procedural times. The reduced fragmentation time is a result of the significantly lower retropulsion of the stones during laser lithotripsy, which improves stone fragmentation efficiency.