• CT scan
• PCNL
• X-ray
• cost
• cystolitholapaxy
• economics
• endourology
• health systems
• imaging
• interventions
• ultrasound scan
• ureteroscopy
• urolithiasis

• Humans
• Urology/economics
• Urolithiasis/economics
• Urolithiasis/diagnostic imaging
• Urolithiasis/therapy
• Europe
• Costs and Cost Analysis
• Diagnostic Imaging/economics
• Societies, Medical
• Internationality

• Adenotonsillectomy
• Bibliometric analysis
• Children
• Comorbidities
• Health-related quality of life
• Multidisciplinary
• Nocturnal enuresis
• Obstructive sleep apnea
• Pathogenesis

• Humans
• Sleep Apnea, Obstructive/complications
• Sleep Apnea, Obstructive/epidemiology
• Nocturnal Enuresis/epidemiology
• Nocturnal Enuresis/etiology
• Nocturnal Enuresis/complications
• Child

• Nos2020YFC2009000 and 2020YFC2009001 National Key Research and Development Program of China
• 2022-151, 2021-139, 2020-83, 2019-93 and 2018-92 The Hunan Provincial Department of Finance Grant
• 2021-212-23 Hunan Provincia Development and Reform Commission of Innovastive Research Program
• 2021ZK4025 Hunan Innovative Province Construction Special Project
• 2020JJ4799 Natural Science Foundation of Hunan Province

• ED visits
• laser lithotripsy
• readmission
• ureteroscopy
• urinary stone disease

• Fluoroscopy
• Percutaneous nephrolithotomy
• Renal stone
• “As low as reasonably achievable”

• Complication
• Feature selection
• Infection
• Machine learning
• Retrograde intrarenal surgery
• Scoring system

• Humans
• Urinary Tract Infections/diagnosis
• Urinary Tract Infections/etiology
• Urinary Tract Infections/epidemiology
• Male
• Female
• Retrospective Studies
• Middle Aged
• Postoperative Complications/etiology
• Postoperative Complications/diagnosis
• Postoperative Complications/epidemiology
• Fever/etiology
• Fever/diagnosis
• Risk Factors
• Adult
• Ureteroscopy/adverse effects
• Aged
• Kidney Calculi/surgery
• Machine Learning
• Risk Assessment/methods
• ROC Curve

• PCNL
• Sepsis
• Stone culture
• Ureteroscopy
• Urine culture

• Humans
• Sepsis/etiology
• Postoperative Complications
• Ureteroscopy
• Nephrolithotomy, Percutaneous
• Standard of Care
• Predictive Value of Tests
• Urinary Tract Infections/etiology
• Kidney Calculi/surgery
• Urolithiasis/surgery
• Nephrostomy, Percutaneous
• Clinical Relevance

• Bibliometric
• Randomized clinical trials
• Renal calculi
• Scopus
• Urolithiasis
• Visualization

• Humans
• Bibliometrics
• Biomedical Research/trends
• Biomedical Research/statistics & numerical data
• Randomized Controlled Trials as Topic/statistics & numerical data
• Urolithiasis/therapy

• AI
• PCNL
• kidney calculi
• shockwave lithotripsy
• simulation
• ureteroscopy
• urolithiasis

• Humans
• Urolithiasis/diagnostic imaging
• Artificial Intelligence
• Machine Learning
• Virtual Reality
• PubMed
• Bibliometrics
• Radiomics

• Artificial intelligence
• Kidney calculi
• Machine learning
• Ureteroscopy

• CKD
• Cystinuria
• Long-term follow-up
• Ureteroscopy

• Humans
• Ureteroscopy
• Male
• Retrospective Studies
• Adult
• Female
• Adolescent
• Tertiary Care Centers
• Cystinuria/complications
• Young Adult
• Treatment Outcome
• Time Factors
• Kidney Calculi/surgery
• Middle Aged
• Child

• Bibliometric
• Laser techniques
• Renal calculi
• Scopus
• Urolithiasis
• Visualization

• Humans
• Holmium
• Thulium
• Bibliometrics
• Postoperative Complications
• Aluminum
• Yttrium

• NHANES
• antioxidants
• kidney stones
• oxidative balance score
• pro-oxidants

• analgesics
• medical expulsive therapy
• silodosin
• stone expulsion time
• tamsulosin

• Artificial intelligence
• Kidney calculi
• Percutaneous nephrolithotomy
• Simulation
• Ureteroscopy
• Urolithiasis

• Artificial intelligence
• PCNL
• kidney calculi
• machine learning
• radiomics
• simulation
• urolithiasis

• Clavien-Dindo
• Nomogram
• Percutaneous nephrolithotomy
• Renal stone
• Urolithiasis

• Kidney
• Kidney calculi
• Lithotripsy
• RIRS
• SWL
• URS
• Ureteroscopy
• Urinary stones

• Humans
• Kidney Calculi/surgery
• Nephrolithotomy, Percutaneous/adverse effects
• Randomized Controlled Trials as Topic
• Systematic Reviews as Topic
• Meta-Analysis as Topic

• Cirugía intrarrenal retrógrada
• Cálculos renales
• Endourology
• Endourología
• Kidney stones
• Retrograde intrarenal surgery
• Ureteral access sheath
• Vaina de acceso ureteral

• Humans
• Kidney Calculi/surgery
• Retrospective Studies
• Ureter
• Ureteroscopes
• Ureteroscopy/methods

To explore the association between Healthy Eating Index (HEI)-2015 and kidney stones in an American adult population.

National Health and Nutrition Examination Survey (NHANES) datasets from 2007 to 2018 were used. Participants aged ≥ 20 years who reported kidney stone history and dietary recall were included. Weighted proportions, multivariable analysis and spline smoothing were used to evaluate the associations between HEI-2015 and nephrolithiasis by adjusting gender, age, race, poverty income ratio, body mass index, education level, marital status, smoking, alcohol intake, energy level, vigorous activity, moderate activity, and some comorbidities.

Totally 30 368 American adults were included, with weighted mean age [standard deviation (SD)] of 47.69 (16.85) years. The overall mean HEI-2015 score (SD) was 50.82 (13.80). In the fully-adjusted multivariable model, HEI-2015 was negatively correlated with urolithiasis [odds ratio (OR) = 0.991; 95% confidence interval (CI) 0.988 to 0.994]. Compared with the first quartile of HEI-2015, the population in the fourth quartile of HEI-2015 had a lower prevalence of kidney stones (OR = 0.716; 95% CI 0.635 to 0.807). The association was modified by education and vigorous activity.

HEI-2015 is inversely associated with the prevalence of kidney stones, which means better diet quality is associated with a lower risk of nephrolithiasis.

• HEI-2015
• NHANES
• association
• cross-sectional analysis
• kidney stones

• Humans
• Kidney Calculi/diagnostic imaging
• Kidney Calculi/surgery
• Middle Aged
• Nephrolithotomy, Percutaneous/methods
• Prospective Studies
• Quality of Life
• Retrospective Studies
• Treatment Outcome

• Humans
• Kidney Calculi/surgery
• Nephrolithotomy, Percutaneous
• Nephrostomy, Percutaneous

• alpha-adrenergic blockers
• distal ureteral stones
• doxazosin
• meta-analysis
• pediatric urolithiasis
• randomized controlled trials
• silodosin
• tamsulosin

Anti-retropulsive devices are often used to prevent stone migration in the treatment of proximal ureteral calculi. They are helpful. However, in the meantime, they also add extra expenses. This study was carried out to investigate the best criteria for treating proximal ureteral stones with anti-retropulsive devices.

Data from all patients who underwent ureteroscopic holmium: YAG laser lithotripsy for solitary upper ureteral stones in 2018 were collected. Patients who encountered stone retropulsion during the process of inserting the ureteroscope were excluded. Patients were divided into either group URS or group URS + ARD depending on whether the anti-retropulsive device was used. Then, the stone-free rate, expenses and other criteria were compared between groups according to stone location. Stone-free was defined as no stones present.

For stones located ≤ 30 mm from the ureteropelvic junction (UPJ), the stone-free rates for the URS group were 80% and 80% at one day and one month after the operation, respectively. Those for the URS + ARD group were 71.4% and 78.6% at one day and one month, respectively. For stones located 31–90 mm from the UPJ, the stone-free rates were 84.7% and 84.7% for the URS group and 89.6% and 95.5% for the URS + ARD group at one day and one month, respectively. A statistically significant difference occurred at one month. For stones located > 90 mm from the UPJ, the two groups were both stone free. In the URS + ARD group, expenses were higher. In addition, the mean diameter of residual stones derived from stones located at 31–90 mm from the UPJ was statistically smaller, and 4 of 7 residual stones passed spontaneously within one month, which was obviously more than that in other locations and the URS group. Other outcomes, including operation time and postoperative stay, showed no significant difference between the groups.

Anti-retropulsive devices are indeed helpful, but they might be cost-effective for stones located solely in the middle part of the upper ureter, not for those too close to or far from the ureteropelvic junction.

The online version contains supplementary material available at 10.1186/s12894-022-00995-9.

• Anti-retropulsive device
• Cost-effective
• Stone-free
• Ureteral calculi
• Ureteroscopy

The burden of urological diseases is rising as the worldwide population ages. Although specialist urological provision is needed, a large proportion of these conditions will be managed in primary care. The importance of including urology in medical education currently remains unclear.

To provide recommendations on undergraduate medical education for urology in Europe.

A three-round Delphi process to reach consensus on standardising the undergraduate urology curriculum in Europe was endorsed by the European School of Urology.

The levels of agreement were set using a nine-point scale according to the GRADE grid: 1–3, disagree; 4–6, uncertain; and 7–9, agree. Consensus was defined as at least 70% of the participants scoring within the same 3-point grouping.

Overall, consensus was reached for 20 of 34 statements (70.5%) across the three Delphi rounds, with agreement for 75% (n = 15) and disagreement for 25% (n = 5). The following main points were agreed. Urological teaching should be introduced before year 5 of medical school, with at least 20 h of theoretical activities and at least 30 h of practical activities. Urology should be taught as a stand-alone subject rather than combined with another surgical specialty or a nephrology programme. The participants agreed that urology should be taught according to symptoms. A urology programme should include the anatomy and physiology of the urinary tract, and students should know how to clinically assess a urological patient.

Our recommended urology pathway will allow European medical schools to provide a more comprehensive undergraduate urology curriculum. It will also help to improve and maintain standards of urology undergraduate teaching across Europe.

Our survey showed that urology in universities should have, at minimum, time for theoretical and practical activities and should be taught as a stand-alone subject on the basis of symptoms. Students should give feedback to facilitate constant improvement and evolution of the teaching programme.

• Delphi consensus
• Education
• Undergraduate medical education
• Urology

• Laser
• Percutaneous nephrolithotomy
• Publications
• Renal stone
• Therapy
• Ureteroscopy
• Urolithiasis

• AI
• PCNL
• TFL
• kidney calculi
• laser
• renal tumour
• ureteroscopy
• urosepsis

Introduction: With the rise in the use of ureteroscopy and laser stone lithotripsy (URSL), a proportionate increase in the risk of post-procedural urosepsis has also been observed. The aims of our paper were to analyse the predictors for severe urosepsis using a machine learning model (ML) in patients that needed intensive care unit (ICU) admission and to make comparisons with a matched cohort. Methods: A retrospective study was conducted across nine high-volume endourology European centres for all patients who underwent URSL and subsequently needed ICU admission for urosepsis (Group A). This was matched by patients with URSL without urosepsis (Group B). Statistical analysis was performed with ‘R statistical software’ using the ‘randomforests’ package. The data were segregated at random into a 70% training set and a 30% test set using the ‘sample’ command. A random forests ML model was then built with n = 300 trees, with the test set used for internal validation. Diagnostic accuracy statistics were generated using the ‘caret’ package. Results: A total of 114 patients were included (57 in each group) with a mean age of 60 ± 16 years and a male:female ratio of 1:1.19. The ML model correctly predicted risk of sepsis in 14/17 (82%) cases (Group A) and predicted those without urosepsis for 12/15 (80%) controls (Group B), whilst overall it also discriminated between the two groups predicting both those with and without sepsis. Our model accuracy was 81.3% (95%, CI: 63.7–92.8%), sensitivity = 0.80, specificity = 0.82 and area under the curve = 0.89. Predictive values most commonly accounting for nodal points in the trees were a large proximal stone location, long stent time, large stone size and long operative time. Conclusion: Urosepsis after endourological procedures remains one of the main reasons for ICU admission. Risk factors for urosepsis are reasonably accurately predicted by our innovative ML model. Focusing on these risk factors can allow one to create predictive strategies to minimise post-operative morbidity.

• kidney calculi
• kidney stones
• laser lithotripsy
• nephrolithiasis
• predictor factors
• ureteroscopy
• urolithiasis
• urosepsis

• Benign prostatic hyperplasia
• Bibliometrics
• Laser
• Publication trends

• Humans
• Internationality
• Laser Therapy/instrumentation
• Laser Therapy/methods
• Laser Therapy/trends
• Lasers, Solid-State/classification
• Lasers, Solid-State/therapeutic use
• MEDLINE/statistics & numerical data
• Male
• Prostatic Hyperplasia/therapy
• Publishing/statistics & numerical data
• Publishing/trends

• Universitätsklinikum Freiburg (8975)

• intrapelvic pressure
• irrigation
• ureteroscopy
• urolithiasis

• endoscopic combined intrarenal surgery
• kidney stones
• mini-endoscopic combined intrarenal surgery
• ultrasonography-guided puncture
• ureteroscopic assistance

• Incidence
• Kidney stone
• Prevalence
• Russian Federation
• Urolithiasis

• Flexible ureteroscopy
• Meta-analysis
• Prestenting
• Upper urinary stone

• MET
• distal ureteral stone
• medical expulsive therapy
• silodosin
• terpen combination
• urolithiasis

• Humans
• Indoles
• Retrospective Studies
• Terpenes
• Treatment Outcome
• Ureteral Calculi/drug therapy

• Humans
• Indoles
• Retrospective Studies
• Ureteral Calculi/diagnostic imaging
• Ureteral Calculi/drug therapy
• Urinary Calculi

Extracorporeal shock wave lithotripsy (ESWL) of kidney stones is losing ground to more expensive and invasive endoscopic treatments.

This proof-of-concept project was initiated to develop artificial intelligence (AI)-augmented ESWL and to investigate the potential for machine learning to improve the efficacy of ESWL.

Two-dimensional ultrasound videos were captured during ESWL treatments from an inline ultrasound device with a video grabber. An observer annotated 23 212 images from 11 patients as either in or out of focus. The median hit rate was calculated on a patient level via bootstrapping. A convolutional neural network with U-Net architecture was trained on 57 ultrasound images with delineated kidney stones from the same patients annotated by a second observer. We tested U-Net on the ultrasound images annotated by the first observer. Cross-validation with a training set of nine patients, a validation set of one patient, and a test set of one patient was performed.

Classical metrics describing classifier performance were calculated, together with an estimation of how the algorithm would affect shock wave hit rate.

The median hit rate for standard ESWL was 55.2% (95% confidence interval [CI] 43.2–67.3%). The performance metrics for U-Net were accuracy 63.9%, sensitivity 56.0%, specificity 74.7%, positive predictive value 75.3%, negative predictive value 55.2%, Youden’s J statistic 30.7%, no-information rate 58.0%, and Cohen’s κ 0.2931. The algorithm reduced total mishits by 67.1%. The main limitation is that this is a proof-of-concept study involving only 11 patients.

Our calculated ESWL hit rate of 55.2% (95% CI 43.2–67.3%) supports findings from earlier research. We have demonstrated that a machine learning algorithm trained on just 11 patients increases the hit rate to 75.3% and reduces mishits by 67.1%. When U-Net is trained on more and higher-quality annotations, even better results can be expected.

Kidney stones can be treated by applying shockwaves to the outside of the body. Ultrasound scans of the kidney are used to guide the machine delivering the shockwaves, but the shockwaves can still miss the stone. We used artificial intelligence to improve the accuracy in hitting the stone being treated.

• Artificial intelligence
• Extracorporeal shockwave lithotripsy
• Kidney stones
• Machine learning
• Neural network