Trial reportInternational braz j urol : official journal of the Brazilian Society of Urology
Predictive model for urosepsis in patients with Upper Urinary Tract Calculi based on ultrasonography and urinalysis using artificial intelligence learning.
Trial report in International braz j urol : official journal of the Brazilian Society of Urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Applications of artificial intelligence algorithms in ultrasound-based kidney stone detection, classification, prediction, and management: a systematic review.Abdominal radiology (New York) · 2026Pooled it
- Risk prediction models for postoperative complications of urosepsis in patients with upper urinary calculi: a systematic review and meta-analysis.BMC infectious diseases · 2026Pooled it
- Artificial intelligence in urolithiasis: a systematic review of utilization and effectiveness.World journal of urology · 2024Pooled it
- Development of a machine learning model for predicting urosepsis after ureteroscopic lithotripsy.Urolithiasis · 2026Article
- Smart Kiosk for Nutritional Management of People With Diabetes in Underserved Communities: Development and Technical Evaluation.JMIR formative research · 2026Article
- Diagnostic tests for urinary tract infections and antimicrobial resistance-a reality check between diagnostic innovation and implementation: a critical narrative review.Frontiers in cellular and infection microbiology · 2026Review
- Exploring the Molecular Mechanisms by Which DEHP Promotes the Occurrence and Progression of Kidney Stones Based on Network Toxicology and Experimental Validation.International journal of general medicine · 2026Article
- Identifying urosepsis risk in diabetic patients with renal and ureteral calculi: Key predictors and clinical implications.World journal of diabetes · 2025Article
- Application of multi-scale dynamic enhancement based on deep neural network and CT urinary tract secretory phase image fusion in the diagnosis of urinary system diseases.BMC medical imaging · 2025Article
- An interpretable machine learning model integrating computed tomography radiomics and clinical features for predicting the urosepsis after percutaneous nephrolithotomy.Biomedical engineering online · 2025Article
- Risk factors for urosepsis in diabetic patients with renal and ureteral calculi: A retrospective study.World journal of diabetes · 2025Article
- Use of Artificial Intelligence Methods for Improved Diagnosis of Urinary Tract Infections and Urinary Stone Disease.Journal of clinical medicine · 2025Review
- Automatic kidney stone identification: an adaptive feature-weighted LSTM model based on urine and blood routine analysis.Urolithiasis · 2024Article
- Risk factors and nomogram for predicting urinary tract infection in patients with ureterolithiasis complicated with hydronephrosis.Translational andrology and urology · 2024Article
- A novel post-percutaneous nephrolithotomy sepsis prediction model using machine learning.BMC urology · 2024Article
- Smart Diagnosis of Urinary Tract Infections: is Artificial Intelligence the Fast-Lane Solution?Current urology reports · 2024Review
- Article
- Risk factors of concurrent urinary sepsis in patients with diabetes mellitus comorbid with upper urinary tract calculi.World journal of diabetes · 2023Article
- HUGO(TM) RAS System in Robotic-Assisted Radical prostatectomy is highligheted in International Brazilian Journal of Urology.International braz j urol : official journal of the Brazilian Society of UrologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo construct a predicting model for urosepsis risk for patients with upper urinary tract calculi based on ultrasound and urinalysis. MATERIALS AND
methodsA retrospective study was conducted in patients with upper urinary tract calculi admitted between January 2016 and January 2020. The patients were randomly grouped into the training and validation sets. The training set was used to identify the urosepsis risk factors and construct a risk prediction model based on ultrasound and urinalysis. The validation set was used to test the performance of the artificial neural network (ANN).
resultsUltimately, 1716 patients (10.8% cases and 89.2% control) were included. Eight variables were selected for the model: sex, age, body temperature, diabetes history, urine leukocytes, urine nitrite, urine glucose, and degree of hydronephrosis. The area under the receiver operating curve in the validation and training sets was 0.945 (95% CI: 0.903-0.988) and 0.992 (95% CI: 0.988-0.997), respectively. Sensitivity, specificity, and Yuden index of the validation set (training set) were 80.4% (85.9%), 98.2% (99.0%), and 0.786 (0.849), respectively.
conclusionsA preliminary screening model for urosepsis based on ultrasound and urinalysis was constructed using ANN. The model could provide risk assessments for urosepsis in patients with upper urinary tract calculi.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.