Bibliographic record
Abstract
You have accessJournal of UrologyThis Month in Pediatric Urology1 Aug 2019This Month in Pediatric Urology Mark P. Cain Mark P. CainMark P. Cain More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000349AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Incidental and Symptomatic Renal Cyst in a Pediatric Cohort undergoing Ultrasonography With increasing use of abdominal imaging in children for a wide variety of diagnoses, urologists have been confronted with an increasing number asymptomatic renal cysts. This new “problem” is like our past challenges in refining the evaluation and management (as well as meaningfulness) of neonates found to have urinary tract dilation on prenatal ultrasound. More than 30 years later we still struggle with the definition of normal variants of perinatal urinary tract dilation that do not require long-term imaging surveillance or surgical intervention, which is similar to our current understanding of renal cysts in children. To help delineate the need for and duration of followup of asymptomatic renal cysts in children, O’Kelly et al (page 394) from Canada reviewed the outcomes of 783 children found to have renal cysts on abdominal ultrasound serial imaging.1 Of this cohort 211 patients had complex cysts and only 4 (1.8%) had renal cancer detected at surgery. Notable findings included a small (<1%) incidence of conversion from simple to complex cyst on ultrasound in older teens with larger cysts at presentation. Followup studies revealed complete resolution of simple cysts in 25% of cases. Based on the data presented and prior literature, the authors reasonably conclude that most asymptomatic renal cysts in children are benign and complex cysts (larger than 1.5 cm or with minimal change after 2 years) can be serially followed. 3D Magnetic Resonance Image-Guided Pelvic Floor Dissection for Bladder Exstrophy Many of the recent technical advances in surgical reconstruction of bladder exstrophy have included a more aggressive dissection of the abnormal pelvic floor muscles of the perineum together with pelvic osteotomies to establish a more normal urogenital diaphragm and potentially improve continence. A key element is placement of the closed bladder and reconstructed bladder outlet/urethra in a more posterior and inferior location next to the levator muscles. To identify these structures intraoperatively with little radiographic guidance has historically relied on surgeon experience. To assist with defining the pelvic musculature during surgical reconstruction for bladder and cloacal exstrophy, Di Carlo et al (page 406) from Baltimore, Maryland used a combination of preoperative magnetic resonance imaging with a new intraoperative magnetic resonance image-guided navigation system developed by Brainlab®.2 During surgery the critical soft tissue and bone landmarks were identified and confirmed by a senior radiologist and senior pediatric urologist with a high level of accuracy, both during dissection and placement of the bladder unit into the posterior levator muscle group. There were no device related complications, and minimal additional operative time in 44 consecutive cases. Potential advantages of this type of surgical and radiographic correlation during repair of exstrophy would be lower risk of failed bladder closure and improved continence with more accurate placement of the bladder in the reconstructed pelvis. This technology also offers the advantage as a teaching and training tool for rare diseases such as bladder exstrophy. References 1. : The prevalence, clinicodemographics, and outcomes of incidental and symptomatic renal cysts in a pediatric cohort undergoing ultrasonography. J Urol 2019; 202: 394. Link, Google Scholar 2. : 3-dimensional magnetic resonance imaging guided pelvic floor dissection for bladder exstrophy: a single arm trial. J Urol 2019; 202: 406. Link, Google Scholar © 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 202Issue 2August 2019Page: 183-183 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Mark P. Cain More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.686 | 0.429 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".