Bladder and Bowel Dysfunction Network: Improving the Management of Pediatric Bladder and Bowel Dysfunction
Bibliographic record
Abstract
Introduction: Lower urinary tract symptoms with constipation characterize bladder and bowel dysfunction (BBD). Due to high referral volumes to hospital pediatric urology clinics and time-consuming appointments, wait times are prolonged. Initial management consists of behavioral modification strategies that could be accomplished by community pediatricians. We aimed to create a network of community pediatricians trained in BBD (BBDN) management and assess its impact on care. Methods: We distributed a survey to pediatricians, and those interested attended training consisting of lectures and clinical shadowing. Patients referred to a hospital pediatric urology clinic were triaged to the BBDN and completed the dysfunctional voiding symptom score and satisfaction surveys at baseline and follow-up. The Bristol stool chart was used to assess constipation. Results were compared between BBDN and hospital clinic patients. Results: Surveyed pediatricians (n = 100) most commonly managed BBD with PEG3350 and dietary changes and were less likely to recommend bladder retraining strategies. Baseline characteristics were similar in BBDN (n = 100) and hospital clinic patients (n = 23). Both groups had similar improvements in dysfunctional voiding symptom score from baseline to follow-up (10.1 ± 4.2 to 5.6 ± 3.3, P = 0.01, versus 10.1 ± 4.2 to 7.8 ± 4.5, P = 0.02). BBDN patients waited less time for their follow-up visit with 56 (28–70) days versus 94.5 (85–109) days for hospital clinic patients ( P < 0.001). Both groups demonstrated high familial satisfaction. Conclusions: Community pediatricians may require more knowledge of management strategies for BBD. Our pilot study demonstrates that implementing a BBDN is feasible, results in shorter wait times, and similar improvement in symptoms and patient satisfaction than a hospital pediatric urology clinic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".