Bibliographic record
Abstract
OBJECTIVE: To review the clinical classification of childhood diurnal enuresis, to describe the evaluation process, and to discuss principles of management. QUALITY OF EVIDENCE: An extensive literature review was performed with a MEDLINE search. Articles were selected according to date of publication, clinical relevance, and availability. Recent articles, cohort studies of at least 50 patients, and randomized clinical trials were preferred. Recent editions of classic textbooks were consulted. Evaluation and management activities discussed in this article are supported by original and relevant literature. MAIN MESSAGE: Most causes of childhood diurnal enuresis can be determined by a thorough history coupled with a complete physical examination and urinalysis and culture. Supplementary investigations include ultrasonography of the kidneys and bladder to screen for neurogenic bladder and urethral obstruction. When obstruction, ectopic ureter, or bladder dysfunction is suspected, voiding cystourethrography and urodynamic studies are needed. Evaluation of neurogenic bladder includes magnetic resonance imaging of the spine. Treatment is aimed at correcting poor toilet habits, preventing or treating urinary tract infections, and using appropriate medication. CONCLUSIONS: In most instances, diurnal enuresis in childhood is a benign condition with an easily identifiable cause and an excellent prognosis with time and appropriate treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".