Bibliographic record
Abstract
INTRODUCTION: Phimosis is defined as the inability to retract the foreskin. Differentiating between physiological phimosis and pathological phimosis is important, as the former is managed conservatively and the latter requires surgical intervention. Referrals of patients with physiological phimosis to urology clinics may create anxiety regarding the need for surgery amongst patients and parents, while unnecessarily expanding the waiting list for specialty assessment. OBJECTIVES: To determine the ability of referring physicians to differentiate physiological from pathological phimosis, and to see whether there is any difference in this ability between generalists versus specialists. MATERIALS AND METHODS: A retrospective chart review of 284 consecutive referrals for phimosis to the Children's Hospital of Eastern Ontario (CHEO) Urology Clinic during November 2000 - April 2003 was conducted. Referral sources included family physicians (FP), pediatricians (PD), emergency physicians (ER), and other subspecialists (SS). Data for this study were obtained from the original referral letters and cross-referenced with the impressions of the pediatric urologist following the initial patient encounter. The accuracy in diagnosing phimosis was evaluated among the various types of referring physicians. RESULTS: A total of 284 phimosis referrals were reviewed of patients ranging from 2 months to 16 years of age (mean = 6.6 years). The referral sources consisted of 222-GP, 33-PD, 23-ER, and 6-SS. The majority of referred cases were diagnosed by the attending pediatric urologist as physiological phimosis across all referral sources, with the exception of subspecialists (FP = 75.2%, PD = 81.8%, ER = 56.5%, SS = 33.3%). Second to this was the diagnosis of pathological phimosis across all referral sources except SS (FP = 14.9%, PD = 12%, ER = 34.8%, SS = 50%). Overall, the circumcision rate for the 284 phimosis referrals reviewed was 14.4%. CONCLUSIONS: Our findings reveal that many physicians continue to face difficulties in distinguishing physiological phimosis from the pathological. As a result, many unnecessary referrals are made for phimosis . We suggest the implementation of improved educational measures regarding preputial pathophysiology in the medical curriculum. Such measures would serve two purposes: first, to reduce the number of unnecessary specialty referrals and secondly, to aid primary care physicians in recognizing the presence of physiological phimosis so that patients and families may be reassured of normalcy.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".