Analysis of the Clinical Significance and Cost Associated With the Routine Pathological Analysis of Pediatric Inguinal Hernia Sacs
Bibliographic record
Abstract
PURPOSE: Pediatric inguinal and scrotal surgeries for inguinal hernia, cryptorchidism and hydrocele are common and usually involve the excision of a hernia sac. Groups at many centers send hernia sacs for pathological analysis to identify occult disease as well as structures that may have been erroneously resected. We hypothesized that, since the incidence of significant findings is low and the associated health care costs are significant, the routine pathological analysis of inguinal hernia sacs is unnecessary. MATERIALS AND METHODS: After receiving institutional review board approval we retrospectively reviewed pathology reports at our institution of patients who underwent surgery with an inguinal hernia sac sent for pathological analysis from January 2000 to September 2009. The primary outcome was to determine the incidence of clinically significant structures in hernia sac specimens. The secondary outcome was to evaluate the costs associated with analyzing these specimens. RESULTS: A total of 2,287 boys and 441 girls underwent some form of inguinal or scrotal surgery during the study. In the 2,287 boys a total of 2,657 hernia sac specimens were analyzed, of which 2 (0.08%) contained clusters of epididymal-like tubules. Most unexpected findings were likely clinically insignificant, including mesothelial proliferation in 5.6% of cases, genital duct remnants in 0.8%, lipoma in 0.23% and adrenocortical rests in 0.04%. The average cost of analyzing hernia sac specimens at our institution was approximately $7,100 Canadian annually. CONCLUSIONS: Routine analysis of inguinal hernia sacs is unnecessary and costly, and should be reserved for cases in which resection of important structures such as the vas deferens is suspected.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".