Review of pathology and cost benefit analysis of hernia sacs processed over a 19-year period
Bibliographic record
Abstract
AIM: Hernia sacs with pathological evaluation over a 19-year period were analysed with regards to pathological diagnoses, full costing and the impact on patient management. MATERIALS AND METHODS: The database of the Department of Pathology were searched over the study period (2001 to 2019 inclusive) for hernia sacs. The total cost of complete pathology examination was calculated on average numbers and rates of pay that existed over the study period. RESULTS: A total of 3619 hernia sacs from the abdominal, hiatus/diaphragmatic, inguinal and femoral hernias were retrieved. Of these 3592 cases (99.25%) had sections taken for histological evaluation. A total of 3437 cases representing 95.7% of all hernia sacs did not show any pathological abnormality. If non-neoplastic clinically insignificant lesions seen in hernia sacs is included, then 3552 of 3592 (98.9%) hernia sacs underwent full pathological evaluation for no patient benefit.On average two blocks or tissue sections per case were processed incurring a technical cost of $53 175.00. The total pathologist cost in reporting the 3592 cases was approximately $39 870.00 and rose to $40 410.00 when interpretation of ancillary tests was factored in. $95 328.90 (average $26.90 per specimen with a yearly average total cost of $5 017.31) was spent over the 19-year period in full pathological examination of 3592 hernia sacs. CONCLUSION: Given the low return on investment and the difficult to quantify time savings and reallocation, we do not advocate the routine sampling of hernia sacs. Gross examination will suffice in 99% of the cases. Selective cases may be sampled if clinically indicated.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".