347 Management of Abdominal Incidental Findings on Computed Tomography Scans in Emergency General Surgery
Bibliographic record
Abstract
Abstract Aim Emergency General Surgery (EGS) patients frequently undergo Computed Tomography (CT) scanning, incidental findings can be noted on the report which are unrelated to the original purpose of the scan that could have potential significance. This study aims to determine if these incidental findings are appropriately acknowledged in documentation and adequately managed. Method A comprehensive retrospective analysis was conducted on all referred EGS patients across a 3-month period in November 2023 to January 2024. CT-scan reports undertaken within 24 hours of referrals were analysed to identify incidental findings. All subsequent documentation were reviewed to ascertain whether they received appropriate management in at least a 6-month period and if suitable documentation of the finding was undertaken. Results 1090 patients were reviewed by the EGS team, of which 367 (33.6%) underwent a CT-scan reported within 24 hours of referral. A total of 152 incidental findings were identified, where at least one finding was reported on 125 (34.1%) of the scans. 30 (19.7%) of the findings required follow-up on radiologist recommendation in the report, of which 21 (70%) were appropriately actioned and 9 (30%) had no documented action. Out of the 125 scans only 27 (21.6%) had acknowledgment of findings on notes or discharge summary. Conclusions This study found that majority of incidental findings were appropriately managed but there is a significant lack of documentation overall. Regardless of if further action is required, all findings should be appropriately acknowledged with a documented plan in record to determine if follow-up is required or not.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".