When the Appendix Is Not Seen on Ultrasound for Right Lower Quadrant Pain
Bibliographic record
Abstract
A survey was administered to 166 academic emergency department (ED) physicians to determine their interpretation and practice after receiving an ultrasound (US) report with nonvisualization of the appendix (NVA). Annual incidence of reported NVA from 2 academic hospitals was calculated for 2002-2013. A retrospective review of the same hospitals revealed that 291 (17.4%) of 1672 USs performed for appendicitis in 2012 indicated NVA. These cases underwent a chart review to determine the negative predictive value of reported NVA and utility of secondary findings. Univariate analysis was performed to determine significant predictors of secondary signs of appendicitis on computed tomography. Ninety eight (59%) of 166 ED physicians completed the survey. Forty nine (52%) of 94 respondents agreed that in the setting of reported NVA with no other acute findings, appendicitis has not been excluded and requires further imaging. There was a significant rise in the incidence rate of reported NVA for appendicitis, 22.5% (2002) up to 41.2% (2013, P < 0.0001). Negative predictive value for reported NVA was 216 (94.3%) of 229; in 9 (69%) of 13 patients, secondary signs of appendicitis were noted. Inflammatory changes in right lower quadrant (P = 0.01) and focal tenderness (P = 0.02) noted on US were significant predictors of a positive computed tomography scan. Current perceptions and practice of some ED physicians equate NVA on US as an inadequate study to exclude appendicitis. However, reported NVA is itself a highly predictive sign (94.3%) of absence of appendicitis even when an alternate cause of pain is not seen.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".