US or CT for Diagnosis of Appendicitis in Children and Adults? A Meta-Analysis
Bibliographic record
Abstract
PURPOSE: To perform a meta-analysis to evaluate the diagnostic performance of ultrasonography (US) and computed tomography (CT) for the diagnosis of appendicitis in pediatric and adult populations. MATERIALS AND METHODS: Medical literature (from 1986 to 2004) was searched for articles on studies that used US, CT, or both as diagnostic tests for appendicitis in children (26 studies, 9356 patients) or adults (31 studies, 4341 patients). Prospective and retrospective studies were included if they separately reported the rate of true-positive, true-negative, false-positive, and false-negative diagnoses of appendicitis from US and CT findings compared with the positive and negative rates of appendicitis at surgery or follow-up. Clinical variables, technical factors, and test performance were extracted. Three readers assessed the quality of studies. RESULTS: Pooled sensitivity and specificity for diagnosis of appendicitis in children were 88% (95% confidence interval [CI]: 86%, 90%) and 94% (95% CI: 92%, 95%), respectively, for US studies and 94% (95% CI: 92%, 97%) and 95% (95% CI: 94%, 97%), respectively, for CT studies. Pooled sensitivity and specificity for diagnosis in adults were 83% (95% CI: 78%, 87%) and 93% (95% CI: 90%, 96%), respectively, for US studies and 94% (95% CI: 92%, 95%) and 94% (95% CI: 94%, 96%), respectively, for CT studies. CONCLUSION: From the diagnostic performance perspective, CT had a significantly higher sensitivity than did US in studies of children and adults; from the safety perspective, however, one should consider the radiation associated with CT, especially in children.
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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 | 0.029 | 0.061 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.022 | 0.080 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".