Impact of computed tomography of the abdomen on clinical outcomes in patients with acute right lower quadrant pain: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Clinical evaluation alone is still considered adequate by many clinicians who treat patients with appendicitis. The impact of computed tomography (CT) on clinical outcomes remains unclear, and there is no consensus regarding the appropriate use of CT in these patients. We sought to evaluate the impact of abdominal CT on the clinical outcomes of patients presenting with suspected appendicitis. METHODS: We conducted a systematic review of the literature to identify studies that examined clinical outcomes related to the use of abdominal CT in the diagnosis of acute appendicitis. Inclusion criteria were studies of adult patients with suspected appendicitis that evaluated the impact of abdominal CT on negative appendectomy rates, perforation rates or time to surgery. Two independent investigators reviewed all titles and abstracts and extracted data from 28 full-text articles. Statistical analysis was conducted using Review Manager 5.0.10 software. RESULTS: The negative appendectomy rate was 8.7% when using CT compared with 16.7% when using clinical evaluation alone (p < 0.001). There was also a significantly lower negative appendectomy rate during the CT era compared with the pre-CT era (10.0% v. 21.5%, p < 0.001). Time to surgery was evaluated in 10 of the 28 studies, 5 of which demonstrated a significant increase in the time to surgery with the use of CT. Appendiceal perforation rates were unchanged by the use of CT (23.4% in the CT group v. 16.7% in the clinical evaluation group, p = 0.15). Similarly, the perforation rate during the CT era was not significantly different than that during the pre-CT era (20.0% v. 19.6%, p = 0.74). CONCLUSION: This meta-analysis supports the hypothesis that the use of preoperative abdominal CT is associated with lower negative appendectomy rates. The use of CT in the absence of an expedited imaging protocol may delay surgery, but this delay is not associated with increased appendiceal perforation rates. Routine CT in all patients presenting with suspected appendicitis could reduce the rate of unnecessary surgery without increasing morbidity.
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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.040 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".