Meta‐analysis: Intestinal ultrasound to evaluate colonic contents and constipation
Bibliographic record
Abstract
BACKGROUND: Constipation can be diagnosed clinically using the Rome criteria. Ultrasound (US), which lacks the radiation exposure of conventional X-ray, holds promise as a non-invasive tool to evaluate colonic contents and constipation. AIM: To examine the role of US in the assessment of constipation. METHODS: We performed a systematic search of Embase (OVID, 1984), Medline (Ovid, 1946), Cochrane Central, ClinicalTrials.gov and Australia New Zealand Clinical Trials Registry from database inception to 26 January 2024 according to PRISMA guidelines and prospectively registered with PROSPERO. All studies using US to assess constipation or colonic contents in either adults or children were included. Rectal diameter measurements were pooled in meta-analysis. Risk of bias was assessed using the Newcastle Ottawa Scales and Joanna Briggs Institute checklists. RESULTS: Of 12,232 studies screened, 51 articles (6084 patients; 3422 children) describing US to assess symptoms in patients with constipation were included. Most studies used Rome criteria to diagnose constipation. Rectal diameter was associated with clinical constipation in 29 paediatric studies (3331 patients). Meta-analysis showed the mean rectal diameter of constipated patients was significantly higher than controls (mean difference 12 mm, 95% confidence intervals (CI): 6.48, 17.93, p < 0.0001, n = 16 studies). Other features of constipation on US included posterior acoustic shadowing and echogenicity of luminal contents. CONCLUSION: US is an appealing imaging modality to assess luminal contents and constipation. Further well-designed studies are required to validate US metrics that accurately identify constipation.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.045 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".