The Diagnostic Accuracy of Abdominal X-ray in Childhood Constipation: A Systematic Review of the Literature
Bibliographic record
Abstract
Background: Previous systematic reviews have found insufficient and conflicting evidence for an association between the clinical and radiographic diagnosis of functional constipation. Abdominal X-ray is frequently used for the diagnosis of functional constipation in clinical practice. The objective of this study was to evaluate the diagnostic accuracy of abdominal X-ray for the evaluation of functional constipation in children. Results: Three studies were included in the final qualitative analysis. They were heterogeneous in their study design, definition of constipation, and radiologic parameters used to evaluate the abdominal X-rays. Sensitivities ranged from 73–92%, specificities ranged from 26–92%, and diagnostic accuracies ranged from 78–90%. Methods: This study involved a systematic review of English literature published between 2012 and 2022 covering children 2–18 years of age with a diagnosis of functional constipation in whom abdominal X-ray was performed. The databases searched include Medline, Embase, and Scopus. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) guidelines were followed. PROSPERO ID: CRD42022301833. Conclusions: There is insufficient evidence to support the use of abdominal X-ray as part of the diagnostic workup of functional constipation. More methodologically rigorous studies are needed to determine the utility of abdominal X-ray in the evaluation of functional constipation. The diagnosis of functional constipation should be based on history and clinical findings.
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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 | 0.024 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".