P134 Point of care ultrasound accurately distinguishes inflammatory from non inflammatory disease in patients presenting with abdominal pain and diarrhea
Bibliographic record
Abstract
Background: There is a considerable overlap between symptoms of irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). It is important to have access to non-invasive, safe, low cost diagnostic tools to differentiate IBD from functional abdominal symptoms such as IBS, and avoid unnecessary invasive investigations including endoscopy. Point of care ultrasound (POCUS) of the bowel is not widely accessible in North America, but is routinely used in Europe. The aim of this study was to evaluate the accuracy of POCUS in the detection of luminal inflammation compared to gold standard ileocolonscopy in patients presenting with undifferentiated lower gastrointestinal symptoms. Methods: A prospective, single- center study of consecutive patients presenting to the GI clinic with symptoms high risk for IBD were evaluated to differentiate IBD from IBS. POCUS was performed, clinical data recorded and C-reactive protein measured prior to ileocolonoscopy, which served as the gold standard. Sensitivity, specificity, positive predictive value and negative predictive value were calculated for POCUS. Results: Eighty-six patients with undifferentiated symptoms of diarrhea (76.7%), abdominal pain (62.8%) and weight loss (18.6%) were evaluated. Nocturnal symptoms (15.1%) and incontinence (11.6%) were infrequent (Table 1). Ileocolonoscopy was negative in 72 patients confirming IBS, 2 patients had diverticulosis, while 12 revealed findings of active endoscopic disease consistent with IBD, confirmed on pathology, 11 with CD and 1 with UC, as well as microscopic colitis (N=8), diverticulosis (N=1), ischemic colitis (N=2) and one solitary rectal ulcer. The overall sensitivity, specificity, PPV and NPV of POCUS were 83.0%, 100%, 100%, and 97.37%, respectively. In cases where POCUS was positive, POCUS predicted the severity of inflammation as seen on ileocolonscopy accurately with correlate findings of 90% (9/10 cases accurately predicted severity). The accuracy of POCUS for predicting IBD was much better than CRP, as the sensitivity of CRP was only 37.5%, specificity 76.2%. Wait time for endoscopy for patients with a positive POCUS was shorter with a median of 3.5 weeks, compared to 4 weeks for those with a negative POCUS. Table 1. Demographics Table 2. Sensitivity, specificity, accuracy, PPV and NPV of POCUS relative to ileocolonoscopy Conclusions: Bedside POCUS is a useful triage tool, better than CRP in disease prediction, helpful to accurately detect the presence and severity of inflammation in the bowel and thus differentiate IBD from IBS. The detection of ileal disease was more accurate compared to colonic disease and future studies should be completed with addition of fecal calprotectin to optimize detection rates and overall accuracy.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".