P138 Platelet-to-lymphocyte ratio index: a reliable tool for non-invasive assessment of endoscopic activity in small bowel Crohn’s Disease
Bibliographic record
Abstract
Abstract Background The platelet-to-lymphocyte ratio (PLR) index has been a recent focus of investigation as a reliable marker of inflammation. This score was recently shown to have a good accuracy upon predicting endoscopic remission in patients with colonic Crohn’s Disease (CD). We aimed to assess the discriminative power of PLR index in patients with isolated small bowel CD. Methods Single center study of consecutive patients with isolated small bowel CD (L1 ± L4 disease according to Montreal classification) who underwent small bowel capsule endoscopy (SBCE) for assessment of endoscopic activity between January 2019 and December 2020. Only complete SBCEs were considered. CD endoscopic activity was classified according to the Lewis score (LS) value. Complete blood count, C-reactive protein and fecal calprotectin values were collected within 1 month of SBCE. Results Final sample included 49 patients, 35 (71.4%) of them females, with a mean age of 35.1±11.8 years. SBCE reported mucosal healing (LS<135) in 30.6% of the patients; mild activity (135≤LS<790) in 42.9% and moderate-to-severe activity (LS≥790) in 26.5% of the patients. PLR index positive correlation with LS was significant and moderate (k=0.597; p<0.001). This correlation was stronger than the one seen between fecal calprotectin (k=0.525; p=0.001) or C-reactive protein (k=0.321; p=0.029) and the LS score. In particular, PLR index presented an excellent accuracy for predicting patients with a moderate-to-severe endoscopic activity (AUC=0.908; 95%CI=0.816–0.999; p<0.001), with an optimal cut-off of PLR above 157 (sensitivity 92.3%; specificity 82.9%). The accuracy for prediction of mucosal healing was good (AUC=0.743; 95%CI=0.600–0.887; p=0.007), with an optimal cut-off of PLR below 126 (sensitivity 66.7%; specificity 80.0%). Conclusion PLR index demonstrated an excellent acuity for predicting patients with moderate to severe disease in small bowel CD. Moreover, it also demonstrated good acuity for predicting mucosal healing on this set of patients. These results come from a significant correlation of PLR index with endoscopic activity in small bowel CD. Our findings establish this index as a promising and easy-to-apply tool for non-invasive and regular follow-up of patients with small bowel CD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".