P178 Role of prognostic nutritional index in predicting severity in active ulcerative colitis
Bibliographic record
Abstract
A large proportion of patients with IBD shows an impairment of nutritional status. Prognostic nutritional index (PNI) has been described as predictor of colectomy and morbidity/mortality during surgery for ulcerative colitis (UC). The aim of the present study was to investigate the correlation between PNI and indices of severity in active UC and the association of PNI with the need for medical or surgical therapy. Consecutive UC patients, referring to our IBD unit, underwent full colonoscopy to assess Mayo endoscopic subscore (MES), Montreal classification (MC) and full Mayo score (FMS). Active patients were defined as FMS >2. Blood exams including C-reactive protein (CRP), serum albumin and complete blood count were analysed. PNI was calculated according to formula: 10 × serum albumin (g/dl) + 0.005 × total lymphocyte count. Patients with previous (last 3 months) use of steroids, immunosuppressants, biological therapy or surgery, use (last 2 weeks) of topical therapy, any ongoing infectious, oncological, metabolic disease in the last 6 months were excluded. Patients were followed up for 30 days and the possible initiation of steroids, biological and immunosuppressive therapy or colectomy was assessed. Ninety-five controls were enrolled among patients referring for IBS symptoms. From 2016 to 2018, 95 active UC patients (47 females) were enrolled. UC patients displayed a median PNI (35.43, IQR 29.91–38.81) significantly lower than controls (40.62, IQR 38.11–41.51). Median PNI values discriminated patients according to disease severity (FMS mild 3−6: PNI 36.72, moderate 4–10: 35.67, severe >10: 29.48, p = 0.001; MES 1: PNI 39.12, 2: 36.44, 3: 31.74, p = 0.001; MC E1: PNI 37.81, E2: 36.21, E3: 32.77, p < 0.001). Multiple logistic regression analysis showed that lower PNI values were associated with the need for steroids/biological therapy within 30 days (OR 1.3), irrespective of age, sex, BMI, disease extent, clinical/endoscopic severity. According to ROC curves, a PNI cut-off (38.06) was identified to discriminate patients from controls (AUC 0.835, sensitivity 78%, specificity 28%) and divide patients into 2 groups. At 30 day follow-up, 53 patients with PNI < 38.06 and 7 with PNI >38.06 initiated steroids/biologics; PNI values <38.06 were associated with an increased risk of steroids/biological therapy (RR = 2.06, CI 1.39–3.05). PNI appears to be a novel and promising biomarker associated with disease activity. Our findings show that PNI might be considered a reliable predictor of steroids or biological therapy in active UC.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".