A244 DEVELOPING AND ASSESSING THE EFFECTIVENESS OF A REMOTE MONITORING PROTOCOL FOR ULCERATIVE COLITIS PATIENTS - ULCERATIVE COLITIS CLINICAL OUTREACH (UCCO)
Bibliographic record
Abstract
Abstract Background Ulcerative colitis (UC) is a chronic inflammatory bowel disease which requires regular gastroenterologist monitoring. Outpatient monitoring programs to date have focused on clinical scores alone, leaving patients with asymptomatic inflammation susceptible to undertreatment despite increased risk of flares and colorectal cancer. The University of Alberta IBD Unit developed and piloted an outreach and remote monitoring protocol for UC patients including clinical and biochemical variables. We assessed the effectiveness of this protocol at improving UC care. Aims This study aimed to develop a clinical outreach and remote patient monitoring protocol for UC patients and assess the impact this protocol had on disease management. Methods Biologic naïve adult UC patients who had not been reviewed by their gastroenterologist in at least six months were contacted by phone and mailed monitoring kits with Partial Mayo, Sutherland Index, and medication adherence questionnaires and a requisition for blood work and fecal calprotectin (FCP). Results were compiled and sent to each patient’s gastroenterologist. Participating gastroenterologists completed a survey about the perceived utility of the protocol and intended UC management changes. Results 85 patients completed the protocol. 86.4% of physician surveys rated the protocol as helpful to clinicians. UC management was changed in 55.6% of cases, with 82.2% of changes being management escalations. Six patients had active flares and 17 patients with asymptomatic inflammation were identified. Endoscopy was completed for 23 patients, with active disease observed in 78.2% of cases. Six patients started biologic therapies based on the protocol and endoscopic findings. UC management escalations were significantly predicted by FCP and Sutherland Index scores on logistic regression analysis. Conclusions This protocol had a meaningful impact on UC management and identified patients with active disease in both the presence and absence of clinical remission. Remote outpatient monitoring in UC should include collection of both FCP and clinical scores every six months to improve UC management. Funding Agencies None
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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 | 0.058 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".