iSTART-II: An Update on the i Support Therapy–Access to Rapid Treatment (iSTART) Approach for Patient-Centered Therapy in Mild-to-Moderate Ulcerative Colitis
Bibliographic record
Abstract
The i Support Therapy-Access to Rapid Treatment (iSTART) was an initiative to improve patient-centered management in mild-to-moderate ulcerative colitis (UC). Our aim was to update the iSTART recommendations in order to include fecal calprotectin (FC) in the monitoring of patients with UC and improve their management. Twelve physicians from nine countries worldwide attended a virtual international consensus meeting on 4 May 2022. Data from three systematic reviews were analyzed, and a new systematic review investigating all studies reporting measurement of FC at home was conducted. Based on literature evidence, statements were formulated, discussed, and approved by voting. Statements were considered approved if at least 75% of participants agreed with a proposed statement. Fourteen statements were approved. Based on this consensus, FC measurement should be routinely performed for monitoring patients with mild-to-moderate UC to identify disease relapses early and initiate an appropriate treatment. Further studies are needed to assess whether self-monitoring of FC is associated with better disease control and improved patients' quality of life.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".