Development and Validation of a Remote Monitoring Tool for Assessment of Mild, Moderate, and Severe Infections in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Immunomodulators and biologics are cornerstones in the management of inflammatory bowel disease [IBD], but are associated with increased risk of infections. Post-marketing surveillance registries are pivotal to assess this risk, yet mainly focus on severe infections. Data on the prevalence of mild and moderate infections are scarce. We developed and validated a remote monitoring tool for real-world assessment of infections in IBD patients. METHODS: A 7-item Patient-Reported Infections Questionnaire [PRIQ] covering 15 infection categories was developed with a 3-month recall period. Infection severity was defined as mild [self-limiting or topical treatment], moderate [oral antibiotics, antivirals, or antifungals], or severe [hospitalisation or intravenous treatment]. Comprehensiveness and comprehensibility were ascertained through cognitive interviewing of 36 IBD outpatients. After implementation in the telemedicine platform myIBDcoach, a prospective, multicentre cohort study was performed between June 2020 and June 2021 in 584 patients, to assess diagnostic accuracy. Events were cross-checked with general practitioner and pharmacy data [gold standard]. Agreement was evaluated using linear-weighted kappa with cluster-bootstrapping to account for within-patient level correlation. RESULTS: Patient understanding was good and interviews did not result in reduction of PRIQ items. During validation, 584 IBD patients {57.8% female, mean age 48.6 (standard deviaton [SD]: 14.8), disease duration 12.6 years [SD: 10.9]} completed 1386 periodic assessments, reporting 1626 events. Linear-weighted kappa for agreement between PRIQ and gold standard was 0.92 (95% confidence interval [CI] 0.89-0.94). Sensitivity and specificity for infection [yes/no] were 93.9% [95% CI 91.8-96.0] and 98.5% [95% CI 97.5-99.4], respectively. CONCLUSIONS: The PRIQ is a valid and accurate remote monitoring tool to assess infections in IBD patients, providing means to personalise medicine based on adequate benefit-risk assessments.
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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 | 0.016 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".