Health-related quality of life in inflammatory bowel disease: a comparison of patients receiving nurse-led versus conventional follow-up care
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD), consisting of Crohn's disease (CD) and ulcerative colitis (UC), is a chronic disorder with a considerable negative impact on health-related quality of life (HRQoL). During the past decade, IBD nurse specialists have been increasingly involved in follow-up care of IBD outpatients, in a consultative and coordinating role, closely cooperating with gastroenterologists. Whether patients' HRQoL differs between nurses' follow-up care (NF) and conventional follow-up care (CF) has not been widely researched and the aim of this study was to compare two different follow-up regimes with respect to patients' HRQoL. METHODS: This cross-sectional, multicenter study involved seven centers; five organized as CF, two as NF. RESULTS: A total of 304 patients aged 18-80 years, 174 females and 130 males, were included, of whom 140 received care under the NF model and 164 under the CF model. Participants in the NF group had a statistically significant higher median total score on the Inflammatory Bowel Disease Questionnaire (IBDQ) (p-value < .001). This pattern could also be seen in the sub-scores of the different IBDQ domains. Despite a trend of higher IBDQ score in all domains in the NF model, the overall result in our study did not reach the limit of 16 points, defined as clinically significant. A higher proportion of NF patients had IBDQ scores defined as remission, as well as a statistically significant higher frequency of outpatient check-ups during a two-year follow-up period. CONCLUSIONS: Nurse-led models are not inferior to conventional models with regards to patient reported HRQoL except in the social domain where the model showed to be clinically significant better. Further studies are needed to advance efforts to implement these models and increase access to IBD care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".