Self‐management programmes for cirrhosis: A systematic review
Bibliographic record
Abstract
BACKGROUND AND AIMS: Liver cirrhosis severely decreases patients' quality of life. Since self-management programmes have improved quality of life and reduce hospital admissions in other chronic diseases, they have been suggested to decrease liver cirrhosis burden. METHODS: We performed a systematic review and meta-analysis to evaluate the clinical impact of self-management programmes in patients with liver cirrhosis, which followed the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Primary outcomes include health-related quality of life (HRQOL) and hospitalisation. We searched MEDLINE, CENTRAL, Embase, CINAHL, PsycINFO and two trial registers to July 2017. RESULTS: We identified four randomised trials (299 patients) all rated at a high risk of bias. No difference was demonstrated for HRQOL (standardised mean difference -0.01, 95% CI: -0.48 to 0.46) and hospitalisation days (incidence rate ratio 1.6, 95% CI: 0.5-4.8). For secondary outcomes, one study found a statistically significant improvement in patient knowledge (mean difference (MD) 3.68, 95% CI: 2.11-5.25) while another study found an increase in model for end-stage liver disease scores (MD 2.8, 95% CI: 0.6-4.9) in the self-management group. No statistical difference was found for the other secondary outcomes (self-efficacy, psychological health outcomes, healthcare utilisation, mortality). Overall, the quality of the evidence was low. The content of self-management programmes varied across studies with little overlap. CONCLUSIONS: The current literature indicates that there is no evidence of a benefit of self-management programmes for people with cirrhosis. RELEVANCE TO CLINICAL PRACTICE: Practitioners should use self-management programmes with caution when delivering care to patients living with cirrhosis. Further research is required to determine what are the key features in a complex intervention like self-management. This review offers a preliminary framework for clinicians to develop a new self-management programme with key features of effective self-management interventions from established models.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".