Identifying opportunities for hepatic encephalopathy self-management: A mixed methods systematic review and synthesis
Bibliographic record
Abstract
Background: Hepatic encephalopathy (HE) in cirrhosis is an extremely challenging complication for patients and care partners. To identify potentially modifiable factors to enhance HE self-management strategies, we conducted a synthesis of quantitative and qualitative research about real-world HE behaviours, knowledge, and experiences. Methods: Using the EPPI-Centre's mixed methods synthesis procedure, a systematic literature search in five databases was completed; methods of selected articles underwent critical appraisal followed by descriptive analysis and coded line-by-line of content. Through refutational translation, the findings from the quantitative and qualitative syntheses were juxtaposed to highlight congruencies, incongruencies, or gaps. These findings informed generation of cross-analytical themes that were transformed into action statements. Results: = 17) generated four themes (patients had low awareness of HE and low treatment adherence rates, physicians had a non-uniform approach to non-pharmaceutical therapies). Meta-aggregation of qualitative data from six articles yielded three themes (patients and care partners had low levels of HE awareness, were unfamiliar with HE self-management, and were adherent to treatments). Comparison of findings revealed three congruencies, two gaps, and one incongruency. The combined synthesis yielded two self-management themes: universal patient-oriented cirrhosis HE education and ensuring each health care encounter systematically addresses HE to guarantee health care is continuously modified to meet their needs. Conclusions: By drawing on elements of Bloom's Taxonomy and distributed knowledge networks, deliberate patient-oriented HE messaging at all health care encounters is greatly needed to improve health outcomes and reduce care burdens related to HE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".