Targets to improve quality of care for patients with hepatic encephalopathy: data from a multi‐centre cohort
Bibliographic record
Abstract
BACKGROUND: Hepatic encephalopathy (HE) can adversely affect outcomes in both in-patients and out-patients with cirrhosis. AIM: To define targets for improving quality of care in HE management in the multi-centre North American Consortium for End-Stage Liver Disease (NACSELD) cohort. METHOD: NACSELD in-patient cohort was analysed for (a) medication-associated precipitants, (b) aspiration pneumonia development, (c) HE medication changes, and (d) 90-day HE recurrence/readmissions. Comparisons were made between patients on no-therapy, lactulose only, rifaximin only or both. Ninety-day HE-readmission analysis was adjusted for MELD score. RESULTS: Two thousand eight hundred and ten patients (1102 no-therapy, 659 lactulose, 154 rifaximin, 859 both) were included. HE on admission, and HE rates during hospitalisation were highest in those on lactulose only or dual therapy compared to no-therapy or rifaximin only (P < 0.001). Medications were the most prevalent precipitants (32%; 21% lactulose over/underuse, 5% benzodiazepines, 4% opioids, 1% rifaximin underuse, 1% hypnotics). Patients with medication-associated precipitants had a better prognosis compared to other precipitants. A total of 23% (n = 217) reached grade 3/4 HE, of which 16% developed HE-related aspiration pneumonia. Two thousand four hundred and twenty patients were discharged alive without liver transplant (790 no-therapy, 639 lactulose, 136 rifaximin, 855 both); 12.5% (n = 99) of no-therapy patients did not receive a discharge HE therapy renewal. Ninety-day HE-related readmissions were seen in 16% of patients (9% no-therapy, 9% rifaximin only, lactulose only 18%, dual 21%, <0.001), which persisted despite MELD adjustment (P = 0.009). CONCLUSION: Several targets to improve HE management were identified in a large cohort of hospitalised cirrhotic patients. Interventions to decrease medication-precipitated HE, prevention of aspiration pneumonia, and optimisation of HE medications are warranted.
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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 | 0.000 | 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 | 0.000 | 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".