Association of non-alcoholic fatty liver disease and all-cause mortality in hospitalized cardiovascular disease patients
Bibliographic record
Abstract
BACKGROUND: Controversy remains concerning the association of the all-cause mortality risk of hospitalized cardiovascular disease (CVD) patients with non-alcoholic fatty liver disease (NAFLD). This study investigated the risks of all-cause mortality among hospitalized CVD patients with NAFLD. METHODS: We used related keywords to search for studies in 3 electronic databases: PubMed, EMBASE, and Cochrane Library. All eligible studies published up to April 2020 were reviewed. The findings of those studies reporting the mortality outcomes of hospitalized CVD patients with and without NAFLD were examined, and the various study results were pooled and analyzed using a random-effects model. A quality assessment using the Newcastle-Ottawa scale was performed on the studies selected for inclusion in a meta-analysis. RESULTS: A total of 2135 studies were found, of which 3 were included in this meta-analysis. All studies were considered good quality. The mean age of the patients in the analysis was 73 years, and about half of them were men. The comorbidities reported were hypertension, diabetes mellitus, and dyslipidemia. The results showed that hospitalized CVD patients with NAFLD were at a significantly higher risk of all-cause mortality than non-NAFLD patients (adjusted hazard ratio of 2.08 [95% confidence interval, 1.56-2.59], P < .001). The included studies showed low heterogeneity (I2 = 0.0%, P = .473), and Begg and Egger tests revealed no apparent publication bias (P = .327 and P = .682, respectively). CONCLUSIONS: Hospitalized CVD patients with NAFLD were at a higher risk of all-cause mortality than those without NAFLD. More studies that further explore this association are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".