Mortality among Heart Failure Patients in the Presence of Cachexia
Bibliographic record
Abstract
Highlights: Around 38.8% of heart failure patients with cachexia died during the 180-1,876-day follow-up period. Cachexia increases the risk of mortality in heart failure patients. Abstract: Despite the fact that obesity has long been recognized as a risk factor for cardiovascular disease, the mortality rate of heart failure (HF) patients with cachexia is still high. Several studies have been conducted to investigate the association between cachexia and mortality in HF patients. However, the research results vary, as do the diagnostic criteria employed to assess cachexia. This meta-analysis aimed to conclusively summarize the association between cachexia and mortality in HF patients. The data were obtained from prospective or retrospective cohort studies with full texts in English or Indonesian and keywords related to "cachexia," "heart failure," and/ or "mortality". Studies that did not assess mortality in HF patients with cachexia and had no full text accessible were omitted. A literature search was conducted through four databases (PubMed, Web of Science, Scopus, and SAGE Journals) using keywords, reference searches, and/ or other methods on April 2022 in accordance with the Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data from the selected studies were presented and analyzed using qualitative and quantitative synthesis methods. The Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias in the selected cohort studies. The qualitative synthesis contained nine studies, whereas the quantitative synthesis (meta-analysis) included six studies. Cachexia was found in 16.0% of the 4,697 patients studied. During the 180-1,876-day follow-up period, 33.0% of the patients died, with a mortality rate of 38.8% among the patients with cachexia. The pooled analysis revealed cachexia to be a significant predictor of mortality in HF patients (hazard ratio (HR)=3.84; 95% CI=2.28-6.45; p<0.00001), but with significant heterogeneity (p<0.00001; I2=88%). In conclusion, cachexia worsens HF prognosis.
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 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 | 0.001 |
| 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".