EFFECT OF SEVERITY AND ETIOLOGY OF CHRONIC KIDNEY DISEASE IN PATIENTS WITH HEART FAILURE WITH MILDLY REDUCED EJECTION FRACTION
Bibliographic record
Abstract
This study explores the impact of chronic kidney disease (CKD) severity and etiology on patients with heart failure with mildly reduced ejection fraction (HFmrEF). Understanding these relationships is crucial for optimizing management strategies and improving patient outcomes. Methods: A cross-sectional study was conducted involving 550 patients diagnosed with HFmrEF. Patients were categorized based on CKD severity (stages 1 to 5) and etiology (diabetic nephropathy, hypertensive nephrosclerosis, glomerulonephritis, and others). Data on demographics, clinical characteristics, laboratory findings, and echocardiographic parameters were collected and analyzed. Results: Data were collected from 550 patients according to the study's criteria. The mean age of the patients was 62.5 ± 10.8 years. Of 550, 320 (58.2%) were male, and 230 (41.8%) were female. According to the NYHA classification, 40 (7.3%) belong to Class I, 290 (52.7%) to Class II, 200 (36.4%) to Class III, and 20 (3.6%) to Class IV. Advanced CKD stage (OR 2.5, 95% CI 1.6-3.8), diabetic nephropathy (OR 1.8, 95% CI 1.1-3.0), and lower eGFR (OR 2.2, 95% CI 1.5-3.2) were all associated with increased risk of mortality and hospitalizations. Conclusions: It is concluded that the severity and etiology of chronic kidney disease significantly impact the outcomes of patients with heart failure with mildly reduced ejection fraction. Advanced CKD stages and diabetic nephropathy are associated with higher mortality rates and more frequent hospitalizations.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".