Predictors of mortality, strategies to reduce readmission, and economic impact of acute decompensated heart failure: Results of the Vellore Heart Failure Registry
Bibliographic record
Abstract
AIM: Heart failure is a global problem that is increasing in prevalence. We undertook the initiative to compile the Vellore Heart Failure Registry (VHFR) to assess the clinical profile, mortality, risk factors and economic burden of heart failure by conducting a prospective, observational, hospital-based cohort study in Vellore, Tamil Nadu. METHODS AND RESULTS: This study was a prospective observational cohort study conducted at the Christian Medical College and Hospital, Vellore, between January 2014 and December 2016. A total of 572 patients who satisfied the Boston criteria for "definite heart failure" were included and the primary outcome was all-cause mortality. The median duration of hospital stay was eight days and the in-hospital, one, three and six month mortalities were 13.25%, 27.3%, 32.53% and 38.15%, respectively. The median duration of survival was 921 days. Readmission for heart failure constituted 42%, and the most common cause of decompensation was an infection(31.5%). The presence of cyanosis at admission, history of previous stroke or transient ischemic attack, and American College of Cardiology (ACC)/American Heart Association (AHA) stage D at the time of discharge were independently associated with mortality at six months. The median total direct cost of admission was INR 84,881.00 ($ 1232.34) CONCLUSION: The VHFR cohort had younger, more diabetic, and fewer hypertensive subjects than most cohorts. Admission for heart failure is a catastrophic health expenditure. Attempts should be made to ensure a reduction in readmission rates by targeting goal-directed therapy. As the most common cause of acute decompensation is pneumonia, vaccinating all patients before discharge may also help in this regard.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".