Health Resource Implications of Heart Failure Hospitalizations in Younger Patients Compared With Older Patients
Bibliographic record
Abstract
Although heart failure (HF) is less common in individuals <50, recent studies have demonstrated a substantial increase in the frequency of young HF over the past 2 decades. 1,2 This has been attributed to the increasing prevalence of obesity, type 2 diabetes mellitus, and hypertension, and better treatments for congenital heart disease, coronary artery disease, dyslipidemia, or hypertension. 2 Recent studies reported decreasing mortality rates in older patients with HF over the past 2 decades, but no appreciable changes in the standardized mortality rate for HF patients <50 years since the turn of the millennium. 1,2However, little is known about hospital resource use by younger versus older patients with HF, and this has major implications for future resource planning.In this retrospective cohort study we examined outcomes for all patients >20 years hospitalized with a primary diagnosis of heart failure in Canada between April 2004 and December 2013.Details on the databases used, International Classification of Diseases, 10th Revision case definitions for HF and all comorbidities, and analytic methods have been published already. 3 This study was approved by the University of Alberta Health Research Ethics Board with waiver of informed consent because we were using deidentified data.In this secondary analysis, we compared 3 outcomes between patients ≤50 years versus those >50 years at the time of their index hospitalization: index hospitalization mortality and, in those that survived to be discharged, length of stay and 30day readmission rates.Adjusted analyses were done using generalized linear mixed models and including baseline covariates recommended by the Centers for Medicare & Medicaid Services (www.cms.gov) for each of the outcomes, as well as hospital type, attending physician specialty, calendar year, number of hospitalizations in the prior 6 months, day of discharge (for the readmission analysis), and 2 random-effects variables to account for clustering effects of province and of hospital.Of the 241 533 patients admitted with a primary diagnosis of HF (mean, 77.4 years, 50.0%male), 7373 (3.1%) were ≤50 (Table ).Younger patients exhibited substantially lower mortality during the index hospitalization (3.3% versus 10.4%, P<0.0001), which was maintained (adjusted odds ratio, 0.36; 95% confidence interval, 0.31-0.41)after adjustment.Of those who survived to discharge (n=217 039), younger patients also had lower 30-day readmissions for any cause (14.1% versus 18.3%, P<0.0001; adjusted odds ratio, 0.82; 95% confidence interval, 0.77-0.88)or for HF (4.7% versus 6.8%, P<0.0001; adjusted odds ratio, 0.74; 95% confidence interval, 0.66-0.83).Although younger patients had shorter length of stay (7.5 days versus 7.8 days, P<0.0001), the difference was not substantial and the association flipped after adjustment for baseline variables: adjusted mean, 8.4 days versus 8.2 days (P=0.002).Although prior studies of young patients with HF have focused on their lower mortality risk, their lower comorbidity burdens, and their increased likelihood of
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".