Digitalis Investigation Group (DIG-BioLINCC)
Bibliographic record
Abstract
**Data Access NOTE**: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. **Objectives ** To determine the effect of increasing age on mortality, hospitalizations, and digoxin side effects in patients with heart failure (HF), and to determine whether the effect of digoxin on clinical outcomes varies as a function of age. **Background ** The incidence and prevalence of HF increase with advancing age, but there are limited data on the clinical course and response to specific interventions in elderly patients with HF. **Participants ** A total of 302 centers in the United States and Canada enrolled 7,788 patients between February 1991 and September 1993. **Design ** The Digitalis Investigation Group (DIG) study was a prospective, randomized clinical trial involving 7,788 patients with HF randomized to digoxin or placebo and followed for an average of 37 months. Interactions between age and the following clinical outcomes were examined: total mortality, all-cause hospitalizations, HF hospitalizations, the composite of HF death or HF hospitalizations, hospitalization for suspected digoxin toxicity and withdrawal from therapy because of side effects. **Conclusions ** Increasing age is associated with progressively worse clinical outcomes in patients with HF. However, the beneficial effects of digoxin in reducing all-cause admissions, HF admissions, and HF death or hospitalization are independent of age. Thus, digoxin remains a useful agent to the adjunctive treatment of HF due to impaired left ventricular systolic function in patients of all ages.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.437 | 0.320 |
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".