Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The prevalence, prognostic import, and impact of renal insufficiency on the benefits of ACE inhibitors and beta-blockers in community-dwelling patients with heart failure are uncertain. METHODS AND RESULTS: We analyzed data from a prospective cohort of 754 patients with heart failure who had ejection fraction, serum creatinine, and weight measured at baseline. Median age was 69 years, and 43% had an ejection fraction > or =35%. By the Cockcroft-Gault equation, 118 patients (16%) had creatinine clearances < or =30 mL/min and 301 (40%) had creatinine clearances between 30 and 59 mL/min. During follow-up (median 926 days), 385 patients (37%) died. Even after adjustment for all other prognostic factors, survival was significantly associated with renal function (P=0.002) in patients with either systolic or diastolic dysfunction; patients exhibited a 1% increase in mortality for each 1-mL/min decrease in creatinine clearance. The associations with 1-year mortality reductions were similar for ACE inhibitors (OR 0.46 [95% CI 0.26 to 0.82] versus OR 0.28 [95% CI 0.11 to 0.70]) and beta-blockers (OR 0.40 [95% CI 0.23 to 0.70] versus OR 0.41 [95% CI 0.19 to 0.85]) in patients with creatinine clearances <60 mL/min versus > or =60 mL/min, although these drugs were used less frequently in patients with renal insufficiency. CONCLUSIONS: Renal insufficiency is more prevalent in patients with heart failure than previously reported and is an independent prognostic factor in diastolic and systolic dysfunction. ACE inhibitors and beta-blockers were associated with similar reductions in mortality in patients with and without renal insufficiency.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it