Characterizing diabetic cardiomyopathy: baseline results from the ARISE-HF trial
Bibliographic record
Abstract
BACKGROUND: Diabetic cardiomyopathy (DbCM) is a form of Stage B heart failure (HF) at high risk for progression to overt disease. Using baseline characteristics of study participants from the Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure (ARISE-HF) Trial we sought to characterize clinical characteristics of individuals with findings consistent with DbCM. METHODS: Among study participants meeting inclusion criteria, clinical characteristics, laboratory testing, imaging, Kansas City Cardiomyopathy Questionnaire (KCCQ), Physical Activity Scale of the Elderly (PASE) and cardiopulmonary exercise testing (CPET) results were tabulated. Cluster phenogroups were identified. RESULTS: Among 691 study participants (mean age 67.4 years; 50% were female), mean duration of type 2 diabetes mellitus (T2DM) was 14.5 years. The median (Q1, Q3) N-terminal pro-B type natriuretic peptide and high sensitivity cardiac troponin T were 71 (35, 135) ng/L and 9 [6, 12] ng/L. The most common echocardiographic abnormalities were reduced global longitudinal strain in 25.3% and impaired diastolic relaxation in 17.7%. Despite rather well-preserved KCCQ scores the average PASE score was markedly impaired at 155 accompanied by an average maximal oxygen consumption of 15.7 mL/Kg/minute on CPET. In K-means clustering, 4 phenogroups were identified including a higher-risk group with more advanced age, greater elevation of cardiac biomarkers, and more prevalent evidence for diastolic dysfunction and left ventricular hypertrophy. CONCLUSIONS: Baseline data from the ARISE-HF Trial provide clinical characterization of individuals with T2DM and features of stage B HF, and may help clarify the diagnosis of DbCM. TRIAL REGISTRATION: ARISE-HF, NCT04083339.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".