Optimal Medical Therapy Attainment by Dialysis Status in the ISCHEMIA-CKD Trial
Bibliographic record
Abstract
Background: The efficacy of an aggressive multiple risk factor intervention approach - optimal medical therapy (OMT) - to reduce major adverse cardiovascular events in patients with CKD has not been tested. Objective: to examine OMT goal attainment in patients with CKD on dialysis (CKD-D) and non-dialysis CKD (CKD-ND) in the ISCHEMIA-CKD trial. Methods: OMT was recommended to all participants in ISCHEMIA-CKD. Longitudinal trajectories of individual OMT components (smoking cessation, systolic blood pressure (SBP) <140 mmHg, low density lipoprotein (LDL) cholesterol <70 mg/dL, high-intensity statin use, and aspirin use) were modeled over study follow-up. Covariateadjusted percentage point difference in each OMT goal achieved at 24 months between CKD-D and CKD-ND groups (% difference [95% credible interval (CrI)]) was estimated. Results: There were 415 CKD-D and 362 CKD-ND patients at baseline. CKD-D were younger (61 v 67 yrs, p<0.001) and less often diabetic (53% v 62%, p=0.023). CKD-D patients were 7.9 % (0.7%, 14.8%) more likely than CKD-ND to attain the SBP goal at 24 months (Figure). CKD-D patients were 22.7% (-33.3%, -11.4%) less likely to receive high-intensity statins. There was a steady and similar increase in proportional achievement of OMT during follow up. Conclusions: OMT improved over time in advanced CKD-ND and CKD-D. CKD-D achieved the SBP goal more than CKD-ND, yet CKD-D were less likely to be treated with high-intensity statin. Future studies should explore systemic and patient-related barriers to attainment of OMT in this high-risk cohort.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".