Guideline-Recommended Care in Patients with CKD and Ischemic Cardiac Events vs. General Population: A Population-Based Study
Bibliographic record
Abstract
Background: Ischemic heart disease (IHD) is a leading cause of mortality in patients with chronic kidney disease (CKD). Despite the high burden, CKD patients remain underrepresented in trials guiding cardiac event management. Using provincial administrative health data, we compared the quality of care (guideline recommended medications and coronary revascularization procedures) for IHD in patients with CKD versus general population. Methods: Using the Alberta Kidney Disease Network database, we identified adults with CKD (aged ≥18) diagnosed with IHD between 2003 and 2019. IHD, STEMI, and NSTEMI were identified via ICD-10 codes from hospital discharges, physician claims, and ambulatory care files. Prescription fills within 6 months post-STEMI/NSTEMI and 12 months post-IHD were assessed in a subgroup diagnosed after January 2008 using Alberta’s Pharmaceutical Information Network (PIN). Receipt of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) within 6 months of STEMI/NSTEMI was assessed from hospital records, physician claims, and ACCS files. Trends across CKD stages were tested using logistic regression for binary outcomes and linear regression for continuous ones, with p-values <0.05 considered statistically significant. Results: Among 522, 961 participants, median age was 57.1 years (IQR 46.1-70.9) were included. Within 12 months of IHD diagnosis, the use of ACE inhibitors/angiotensin receptor blockers, statins and beta blockers declined with worsening CKD stage (p-trend <0.001), though patients with CKD were more likely to receive these medications than those with eGFR >60 ml/min/1.73m2. For example, statin use was 38.5% in patients with eGFR >60 ml/min/1.73m2, compared to 59.6% (eGFR 45-59) and 54.5% (eGFR 30-44). Within 6 months of a STEMI or NSTEMI the use of P2Y12 inhibitors, ACE inhibitors/ARBs, statins, beta blockers and coronary artery revascularization declined with lower eGFR (p-trend <0.001). Conclusion: Uptake of guideline based therapy remains suboptimal among patients with CKD, and is less common with worsening renal function. This work has implications for shaping cardiovascular care among patients with CKD. Funding: Government Support – Non-U.S.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".