Trends in the Burden of Ischemic Heart Disease among Patients with CKD in Alberta
Bibliographic record
Abstract
Background: Ischemic heart disease (IHD) is a leading cause of mortality in patients with chronic kidney disease (CKD). The last decades have witnessed significant improvements in both IHD and CKD care. Information on the burden of IHD in the Canadian CKD population is limited. Methods: Using the Alberta Kidney Disease Network database, we created a cohort with CKD (aged 18 years and above) who received a diagnosis of IHD between 2003 and 2019. CKD was defined based on standard methods. Case definitions for IHD, STEMI, and NSTEMI were determined using ICD-10 codes and obtained from hospital discharge records, physician billing claims, and ambulatory care classification system (ACCS) files. The date of diagnosis of IHD was the date of inpatient hospital separation or the physician visit, whichever came first. Univariate least squares regression analysis and the negative binomial model were used to evaluate the trend in the adjusted prevalence and incident rates for the conditions of interest. The rates were standardized by age group and sex based on the 2011 Canadian population. STATA v18 was used in the analysis and p < 0.05 as the threshold for statistical significance. Results: The age and sex standardized prevalence of IHD increased across all stages of kidney function. Compared to patients with an eGFR ≥ 60 ml/min, the rate of change in the prevalence of IHD was higher in patients with an eGFR 45-59 ml/min, with an annual rate of change of 0.86 (95% CI: 0.66 - 1.05; test for interaction p <0.001). The incidence of STEMI decreased across all eGFRs from 2003 to 2019 except for patients with an eGFR 45-59 ml/min/1.73m2 (incidence risk ratio (IRR) of 0.93 (CI 95% 0.87, 1.00). The incidence of NSTEMI decreased across all eGFRs from 2003 to 2019 except for patients with an eGFR <15 ml/min/1.73m2 (IRR: 0.96; CI 95%: 0.91, 1.02). Conclusion: Between 2003 and 2019, the prevalence of IHD increased across all stages of CKD, and there was a concomitant decreasing trend in the incidence of the acute forms of IHD (STEMI and NSTEMI). This may reflect increasing longevity of patients with IHD and CKD in Alberta between 2003 and 2019, due to improvements in their care. Future studies should evaluate the quality of care received by patients with IHD and CKD and relationships to adverse clinical outcomes including hospitalizations, recurrent events and mortality. Funding: Private Foundation Support
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".