Association Between CKD Progression and Heart Failure: A Retrospective Cohort Study
Bibliographic record
Abstract
Background: Heart failure (HF) and chronic kidney disease (CKD) are strongly interlinked through multifaceted inter-organ cross-talk that increase the risk of the coexistence of both conditions. HF and CKD separately and in combination, are associated with high symptom burden, mortality risk and increased healthcare costs. We sought to determine if heart failure is a risk factor for adverse renal outcomes and death in patients with CKD and to quantify the magnitude of its effect. Methods: We conducted a retrospective cohort study using administrative health data from Manitoba, Canada. We included all adults (≥ 18 years) with prevalent CKD (as defined by KDIGO using CDK-EPI eGFR <60 mL/min/1.73 m2 and/or proteinuria for over 3 months) between January 1st, 2007, and Jan 1st, 2018. We identified a subgroup of patients with HF at baseline. We examined the association of interim HF event (as timedependent exposure) with study outcomes using time-dependent Cox models adjusted for demographics, comorbidities, eGFR, UACR, and medications (e.g., RAASi, beta blockers). The primary composite outcome was ≥ 40% decline in estimated glomerular filtration rate (eGFR), renal replacement therapy (chronic dialysis or kidney transplant), or all-cause mortality: DD40 events. Results: Of the 18,880 prevalent CKD, 3,650 (19%) had history of HF at baseline. The mean eGFR was 51 ± 26 mL/min/1/.73m2 and the median UACR was 6.20 mg/mmol (IQR: 1.4 - 32.4). There were 4,546 (24%) patients with at least 1 interim HF event, with a median time to first interim HF event of 1.9 years. In time-dependent analysis, those with HF at baseline had a higher risk of DD40 events as well as its components after an interim HF event compared to those without interim HF events adjusted HR for DD40 (aHR): 1.98; 95%CI: 1.81-2.17. Similarly, in those without HF at baseline, interim HF hospitalization was associated with higher risk of DD40 events compared to those without interim HF events (aHR: 1.59; 95%CI: 1.50-1.69). Conclusions: Interim heart failure is associated with an increased risk of a composite outcome of all-cause mortality, ESKD, and ≥ 40% decline in eGFR in patients with CKD irrespective of history of HF. These findings strongly support efforts to optimize treatment for primary and secondary prevention of heart failure hospitalizations in patients with CKD. Funding: Private Foundation Support
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".