The management of left ventricular systolic dysfunction in patients with advanced chronic kidney disease
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Bibliographic record
Abstract
BACKGROUND: Left ventricular systolic dysfunction (LVSD) is frequently observed in patients with advanced chronic kidney disease (CKD) and its presence is associated with a poor prognosis. Renin-angiotensin system (RAS) inhibition and beta-adrenergic blockade are the cornerstones of medical management for LVSD. Current guidelines advocate that CKD patients with advanced LVSD should receive these therapies. The extent to which these recommendations are followed is unclear. The goal of this study was to evaluate practice patterns for LVSD management across the spectrum of patients with advanced CKD, and to determine the rate of utilization of recommended therapies for LVSD. METHODS: This cross-sectional study encompassed all long-term dialysis patients (n=299) and patients with advanced pre-dialysis CKD who were followed in a multidisciplinary clinic (n=176) at a tertiary care center in Toronto, Canada. Echocardiographic and pharmacotherapy data were sought for each patient. In patients with moderate-severe LVSD (ejection fraction <40%), we evaluated the extent to which optimal pharmacotherapy, defined as the receipt of a beta-adrenergic receptor blocker and a RAS inhibitor (an angiotensin-converting enzyme inhibitor or an angiotensin II receptor blocker), was applied. We then sought to identify factors to explain the usage of these therapies. RESULTS: Of the 475 eligible patients, 387 had echocardiographic data available for analysis. Among these individuals, 34 (8.8%) had moderate-severe LVSD, of whom 23 (67.7%) were receiving optimal therapy. Non-receipt of optimal therapy could not be explained by hypotension, hyperkalemia, known drug sensitivities, or pill burden. CONCLUSIONS: Approximately one-third of patients with advanced CKD and significant LVSD were not receiving optimal pharmacotherapy, in the absence of known contraindication or intolerance. Identifying and overcoming barriers to care will be crucial in order to enhance the management of this high-risk population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it