Left ventricular geometric patterns in end‐stage kidney disease: Determinants and course over time
Bibliographic record
Abstract
INTRODUCTION: While concentric left ventricular hypertrophy (cLVH) predominates in non-dialysis-dependent chronic kidney disease (CKD), eccentric left ventricular hypertrophy (eLVH) is most prevalent in dialysis-dependent CKD stage 5 (CKD5D). In these patients, the risk of sudden death is 5× higher than in individuals with cLVH. Currently, it is unknown which factors determine left ventricular (LV) geometry and how it changes over time in CKD5D. METHODS: Data from participants of the CONvective TRAnsport Study who underwent serial transthoracic echocardiography were used. Based on left ventricular mass (LVM) and relative wall thickness (RWT), 4 types of left ventricular geometry were distinguished: normal, concentric remodeling, eLVH, and cLVH. Determinants of eLVH were assessed with logistic regression. Left ventricular geometry of patients who died and survived were compared. Long-term changes in RWT and LVM were evaluated with a linear mixed model. FINDINGS: Three hundred twenty-two patients (63.1 ± 13.3 years) were included. At baseline, LVH was present in 71% (cLVH: 27%; eLVH: 44%). Prior cardiovascular disease (CVD) was positively associated with eLVH and ß-blocker use inversely. None of the putative volume parameters showed any relationship with eLVH. Although eLVH was most prevalent in non-survivors, the distribution of left ventricular geometry did not vary over time. DISCUSSION: The finding that previous CVD was positively associated with eLVH may result from the permanent high cardiac output and the strong tendency for aortic valve calcification in this group of long-term hemodialysis patients, who suffer generally also from chronic anemia and various other metabolic derangements. No association was found between eLVH and parameters of fluid balance. The distribution of left ventricular geometry did not alter over time. The assumption that LV geometry worsens over time in susceptible individuals, who then suffer from a high risk of dying, may explain these findings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.008 | 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".