Prognostic values of left ventricular mass index in chronic kidney disease patients
Bibliographic record
Abstract
BACKGROUND: Left ventricular hypertrophy is causally implicated in the high risk of death and heart failure (HF) in chronic kidney disease (CKD) patients. Whether the left ventricular mass index (LVMI) adds meaningful predictive power for mortality and de novo HF to simple risk models has not been tested in the CKD population. METHODS: We investigated this problem in 1352 CKD patients enrolled in the Chronic Renal Insufficiency Cohort (CRIC). LVMI was measured by echocardiography and the risks for death and HF were estimated by the Study of Heart and Renal Protection (SHARP) score, a well-validated risk score in CKD patients. RESULTS: During a median follow-up of 7.7 years, 326 patients died and 208 had de novo HF. The LVMI and the SHARP score and a cross-validated model for HF (CRIC model) were all significantly (P < 0.001) related to the risk of death and HF. LVMI showed a discriminatory power for death (Harrell's C index 66%) inferior to that of the SHARP score (71%) and the same was true for the risk of HF both in the test (LVMI 72%, CRIC model 79%) and in the validation cohort (LVMI 71%, CRIC model 74%). LVMI increased very little the discriminatory (2-3%) and the risk reclassification power (3.0-4.8%) by the SHARP score and the CRIC model for HF for the same outcomes. CONCLUSIONS: In CKD, measurement of LVMI solely for the stratification of risk of death and perhaps for the risk of HF does not provide evident prognostic values in this condition.
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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 | 0.000 | 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 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".