Association between routine and standardized blood pressure measurements and left ventricular hypertrophy among patients on hemodialysis
Bibliographic record
Abstract
BACKGROUND: Left ventricular (LV) hypertrophy is common among patients on hemodialysis. While a relationship between blood pressure (BP) and LV hypertrophy has been established, it is unclear which BP measurement method is the strongest correlate of LV hypertrophy. We sought to determine agreement between various blood pressure measurement methods, as well as identify which method was the strongest correlate of LV hypertrophy among patients on hemodialysis. METHODS: This was a post-hoc analysis of data from a randomized controlled trial. We evaluated the agreement between seven BP measurement methods: standardized measurement at baseline; single pre- and post-dialysis, as well as mean intra-dialytic measurement at baseline; and cumulative pre-, intra- and post-dialysis readings (an average of 12 monthly readings based on a single day per month). Agreement was assessed using Lin's concordance correlation coefficient (CCC) and the Bland Altman method. Association between BP measurement method and LV hypertrophy on baseline cardiac MRI was determined using receiver operating characteristic curves and area under the curve (AUC). RESULTS: Agreement between BP measurement methods in the 39 patients on hemodialysis varied considerably, from a CCC of 0.35 to 0.94, with overlapping 95% confidence intervals. Pre-dialysis measurements were the weakest predictors of LV hypertrophy while standardized, post- and inter-dialytic measurements had similar and strong (AUC 0.79 to 0.80) predictive power for LV hypertrophy. CONCLUSIONS: A single standardized BP has strong predictive power for LV hypertrophy and performs just as well as more resource intensive cumulative measurements, whereas pre-dialysis blood pressure measurements have the weakest predictive power for LV hypertrophy. Current guidelines, which recommend using pre-dialysis measurements, should be revisited to confirm these results.
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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".