Pulse Pressure Determinants in Chronic Hemodialysis Patients
Bibliographic record
Abstract
Introduction: Hypertension contributes to the cardiovascular morbidity in patients undergoing chronic hemodialysis therapy (PCHD). Pulse pressure (PP) was recognized as a correlate of mortality in PCHD. In order to demonstrate determinants of predialysis and postdialysis PP values in a group of PCHD, we conducted this study. Subjects and methods: Study subjects were 23 PCHD. Study time was 15 months. One hundred thirty six single hemodialysis (HD) treatments were processed. PP was computed as systolic-diastolic blood pressure (mmHg). Statistical methods used were Student's t test for independent data, multivariate analysis of variance, Pearson's correlation, and forward stepwise multiple regression analysis. Results: Postdialysis and predialysis PPs differed significantly (65.51 ± 19.00 vs. 60.55 ± 19.35, p = 0.002). We did not find gender differences in PP before and after HD. PP before HD was in negative correlation with phosphorus concentration (r = − 0.244, p = 0.002), parathyroid hormone (PTH)(r = − 0.177, p = 0.020), hemoglobin (r = − 0.301, p < 0.001), single HD duration (r = − 0.162, p = 0.030), ultrafiltration rate per HD (r = − 0.290, p = 0.001), years on the chronic hemodialysis treatment (r = − 0.261, p = 0.001) and ultrafiltration volume/dry body mass ratio (UF/W)(r = − 0.222, p = 0.005) and in positive concentration with weekly erythropoietin (r = 0.391, p < 001) and age (r = 0.285, p < 0.001). PP after HD was in significant negative correlation with phosphorus concentration (r = − 0.205, p = 0.009), PTH (r = − 0.187, p = 0.015), hemoglobin (r = − 0.238, p = 0.005), ultrafiltration per HD (r = − 0.370, p < 0.001), dry body mass index (r = − 0.225, p = 0.003), years of the chronic hemodialysis treatment (r = 0.330, p < 0.001), UF/W (r = − 0.340, p < 0.001) and in positive concentration with weekly erythropoietin (r = 0.361, p < 0.001) and age (r = 0.227, p = 0.004). Multiple regression analyses unveiled the strongest and negative correlations between PP after HD and UF/W ratio (β = − 0.41, p < 0.001). The strongest, but positive correlation was found between PP before HD and erythropoietin per week (β = 0.51, p < 0.001). Conclusion: Determinants of the pre/post PP values are similar. Ultrafiltration is a strong predictor of postdialysis PP value.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".