Correlation between Intradialytic Blood Pressure Variability and Cognitive Impairment in Patients on Maintenance Hemodialysis
Bibliographic record
Abstract
Background: Cognitive impairment (CI) is a risk factor for death and poor prognosis in maintenance hemodialysis (MHD) patients. MHD patients are more likely to have fluctuating BP during dialysis, which may have a greater impact on CI. Our present study aimed to illustrate the correlation between intradialysis BPV and CI in MHD patients. Methods: Overall cognitive function was assessed by the Beijing version of the Montreal Cognitive Assessment (MoCA-B) scale. The patient's SBP was converted to the following 4 candidate BPV indices: standard deviation (SD), coefficient of variation (CV), average real variability (ARV), RANGE. P < 0.05 was considered statistically significant. Results: 170 patients were enrolled, with a total of 6,662 dialysis recordings and 26,580 SBP measurement recordings. The mean age of the patients was 57.99 years. The proportion of males was 58.24%, and CI prevalence was 78.24%. SBP ARV is an independent risk factor for CI (Table 1). We observed a non-linear relationship between SBP ARV and CI (Figure 1). We compared two fitting models to explore the curved associations, the p-value of the log-likelihood ratio test is 0.008. The inflection point of SBP ARV was 7.52. When SBP ARV ≥ 7.52, the risk of CI increased as the SBP ARV increased (OR: 4.10, 95 % CI1.61-10.46, P = 0.003). When SBP ARV < 7.52, there was no significant correlation between SBP ARV and CI (OR = 0.43, 95 % CI 0.15-1.26, p = 0.125). Conclusion: Intradialytic BPV was associated with CI in MHD patients. Intradialytic SBP ARV may be a better candidate for predicting CI in MHD patients, with nonlinear dose-response relationship. Funding: Government Support – Non-U.S.Table1. The results of mutivariate analysis between SBP ARV and CIFigure 1.Curve fitting between SBP ARV and CI.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".