A study of the extracorporeal rate of blood flow and blood pressure during hemodialysis
Bibliographic record
Abstract
Hemodynamic instability is a common problem during hemodialysis (HD). The effect of blood flow rate (BFR) on blood pressure (BP) during HD has not been previously evaluated. Subjects receiving HD for the treatment of renal failure were enrolled (n=34). For each patient, during the last hour of 2 consecutive HD sessions the BFR was set at 200 mL/min for 30 min and at 400 mL/min for 30 min, during which period the fluid removal rate was kept constant. The order of the BFR alterations was randomized. The study procedure was repeated during the next HD session but with reversal of the order of the altered BFR. During each 30-min period, BP was recorded at baseline and subsequently every 10 min. During the BFR of 400 mL/min, subjects had a higher systolic BP by an average of 4.1 mmHg compared with the BFR of 200 mL/min (95% confidence interval [CI] 0.22-7.98; p=0.038). Similarly, during the BFR of 400 mL/min, subjects had a higher diastolic BP by an average of 3.04 mmHg compared with the BFR of 200 mL/min (95% CI 0.55-5.53; p=0.017). Likewise, during the BFR of 400 mL/min, subjects had a higher mean arterial pressure by an average of 3.44 mmHg (95% CI 0.77-6.11; p=0.012). The findings suggest that during HD, BPs are maintained higher at higher BFRs as compared with lower BFRs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".