Effect of chronic kidney disease on red blood cell rheology.
Bibliographic record
Abstract
BACKGROUND: Anemia of renal failure is primarily a problem of decreased RBC production due to erythropoietin deficiency. RBC survival is also reduced, perhaps due to decreased RBC deformability. This study measured blood viscosity over a range of shear rates in erythropoietin-treated patients on hemodialysis (HD), and compared the findings to matched patients with chronic renal insufficiency (CRI) and healthy controls. METHODS: Four groups (control, CRI, non-diabetic HD, and diabetic HD) of 9 matched subjects were recruited. Blood viscosity was measured using a cone-plate viscometer over a variety of shear rates (11 to 225 s(-1)). RESULTS: Control subjects had lower viscosity values throughout all shear rates when compared to the 3 renal disease groups (P value=0.039). A trend was observed to higher levels of renal function being associated with decreased blood viscosity in patients with CRI. CONCLUSIONS: Patients with kidney disease have increased blood viscosity at all shear rates. This may be related to changes in RBC shape and decreased deformability in patients with kidney disease, independent of HD- or DM-status. This may have implications for strategies to treat anemia in these patients.
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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 | 0.001 |
| 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) | 0.002 | 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".