P.041 Does brain tissue oxygenation (BtO2) predict cognitive decline in patients undergoing hemodialysis? A feasibility study
Bibliographic record
Abstract
Background: Cognitive impairment is highly prevalent in individuals with end stage kidney disease (ESKD) undergoing hemodialysis. The cause is not understood. Our overall hypothesis is that repetitive cerebral hypoperfusion during hemodialysis contributes to accelerated cognitive dysfunction in this patient population. Methods: All participants underwent a baseline assessment with the KINARM, a robotic device that provides quantitative metrics of the sensorimotor control of the upper limb in humans. For patients undergoing hemodialysis, BtO2 was monitored during one dialysis session per week. Follow up KINARM assessment was done at 3 months. Results: To date, 7 patients have completed baseline testing, with 3 being re-evaluated at 3 months. At baseline, patients were impaired on of the 8 tasks, with the exception of a test of working memory. There was a variable correlation between hemodynamics (e.g. blood pressure and heart rate), fluid removal, and BtO2 levels. At 3 months, the 3 patients improved on the majority of the performance metrics assessed with the KINARM. Conclusions: The KINARM is a feasible instrument to measure cognitive dysfunction in individuals with ESKD. In a small cohort, there is improvement in neurocognitive function 3 months after the initiation of dialysis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".