Haemodialysis and Cerebral Oedema
Bibliographic record
Abstract
BACKGROUND: Haemodialysis may cause neurological symptoms ranging from inconvenient feelings of disequilibrium to life-threatening neurological complications. There are animal data to suggest cerebral swelling may accompany haemodialysis and contribute symptomatically to dialysis disequilibrium. However, MR images acquired following haemodialysis often fail to demonstrate evidence of cerebral oedema. We wished to quantify any potential cerebral volume change which is caused by haemodialysis treatment. METHOD: Five renal patients and 5 control subjects had a two volumetric T1-weighted MRI scans on the same day. The patients were imaged immediately before and after haemodialysis. None were taking steroids. Precise positional matching (registration) was used to quantify cerebral volume change. RESULTS: Patients had an increase in cerebral volume following dialysis which averaged 32.8 ml (SE 7.4 ml, 3% brain volume). The change in the controls was 1.4 ml (SE 0.6 ml), p < 0.001. No patient had significant neurological symptoms. CONCLUSION: Cerebral oedema developed in the patients following dialysis. There is a good biological model for these observations. Modifications to dialysis may help. Common problems which increase cerebral volume, e.g. acute stroke, require careful appraisal in these patients. These observations need consideration when quantifying atrophy in dialysis 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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".