The nature, consequences, and management of neurological disorders in chronic kidney disease
Bibliographic record
Abstract
Perhaps no other organ in the body is affected as often and in as many ways as the brain is in patients with chronic kidney disease (CKD). Several factors contribute to the neurological disorders in CKD including accumulation of uremic toxins, metabolic and hemodynamic disorders, oxidative stress, inflammation, and impaired blood brain barrier among others. The neurological disorders in CKD involve both peripheral and central nervous system. The peripheral neurological symptoms of CKD are due to somatic and cranial peripheral neuropathies as well as a myopathy. The central neurological symptoms of CKD are due to the cortical predominantly cortical, or subcortical lesions. Cognitive decline, encephalopathy, cortical myoclonus, asterixis and epileptic seizures are distinct features of the cortical disorders of CKD. Diffuse white matter disease due to ischemia and hypoxia may be an important cause of subcortical encephalopathy. A special and more benign form of subcortical disorder caused by brain edema in CKD is termed posterior reversible encephalopathy. Subcortical pathology especially when it affects the basal ganglia causes a number of movement disorders including Parkinsonism, chorea and dystonia. A stimulus-sensitive reflex myoclonus is believed to originate from the medullary structures. Sleep disorder and restless leg syndrome are common in CKD and have both central and peripheral origin. This article provides an overview of the available data on the nature, prevalence, pathophysiology, consequences and treatment of neurological complications of CKD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".