Bibliographic record
Abstract
OBJECTIVE: We will review the available evidence on the frequency, clinical correlates, mechanism, and treatment of apathy following stroke. METHODS: We have explored relevant databases (that is, PubMed, MEDLINE, and PsycINFO) using the following key words and their combinations: apathy, motivation, abulia, stroke, cerebrovascular disease, basal ganglia, prefrontal cortex, anterior cerebral infarction, and thalamus. RESULTS: The frequency of apathy following stroke has been consistently estimated between 20% and 25%. It appears to be associated with the presence of cognitive impairment, a chronic course characterized by progressive functional decline, and with disruption of neural networks connecting the anterior cingulate gyrus, the dorsomedial frontal cortex, and the frontal pole with the ventral aspects of the caudate nucleus, the anterior and ventral globus pallidus, and the dorsomedian and intralaminar thalamic nuclei. Published treatment studies have been mostly limited to anecdotal case reports, generally using dopamine agonists or stimulant medications. Cholinesterase inhibitors and nefiracetam may significantly reduce apathetic symptoms. However, their efficacy was examined in relatively small clinical trials that require replication. CONCLUSION: Apathy is a frequent neuropsychiatric complication of stroke that, although often associated with depression and cognitive impairment, may occur independently of both. Its presence has been consistently associated with greater functional decline. However, there is no conclusive evidence about which is the best treatment for this condition.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".