The Cognitive Cost of Anticholinergic Burden: Decreased Response to Cognitive Training in Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Schizophrenia is treated with medications that raise serum anticholinergic activity and are known to adversely affect cognition. The authors examined the relationship between serum anticholinergic activity and baseline cognitive performance and response to computerized cognitive training in outpatients with schizophrenia. METHOD: Fifty-five patients were randomly assigned to either computerized cognitive training or a computer games control condition. A neurocognitive battery based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative was performed at baseline and after the intervention. Serum anticholinergic activity, measured at study entry by radioreceptor assay, was available for 49 patients. RESULTS: Serum anticholinergic activity showed a significant negative correlation with baseline performance in verbal working memory and verbal learning and memory, accounting for 7% of the variance in these measures, independent of age, IQ, or symptom severity. Patients in the cognitive training condition (N=25) showed a significant gain in global cognition compared to those in the control condition, but this improvement was negatively correlated with anticholinergic burden. Serum anticholinergic activity uniquely accounted for 20% of the variance in global cognition change, independent of age, IQ, or symptom severity. CONCLUSIONS: Serum anticholinergic activity in schizophrenia patients shows a significant association with impaired performance in MATRICS-based measures of verbal working memory and verbal learning and memory and is significantly associated with a lowered response to an intensive course of computerized cognitive training. These findings underscore the cognitive cost of medications that carry a high anticholinergic burden. The findings also have implications for the design and evaluation of cognitive treatments for schizophrenia.
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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 | 0.002 |
| 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) | 0.001 | 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".