Association of anticholinergic burden with hippocampal subfields volume in first-episode psychosis
Bibliographic record
Abstract
• Polypharmacy is expected in early psychosis. However, the impact of the anticholinergic burden has been overlooked, despite its association with cognitive deficits. • First-episode psychosis patients with a high anticholinergic burden showed a more significant reduction in left fimbria volume than those with a low anticholinergic burden and healthy controls. • Our study highlights the importance of considering the anticholinergic burden when prescribing medication in first-episode psychosis, given its potential implications for hippocampal dysfunction and cognitive deficits. Polypharmacy is relatively common in early psychosis, but little attention has been paid to the anticholinergic burden of medication use (the cumulative effect of medications that block the cholinergic system). Evidence suggests that anticholinergic burden is associated with cognitive deficits and that hippocampal dysfunction may be involved in those impairments. We aimed to examine this association in a cohort of patients with first-episode psychosis. We hypothesized that patients with the highest burden would experience a more significant reduction in hippocampal volume compared to those with low burden and healthy controls, both at baseline (3 months) and at month 12. Patients ( n = 82; low burden [ n = 64] and high burden [ n = 18], defined by a Drug Burden Index cut-off of 1) followed at the PEPP-Montreal clinic, and controls ( n = 55) completed a 3T MRI at both timepoints. After controlling for antipsychotic dosage at both timepoints, results at baseline and over time revealed a greater reduction in left fimbria volumes in high-burden patients compared to low-burden patients and controls. Overall, the associations observed between high anticholinergic burden and hippocampal volume provide further evidence for considering this dimension when prescribing medication in early psychosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".