A review of published anticholinergic scales and measures and their applicability in database analyses
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Available metrics for characterizing cumulative anticholinergic exposure over time may not be well suited for use across all US data sources. In this review, the properties of existing anticholinergic scales and measures were evaluated to determine their suitability for implementation in observational studies relying on administrative data. METHODS: A targeted literature review was conducted to identify available anticholinergic scales and measures. Suitability of the identified scales and measures for quantification of anticholinergic exposure was evaluated based on pre-defined criteria. Agreement between selected scales was characterized by the percentage overlap of included drugs and inter-scale Spearman's correlation of scores. RESULTS: Sixteen scales were identified; six were relevant and suitable for the quantification of anticholinergic exposure. When implemented on administrative data the Anticholinergic Drug Scale and Anticholinergic Cognitive Burden scale demonstrated the most agreement, with an inter-scale correlation coefficient of 0.82. Scale performance varied by outcome of interest, and underlying disease profile of the population of interest. Variability across the two measures ("average daily dose" and "cumulative dose") was observed, with neither considering both dose and anticholinergic potency in score calculations. CONCLUSIONS: Accurate quantification of anticholinergic burden is important in assessing relative risks versus benefits of prescribing anticholinergic medications. In this review, the Anticholinergic Drug Scale and the Anticholinergic Cognitive Burden scale and the average daily dose and cumulative dose measures, were determined to be well suited for the quantification of anticholinergic exposure, particularly in the context of administrative data analyses; however, methods to characterize anticholinergic burden through consideration of both anticholinergic dose and potency are needed.
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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 | 0.042 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.022 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| 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".