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Record W3113210257 · doi:10.1002/alz.047086

Validation of a new serum anticholinergic assay using anticholinergic burden scales and cognitive assessments in older adults with mild cognitive impairment or major depressive disorder

2020· article· en· W3113210257 on OpenAlexaff
Susmita Chandramouleeshwaran, Tarek K. Rajji, Naba Ahsan, Roger Raymond, José N. Nóbrega, Corinne E. Fischer, Alastair J. Flint, Nathan Herrmann, Sanjeev Kumar, Linda Mah, Benoit H. Mulsant, Bruce G. Pollock

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of TorontoUniversity Health NetworkBaycrest HospitalSt. Michael's HospitalSunnybrook Health Science CentreCentre for Addiction and Mental Health
Fundersnot available
KeywordsAnticholinergicMajor depressive disorderInternal medicineCognitionAnticholinergic agentsPsychologyMedicineCognitive impairmentPsychiatryClinical psychology

Abstract

fetched live from OpenAlex

Abstract Background A high anticholinergic burden has been associated with deleterious effects on cognition, especially in the elderly. We developed a new serum anticholinergic assay (SAA) to measure the anticholinergic burden, and report on validating this new SAA using established anticholinergic burden scales and cognitive assessments in older patients with mild cognitive impairment (MCI) or major depressive disorder (MDD). Method Baseline serum samples were collected from 311 participants (154 with MCI, 57 with MDD, and 100 with MCI + MDD). The new SAA assay uses radio‐ligand binding to cultured cells stably expressing the muscarinic M1 receptors, with an added procedure to remove potential confounds associated with the effects of proteins in serum. We then calculated correlations between new SAA scores and each of the Anticholinergic Burden Scale (ACB) and Anticholinergic Drug Scale (ADS) total scores. Multiple regression models assessed the relationships between SAA and cognitive performance on a comprehensive cognitive battery. Result Baseline serum samples were collected from 311 participants (154 with MCI, 57 with MDD, and 100 with MCI + MDD). The mean SAA value was 1.65 pmol/L, SD = 1.83). Mean age of the sample was 71.96 years, range 60‐90 years, SD=6.2. 38.7 % were males. In both the ACB and ADS scores, participants with the highest total scores had the highest SAA values. ADS: F (2,98) = 7.84, p = 0.001, SAA (3+) > SAA (1); ACB: F (2,121) = 5.89, p = 0.004, SAA (3+) > SAA (1) and > SAA (2). SAA was significantly associated with performance on executive function after adjusting for age, gender, education, diagnosis, controlling for multiple testing. (β = ‐0.152, SE = 0.024, p = 0.007) There was no association with overall cognitive composite score combining all domains. Conclusion The above results support the use of the new SAA as a measure of anticholinergic burden. Of note, the effect of SAA on executive function was almost equivalent, though in the opposite direction, to the effect of education on executive function.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.020
GPT teacher head0.290
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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