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Record W4312087068 · doi:10.1002/alz.068722

Smoking Gun? Effect of smoking history on cognition in AD and MCI

2022· article· en· W4312087068 on OpenAlexaffabout
Lucas M Crawford‐Holland, Jennifer S. Rabin, Luis Fornazzari, Tom A. Schweizer, Corinne E. Fischer, David G. Munoz, Sanjeev Kumar, Sandra E. Black, Morris Freedman, Michael Borrie, Andrew Frank, Stephen Pasternak, Bruce G. Pollock, Tarek K. Rajji, Dallas Seitz, David F. Tang‐Wai, Maria Carmela Tartaglia, Donna Kwan, Brian Tan

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsUniversity of CalgaryRobarts Clinical TrialsBruyèreLawson Health Research InstituteSunnybrook Health Science CentreUniversity of TorontoSunnybrook HospitalBaycrest HospitalWestern UniversitySt. Michael's Hospital
Fundersnot available
KeywordsSmoking historyMedicineCognitionMontreal Cognitive AssessmentLongitudinal studyCohortCigarette smokingDemographyCohort studyMedical historyInternal medicineCognitive impairmentPsychiatryPathology

Abstract

fetched live from OpenAlex

Abstract Background Many lifestyle factors have been associated with lower rates of cognitive decline in AD and MCI patients, however the effect of tobacco smoking remains unclear. This study examined how longitudinal cognitive performance in AD and MCI patients varied for those with versus without smoking history. Method The study included all 126 patients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) AD/MCI cohort. The patients were divided into those with a history of cigarette smoking (n = 67) vs without (n = 59), defined as greater than two years of daily smoking. To measure longitudinal cognition, MoCA scores were taken three times with one year elapsing between assessments. Result Linear mixed effects models were performed, with MoCA score as the dependent variable. Time point, smoking history, sex, education, age, clinical diagnosis (AD vs MCI) and number of languages spoken were fixed effects and subject was a random effect. The presence of smoking history had a significant effect on MoCA score (χ2(1) = 4.5, p = 0.034), improving the average score by 1.37 points ± 0.66 (standard errors). A strong interaction was also found between smoking history and time point (χ2(1) = 8.2, p = 0.0042), as the positive effect of smoking history on MoCA score increased with time. No other significant interactions were found. Conclusion Our findings indicate that smoking history may improve longitudinal cognition in AD and MCI patients. It is unclear whether smoking history is simply a mediating variable for another protective factor, or whether these results arise from cigarette smoking itself affecting some stage of disease progression. Smoking has been consistently associated with a lower risk of developing Parkinson’s disease (PD), however the mechanism for such protection remains unclear. Further research into any association between smoking history and longitudinal cognition in AD and MCI might indicate whether a similar protective association is found in AD and MCI as exists in PD. However, it must be remembered that smoking is associated with many serious diseases, particularly lung cancer, and remains one of the biggest causes of preventable death worldwide.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.257
Teacher spread0.236 · 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 teacher head, not a consensus.

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

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
Published2022
Admission routes2
Has abstractyes

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