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Record W4311450893 · doi:10.1155/2022/6025732

Correlation between Body Mass Index and Cognitive Function in Patients with Atrial Fibrillation

2022· article· en· W4311450893 on OpenAlexaboutno aff
Li Guo, Ping Yin, Xiangting Li, Xin Wang, Jing Xue, Wenqing Wang, Dongmei Song, Guomei Xu, Miaomiao Shang, Shuai Liu, Yuanyuan Chen, Qingyun Zhang, Dandan Sun

Bibliographic record

VenueJournal of Interventional Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtrial fibrillationBody mass indexInternal medicineCognitionConfidence intervalInflection pointMontreal Cognitive AssessmentCardiologyCorrelationCognitive impairmentDiseasePsychiatry

Abstract

fetched live from OpenAlex

Background. Evidence regarding the relationship between body mass index (BMI) and cognitive function was limited. Therefore, the objective of this research is to investigate whether BMI is independently related to cognitive function in Chinese patients with atrial fibrillation after adjusting for other covariates. Methods. The present study is a cross-sectional study. A total of 281 patients with atrial fibrillation who were hospitalized at the Affiliated Hospital of Jining Medical University in Shandong Province from January 2021 to November 2021 were included in the study. The target independent variable and the dependent variable were BMI and cognitive function in patients with atrial fibrillation, respectively. The patients’ general information, BMI, past history, medication history, and other disease-related data were collected. The Montreal cognitive assessment scale (MoCA) was used to evaluate cognitive function. Results. A total of 244 patients with atrial fibrillation were collected in this study, with an average age of (67.28 ± 10.33) years, of whom 55.3% were male. The average BMI was (25.33 ± 4.27) kg/m2, and the average cognitive function score was (19.25 ± 6.88) points. The results of the smooth curve fitting and threshold effect tests showed that there was a curve correlation between BMI and cognitive function score, and its inflection point was 24.56 kg/m2. To the left of the inflection point, the relationship was significant; the effect size and the confidence interval were 0.43 and 0.01–0.85, respectively. To the right of the inflection point, there was no significant correlation between BMI and cognitive function ( P = 0.152 ). Conclusion. When BMI is lower than 24.56 kg/m2, the cognitive function score increases by 0.43 points for each unit increase in BMI in patients with atrial fibrillation. An increase in BMI at this time is a protective factor for cognitive function. Within the normal range of BMI, the higher the BMI in atrial fibrillation patients, the higher the cognitive function score. We encourage atrial fibrillation patients with normal BMI to maintain their current weight.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.300
Teacher spread0.273 · 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 designObservational
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".

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Citations2
Published2022
Admission routes1
Has abstractyes

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