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Record W4309740553 · doi:10.3389/fcvm.2022.1054208

Prevalence and possible factors of cognitive frailty in the elderly with hypertension and diabetes

2022· article· en· W4309740553 on OpenAlexaboutno aff
Shourong Lu, Qiao Xu, Jie Yu, Ying Yang, Zhuo Wang, Bingshan Zhang, Shuqiang Wang, Xiaorong Chen, Yunyun Zhang, Xiaowei Zhu, Hong Kan

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersWuxi Health and Family Planning Commission
KeywordsDementiaMedicineDiabetes mellitusGerontologyCognitionConfoundingClinical Dementia RatingCognitive declineDepression (economics)Activities of daily livingPhysical therapyCognitive impairmentPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

Background Cognitive frailty is the coexistence of physical frailty and mild cognitive impairment. Research shows that cognitive frailty is related to an increased risk of hospitalization, mortality, disability, and dementia. Diabetes and hypertension are common risk factors for physical frailty and cognitive impairment. However, the factors influencing cognitive frailty in the elderly with hypertension and diabetes are still unclear. This study aimed to investigate the possible factors influencing cognitive frailty in the elderly with hypertension and diabetes. Methods A cross-sectional study was conducted. We evaluated people over 60 years with hypertension and diabetes who underwent physical examination in Wuxi Xin'an Community Health Service Center. Frail scale, Montreal Cognitive Assessment-Basic and clinical dementia rating were used to assess cognitive frailty. We collected demographic characteristics, hypertension and diabetes-related laboratory indicators of the participants. We also used various scales to assess the overall health status of the elderly. Results Approximately 20.8% of the participants were determined to have cognitive frailty in elderly adults with hypertension and diabetes. These participants were older, had a lower monthly income, and included a higher proportion of peasants. They also had a higher level of depression ( p = 0.037), higher risk of falls ( p = 0.000), higher risk of malnutrition ( p = 0.002), poorer ability to perform activities of daily living (ADL) ( p = 0.000), and less social support ( p = 0.030). Multivariate regression analysis was used to further assess the factors for cognitive frailty. After adjusting for possible confounders, age and ADL score emerged as risk factors, whereas high monthly income decreased the risk of cognitive frailty. Conclusion Cognitive frailty is correlated with age, income, and ability to perform daily living activities in the elderly with diabetes and hypertension. Closer attention to the elderly who have low income and poor self-care ability may play an important role in the early prevention of cognitive frailty and even dementia.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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 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".

Quick stats

Citations28
Published2022
Admission routes1
Has abstractyes

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