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Record W3010861715 · doi:10.1016/j.exger.2020.110926

Association of hsCRP and vitamin D levels with mild cognitive impairment in elderly type 2 diabetic patients

2020· article· en· W3010861715 on OpenAlexaboutno aff
Małgorzata Górska-Ciebiada, Maciej Ciebiada

Bibliographic record

VenueExperimental Gerontology · 2020
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
FundersUniwersytet Medyczny w Lodzi
KeywordsMedicineInternal medicineVitamin D and neurologyDiabetes mellitusCognitive impairmentC-reactive proteinvitamin D deficiencyType 2 diabetesGastroenterologyProspective cohort studyMontreal Cognitive AssessmentInflammationEndocrinologyDisease

Abstract

fetched live from OpenAlex

AIMS: The aim of the study was to determine the serum levels of 25-hydroxyvitamin D and high-sensitivity C-reactive protein (hsCRP) in elderly diabetic patients with and without mild cognitive impairment (MCI) and to examine factors (including 25-hydroxyvitamin D and hsCRP) associated with MCI in elderly patients with type 2 diabetes (T2DM). METHODS: A total of 194 T2DM elders were evaluated: 62 subjects with MCI and 132 controls. Data was collected concerning biochemical parameters and biomarkers. RESULTS: HsCRP concentration was elevated and 25-hydroxyvitamin D level was decreased in MCI patients to controls. HsCRP level was negatively correlated with 25-hydroxyvitamin D level and with MoCA score, and highly correlated with HbA1c level. The multivariable analysis indicated that less years of formal education, previous CVD and hypertension, increased number of co-morbidities, higher level of hsCRP and lower level of 25-hydroxyvitamin D, are the predisposing factors for MCI. CONCLUSIONS: Higher hsCRP level and lower 25-hydroxyvitamin D may be regarded as a state of cognitive impairment in elderly patients with T2DM. Further prospective larger studies should be conducted to check the association between decreased vitamin D and risk of cognitive decline and to clarify whether this association may be mediated by systemic inflammation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.371

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 head0.038
GPT teacher head0.328
Teacher spread0.290 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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