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Low Levels of Selenoprotein P Are Associated With Cognitive Impairment in Patients Hospitalized for Heart Failure

2024· article· en· W4391850257 on OpenAlexaboutno aff
Amra Jujić, John Molvin, Erik Nilsson, Hannes Holm Isholth, Anna Dieden, Johan Korduner, Amir Zaghi, Zainu Nezami, Andreas Bergmann, Lutz Schomburg, Martin Magnusson

Bibliographic record

VenueJournal of Cardiac Failure · 2024
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsnot available
FundersMedicinska Fakulteten, Lunds UniversitetMedical Research CouncilVetenskapsrådetKnut och Alice Wallenbergs StiftelseHjärt-LungfondenCrafoordska Stiftelsen
KeywordsMedicineSelenoprotein PHeart failureCognitive impairmentCognitionInternal medicineCardiologyIntensive care medicinePsychiatryOxidative stress

Abstract

fetched live from OpenAlex

BACKGROUND: Selenoprotein P (SELENOP) is a transporter for selenium and has been shown to protect selenium-status maintenance in the brain against deficiency and to support neuronal development, neurogenesis and neurocognitive function. Selenium deficiency has previously been associated with cognitive impairment in various populations, but no studies have been carried out in subjects with heart failure (HF). PURPOSE: To explore whether SELENOP deficiency in subjects with acute HF is associated with cognitive impairment. METHODS: Plasma SELENOP, as measured by an immunoassay analysis, is a well-validated marker of plasma selenium status and has the benefit of providing information on the bioavailable fraction of selenium to preferentially supplied cells equipped with receptors for SELENOP uptake. SELENOP was measured in 320 subjects hospitalized for HF. Of the subjects, 187 also underwent 4 cognitive tests assessing global cognitive function: Montreal Cognitive Assessment (MoCA); information processing (Symbol Digit Modalities Test [SDMT]); visual attention and task switching (Trailmaking Test A [TMT-A]); and executive speed (A Quick Test of Cognitive Speed [AQT] form and color). Appropriate cutoffs were used for each cognitive test to define cognitive impairment. Cross-sectional associations between SELENOP concentrations and cognitive impairment, as defined by each cognitive test, were explored using multivariable logistic models. Further, multivariable logistic models exploring associations between selenium deficiency, defined as the lowest quartile of SELENOP levels, and cognitive impairment, defined by each cognitive test, were carried out. RESULTS: . Each 1 standard deviation increment in SELENOP concentrations was associated with lower odds of cognitive impairment, defined as a MoCA cut-off score < 23 (odds ratio [OR] 0.60; 95% CI 0.40-0.91; P = 0.017). Further, SELENOP concentrations in the lowest quartile (≤ 2.3 mg/L) were associated with cognitive impairment as measured by MoCA (OR 3.10; 95% CI 1.38-6.97; P = 0.006), SDMT (OR 2.26; 95% CI 1.10-4.67; P = 0.027) and TMT-A (OR 3.40; 95% CI 1.47-7.88; P = 0.004) but not by AQT form and color. CONCLUSIONS: In subjects admitted for HF, higher SELENOP concentrations were associated with better performance on the MoCA test, reflecting global cognition, and SELENOP deficiency was associated with cognitive impairment as defined by 3 cognitive tests.

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)0.001
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 score0.023
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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