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Record W3120940135 · doi:10.1111/sdi.12948

Serum NT‐proBNP levels are associated with cognitive functions in hemodialysis patients

2021· article· en· W3120940135 on OpenAlexaboutno aff
Gülsüm Akkuş, Muhammed Seyithanoğlu, Hadi Akkus, Sena Ulu, Muhammed Çiftçioğlu, Ertuğrul Erken, Orçun Altunören, Özkan Güngör

Bibliographic record

VenueSeminars in Dialysis · 2021
Typearticle
Languageen
FieldMedicine
TopicGDF15 and Related Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineInternal medicineCognitionHemodialysisDialysisRecallDiseaseCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

It has been demonstrated that NT-proBNP and macrophage inhibitor cytokine-1 (MIC-1/GDF-15) are associated with cognitive functions in patients without renal disease. In the present study, we examined the association of these two molecules with cognitive functions in hemodialysis patients for the first time in the literature. A total of 94 patients were enrolled. The Mini-Mental Test and the Montreal Cognitive Assessment Test (MoCA) were applied for the purpose of measuring the cognitive functions. The NT-proBNP and MIC-1/GDF-15 levels were examined with the ELISA. The mean age of the patients was 48 ± 12; 58 (61.7%) of them were male and 21.3% were diabetic. We found that in 77% of patients have impaired cognitive functions (MoCA total score <24). The NT-proBNP level had a significant and negative correlation with the MoCA Test Delayed Recall and Total Score. When the patients were divided into two groups according to NT-proBNP levels (above 10.500 and below), it was observed that the Mini-Mental Test Record Memory, MoCA Test Delayed Recall, and MoCA test total scores were significantly different from each other. In the present study, we show, for the first time in the literature, that NT-proBNP levels are associated with cognitive functions in dialysis patients.

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)0.001
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 score0.006
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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