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Record W3158989165 · doi:10.1080/0886022x.2021.1914656

A pilot study of thiamin and folic acid in hemodialysis patients with cognitive impairment

2021· article· en· W3158989165 on OpenAlexaboutno aff

Bibliographic record

VenueRenal Failure · 2021
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsnot available
Fundersnot available
KeywordsHemodialysisCognitive impairmentFolic acidKidney diseaseHomocysteineCognition

Abstract

fetched live from OpenAlex

Objective This study aimed to explore the effectiveness of thiamin and folic acid supplementation on the improvement of the cognitive function in patients with maintenance hemodialysis.Method In the present study, we randomly assigned patients undergoing hemodialysis who had the Montreal Cognitive Assessment (MoCA) score lower than 26 to treatment group (n = 25, thiamin 90 mg/day combined with folic acid 30 mg/day) or control group (n = 25, nonintervention). All subjects were followed up for 96 weeks. The primary outcome was the improvement of the MoCA score. The secondary outcomes included homocysteine level, survival and safety.Results Patients in treatment group had an increase of the MoCA score from 21.95 ± 3.81 at baseline to 25.68 ± 1.96 at week 96 (p < 0.001, primary outcome), as compared with the MoCA score from 20.69 ± 3.40 to 19.62 ± 3.58 in control group. Thiamin combined with folic acid treatment also resulted in lower level of serum homocysteine in treatment group compare with control group at week 96 (p < 0.05, secondary outcome). 3 patients and 9 patients died during follow-up period in treatment and control group respectively (p = 0.048). The proportion of adverse events in treatment group was significantly lower than that in control group.Conclusion Hemodialysis patients with cognitive impairment treated with thiamin and folic acid had a significant improvement in MoCA score.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.246
Teacher spread0.235 · 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 designNon-randomized trial
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

Citations10
Published2021
Admission routes1
Has abstractyes

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