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Record W4394334103 · doi:10.6084/m9.figshare.14680514

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

2021· dataset· en· W4394334103 on OpenAlexaffabout
Renhua Lu, Yan Fang, Yijun Zhou, Miaolin Che, Jianxiao Shen, Qian Liu, Shuting Pan, Yan Lin, Qin Wang, Shan Mou, Zhaohui Ni, Leyi Gu

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCognitive impairmentFolic acidHemodialysisMedicineInternal medicineCognitionPsychiatry

Abstract

fetched live from OpenAlex

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. In the present study, we randomly assigned patients undergoing hemodialysis who had the Montreal Cognitive Assessment (MoCA) score lower than 26 to treatment group (<i>n</i> = 25, thiamin 90 mg/day combined with folic acid 30 mg/day) or control group (<i>n</i> = 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. 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 (<i>p</i> &lt; 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 (<i>p</i> &lt; 0.05, secondary outcome). 3 patients and 9 patients died during follow-up period in treatment and control group respectively (<i>p</i> = 0.048). The proportion of adverse events in treatment group was significantly lower than that in control group. 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.943
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0110.000

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 head0.032
GPT teacher head0.278
Teacher spread0.247 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes2
Has abstractyes

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