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Effect of Combination of L-Arginine and L-Carnitine on Serum AGEs Level, Kidney and Endothelial Function in Patients with Chronic Heart Fa

2018· article· en· W2914457510 on OpenAlexvenueno aff
O. Kuryata, Oksana Sirenko, Abdunaser A. Zabida

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCarnitineInternal medicineEndocrinologyArginineRenal functionMedicineKidneyChemistryBiochemistryAmino acid

Abstract

fetched live from OpenAlex

The aim of the study to evaluate the effect of combination of L-Arginine with L-Carnitine on GFR, serum AGEs level and endothelial function in chronic heart failure (HF) patients with preserved ejection fraction (HFpEF). Materials and Methods: 35 patients with mean age 60,1 [56,7; 77,3] years with an established diagnosis of HFpEF were enrolled. The patients were randomly and blindly divided into 2 groups: first (1st) group pts were treated with a combination of L-Carnitine and L-Arginine in addition to standard treatment; 2nd group pts – with L-Arginine in addition to conventional treatment. Standard laboratory blood tests, lipid profile, glucose, renal and liver function tests, serum advanced glycation end-product (AGEs) level, echocardiographic examination, flow-mediated dilatation (FMD%) were performed for all patients baseline and after 10 days of treatment. The glomerular filtration rate (GFR) was estimated using the CKD-EPI formula. Results: Median level of AGEs was 1.72 [1.34; 1.93] mg/ml. The level of AGEs was correlated with age (R = 0.71, p<0.05), disease duration (R = 0.69, p<0.05). After 10 days of treatment with a combination of L-Carnitine with L-Arginine mean AGEs was decreased by 13.1% in comparison with L-Arginine treatment group (p=0.0003). After the treatment in 1st group mean AGEs was significantly lower in comparison with the 2nd group (p=0.004). Baseline median level of GFR was 81.2 [72,1; 86,2] ml/min and correlated with disease duration (R = 0.71, p<0.05), AGEs level (R = -0.73, p<0.05). The inclusion combination of L-arginine aspartate with L-Carnitine contributed to the significant increase of GFR level (p=0.003). The median FMD% level was 6.2 [4.4; 7.9] % and correlated with age (R=-0.61, p < 0.05), GFR (R=0.54, p < 0.05). After the 10 days it had been established significant increasing of FMD% level on 47.9 % in 1st group (p=0.0005), and on 29.3 % in 2nd group (p=0.003). Endothelial function normalizing was achieved in 10 (66 %) pts of 1st group and in 9 (45%) pts of 2nd group (p=0.002). Conclusion: The combination of L-Carnitine, and L-Arginine improves kidney, endothelial function and contributes to decreasing of AGEs level in pts with HFpEF.

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 score0.273
Threshold uncertainty score0.236

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 head0.008
GPT teacher head0.247
Teacher spread0.238 · 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".

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Citations0
Published2018
Admission routes1
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