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Clinical and pathogenetic features of the development of endothelial dysfunction in patients with chronic kidney disease and its contribution to the development of cognitive impairments

2024· article· en· W4400687152 on OpenAlexaboutno aff
M. G. Panchenko, М. З. Гасанов, М. М. Batyushin, A. A. Kazanskaya, G. I. Appakov

Bibliographic record

VenueNephrology (Saint-Petersburg) · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEndothelial dysfunctionKidney diseaseDiseaseCognitionMedicineIntensive care medicinePsychologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

THE AIM: to study the clinical and pathogenetic features of the development of endothelial dysfunction (ED) in patients with chronic kidney disease stages 3A-5D and its contribution to the development of cognitive impairment. PATIENTS AND METHODS: The study included 80 patients with CKD stages 3A-5D aged from 26 to 79 years (average age 58.9 ± 1.4 years): 43 women (average age 60.1 ± 1.9 years) and 37 men (average age 57.4±2.3 years). The patients were divided into 2 groups: group 1 included 40 patients with CKD 3A-5 (average age 59.9 ± 2.1 years), group 2 included 40 patients with CKD 5D (average age 58.1 ± 2 years). All patients underwent common and biochemical blood tests, the levels of endothelial nitric oxide synthase 3 (eNOS-3) and endothelin-1 (END-1) were determined, an endothelium-dependent vasodilation test (EDVD) was performed, testing for the presence and severity of cognitive disorders using the Montreal Cognitive Assessment Scale (MoCA) and the Mini Mental State Examination (MMSE). RESULTS: The prevalence of ED in the overall cohort of patients based on the results of a positive test with EDVD was 55 % of cases. ED was statistically significantly more often detected in the group of patients receiving hemodialysis treatment compared to patients in group 1: 70 % versus 40 %, respectively (p=0.007). The level of eNOS-3 in group 1 was higher compared to group 2 and amounted to 1.01±0.5 ng/ml versus 0.76±0.3 ng/ml (p=0.008). While the level of END-1 was statistically significantly lower in patients of group 1 compared to group 2 and amounted to 45.4±9.1 pg/ml versus 54.9±4.7 pg/ml (p<0.001). Cognitive impairments were identified in the general cohort: according to MMSE – in 67.5 % of cases, according to MoCA – in 71.3 %, and were more common in group 2. There were no statistically significant relationships between the results of the EDVD test and testing on the MoCA and MMSE scales. The level of eNOS-3 was lower in the subgroup of patients with cognitive impairment according to MoCA compared to the subgroup without it: 0.73±0.1 ng/ ml versus 0.94±0.2 ng/ml (p=0.127). The content of END-1 was statistically significantly higher in the subgroup of patients with cognitive impairment according to MoCA – 52.98±1.2 pg/ml compared to the subgroup without it – 47.67±1.5 pg/ml (p=0.043). When assessing the relationship between the levels of eNOS-3 and END-1 and the results of the EDVD test, it was found that in patients with a positive test in group 1, the level of eNOS-3 was statistically significantly higher compared to group 2 (p=0.01). An inverse relationship was observed for END-1; its level was lower in patients of group 1 compared to group 2 (p<0.01). CONCLUSION. Thus, the study revealed a high prevalence of endothelial dysfunction in patients with CKD stages 3A-5D. Progressive loss of renal function leads to dysregulation of the molecular mechanisms controlling vascular tone and the development of ED. eNOS-3 and END-1 have demonstrated high sensitivity for ED verification, and their detection improves the quality of the EDVD test. The development and progression of ED in patients with CKD is a multifactorial process that leads to hemodynamic disturbances in various organs and tissues, their damage and has a negative impact on the patient’s quality of life, his cognitive status and life expectancy.

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 score0.071
Threshold uncertainty score0.399

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 head0.013
GPT teacher head0.255
Teacher spread0.243 · 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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Citations2
Published2024
Admission routes1
Has abstractyes

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