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Record W4229003597 · doi:10.1093/ndt/gfac083.050

MO868: The Impact of Cognitive Impairment in Sleep Disorders in Haemodialysis and Peritoneal Dialysis Patients

2022· article· en· W4229003597 on OpenAlexaboutno aff
Merita Rroji, Larisa Shehaj

Bibliographic record

VenueNephrology Dialysis Transplantation · 2022
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsEpworth Sleepiness ScaleMedicinePeritoneal dialysisInternal medicinePopulationMontreal Cognitive AssessmentDialysisHemodialysisRestless legs syndromePhysical therapyEnd stage renal diseaseDiseaseCognitive impairmentPolysomnographyPsychiatryInsomnia

Abstract

fetched live from OpenAlex

Abstract BACKGROUND AND AIMS Patients undergoing dialysis have a higher cognitive impairment (CI) risk than the general population. We evaluated the association of cognitive function (CI) in haemodialysis (HD)and peritoneal dialysis patients (PD) and the relationship with restless leg syndrome (RLS) and hypersomnolence. METHOD This is a cross-section study evaluating 167 patients who met the inclusion criteria in the study. Of these, 39% were on Haemodialysis, 22% on Peritoneal Dialysis, 19% on Transplant and 20% with CKD stage IV-V. Cognitive impairment (CI) in the study population was assessed based on the MoCA test. Patients with a MoCA global score of 24/30 were considered cognitively impaired. The rating is classified: light, moderate, heavy and very heavy.The International Restless Legs Syndrome study group (IRLSSG) was used for evaluation of restless leg and the Epworth Sleepiness Scale is used as a The Epworth Sleepiness Scale is widely used in the field of sleep medicine as a subjective measure of a patient's sleepiness. RESULTS The frequency of CI based on the test classification was 20% mild, 61% moderate, 15% severe and 3% very severe. In the studied population, it was observed that there is a significant relationship between cognitive impairment and forms of renal replacement therapy (P < 0.001) and the etiology of the underlying disease, P = 0.0011). The multivariate linear regression test shows an independent relationship of CI with age, where each increase of 1 year in age leads to a decrease of 0.094 points of the MoCA test. Patients in the study were evaluated as having enough sleep (60.8% patients), mildly sleepy (10.1% patients) and sleepy (29.1% patients). In 59% of patients that responded positively for restless leg syndrome, the degree of severity was significantly correlated with dialysis treatment (P < 0.001) and not with time in dialysis. The comparison between the three tests performed in the studied population showed a positive correlation of sleepiness and restless leg syndrome (r = 0.32) and a negative correlation between CG and CK(r = –0.38). CONCLUSION In this study, we saw the impact of RRT on CI, RLS and Sleepiness, affecting the quality of life negatively. Cognitive function disorders negatively impact the independence of realizing essential life functions, thus reducing compliance with medical care. Sleep fragmentation in sleepiness can also affect CI through dysfunction in neural networks, particularly in the frontal lobes, probably reducing the efficiency of restorative processes in the prefrontal cortex leading to cellular and biochemical stress. RLS is associated with sleepiness, and both negatively affect the quality of life and emotional states like anxiety and depression.

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)0.001
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 score0.015
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.296
Teacher spread0.285 · 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
Published2022
Admission routes1
Has abstractyes

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