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ASSESSMENT OF COGNITIVE FUNCTION IN PATIENTS WITH CHRONIC KIDNEY DISEASE

2018· article· en· W2906742688 on OpenAlexaboutno aff
Priti Maheshwari

Bibliographic record

VenueAsian Journal of Pharmaceutical and Clinical Research · 2018
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDialysisKidney diseaseInternal medicineMontreal Cognitive AssessmentCognitionRenal functionPopulationDiseaseCognitive impairmentPsychiatry

Abstract

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Objectives: The objectives of this study were to evaluate cognitive profile in patients with chronic kidney disease (CKD) pre-dialysis and post-dialysis, to assess the severity of cognitive impairment in patients with kidney disease before and after dialysis, and to determine the association of cognitive impairment in relation to dialysis.Methods: A total of 59 patients were recruited with CKD Stage V on dialysis for >6 months. Cognitive function of the patient was assessed by Montreal Cognitive Assessment test scale method for three intervals (before dialysis and two intervals post-dialysis), and the incidence of impairment was analyzed using one-way ANOVA variance test.Results: Among the 59 patients, there were 13 patients with the age of 18–33 years (22.033%), 11 patients with from age 34 to 49 years (18.64%), 21 patients at the age of 50–65 years (35.59%), and 15 patients around 66–80 years (25.42%). From the above categories, population with the age of 50–65 years is at maximum affected by CKD. Among the 59 patients, 24 patients (40.677%) are male and 35 patients (59.33%) are female. There was a mild significant difference seen in cognitive functioning between pre-dialysis and post-dialysis (p≤0.02).Conclusion: It was found that patients with CKD had mild-to-moderate cognitive dysfunction due to morbidities associated with CKD. Inthis study, significant differences of cognitive function result in CKD patients and the severity of cognitive impairment was associatedwith the severity of the kidney disease, which improved with dialysis. Finally, our study suggests that cognitive performance wasimproved after initiation of dialysis and that further management through medications could provide a better outcome in cognitiveperformance.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.124
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.510
Teacher spread0.409 · 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
Has abstractyes

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