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A Study Describing Patients’ Perspectives on Cognitive Function Screening During Hemodialysis

2022· article· en· W4284958335 on OpenAlexaboutno aff
Maureen Metzger, Souad Benloukil, Zahra Alisa, Liza Foxx

Bibliographic record

VenueNephrology Nursing Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMedicineHemodialysisDepression (economics)Geriatric Depression ScaleCognitive impairmentScreening testDiseasePhysical therapyGerontologyClinical psychologyFamily medicineInternal medicinePsychiatryDepressive symptoms

Abstract

fetched live from OpenAlex

Routine screening of cognitive function in patients with end stage kidney disease (ESKD) is recommended, yet rarely it happens. This study sought to identify barriers to cognitive function screening for patients with ESKD receiving in-center hemodialysis. To ascertain their perceptions of cognitive function screening, 100 patients aged 50 years and older (48% female, 49% Black/African-American) from seven hemodialysis centers participated in structured interviews after completing the Montreal Cognitive Assessment and Geriatric Depression Scale. Participants rated the screening experience favorably, indicating cognitive function screening is acceptable to patients receiving hemodialysis. The level of cognitive impairment was the only factor significantly associated with screening evaluation scores, with participants with scores indicating mild or moderate impairment evaluating screening less favorably than those with normal cognitive function scores. Next steps include identifying systems level barriers and establishing appropriate follow up for patients with abnormal screening results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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