MétaCan
Menu
Back to cohort
Record W4412774932 · doi:10.3389/fneur.2025.1619083

The relationship between protein-energy wasting and cognitive impairment in patients receiving maintenance hemodialysis

2025· article· en· W4412774932 on OpenAlexaboutno aff
Jun Liu, Jingfang Wan, Kehong Chen, Yani He, Weiwei Zhang, Dan Li

Bibliographic record

VenueFrontiers in Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentWastingLogistic regressionInternal medicineHemodialysisCognitionPhysical therapyCognitive impairment

Abstract

fetched live from OpenAlex

Objectives To investigate the relationship between protein-energy wasting (PEW) and cognitive impairment (CI) in patients undergoing maintenance hemodialysis (MHD). Methods A total of 185 patients undergoing MHD between June 2020 and April 2022 were initially recruited. Among the initially recruited patients, 25 patients were excluded, and 160 patients were finally involved in this study. The Montreal Cognitive Assessment-Basic (MoCA-B) was utilized to assess patients’ cognitive functions. Patients were categorized into two groups based on the presence or absence of PEW as per the diagnostic criteria. The severity of PEW was evaluated using the Scored Patient-Generated Subjective Global Assessment (PG-SGA) and Malnutrition Inflammation Score (MIS). Baseline data, PEW-related indicators, and cognitive function scores were compared between the CI and non-CI groups. Logistic regression analysis was employed to identify the factors influencing CI in patients undergoing MHD. Results There were significant differences between the two groups in terms of age, educational level, Kt/V, PEW detection rate, PEW-related indicators [albumin (ALB)], lean body mass, arm muscle circumference (AMC), normalized dietary protein intake (nDPI), PG-SGA score, and MIS score (p < 0.05). The MoCA-B scores of MHD patients with PEW were significantly lower than those of patients without PEW (p < 0.05). The two groups exhibited significant differences in executive function, orientation, abstraction, delayed recall, and attention scores (p < 0.05). Multivariate logistic regression analysis indicated that age, PEW severity, Kt/V, and ALB were significant influential factors of CI in patients undergoing MHD (p < 0.05). Conclusion PEW was closely associated with CI in patients undergoing MHD. Those combined with PEW were more likely to develop CI, and to suffer from more severe CI. Active precautionary measures should be taken against PEW to delay the progression of CI in patients undergoing MHD.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.009
GPT teacher head0.234
Teacher spread0.226 · 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 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicDialysis and Renal Disease ManagementFrench-language works237,207