Evidence map›Paper›PMID 40822042›Full record

ArticleNeuropsychiatric disease and treatment2025

Development of a Lasso-Nomogram-Based Risk Prediction Model for Cognitive Frailty in Elderly MHD Patients.

Ning-Ning Xia, Jing Liu, Hongying Wang

Abstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ning-Ning XiaBlood Purification Center, Nanjing BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, People's Republic of China.ORCID 0000-0003-0337-7551
Jing LiuBlood Purification Center, Nanjing BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, People's Republic of China.ORCID 0009-0009-4206-4225
Hongying WangBlood Purification Center, Nanjing BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cognitive frailty is increasingly recognized among older adults receiving maintenance hemodialysis (MHD), yet effective screening tools tailored for this population are lacking. This study aimed to develop a predictive model to identify MHD patients of advanced age who are at high risk for cognitive frailty, thereby facilitating early detection and intervention. Methods: A cross-sectional study was conducted between February and December 2024, enrolling 223 older individuals undergoing MHD at a tertiary hospital in Nanjing, China. Data on demographic and clinical characteristics were collected, along with assessments using standardized instruments, including the Kidney Disease Quality of Life Instrument, Geriatric Depression Scale-5, Subjective Cognitive Decline Questionnaire-9, Montreal Cognitive Assessment, Clinical Dementia Rating, Fried Frailty Phenotype, and Cognitive Reserve Index Questionnaire. Least absolute shrinkage and selection operator (LASSO) regression was used to identify relevant variables, which were subsequently entered into multivariate logistic regression to determine independent risk factors. A nomogram was constructed based on the final model. Results: Cognitive frailty was identified in 85 patients, indicating a prevalence of 38.1%. Eight variables were found to be independent risk factors: serum phosphorus, hemoglobin level, depression score, cognitive reserve, age, dialysis duration, dialysis adequacy (Kt/V), and intradialytic hypotension. The predictive nomogram showed excellent discriminative performance, with an area under the receiver operating characteristic curve of 0.986 (95% confidence interval: 0.970-0.999), sensitivity of 94.9%, and specificity of 97.6%. Decision curve analysis demonstrated favorable clinical utility. Conclusion: Cognitive frailty is prevalent among older patients receiving MHD. The nomogram incorporating eight key variables provides a practical tool for early screening and personalized intervention in this high-risk population.

Indexed as

CFcognitive frailtycognitive reservemaintenance hemodialysisMHDprediction model

Identifiers

PMID40822042
PMCPMC12357605

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.