Evidence map›Paper›PMID 39193561›Full record

ArticleFrontiers in nutrition2024

External validation of a novel nomogram for diagnosis of Protein Energy Wasting in adult hemodialysis patients.

Danying Yan, Yi Wang, Jing Hu, Renhua Lu, Chaoyang Ye, Nanmei Liu, Dongping Chen, Weiwei Liang, Liang Zheng, Wenrui Liu and 6 more

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. 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

16 authors.

Danying Yan *Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Yi Wang *Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Jing HuDepartment of Nephrology, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Renhua LuDepartment of Nephrology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Chaoyang YeDepartment of Nephrology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Nanmei LiuInternational Medicine III (Nephrology & Endocrinology), Naval Medical Center of People's Liberation Army of China, Naval Medical University, Shanghai, China.
Dongping ChenDepartment of Nephrology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Weiwei LiangDepartment of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Liang ZhengKey Laboratory of Arrhythmias of the Ministry of Education of China, Research Center for Translational Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Wenrui LiuDepartment of Nephrology, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Tianying LanDepartment of Nephrology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Naiying LanInternational Medicine III (Nephrology & Endocrinology), Naval Medical Center of People's Liberation Army of China, Naval Medical University, Shanghai, China.
Qing ShaoInternational Medicine III (Nephrology & Endocrinology), Naval Medical Center of People's Liberation Army of China, Naval Medical University, Shanghai, China.
Shougang ZhuangDepartment of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Xiaoyan MaDepartment of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Na LiuDepartment of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Protein Energy Wasting (PEW) has high incidence in adult hemodialysis patients and refers to a state of decreased protein and energy substance. It has been demonstrated that PEW highly affects the quality of survival and increases the risk of death. Nevertheless, its diagnostic criteria are complex in clinic. To simplify the diagnosis method of PEW in adult hemodialysis patients, we previously established a novel clinical prediction model that was well-validated internally using bootstrapping. In this multicenter cross-sectional study, we aimed to externally validate this nomogram in a new cohort of adult hemodialysis patients. Methods: The novel prediction model was built by combining four independent variables with part of the International Society of Renal Nutrition and Metabolism (ISRNM) diagnostic criteria including albumin, total cholesterol, and body mass index (BMI). We evaluated the performance of the new model using discrimination (Concordance Index), calibration plots, and Clinical Impact Curve to assess its predictive utility. Results: From September 1st, 2022 to August 31st, 2023, 1,158 patients were screened in five medical centers in Shanghai. 622 (53.7%) hemodialysis patients were included for analysis. The PEW predictive model was acceptable discrimination with the area under the curve of 0.777 (95% CI 0.741-0.814). Additionally, the model revealed well-fitted calibration curves. The McNemar test showed the novel model had similar diagnostic efficacy with the gold standard diagnostic method ( Conclusion: Our results from this cross-sectional external validation study further demonstrate that the novel model is a valid tool to identify PEW in adult hemodialysis patients effectively.

Indexed as

diagnosisexternal validationhemodialysisprediction modelProtein Energy Wasting

Identifiers

PMID39193561
PMCPMC11347328

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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.