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

**Authors:** Danying Yan, Yi Wang, Jing Hu, Renhua Lu, Chaoyang Ye, Nanmei Liu, Dongping Chen, Weiwei Liang, Liang Zheng, Wenrui Liu, Tianying Lan, Naiying Lan, Qing Shao, Shougang Zhuang, Xiaoyan Ma, Na Liu

PMC · DOI: 10.3389/fnut.2024.1351503 · Frontiers in Nutrition · 2024-08-13

## TL;DR

A new diagnostic model for identifying Protein Energy Wasting in hemodialysis patients was validated across multiple centers and showed good accuracy.

## Contribution

A novel nomogram for diagnosing Protein Energy Wasting in hemodialysis patients was externally validated for clinical use.

## Key findings

- The model showed good discrimination with an area under the curve of 0.777.
- Calibration curves indicated the model fits well with observed outcomes.
- The model's diagnostic efficacy was comparable to the gold standard method.

## Abstract

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.

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.

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 (p > 0.05).

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.

## Full-text entities

- **Genes:** ALB (albumin) [NCBI Gene 213] {aka FDAHT, HSA, PRO0883, PRO0903, PRO1341}
- **Diseases:** death (MESH:D003643)
- **Chemicals:** cholesterol (MESH:D002784)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

43 references — full list in the complete paper: https://tomesphere.com/paper/PMC11347328/full.md

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Source: https://tomesphere.com/paper/PMC11347328