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A nomogram based on shear wave elastography for assessment of renal fibrosis in patients with chronic kidney disease

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Abstract

Background

Non-invasive evaluation of renal fibrosis is still challenging. This study aimed to establish a nomogram based on shear wave elastography (SWE) and clinical features for the assessment of the severity of renal fibrosis in patients with chronic kidney disease (CKD).

Methods

One hundred and sixty-two patients with CKD who underwent kidney biopsy and SWE examination were prospectively enrolled between April 2019 and December 2021. Patients were classified into mildly or moderately-severely impaired group based on pathology results. All patients were randomly divided into a training (n = 113) or validation cohort (n = 49). Least absolute shrinkage and selection operator (LASSO) algorithm was used for data dimensionality reduction and feature selection. Then, a diagnostic nomogram incorporating the selected features was constructed using multivariable logistic regression analysis. Nomogram performance was evaluated for discrimination, calibration, and clinical utility in training and validation cohorts.

Results

The established SWE nomogram, which integrated SWE value, hypertension, and estimated glomerular filtration rate, showed fine calibration and discrimination in both training (area under the receiver operator characteristic curve (AUC) = 0.94; 95% confidence interval (CI) 0.89–0.98) and validation cohorts (AUC = 0.84; 95% CI 0.71–0.96). Significant improvement in net reclassification and integrated discrimination indicated that the SWE value is a valuable biomarker to assess moderate-severe renal impairment. Furthermore, decision curve analysis revealed that the SWE nomogram has clinical value.

Conclusion

The proposed SWE nomogram showed favorable performance in determining individualized risk of moderate-severe renal pathological impairment in patients with CKD, which will help to facilitate clinical decision-making.

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Funding

The work was supported by the Natural Science Foundation of Guangdong Province [2018A0303130070]; National Natural Science Foundation of China [82072038].

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Author notes

  1. Ziman Chen and Jiaxin Chen contributed equally to this work.

Authors and Affiliations

  1. Department of Ultrasound, Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China

    Ziman Chen, Jiaxin Chen, Hui Chen & Zhongzhen Su

Authors
  1. Ziman Chen
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  2. Jiaxin Chen
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  3. Hui Chen
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  4. Zhongzhen Su
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Contributions

Conceptualization: ZC, JC, HC, and ZS; Data curation: JC; Formal analysis: ZS; Funding acquisition: ZS; Investigation: ZS; Methodology: ZC, JC, HC; Project administration: ZS; Resources: ZS; Software: ZC; Supervision: ZS; Validation: ZS; Visualization: ZS; Writing-original draft: ZC; Writing-review and editing: ZS.

Corresponding author

Correspondence to Zhongzhen Su.

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Conflict of interest

The authors declare that there is no conflict of interest.

Ethical approval

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Fifth Affiliated Hospital of Sun Yat-sen University (protocol code K09-1; approval date: May 2019).

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Chen, Z., Chen, J., Chen, H. et al. A nomogram based on shear wave elastography for assessment of renal fibrosis in patients with chronic kidney disease. J Nephrol 36, 719–729 (2023). https://doi.org/10.1007/s40620-022-01521-8

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  • DOI: https://doi.org/10.1007/s40620-022-01521-8

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