Journal of Inflammation Research (Jul 2024)

Prediction Model for Early-Stage CKD Using the Naples Prognostic Score and Plasma Indoleamine 2,3-dioxygenase Activity

  • Hong H,
  • Zheng J,
  • Shi H,
  • Zhou S,
  • Chen Y,
  • Li M

Journal volume & issue
Vol. Volume 17
pp. 4669 – 4681

Abstract

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Hao Hong,1 Junyao Zheng,2 Haimin Shi,2 Suya Zhou,3 Yue Chen,4 Ming Li2 1Department of Intensive Care Unit, The First Affiliated Hospital of Soochow University, Soochow, People’s Republic of China; 2Laboratory Nephrology, The First Affiliated Hospital of Soochow University, Soochow, People’s Republic of China; 3Laboratory Nephrology, Jinshan Hospital of Fudan University, Shanghai, People’s Republic of China; 4Laboratory Nephrology, The First People’s Hospital of Kunshan, Soochow, People’s Republic of ChinaCorrespondence: Ming Li, Email [email protected]: Changes in inflammation, immunity, and nutritional status can promote the development of chronic kidney disease (CKD), and the Naples prognostic score (NPS) reflects changes in these three general clinical parameters. Indoleamine 2.3-dioxygenase (IDO) can block the function of inflammatory cells and inhibit the production of inflammatory cytokines. We examined use of the NPS and IDO activity to predict early-stage CKD.Patients and Methods: Clinical and demographic parameters and the NPS were recorded for 47 CKD patients and 30 healthy controls. A one-way ANOVA or the rank sum test was used to compare variables in the different groups. Spearman or Pearson correlation coefficients were calculated, and logistic regression was used to identify significant factors. Receiver operating characteristic (ROC) analysis was also performed.Results: The NPS had a positive correlation with plasma IDO activity and IDO activity was lowest in controls, and increased with CKD stage. ROC analysis indicated that NPS had an area under the curve (AUC) of 0.779 when comparing controls with all CKD patients. A prediction model for CKD (− 4.847 + [1.234 × NPS] + [6.160 × plasma IDO activity]) demonstrated significant differences between controls and patients with early-stage CKD, and for patients with different stages of CKD. This model had AUC values of 0.885 (control vs CKD1– 4), 0.876 (control vs CKD2), 0.818 (CKD2 vs CKD3), and 0.758 (CKD3 vs CKD4).Conclusion: A prediction model based on the NPS and IDO provided good to excellent predictions of early-stage CKD.Keywords: inflammation, immune, nutrition, score, metabolomic, kynurenine pathway

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