Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study
BackgroundOur previous cross-sectional study has demonstrated the independently non-linear relationship between fasting C-peptide with renal dysfunction odds in patients with type 2 diabetes (T2D) in China. This longitudinal observational study aims to explore the role of serum C-peptide in risk pre...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-07-01
|
| Series: | Frontiers in Endocrinology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1227260/full |
| _version_ | 1797770337620852736 |
|---|---|
| author | Dongmei Sun Yifei Hu Yongjun Ma Huabin Wang |
| author_facet | Dongmei Sun Yifei Hu Yongjun Ma Huabin Wang |
| author_sort | Dongmei Sun |
| collection | DOAJ |
| description | BackgroundOur previous cross-sectional study has demonstrated the independently non-linear relationship between fasting C-peptide with renal dysfunction odds in patients with type 2 diabetes (T2D) in China. This longitudinal observational study aims to explore the role of serum C-peptide in risk prediction of new-onset renal dysfunction, then construct a predictive model based on serum C-peptide and other clinical parameters.MethodsThe patients with T2D and normal renal function at baseline were recruited in this study. The LASSO algorithm was performed to filter potential predictors from the baseline variables. Logistic regression (LR) was performed to construct the predictive model for new-onset renal dysfunction risk. Power analysis was performed to assess the statistical power of the model.ResultsDuring a 2-year follow-up period, 21.08% (35/166) of subjects with T2D and normal renal function at baseline progressed to renal dysfunction. Six predictors were determined using LASSO regression, including baseline albumin-to-creatinine ratio, glycated hemoglobin, hypertension, retinol-binding protein-to-creatinine ratio, quartiles of fasting C-peptide, and quartiles of fasting C-peptide to 2h postprandial C-peptide ratio. These 6 predictors were incorporated to develop model for renal dysfunction risk prediction using LR. Finally, the LR model achieved a high efficiency, with an AUC of 0.83 (0.76 - 0.91), an accuracy of 75.80%, a sensitivity of 88.60%, and a specificity of 70.80%. According to the power analysis, the statistical power of the LR model was found to be 0.81, which was at a relatively high level. Finally, a nomogram was developed to make the model more available for individualized prediction in clinical practice.ConclusionOur results indicated that the baseline level of serum C-peptide had the potential role in the risk prediction of new-onset renal dysfunction. The LR model demonstrated high efficiency and had the potential to guide individualized risk assessments for renal dysfunction in clinical practice. |
| first_indexed | 2024-03-12T21:21:50Z |
| format | Article |
| id | doaj.art-75c79deb84b148ec9a4e512087514c35 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-12T21:21:50Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-75c79deb84b148ec9a4e512087514c352023-07-28T17:33:27ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-07-011410.3389/fendo.2023.12272601227260Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational studyDongmei SunYifei HuYongjun MaHuabin WangBackgroundOur previous cross-sectional study has demonstrated the independently non-linear relationship between fasting C-peptide with renal dysfunction odds in patients with type 2 diabetes (T2D) in China. This longitudinal observational study aims to explore the role of serum C-peptide in risk prediction of new-onset renal dysfunction, then construct a predictive model based on serum C-peptide and other clinical parameters.MethodsThe patients with T2D and normal renal function at baseline were recruited in this study. The LASSO algorithm was performed to filter potential predictors from the baseline variables. Logistic regression (LR) was performed to construct the predictive model for new-onset renal dysfunction risk. Power analysis was performed to assess the statistical power of the model.ResultsDuring a 2-year follow-up period, 21.08% (35/166) of subjects with T2D and normal renal function at baseline progressed to renal dysfunction. Six predictors were determined using LASSO regression, including baseline albumin-to-creatinine ratio, glycated hemoglobin, hypertension, retinol-binding protein-to-creatinine ratio, quartiles of fasting C-peptide, and quartiles of fasting C-peptide to 2h postprandial C-peptide ratio. These 6 predictors were incorporated to develop model for renal dysfunction risk prediction using LR. Finally, the LR model achieved a high efficiency, with an AUC of 0.83 (0.76 - 0.91), an accuracy of 75.80%, a sensitivity of 88.60%, and a specificity of 70.80%. According to the power analysis, the statistical power of the LR model was found to be 0.81, which was at a relatively high level. Finally, a nomogram was developed to make the model more available for individualized prediction in clinical practice.ConclusionOur results indicated that the baseline level of serum C-peptide had the potential role in the risk prediction of new-onset renal dysfunction. The LR model demonstrated high efficiency and had the potential to guide individualized risk assessments for renal dysfunction in clinical practice.https://www.frontiersin.org/articles/10.3389/fendo.2023.1227260/fulltype 2 diabetesrenal dysfunctionserum C-peptidenew-onsetpredictive role |
| spellingShingle | Dongmei Sun Yifei Hu Yongjun Ma Huabin Wang Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study Frontiers in Endocrinology type 2 diabetes renal dysfunction serum C-peptide new-onset predictive role |
| title | Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study |
| title_full | Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study |
| title_fullStr | Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study |
| title_full_unstemmed | Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study |
| title_short | Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study |
| title_sort | predictive role of serum c peptide in new onset renal dysfunction in type 2 diabetes a longitudinal observational study |
| topic | type 2 diabetes renal dysfunction serum C-peptide new-onset predictive role |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1227260/full |
| work_keys_str_mv | AT dongmeisun predictiveroleofserumcpeptideinnewonsetrenaldysfunctionintype2diabetesalongitudinalobservationalstudy AT yifeihu predictiveroleofserumcpeptideinnewonsetrenaldysfunctionintype2diabetesalongitudinalobservationalstudy AT yongjunma predictiveroleofserumcpeptideinnewonsetrenaldysfunctionintype2diabetesalongitudinalobservationalstudy AT huabinwang predictiveroleofserumcpeptideinnewonsetrenaldysfunctionintype2diabetesalongitudinalobservationalstudy |