Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis
BackgroundEarly identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.ObjectiveTo establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).MethodsThe derivation cohort was from a...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-02-01
|
| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128069/full |
| _version_ | 1797900490801938432 |
|---|---|
| author | Xixi Liu Dong Chen Hongmin Fu Xinbang Liu Qiumei Zhang Jingyun Zhang Min Ding Juanjuan Wen Bai Chang |
| author_facet | Xixi Liu Dong Chen Hongmin Fu Xinbang Liu Qiumei Zhang Jingyun Zhang Min Ding Juanjuan Wen Bai Chang |
| author_sort | Xixi Liu |
| collection | DOAJ |
| description | BackgroundEarly identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.ObjectiveTo establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).MethodsThe derivation cohort was from a meta-analysis. Risk factors and the corresponding risk ratio (RR) were extracted. Only risk factors with statistical significance were included in the model and were scored by their weightings. An external cohort were used to validate this model. The outcome was the occurrence of DPN.ResultsA total of 95,604 patients with T2DM from 18 cohorts were included. Age, smoking, body mass index, duration of diabetes, hemoglobin A1c, low HDL-c, high triglyceride, hypertension, diabetic retinopathy, diabetic kidney disease, and cardiovascular disease were enrolled in the final model. The highest score was 52.0. The median follow-up of validation cohort was 4.29 years. The optimal cut-off point was 17.0, with a sensitivity of 0.846 and a specificity of 0.668, respectively. According to the total scores, patients from the validation cohort were divided into low-, moderate-, high- and very high-risk groups. The risk of developing DPN was significantly increased in moderate- (RR 3.3, 95% CI 1.5–7.2, P = 0.020), high- (RR 15.5, 95% CI 7.6–31.6, P < 0.001), and very high-risk groups (RR 45.0, 95% CI 20.5–98.8, P < 0.001) compared with the low-risk group.ConclusionA risk prediction model for DPN including 11 common clinical indicators were established. It is a simple and reliable tool for early prevention and intervention of DPN in patients with T2DM. |
| first_indexed | 2024-04-10T08:45:50Z |
| format | Article |
| id | doaj.art-6648a85b3b2c499bb140f127e8c7e803 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-10T08:45:50Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-6648a85b3b2c499bb140f127e8c7e8032023-02-22T07:44:09ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-02-011110.3389/fpubh.2023.11280691128069Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysisXixi Liu0Dong Chen1Hongmin Fu2Xinbang Liu3Qiumei Zhang4Jingyun Zhang5Min Ding6Juanjuan Wen7Bai Chang8NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaNHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, ChinaBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, ChinaBackgroundEarly identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.ObjectiveTo establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).MethodsThe derivation cohort was from a meta-analysis. Risk factors and the corresponding risk ratio (RR) were extracted. Only risk factors with statistical significance were included in the model and were scored by their weightings. An external cohort were used to validate this model. The outcome was the occurrence of DPN.ResultsA total of 95,604 patients with T2DM from 18 cohorts were included. Age, smoking, body mass index, duration of diabetes, hemoglobin A1c, low HDL-c, high triglyceride, hypertension, diabetic retinopathy, diabetic kidney disease, and cardiovascular disease were enrolled in the final model. The highest score was 52.0. The median follow-up of validation cohort was 4.29 years. The optimal cut-off point was 17.0, with a sensitivity of 0.846 and a specificity of 0.668, respectively. According to the total scores, patients from the validation cohort were divided into low-, moderate-, high- and very high-risk groups. The risk of developing DPN was significantly increased in moderate- (RR 3.3, 95% CI 1.5–7.2, P = 0.020), high- (RR 15.5, 95% CI 7.6–31.6, P < 0.001), and very high-risk groups (RR 45.0, 95% CI 20.5–98.8, P < 0.001) compared with the low-risk group.ConclusionA risk prediction model for DPN including 11 common clinical indicators were established. It is a simple and reliable tool for early prevention and intervention of DPN in patients with T2DM.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128069/fulltype 2 diabetes mellitusdiabetic peripheral neuropathyrisk factorsprediction modelcohort studymeta-analysis |
| spellingShingle | Xixi Liu Dong Chen Hongmin Fu Xinbang Liu Qiumei Zhang Jingyun Zhang Min Ding Juanjuan Wen Bai Chang Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis Frontiers in Public Health type 2 diabetes mellitus diabetic peripheral neuropathy risk factors prediction model cohort study meta-analysis |
| title | Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis |
| title_full | Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis |
| title_fullStr | Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis |
| title_full_unstemmed | Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis |
| title_short | Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis |
| title_sort | development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta analysis |
| topic | type 2 diabetes mellitus diabetic peripheral neuropathy risk factors prediction model cohort study meta-analysis |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128069/full |
| work_keys_str_mv | AT xixiliu developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT dongchen developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT hongminfu developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT xinbangliu developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT qiumeizhang developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT jingyunzhang developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT minding developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT juanjuanwen developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis AT baichang developmentandvalidationofariskpredictionmodelforearlydiabeticperipheralneuropathybasedonasystematicreviewandmetaanalysis |