Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes
BackgroundPolysomnography (PSG) is the gold standard for diagnosis of sleep-disordered breathing (SDB). But it is impractical to perform PSG in all patients with diabetes. The objective was to develop a clinically easy-to-use prediction model to diagnosis SDB in patients with diabetes.MethodsA total...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-03-01
|
| Series: | Frontiers in Endocrinology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2021.598470/full |
| _version_ | 1818439190050766848 |
|---|---|
| author | Lihong Chen Weiwei Tang Chun Wang Dawei Chen Yun Gao Wanxia Ma Panpan Zha Fei Lei Xiangdong Tang Xingwu Ran |
| author_facet | Lihong Chen Weiwei Tang Chun Wang Dawei Chen Yun Gao Wanxia Ma Panpan Zha Fei Lei Xiangdong Tang Xingwu Ran |
| author_sort | Lihong Chen |
| collection | DOAJ |
| description | BackgroundPolysomnography (PSG) is the gold standard for diagnosis of sleep-disordered breathing (SDB). But it is impractical to perform PSG in all patients with diabetes. The objective was to develop a clinically easy-to-use prediction model to diagnosis SDB in patients with diabetes.MethodsA total of 440 patients with diabetes were recruited and underwent overnight PSG at West China Hospital. Prediction algorithms were based on oxygen desaturation index (ODI) and other variables, including sex, age, body mass index, Epworth score, mean oxygen saturation, and total sleep time. Two phase approach was employed to derivate and validate the models.ResultsODI was strongly correlated with apnea-hypopnea index (AHI) (rs = 0.941). In the derivation phase, the single cutoff model with ODI was selected, with area under the receiver operating characteristic curve (AUC) of 0.956 (95%CI 0.917–0.994), 0.962 (95%CI 0.943–0.981), and 0.976 (95%CI 0.956–0.996) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. We identified the cutoff of ODI 5/h, 15/h, and 25/h, as having important predictive value for AHI ≥5/h, ≥15/h, and ≥30/h, respectively. In the validation phase, the AUC of ODI was 0.941 (95%CI 0.904–0.978), 0.969 (95%CI 0.969–0.991), and 0.949 (95%CI 0.915–0.983) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. The sensitivity of ODI ≥5/h, ≥15/h, and ≥25/h was 92%, 90%, and 93%, respectively, while the specificity was 73%, 89%, and 85%, respectively.ConclusionsODI is a sensitive and specific tool to predict SDB in patients with diabetes. |
| first_indexed | 2024-12-14T17:52:31Z |
| format | Article |
| id | doaj.art-97cb0571222e4d73b31c1daca76e36a7 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-12-14T17:52:31Z |
| publishDate | 2021-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-97cb0571222e4d73b31c1daca76e36a72022-12-21T22:52:38ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922021-03-011210.3389/fendo.2021.598470598470Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With DiabetesLihong Chen0Weiwei Tang1Chun Wang2Dawei Chen3Yun Gao4Wanxia Ma5Panpan Zha6Fei Lei7Xiangdong Tang8Xingwu Ran9Diabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaSleep Medicine Center, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, ChinaSleep Medicine Center, Mental Health Center, Translational Neuroscience Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, ChinaDiabetic Foot Care Center, Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, ChinaBackgroundPolysomnography (PSG) is the gold standard for diagnosis of sleep-disordered breathing (SDB). But it is impractical to perform PSG in all patients with diabetes. The objective was to develop a clinically easy-to-use prediction model to diagnosis SDB in patients with diabetes.MethodsA total of 440 patients with diabetes were recruited and underwent overnight PSG at West China Hospital. Prediction algorithms were based on oxygen desaturation index (ODI) and other variables, including sex, age, body mass index, Epworth score, mean oxygen saturation, and total sleep time. Two phase approach was employed to derivate and validate the models.ResultsODI was strongly correlated with apnea-hypopnea index (AHI) (rs = 0.941). In the derivation phase, the single cutoff model with ODI was selected, with area under the receiver operating characteristic curve (AUC) of 0.956 (95%CI 0.917–0.994), 0.962 (95%CI 0.943–0.981), and 0.976 (95%CI 0.956–0.996) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. We identified the cutoff of ODI 5/h, 15/h, and 25/h, as having important predictive value for AHI ≥5/h, ≥15/h, and ≥30/h, respectively. In the validation phase, the AUC of ODI was 0.941 (95%CI 0.904–0.978), 0.969 (95%CI 0.969–0.991), and 0.949 (95%CI 0.915–0.983) for predicting AHI ≥5/h, ≥15/h, and ≥30/h, respectively. The sensitivity of ODI ≥5/h, ≥15/h, and ≥25/h was 92%, 90%, and 93%, respectively, while the specificity was 73%, 89%, and 85%, respectively.ConclusionsODI is a sensitive and specific tool to predict SDB in patients with diabetes.https://www.frontiersin.org/articles/10.3389/fendo.2021.598470/fullsleep disordered breathing (obstructive/central sleep apnea)diabetesoxygen desaturation index (ODI)polysomnogram (PSG)diagnostic accuracy |
| spellingShingle | Lihong Chen Weiwei Tang Chun Wang Dawei Chen Yun Gao Wanxia Ma Panpan Zha Fei Lei Xiangdong Tang Xingwu Ran Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes Frontiers in Endocrinology sleep disordered breathing (obstructive/central sleep apnea) diabetes oxygen desaturation index (ODI) polysomnogram (PSG) diagnostic accuracy |
| title | Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes |
| title_full | Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes |
| title_fullStr | Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes |
| title_full_unstemmed | Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes |
| title_short | Diagnostic Accuracy of Oxygen Desaturation Index for Sleep-Disordered Breathing in Patients With Diabetes |
| title_sort | diagnostic accuracy of oxygen desaturation index for sleep disordered breathing in patients with diabetes |
| topic | sleep disordered breathing (obstructive/central sleep apnea) diabetes oxygen desaturation index (ODI) polysomnogram (PSG) diagnostic accuracy |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2021.598470/full |
| work_keys_str_mv | AT lihongchen diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT weiweitang diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT chunwang diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT daweichen diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT yungao diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT wanxiama diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT panpanzha diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT feilei diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT xiangdongtang diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes AT xingwuran diagnosticaccuracyofoxygendesaturationindexforsleepdisorderedbreathinginpatientswithdiabetes |