Intelligent system to predict intradialytic hypotension in chronic hemodialysis
Background: Intradialytic hypotension (IDH) is a serious complication and a major risk factor of increased mortality during hemodialysis (HD). However, predicting the occurrence of intradialytic blood pressure (BP) fluctuations clinically is difficult. This study aimed to develop an intelligent syst...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2018-10-01
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| Series: | Journal of the Formosan Medical Association |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0929664618302584 |
| _version_ | 1818517760743833600 |
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| author | Cheng-Jui Lin Chih-Yang Chen Pei-Chen Wu Chi-Feng Pan Hong-Mou Shih Ming-Yuan Huang Li-Hua Chou Jin-Sheng Tang Chih-Jen Wu |
| author_facet | Cheng-Jui Lin Chih-Yang Chen Pei-Chen Wu Chi-Feng Pan Hong-Mou Shih Ming-Yuan Huang Li-Hua Chou Jin-Sheng Tang Chih-Jen Wu |
| author_sort | Cheng-Jui Lin |
| collection | DOAJ |
| description | Background: Intradialytic hypotension (IDH) is a serious complication and a major risk factor of increased mortality during hemodialysis (HD). However, predicting the occurrence of intradialytic blood pressure (BP) fluctuations clinically is difficult. This study aimed to develop an intelligent system with capability of predicting IDH. Methods: In developing and training the prediction models in the intelligent system, we used a database of 653 HD outpatients who underwent 55,516 HD treatment sessions, resulting in 285,705 valid BP records. We built models to predict IDH at the next BP check by applying time-dependent logistic regression analyses. Results: Our results showed the sensitivity of 86% and specificity of 81% for both nadir systolic BP (SBP) of <90 mmHg and <100 mmHg, suggesting good performance of our prediction models. We obtained similar results in validating via test data and data of newly enrolled patients (new-patient data), which is important for simulating prospective situations wherein dialysis staff are unfamiliar with new patients. This compensates for the retrospective nature of the BP records used in our study. Conclusion: The use of this validated intelligent system can identify patients who are at risk of IDH in advance, which may facilitate well-timed personalized management and intervention. Keywords: Hemodialysis, Intelligent system, Intradialytic hypotension |
| first_indexed | 2024-12-11T01:00:37Z |
| format | Article |
| id | doaj.art-4fcc3498fada4a9a9a503e162e86cfba |
| institution | Directory Open Access Journal |
| issn | 0929-6646 |
| language | English |
| last_indexed | 2024-12-11T01:00:37Z |
| publishDate | 2018-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of the Formosan Medical Association |
| spelling | doaj.art-4fcc3498fada4a9a9a503e162e86cfba2022-12-22T01:26:20ZengElsevierJournal of the Formosan Medical Association0929-66462018-10-0111710888893Intelligent system to predict intradialytic hypotension in chronic hemodialysisCheng-Jui Lin0Chih-Yang Chen1Pei-Chen Wu2Chi-Feng Pan3Hong-Mou Shih4Ming-Yuan Huang5Li-Hua Chou6Jin-Sheng Tang7Chih-Jen Wu8Division of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, Mackay Medical College, New Taipei, Taiwan; Mackay Junior College of Medicine, Nursing and Management, Taipei, TaiwanDivision of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, TaiwanDivision of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, TaiwanDivision of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, TaiwanDivision of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan; Graduate Institute of Physiology, College of Medicine, National Taiwan University, Taipei, TaiwanDepartment of Medicine, Mackay Medical College, New Taipei, TaiwanDivision of Hemodialysis and Peritoneal Dialysis, Department of Nursing, MacKay Memorial Hospital, Taipei, TaiwanDepartment of Information Technology, MacKay Memorial Hospital, Taipei, TaiwanDivision of Nephrology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, Mackay Medical College, New Taipei, Taiwan; Graduate Institute of Medical Sciences and Department of Pharmacology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan; Corresponding author. Department of Medicine, MacKay Memorial Hospital, No. 92, Sec. 2, Zhongshan N. Rd., Taipei 10449, Taiwan. Fax: +886 2 25433642.Background: Intradialytic hypotension (IDH) is a serious complication and a major risk factor of increased mortality during hemodialysis (HD). However, predicting the occurrence of intradialytic blood pressure (BP) fluctuations clinically is difficult. This study aimed to develop an intelligent system with capability of predicting IDH. Methods: In developing and training the prediction models in the intelligent system, we used a database of 653 HD outpatients who underwent 55,516 HD treatment sessions, resulting in 285,705 valid BP records. We built models to predict IDH at the next BP check by applying time-dependent logistic regression analyses. Results: Our results showed the sensitivity of 86% and specificity of 81% for both nadir systolic BP (SBP) of <90 mmHg and <100 mmHg, suggesting good performance of our prediction models. We obtained similar results in validating via test data and data of newly enrolled patients (new-patient data), which is important for simulating prospective situations wherein dialysis staff are unfamiliar with new patients. This compensates for the retrospective nature of the BP records used in our study. Conclusion: The use of this validated intelligent system can identify patients who are at risk of IDH in advance, which may facilitate well-timed personalized management and intervention. Keywords: Hemodialysis, Intelligent system, Intradialytic hypotensionhttp://www.sciencedirect.com/science/article/pii/S0929664618302584 |
| spellingShingle | Cheng-Jui Lin Chih-Yang Chen Pei-Chen Wu Chi-Feng Pan Hong-Mou Shih Ming-Yuan Huang Li-Hua Chou Jin-Sheng Tang Chih-Jen Wu Intelligent system to predict intradialytic hypotension in chronic hemodialysis Journal of the Formosan Medical Association |
| title | Intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| title_full | Intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| title_fullStr | Intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| title_full_unstemmed | Intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| title_short | Intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| title_sort | intelligent system to predict intradialytic hypotension in chronic hemodialysis |
| url | http://www.sciencedirect.com/science/article/pii/S0929664618302584 |
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