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Tong Y, Ding Y, Han Z, Duan H, Geng X. Optimal rehabilitation strategies for early postacute stroke recovery: An ongoing inquiry. Brain Circ 2023; 9:201-204. [PMID: 38284113 PMCID: PMC10821682 DOI: 10.4103/bc.bc_33_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/26/2023] [Accepted: 08/29/2023] [Indexed: 01/30/2024] Open
Abstract
Early rehabilitation is crucial in reducing stroke-related disability, but the optimal training model remains unclear. We conducted a trial comparing different initiation timings and intensities of mobilization strategies after stroke. Results showed that early intensive mobilization had favorable outcomes at 3 months post-stroke, while very early intensive mobilization had poorer chances of favorable outcomes. Our investigation into brain injury mechanisms induced by very early exercise within 24 hours of stroke onset aligned with guidelines advising against high-dose very early mobilization. Additionally, we are studying the effects of various exercise intensities and frequencies on early stroke rehabilitation. Integrated rehabilitation models, such as combining remote ischemic conditioning (RIC) with exercise (RICE), hold promise. Our study found RICE to be safe and feasible for early rehabilitation of acute ischemic stroke patients, and further research is underway to determine its efficacy in a larger sample size. Despite extensive research, identifying the most effective early recovery strategies remains a complex challenge, necessitating ongoing work in the field of early rehabilitation after stroke.
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Affiliation(s)
- Yanna Tong
- Department of Neurology, Beijing Luhe Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Luhe Institute of Neuroscience, Capital Medical University, Beijing, China
| | - Yuchuan Ding
- Department of Neurosurgery, Wayne State University School of Medicine, Detroit, MI, USA
| | - Zhenzhen Han
- Department of Neurology, Beijing Luhe Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Luhe Institute of Neuroscience, Capital Medical University, Beijing, China
| | - Honglian Duan
- Department of Neurology, Beijing Luhe Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Luhe Institute of Neuroscience, Capital Medical University, Beijing, China
| | - Xiaokun Geng
- Department of Neurology, Beijing Luhe Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Luhe Institute of Neuroscience, Capital Medical University, Beijing, China
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Yan C, Zheng Y, Zhang X, Gong C, Wen S, Zhu Y, Jiang Y, Li X, Fu G, Pan H, Teng M, Xia L, Li J, Qian K, Lu X. Development and validation of a nomogram model for predicting unfavorable functional outcomes in ischemic stroke patients after acute phase. Front Aging Neurosci 2023; 15:1161016. [PMID: 37520125 PMCID: PMC10375043 DOI: 10.3389/fnagi.2023.1161016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/03/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction Prediction of post-stroke functional outcome is important for personalized rehabilitation treatment, we aimed to develop an effective nomogram for predicting long-term unfavorable functional outcomes in ischemic stroke patients after acute phase. Methods We retrospectively analyzed clinical data, rehabilitation data, and longitudinal follow-up data from ischemic stroke patients who underwent early rehabilitation at multiple centers in China. An unfavorable functional outcome was defined as a modified Rankin Scale (mRS) score of 3-6 at 90 days after onset. Patients were randomly allocated to either a training or test cohort in a ratio of 4:1. Univariate and multivariate logistic regression analyses were used to identify the predictors for the development of a predictive nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive ability in both the training and test cohorts. Results A total of 856 patients (training cohort: n = 684; test cohort: n = 172) were included in this study. Among them, 518 patients experienced unfavorable outcomes 90 days after ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment classification (p = 0.024), antihypertensive agents use [odds ratio (OR) = 1.86; p = 0.041], 15-day Barthel Index score (OR = 0.930; p < 0.001) and 15-day mRS score (OR = 13.494; p < 0.001) were selected as predictors for the unfavorable outcome nomogram. The nomogram model showed good predictive performance in both the training (AUC = 0.950) and test cohorts (AUC = 0.942). Conclusion The constructed nomogram model could be a practical tool for predicting unfavorable functional outcomes in ischemic stroke patients underwent early rehabilitation after acute phase.
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Affiliation(s)
- Chengjie Yan
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Zheng
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xintong Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chen Gong
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shibin Wen
- Department of Neurology, Jiuquan City People’s Hospital, Jiuquan, China
| | - Yonggang Zhu
- Department of Rehabilitation Medicine, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Yujuan Jiang
- Department of Rehabilitation Medicine, Cangzhou Central Hospital, Cangzhou, China
| | - Xipeng Li
- Department of Neurology, Xingtai People’s Hospital, Xingtai, China
| | - Gaoyong Fu
- Department of Rehabilitation Medicine, The First People’s Hospital of Yibin, Yibin, China
| | - Huaping Pan
- Department of Rehabilitation Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Meiling Teng
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lingfeng Xia
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jian Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kun Qian
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Lu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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