1
|
Chen D, Zhao Z, Zhang S, Chen S, Wu X, Shi J, Liu N, Pan C, Tang Y, Meng C, Zhao X, Tao B, Liu W, Chen D, Ding H, Zhang P, Tang Z. Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques. Transl Stroke Res 2024:10.1007/s12975-024-01244-x. [PMID: 38558011 DOI: 10.1007/s12975-024-01244-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/06/2024] [Accepted: 03/19/2024] [Indexed: 04/04/2024]
Abstract
Intracerebral hemorrhage (ICH) is the most serious form of stroke and has limited available therapeutic options. As knowledge on ICH rapidly develops, cutting-edge techniques in the fields of surgical robots, regenerative medicine, and neurorehabilitation may revolutionize ICH treatment. However, these new advances still must be translated into clinical practice. In this review, we examined several emerging therapeutic strategies and their major challenges in managing ICH, with a particular focus on innovative therapies involving robot-assisted minimally invasive surgery, stem cell transplantation, in situ neuronal reprogramming, and brain-computer interfaces. Despite the limited expansion of the drug armamentarium for ICH over the past few decades, the judicious selection of more efficacious therapeutic modalities and the exploration of multimodal combination therapies represent opportunities to improve patient prognoses after ICH.
Collapse
Affiliation(s)
- Danyang Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhixian Zhao
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shenglun Zhang
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shiling Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuan Wu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jian Shi
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Na Liu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chao Pan
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yingxin Tang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Cai Meng
- School of Astronautics, Beihang University, Beijing, China
| | - Xingwei Zhao
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bo Tao
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenjie Liu
- Beijing WanTeFu Medical Instrument Co., Ltd., Beijing, China
| | - Diansheng Chen
- Institute of Robotics, School of Mechanical Engineering and Automation, Beihang University, Beijing, China
| | - Han Ding
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ping Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Zhouping Tang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| |
Collapse
|
2
|
Zhang Y, Rao C, Ran X, Hu H, Jing L, Peng S, Zhu W, Li S. How to predict the death risk after an in-hospital cardiac arrest (IHCA) in intensive care unit? A retrospective double-centre cohort study from a tertiary hospital in China. BMJ Open 2023; 13:e074214. [PMID: 37798030 PMCID: PMC10565198 DOI: 10.1136/bmjopen-2023-074214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 08/07/2023] [Indexed: 10/07/2023] Open
Abstract
OBJECTIVES Our objective is to develop a prediction tool to predict the death after in-hospital cardiac arrest (IHCA). DESIGN We conducted a retrospective double-centre observational study of IHCA patients from January 2015 to December 2021. Data including prearrest diagnosis, clinical features of the IHCA and laboratory results after admission were collected and analysed. Logistic regression analysis was used for multivariate analyses to identify the risk factors for death. A nomogram was formulated and internally evaluated by the boot validation and the area under the curve (AUC). Performance of the nomogram was further accessed by Kaplan-Meier survival curves for patients who survived the initial IHCA. SETTING Intensive care unit, Tongji Hospital, China. PARTICIPANTS Adult patients (≥18 years) with IHCA after admission. Pregnant women, patients with 'do not resuscitation' order and patients treated with extracorporeal membrane oxygenation were excluded. INTERVENTIONS None. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome was the death after IHCA. RESULTS Patients (n=561) were divided into two groups: non-sustained return of spontaneous circulation (ROSC) group (n=241) and sustained ROSC group (n=320). Significant differences were found in sex (p=0.006), cardiopulmonary resuscitation (CPR) duration (p<0.001), total duration of CPR (p=0.014), rearrest (p<0.001) and length of stay (p=0.004) between two groups. Multivariate analysis identified that rearrest, duration of CPR and length of stay were independently associated with death. The nomogram including these three factors was well validated using boot calibration plot and exhibited excellent discriminative ability (AUC 0.88, 95% CI 0.83 to 0.93). The tertiles of patients in sustained ROSC group stratified by anticipated probability of death revealed significantly different survival rate (p<0.001). CONCLUSIONS Our proposed nomogram based on these three factors is a simple, robust prediction model to accurately predict the death after IHCA.
Collapse
Affiliation(s)
- Youping Zhang
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Critical Care Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Caijun Rao
- Department of Geriatric, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiao Ran
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Critical Care Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hongjie Hu
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Liang Jing
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Critical Care Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shu Peng
- Department of Thoracic Surgery, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wei Zhu
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Critical Care Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shusheng Li
- Department of Emergency Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Department of Critical Care Medicine, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China
| |
Collapse
|