根據統計,有15-33%的嚴重頭部外傷患者會合併發生自主神經活性異常。他們的臨床表現為高燒、心跳快、血壓高、呼吸急促、肌肉張力異常、盜汗、腦壓上升等。這對一剛受傷的腦來說,很容易再造成二次傷害,而增加了罹病率與死亡率。及早的臨床評估且完善的醫療照護,是決定神經重症病患對於預後的重要因素。要達到這樣的目標,首先,必須要有完善的神經重症監測系統。 本研究將結合工程分析理論與頭部外傷臨床照護兩大領域,以目前加護病房中現有的頭部外傷監測系統為基礎,建立一非侵入式頭部外傷患者自主神經活性評估系統。研究中將採用受測者心電圖訊號,結合心率變異度與去趨勢波動分析法,利用不同尺度來觀察訊號在碎形特性上變化的結果,評估自主神經系統之活性。 本研究首先針對正常人族群進行試驗性研究,探討正常人在各外來刺激影響下自主神經活性之變化,目的在於幫助自主神經活性評估指標之測試與建立。研究後期我們將進一步選擇重度昏迷且神經反射功能喪失之嚴重頭部外傷患者進行資料收集與分析,利用神經評估指標探討嚴重頭部外傷患者於病程中自主神經活性之變化,並比對臨床相關因子間關聯性,藉以評估患者對臨床治療的反應。最後。期盼未來可依此非侵入自主神經活性評估系統指導頭部外傷患者臨床照護工作的進行,預測預後,提高醫療品質與病患安全。
Autonomic dysfunction syndrome (ADS) is reported in 15-33% of cases after severe traumatic brain injury (TBI). The clinical manifestations consist of fever, tachycardia, hypertension, tachypnea, dystonia, diaphoresis, increased intracranial pressure (IICP), etc. The vulnerable injured brain is easy to suffer from the secondary injury resulting from ADS in the acute stage. Increased morbidity and mortality are usually associated. Timely clinical assessment and fine critical care are crucial to the prognosis, and this should be proceeded aggressively under careful monitoring. By joining the engineering technique and clinical medical care system together, this study is aimed to establish an autonomic nerval monitoring system based on the currently-used monitoring in the intensive care unit (ICU) for TBI patients. In this study, we choose the electrocardiogram, and apply the analytic algorithms of detrended fluctuation analysis (DFA) in heart rate variability analysis (HRV). With the characteristic of fractal and self-similarity, the activity of the autonomic nervous system could be assessed. In order to help to test and establish the index of autonomic nervous system (ANS), we apply the data recorded from normal subjects to investigate the ANS activity with different influence of external stimulations on the beginning stage of this study. On the second stage of this study, we further choose the severe TBI patients who are under heavy coma and lose the function of ANS as material for this investigation, and assess the activity of ANS along the treatment course for the severe TBI patients via the ANS index. Moreover, we observe the relationship between the activity of ANS and clinical condition. By the information derived in this study, we wish to predict prognosis and monitor the patients’ response to the therapeutic intervention. Finally, we hope this monitoring system would deliver the information to guide the clinicians to predict outcome and make treatment plan for the clinical care. Therefore, the patients’ safety and the quality of clinical cares are enhanced.