| Abstract: | QT間距可利用心電圖檢查方便取得，由於QT波會隨時間改變以及因人而異，所以在計算時會經過RR間距來做校正，即所謂的QTc。QT間距反應了心臟心室去極化開始到復極化的時間，QTc若過長(男性>450毫秒，女性>470毫秒)則定義為QT間距延長症候群(LQTS)，此種疾病可能先天性遺傳以及後天條件造成。先天性主要是因為心肌細胞之細胞膜上的離子通道功能異常，造成膜電位失衡而產生復極化延遲的現象。後天條件包括了疾病、藥物治療、電解質失衡、神經失調…所造成復極化延遲的症狀。LQTS屬於一種急性且極危險的心臟疾病，進而會導致多型性心室性心律不整(TDP)、心因性的休克、昏厥，嚴重時會發生猝死的可能。然而，本篇研究目的為睡眠時的QT間距在睡眠期間的變化，以及其危險相關因子之探討兩個方向。自民國99~100年間，在全台各地招募了416位男性受試者進行研究，受試對象主要會進行6項檢查：生活型態問卷、愛普沃斯嗜睡量表、身體基本量測、睡眠生理檢查、血液生化分析以及運動心肺生理檢查。經由條件之篩選(1.慢性疾病史 2.資料不全 3.訊號異常)後留下369人進行統計分析，資料庫的建立是利用各項檢查報告以及問卷透過MATLAB軟體進行數據的計算及轉換。因實驗設計需求將受試對象分為兩組模型(Model 1：91人皆包含了所有睡眠期別，Model 2：369人)進行統計分析，所有統計分析皆以SPSS 17.0軟體進行。結果顯示在不分睡眠呼吸中止症(OSA)嚴重度的情況下，一般人在Sleep 2(淺睡期)含有最低之QTc。此外，QTc之長短會與OSA之嚴重度呈現獨力正相關。最後在複迴歸分析模式中，我們利用了大量檢查指標進行逐步迴歸分析以探討QTc之危險預測因子，結果顯示胰島素(Insulin)、呼吸障礙指標(AHI)、用力肺活量(FVC)為影響力最大的三項預測指標。本篇結論為一般人在睡眠Sleep 2含有最低之QTc，由於Sleep 2是人人睡著時皆可達到之睡眠期別，所以我們預期S2之QTc可做為診斷之依據。在複迴歸分析研究中，我們證實了胰島素和QTc成正相關性，由於胰島素會影響細胞膜之膜電位的改變以及造成交感神經的活化進而影響了QTc。而AHI指標則反應了OSA的嚴重程度，OSA患者伴隨著夜間反覆低血氧的症狀，血流動力學的改變以及交感神經的活化間接影響到QTc。最後，FVC被許多研究證實與胰島素阻抗性相關，隨後會發生血中胰島素濃度升高之情形，透過胰島素間接影響了QTc，FVC和QTc則有顯著性的負相關。我們證實了這三項指標會共同影響QT間距，並認為這三項指標為LQTS之危險預測因子。
QT intervals can be easily gotten through electrocardiography. Since QT waves will fluctuate with the passing of time and from person to person, they will be under correction with RR intervals while being calculated; the whole process is so-called QTc. QT intervals reflect the time needed from ventricular depolarization to ventricular repolarization. If one’s QTc is too long, which means that the testing result of a male subject is over 450 milliseconds and the result of a female subject is over 470 milliseconds, he will be diagnosed with Long QT Syndrome (LQTS). This syndrome can be either congenital or acquired. If it is congenital, then it’s mainly caused by the delay of ventricular repolarization, which is due to the imbalance of membrane potential resulting from the malfunctioning of channelopathies on the cell membrane of cardiomyocytes. As for the acquired ones, the causes of the delay of ventricular repolarization include diseases, medication, electrolyte disorders, and nervous system disorders, etc. LQTS belongs to one kind of acute and extremely dangerous heart disease, whilch will lead to Torsades de Pointes(TDP), cardiac arrest, and fainting; what’s even worse, the possibility of sudden death. Nonetheless, the purpose of this research is to explore the following two dimensions: the fluctuation of QT intervals during one’s sleep time and the related risk-causing factors. From 2010 to 2011, 416 male subjects were recruited to undergo the research from all over Taiwan. The subjects needed to take six examinations: lifestyle questionnaires, Epworth Sleepiness Scale, body measurement, polysomnography, blood test, and cardiopulmonary exercise testing. After screening and excluding out those who had the history of chronic diseases, who didn’t provide complete information, and whose resulting signals were abnormal, 369 people’s data were left to carry out statistical analysis. The database is established through the calculation and transformation by the MATLAB software by using the resulting reports of every examination and the data of questionnaires. Due to the requirement of the design of the experiment, the subjects were divided into two modes (Mode1: The entire 91 people include all of the sleep stages. Mode2: The whole 369 subjects.) to be under statistical analysis and the entire analysis is conducted with SPSS 17.0 software. The result reveals that without considering the severity of obstructive sleep apnea syndrome(OSA), the majorities have the lowest QTc in Sleep 2(light sleep). Moreover, the length of QTc will appear in independently positive proportion to the severity of OSA. At last, in the multiple regression analysis, we used a large number of examination index to conduct stepwise regression analysis to study the risk prediction factors. The result demonstrates that insulin, AHI and FVC are the three most influential prediction index. The conclusion of this research is that ordinary people have the lowest QTc in Sleep 2 and that since Sleep 2 is the sleep stage that everyone can reach when falling asleep, we predict that the QTc of S2 can become the criterion of diagnosis. In the research of multiple regression analysis, we have confirmed that insulin is in proportion to QTc, for insulin has influence on the fluctuation of membrane potential of cell membrane and cause the activation of sympathetic nervous, thus affecting QTc. On the other hand, AHI index reflects the severity of OSA and the persistent hypoxemia syndrome at night, the fluctuation of hemodynamic and the activation of sympathetic nervous affects QTc indirectly. Eventually, according to a lot of research, FVC has been confirmed to be related to insulin resistance, and subsequently resulting in the increasing density of insulin in the blood, and FVC indirectly affects QTc through insulin; therefore, FVC is in significant negative correlation with QTc. We have confirmed that these three indexes co-affect QT intervals and we believe that these three indexes are the risk predicting factors of LQTS. |
