院內心跳驟停 (In-hospital cardiac arrest, IHCA) 的發生，嚴重威脅病人生命安全與醫療照護品質。美國心臟學會 (American Heart Association, AHA) 2015提出IHCA生存之鏈之概念，2019年更強調早期辨識IHCA風險、預防是生存首重的關鍵，建議使用預警系統識別，防堵心臟驟停之發生。多數IHCA分析、預警系統以住院病人為主；急診IHCA發生反映急診醫療照護品質與應變能力指標，面對急診病人的高流量、高流動率、高變異的疾病嚴重度，更需能及早、有效率辨識IHCA高風險病人，即時介入，以降低IHCA發生。本研究運用決策樹方法學做為機器學習，協助辨識出造成急診IHCA的高風險因子。
研究方法：採病歷回溯性研究，以台北市某聯合醫院5大院區急診室，收集自2019年1月至2020年12月，以符合收案條件之IHCA案例病歷紀錄與異常事件通報表，進行資料收集；並以急診轉入加護病房病患共100筆資料作為對照組，作為本研究訓練模型之特徵屬性資料，運用CART決策樹Gini模型進行分析演算。
研究結果：共納入129筆IHCA與98筆非IHCA進行分析，兩組在個人屬性、慢性疾病比較，呈現非IHCA組有較高的BMI數值、心臟病、失智病史比率高於IHCA組; 而IHCA在肺炎病史、消化性潰瘍疾病、癌症比率高於非IHCA組。第一階段以個人基本屬性、個人嗜好、生命徵項進行分析，找出造成IHCA之重要特徵為:體溫、BMI、收縮壓、心跳速率、與年齡，預測準確率達86.78%；第二階段納入慢性共病分析，造成IHCA之重要特徵為:低收縮壓、舒張壓、發燒、BMI低於(含) 20.5、年齡66.5歲(含)以上、男性、肺炎/肺病與高血壓共病病史，預測準確率達88.11%，結果顯示本研究模組有良好的預測準確度。
結論：研究結果顯示急診IHCA病人發生心跳驟停前的生命徵象呈現敗血症、休克狀態，年齡66歲以上老人、營養狀態差的病人、與肺病病史等為預測IHCA發生的風險因子。結果有助於第一線急診醫療照護人員能盡早辨識出高風險病人，及時啟動緊急處置，以降心跳停止的發生。未來可進一步結合預測因子建立警訊系統，結合醫令系統，主動跳出提醒欄，提醒急診醫護人員，達到有效預警IHCA事件發生。

The incidence of in-hospital cardiac arrest (IHCA) poses a serious threat to patient safety and quality of medical care. The American Heart Association (AHA) introduced the concept of IHCA chain of survival in 2015. In 2019, the AHA highlighted that early identification of IHCA risk and prevention is the key to survival and recommended the use of early warning systems to identify and avoid the deterioration of sudden cardiac arrest. Most of the IHCA analysis and early warning systems are mainly for inpatients. The number of emergency IHCAs reflects the quality of emergency medical care and responding capability. Given the high patients rate, high turnover rate, and high variability of disease severity in emergency patients, it is important to identify patients at high risk of IHCA early and efficiently so that immediate intervention can be taken to reduce the occurrence of IHCA. This study applied the decision tree method for machine learning to help identify the high-risk factors that cause IHCA in the emergency room.
METHODS: This study was conducted using the retrospective chart review method. The data were collected based on the medical records and incident event reports of IHCA cases eligible for the requirements of this study from January 2019 to December 2020 in the emergency rooms of five major branches of a united hospital in Taipei. A total of 100 cases of patients transferred from the emergency room to the intensive care unit were used as the control group for the training model of this study, and the CART decision tree Gini model was employed for analysis and calculation.
RESULTS: A total of 129 cases of IHCA and 98 cases of non-IHCA were included for analysis. After comparing the two groups in terms of personal attributes and chronic diseases, it was found that the non-IHCA group had higher BMI, heart disease, and dementia history than the IHCA group. The IHCA group revealed a higher rate of pneumonia, peptic ulcer disease, and cancer than the non-IHCA group. In the first stage, we analyzed the basic personal attributes, personal hobbies, and vital signs to identify the important characteristics of IHCA, including body temperature, BMI, systolic blood pressure, heart rate, and age, with an accuracy rate of 86.78%. In the second stage, chronic co-morbidities were included in the analysis. The important characteristics of IHCA, including low systolic blood pressure, diastolic blood pressure, fever, BMI below (including) 20.5, age 66.5 years or older, male, and history of pneumonia/lung disease and hypertension, were identified with 88.11% prediction accuracy. The results showed that this study module yielded good predictive accuracy.
CONCLUSION: The results of the study showed that the vital signs of emergency patients with IHCA were showed as sepsis and shock before the onset of sudden cardiac arrest. Age 66 years or older, poor nutritional status, and history of pulmonary disease are risk factors for predicting the occurrence of IHCA. The results of this study could help frontline emergency medical care providers to identify high-risk patients as early as possible and initiate emergency treatment in a timely manner to reduce the incidence of cardiac arrest. In the future, an alert system can be established by combining the predictive factors with the medical order system to proactively pop up the alert bar to remind the emergency medical staff to effectively warn the incidence of IHCA.

目錄
中文摘要........................Ⅰ
英文摘要………………………………………………………………Ⅲ
目次……………………………………………………………………Ⅴ
表目錄…………………………………………………………………Ⅶ
圖目錄…………………………………………………………………Ⅷ
第一章 緒論
第一節 研究動機與重要性……………….………………………...…1
第二節 研究目的………………………………….……………….......4
第三節 名詞解釋………………….……………………………….......4
第二章 文獻查證
第一節 非預期院內心跳驟停現況與重要……………………………6
第二節 非預期院內心跳驟停之可能相關因素………………………8
第三節 非預期院內心跳驟停與共病關係……………………..……14
第四節 決策樹演算法分析…………………………………………..15
第三章 研究方法
第一節 研究設計……………………………………………………..18
第二節 研究場所與對象……………………………………………..19
第三節 研究架構…………………………………………………..…20
第四節 研究工具…………………………………………………..…21
第五節 資料分析……………………………………………………..28
第六節 研究步驟……………………………………………………29
第七節 倫理考量及研究資料保護…………………………………31
第四章 研究結果
第一節 個人特徵屬性………………………………………………32
第二節 疾病特性…………………………………………………....34
第三節 決策樹模型建構…………………………………………....38
第四節 CART決策樹準確度衡量效能指標…………………….....53
第五章 討論
第一節 探討造成急診病人IHCA可能的影響因素………….…..54
第二節 非預期性心跳驟停預測模式……………………………...57
第六章 結論與建議
第一節 結論 ……………………………………………………….59
第二節 研究限制……………………………………………...........60
第三節 實務與未來研究之建議 ………………………………….61
參考文獻
中文部分…………………………………………………………………62
西文部分…………………………………………………………………62
附錄
附錄一、聯合醫院人體研究倫理審查委員會計畫執行許可書……...68


表目次
表1 早期預警評分系統 (NEWS)…………………..…………..………...24
表2 Charlson Comorbidity Index (CCI)權重分數...…..……………........26
表3 IHCA與非IHCA個人屬性分布表…….………………………….31
表4 IHCA與非IHCA慢性疾病特性分析……………………………..33
表5 IHCA病人共病指數分組對接受CPR與ROSC差異…………....34
表6 IHCA最早病人發生致命性心律分析表………….…………….....35
表7 IHCA接受心肺復甦術回復自發性血液循環之成效……………..37
表8 導致IHCA原因統計表………………………………………….....37
表9 類別變數與數值變項資料編碼轉換…………………..……….......38
表10 第一階段CART IHCA重要性特徵表..………………….………...44
表11 類別變項資料編碼轉換表………………………………..................45
表12 數值變項資料編碼轉換表………………………………..................46
表13 第二階段CART IHCA重要性特徵表..………………….………...51
表14 預測的樣本模型混淆矩陣(Confusion matrix)………..………….....55
表15 CART決策樹準確度…..….……………….……………..…………..55

圖目次
圖1 病人安全通報系統院內非預期性心跳驟停10年曲線圖…..…….1
圖2 2020年成人IHCA的「生存之鏈」………………………………1
圖3 研究架構圖 ………………………………………………………..22
圖4 研究流程圖 ………………………………………………………..32
圖5 第一階段CART決策樹分析結果樹狀圖 ……………………….45
圖6 第二階段CART決策樹分析結果樹狀圖 ……………………….52

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