臺灣博碩士論文加值系統

背景：術中併發症與術後不良反應之間的關係甚少被討論，因此，對於術中併發症因子可能會與術後不良反應有關，以及影響術後不良反應的程度是十分值得研究的議題。本論文利用某醫學中心麻醉臨床登記資料，進行麻醉術中併發症與術後不良反應之相關研究。

研究目的：本論文研究目的有
(1)探討麻醉術中併發症及術後不良反應之發生。
(2)以比例勝算廻歸模型探討術中併發症對術後不良反應之影響
(3)利用廣義估計模式並考量相同病人不同結果測量間之相關性下，探討術中併發症對術後不良反應之相關
(4)依術後不良反應進行危險分層並以比例勝算廻歸模型探討相關術中併發症
(5)以驗證性因素分析方法探索術後不良反應之可能術中併發症原因進行路徑。
(6)依研究結果提供麻醉臨床決策以減低術後不良反應之產生及照護品質之確保。

研究材料及方法：本研究為前膽性之觀察性研究設計，收集2011年至2014年間台北及淡水馬偕醫院接受手術之麻醉病人世代資料進行分析。收集與術前準備、術前流程、用藥及輸液、上呼吸道、呼吸系統、心血管系統、神經系統及其他等相關之八個麻醉術中併發症分類相關資料，其中包含相關共計46項品質指標之資料收集，而由具訓練登記員於術後24小時內進行14項術後訪視包含心跳血壓、意識、呼吸、呼吸系統支援、體溫、呼吸道系統、心血管系統、神經系統、組織傷害、過敏反應、噁心、嘔吐、暈眩、麻醉中甦醒之資料收集及登記。

統計方法：以傳統比例勝算廻歸模型，對14項術後不良反應分別探討可能之術中併發症因子，並進一步利用廣義估計模式，考量相同病人多重術後不良反應間之相關性下，探討麻醉術中併發症對術後訪視結果之相關。再者，就多重術後不良反應情形做累積加總，將此分數分為四層，無事件、具一項事件、二項事件及二項以上事件，據以將此術後不良反應分數視為序列變項，以比例勝算廻歸模型分析與麻醉術中併發症間之關係。最後再以驗證性因素分析方法探索包含組織傷害、生命系統傷害、症狀反應、呼吸反應及生命徵象五個主要因素與術後不良反應間之因素路徑分析。

結果：本論文發現在考量了病人性別、年齡ASA分級及麻醉方法後，術中併發症與術後不良反應具高度相關性。性別在不同不良反應有不同的作用，例如男性有較高的風險會有心跳血壓異常(勝算比(Odds Ratio, OR)=1.28, 95% 信賴區間 (confidence interval, CI): 1.05, 1.57), 意識問題(OR=1.75, 95% CI: 1.27, 2.40), 上呼吸道問題 (OR=1.66, 95% CI: 1.45, 1.90), 需要呼吸輔助儀器(OR=1.55, 95% CI: 1.43, 1.69)，及體溫異常(OR=1.29, 95% CI: 1.19, 1.39)等問題，然而女性有較高風險會在術後噁心(OR=0.45, 95% CI: 0.42, 0.48)、嘔吐(OR=0.36, 95% CI: 0.34, 0.39)及暈眩(OR=0.52, 95% CI: 0.49, 0.54)。年長及麻醉方式對大多數的術後不良反應均為有意義的危險因子。相較於靜脈麻醉，全身麻醉在各類術後不良反應有2.33-19.94倍的風險，而對術後呼吸異常的風險更高達530倍，相較之下，局部麻醉的風險較全身麻醉略低，但仍高於靜脈麻醉，具1.22-9.77倍不等的風險。ASA較高等級也會有較大的術後不良反應風險，但對噁心、嘔吐及周邉神經傷害則為負向關係。
就術中併發症而言，術前準備問題及神經系統問題與術後不良反應較無明顯相關，但在神經系統問題中的其中一項：麻醉深度不足或術中甦醒會增加術後手術記憶(OR=267, 95% CI: 57-1248)。在手術麻醉全過程方面，非計畫性轉加護病房是影響最多類術後不良反應的事件，在藥物與輸血問題方面，則是輸血液製品高於四單位者是最重要因子，就呼吸系統問題而言，低血氧、高碳酸血症、吸入胃容物均是引發術後不良反應的危險因子，心血管系統問題亦會引致術後不良反應，此外，高體溫及少尿症均為許多術後不良反應的危險因子。
若同時考慮多個術後不良反應，則發現女性(OR=1.40, 95% CI: 1.37, 1.45), 年長、ASA分級III以上(OR=1.34, 95% CI: 1.29, 1.39)、全身麻醉(OR=9.07, 95% CI: 8.44, 9.75)及局部麻醉(OR=5.28, 95% CI: 4.88, 5.71)均為術後不良反應的危險因子。非計畫性轉加護病房(OR=1.49, 95% CI: 1.14, 1.94)、輸血液製品高於四單位(OR=1.70, 95% CI: 1.59, 1.83)、心臟停止 (OR=2.24, 95% CI: 1.16, 4.32), 心律過快(OR=1.43, 95% CI: 1.22, 1.67)、高血壓(OR=1.12, 95% CI: 1.01, 1.25)、低血壓(OR=1.15, 95% CI: 1.09, 1.22)、中樞神經併發症(OR=4.21, 95% CI: 4.12, 4.31)、牙齒傷害(OR=1.89, 95% CI: 1.23, 2.90)、唇口鼻出血或傷害(OR=1.36, 95% CI: 1.07, 1.72)、皮膚傷害(OR=1.83, 95% CI: 1.42, 2.34)、眼球傷害(OR=2.10, 95% CI: 1.29, 3.42)、低體溫(OR=1.24, 95% CI: 1.13, 1.35)、高體溫(OR=1.53, 95% CI: 1.22, 1.92)、少尿症(OR=1.57, 95% CI: 1.41, 1.75)及嚴重嘔吐(OR=2.33, 95% CI: 1.68, 3.23)亦與術後不良反應相關。分析新分類不良反應分級風險的危險因子則於多重不良反應分析結果相似。
驗證性因素分析方法結果發現症狀反應(0.06 (SE=0.007, t=8.13))與呼吸反應(0.56 (SE=0.026, t=21.10))影響生命徵象異常具顯著作用。

結論：年齡、性別、ASA分級及麻醉方法與術後不良反應具相關性。而術中併發症中所涉及用藥與輸液、呼吸系統問題、心血管問題與其他未歸類問題為四種主要與術後不良反應相關的原因。本研究驗證性分析結果可協助臨床麻醉之術後不良反應影響因素路徑之探究。

Abstract

Background: As the impact of intraoperative undesired incident events on the anesthesia-related adverse outcomes is not well-addressed, it is valuable to elucidate whether and what kinds of intraoperative undesired events are associated with anesthesia-related adverse outcomes. Beside, most of studies treat a constellation of outcomes with repeat to postoperative complications as independent one in the same individual patients, while studying the relationship of undesired incident events to postoperative complications. The failure of considering these multiple outcomes as correlated outcome may affect the effect sizes regarding the association between intraoperative undesired incident events and postoperative complications. As factors in association with adverse events are numerous how to clarify which factors are medicated through another set of factors is of great interest. By using anesthesia clinical outcomes registry data from one medical center in Taiwan, we have chance to apply a series of statistical models making allowance of correlation property in the association study between intraoperative undesired event and postoperative complications

Aims: The aims of this thesis were
1.to explore the incidence of intraoperative undesired incidents and postoperative anesthesia adverse events;
2.to elucidate whether the intraoperative incidents have influence on the postoperative adverse events by using proportional odds regression models;
3.to investigate the effect of the intraoperative undesired incidents on multiple postoperative adverse events taking into account the correlation property within subject by using general estimating equation model;
4.to assess the anesthesia risk factors with proportional odds regression models on the newly classified risk groups;
5.to investigate the conservative relationships between postoperative adverse events, resulting in postoperative complications by using confirmatory factor analysis;
6.to tailor the clinicians to anesthesia decision to reduce the occurrence of these side effects and to ensure the quality assurance of care.

Material and method:By using a prospective observation study design, a cohort of patients receiving operation at Taipei or Tamsui branch of Mackay Memorial Hospital between 2011 and 2014 were enrolled. The quality indices including 46 items and eight aspects considering the intraoperative undesired incidents/postoperative adverse events were collected. The 14 defined outcomes of undesired events were ascertained by an interview performed by trained anesthetic registers within 24 hours after the operation. Total of 88,990 patients were enrolled in our analysis.
A series of conventional proportional odds regression models were applied to assess the significance between the items of the intraoperative undesired incidents and each of the 14 undesirable events adjusting for age, sex, and anesthesia techniques. This is followed by applying the generalized estimating equation models to take into account the correlated characteristics of the 14 undesirable events when assessing the significance of the multiple quality indices. Alternatively, we reclassified patients into different groups according to the summation of the 14 adverse events for a better reorganization of the risk factors associated with the spectrum of postoperative adverse events. We further applied confirmatory factor analysis to elucidate the influence of the intraoperative undesired incidents on the multiple adverse events with the consideration of paths between five components toward adverse events (tissue injury, vital system injury, symptomatic response, respiratory response, and vital signs).

Results:A total of 88,990 patients underwent surgery in MacKay Memorial Hospital were recruited in the current analysis. After adjustment for patient factors, there were strong relation between postop adverse events and periop anesthesia-related incidents. Gender difference was not consistent across postoperative complications. Male had higher risk for hemodynamic instability (OR=1.28, 95% CI: 1.05, 1.57), conscious disturbance (OR=1.75, 95% CI: 1.27, 2.40), upper airway discomfort or dyspnea (OR=1.66, 95% CI: 1.45, 1.90), respiratory assistant devices requirement (OR=1.55, 95% CI: 1.43, 1.69), and abnormal thermoregulation (OR=1.29, 95% CI: 1.19, 1.39), whereas female were more likely to have reactions of nausea (OR=0.45, 95% CI: 0.42, 0.48), vomiting (OR=0.36, 95% CI: 0.34, 0.39), and dizziness (OR=0.52, 95% CI: 0.49, 0.54) after surgery. Age, and anesthesia techniques were consistent risk factors. Compared with sedation, general anesthesia had 2.33-19.94 fold risk for most postoperative adverse events, except 530-fold for respiratory abnormality, and regional anesthesia had smaller effects with a range of 1.22-9.77. ASA class III+ was more likely to have postoperative complications, except nausea, dizziness, and peripheral nerve injury, with which ASA class III+ was negatively associated.
When we examined the intraoperative undesired events, none under the categories of preoperative preparation and nervous system was significant associated with postoperative complications, except inadequate depth of anesthesia/awake during operation which was strongly associated with perioperative awareness (OR=267, 95% CI: 57-1248) (but only affecting this complication). In the realm of perioperative process, unplanned ICU admission was the most significant one. In the realm of medicine and transfusion, blood transfusion with more than four units was the most important one. For respiratory system, hypoxia, hypercapnia, aspiration of stomach contents were commonly associated with complications after operation. The detailed items listed in the cardiovascular system commonly contributed to postoperative complications. Hyperthermia and oliguria were two major intraoperative undesired incidents which contributed the largest number of postoperative complications.
When the multiple postoperative complications were considered simultaneously, female (OR=1.40, 95% CI: 1.37, 1.45), elderly age with increasing risk by 1% per 1 year of age, ASA class III+ (OR=1.34, 95% CI: 1.29, 1.39), and general (OR=9.07, 95% CI: 8.44, 9.75) or regional (OR=5.28, 95% CI: 4.88, 5.71) anesthesia were identified as risk factors. unplanned ICU admission (OR=1.49, 95% CI: 1.14, 1.94), blood transfusion with more than four units (OR=1.70, 95% CI: 1.59, 1.83), cardiac arrest (OR=2.24, 95% CI: 1.16, 4.32), tachycardia requirement (OR=1.43, 95% CI: 1.22, 1.67), hypertension (OR=1.12, 95% CI: 1.01, 1.25), hypotension (OR=1.15, 95% CI: 1.09, 1.22), complications of central nerve system (OR=4.21, 95% CI: 4.12, 4.31), injury of teeth (OR=1.89, 95% CI: 1.23, 2.90), lip/oral cavity/nose (OR=1.36, 95% CI: 1.07, 1.72), skin (OR=1.83, 95% CI: 1.42, 2.34), and eyes (OR=2.10, 95% CI: 1.29, 3.42), hypothermia (OR=1.24, 95% CI: 1.13, 1.35), hyperthermia (OR=1.53, 95% CI: 1.22, 1.92), oliguria (OR=1.57, 95% CI: 1.41, 1.75), and severe vomiting (OR=2.33, 95% CI: 1.68, 3.23) were more likely to have postoperative complications. The findings for collective categories of intraoperative events were similar to previous findings. The consistent findings were also found when the outcome of interests was the level of numbers of postoperative complications.
Using the confirmatory factor analysis to assessing the relevance from the multiple items of quality indices to the undesired events and thereafter between the cluster of undesired events, the significant path through the component of symptomatic response to that of abnormality in vital signs (0.06 (SE=0.007, t=8.13)) and that from respiratory response to that of abnormality in vital signs (0.56 (SE=0.026, t=21.10)) were revealed. The significance between the predictor of quality indices to the undesired events and that of each component measured by relevant undesired events were also found.

Conclusions:Age, gender, ASA class, and anesthesia techniques were associated with postoperative adverse events. Intraoperative undesired incidents in medicine/transfusion, respiratory system, cardiovascular system, and other ungrouped factors are four major undesired incident events that account for postoperative adverse events or adverse risk scores. These risk factors making different contribution to different categorized adverse events were noted. The results of confirmatory factor analysis can be applied to aiding in clarifying the path of adverse events in clinical practice.

Contents

Practicum Unit Feature 1
Chapter 1 Introduction 2
1.1 Background 2
1.2 Aims 3
Chapter 2. Literature review 5
2.1 Trend of quality improvement of anesthesia 5
2.2 The anesthesia-related mortality in Taiwan 6
2.3 The literature regarding the anesthesia-related adverse events 8
Chapter 3 Material and method 18
3.1 Data sources 18
3-2 Statistical Methods 22
Chapter 4 Results 27
4.1 Descriptive results of study population 27
4.2 The association between intraoperative undesired incidents and postoperative adverse events 32
4.3 Multivariate analysis for multiple undesirable events 42
4.4 Multivariate analysis for summarized undesirable risk score 44
4.5 Confirmatory factor analysis for the elucidation of the path of adverse events 46
Chapter 5. Discussion 50
5.1 New thoughts on analysis of intraoperative undesired incidents on postoperative adverse events 50
5.2 Identification of risk factors with different analyses 52
5.3 Comparison with previous studies 54
5.4 Limitations 55
5.5 Conclusion 56
References 57

Indexes of Tables & Figures

Table 4.1.1 Characteristics of 88,990 anesthesia patients 60
Table 4.1.2 Numbers of intraoperative undesired incidents 61
Table 4.1.3 The distribution of risk factors by hemodynamic instability among anesthesia patients 63
Table 4.1.4 The distribution of risk factors by conscious disturbance among anesthesia patients 65
Table 4.1.5 The distribution of risk factors by respiratory abnormality among anesthesia patients 67
Table 4.1.6 The distribution of risk factors by respiratory assist device among anesthesia patients 69
Table 4.1.7 The distribution of risk factors by abnormalities of thermoregulation among anesthesia patients 71
Table 4.1.8 The distribution of risk factors by upper airway discomfort or dyspnea among anesthesia patients 73
Table 4.1.9 The distribution of risk factors by chest tightness or dysrhythmia among anesthesia patients 75
Table 4.1.10 The distribution of risk factors by peripheral nerve injury among anesthesia patients 77
Table 4.1.11 The distribution of risk factors by tissue damage among anesthesia patients 79
Table 4.1.12 The distribution of risk factors by allergic reaction among anesthesia patients 81
Table 4.1.13 The distribution of risk factors by neusea among anesthesia patients 83
Table 4.1.14 The distribution of risk factors by vomiting among anesthesia patients 85
Table 4.1.15 The distribution of risk factors by dizziness among anesthesia patients 87
Table 4.1.16 The distribution of risk factors by periop awareness among anesthesia patients 89
Table 4.2.1 Estimated results on the association between the hemodynamic instability and intraoperative undesired incidents by using multivariable proportional odds model 91
Table 4.2.2 Estimated results on the association between the conscious disturbance and intraoperative undesired incidents by using multivariable proportional odds model 93
Table 4.2.3 Estimated results on the association between the upper airway discomfort or dyspnea and intraoperative undesired incidents by using multivariable proportional odds model 95
Table 4.2.4 Estimated results on the association between the required for respiratory assistant devices and intraoperative undesired incidents by using multivariable proportional odds model 97
Table 4.2.5 Estimated results on the association between the abnormalities of thermoregulation and intraoperative undesired incidents by using multivariable proportional odds model 99
Table 4.2.6 Estimated results on the association between the nausea and intraoperative undesired incidents by using multivariable proportional odds model 101
Table 4.2.7 Estimated results on the association between vomiting and intraoperative undesired incidents by using multivariable proportional odds model 103
Table 4.2.8 Estimated results on the association between dizziness and intraoperative undesired incidents by using multivariable proportional odds model 105
Table 4.2.9 Estimated results on the association between the respiratory abnormality and intraoperative undesired incidents by using multivariable proportional odds model 107
Table 4.2.10 Estimated results on the association between the chest tightness or dysrhythmia and intraoperative undesired incidents by using multivariable proportional odds model 109
Table 4.2.11 Estimated results on the association between the peripheral nerve injury and intraoperative undesired incidents by using multivariable proportional odds model 111
Table 4.2.12 Estimated results on the association between tissue damage and intraoperative undesired incidents by using multivariable proportional odds model 113
Table 4.2.13 Estimated results on the association between allergic reaction and intraoperative undesired incidents by using multivariable proportional odds model 115
Table 4.2.14 Estimated results on the association between periop awareness and intraoperative undesired incidents by using multivariable proportional odds model 117
Table 4.2.15 Estimated results on the association between hemodynamic instability and intraoperative undesired incidents by using multivariable proportional odds model 119
Table 4.2.16 Estimated results on the association between conscious disturbance and intraoperative undesired incidents by using multivariable proportional odds model 120
Table 4.2.17 Estimated results on the association between upper airway discomfort or dyspnea and intraoperative undesired incidents by using multivariable proportional odds model 121
Table 4.2.18 Estimated results on the association between required for respiratory assistant devices and intraoperative undesired incidents by using multivariable proportional odds model 122
Table 4.2.19 Estimated results on the association between abnormalities of thermoregulation and intraoperative undesired incidents by using multivariable proportional odds model 123
Table 4.2.21 Estimated results on the association between vomiting and intraoperative undesired incidents by using multivariable proportional odds model 125
Table 4.2.22 Estimated results on the association between dizziness and intraoperative undesired incidents by using multivariable proportional odds model 126
Table 4.2.23 Estimated results on the association between respiratory abnormality and intraoperative undesired incidents by using multivariable proportional odds model 127
Table 4.2.24 Estimated results on the association between chest tightness or dysrhythmia and intraoperative undesired incidents by using multivariable proportional odds model 128
Table 4.2.25 Estimated results on the association between peripheral nerve injury and intraoperative undesired incidents by using multivariable proportional odds model 129
Table 4.2.26 Estimated results on the association between tissue damage and intraoperative undesired incidents by using multivariable proportional odds model 130
Table 4.2.27 Estimated results on the association between allergic reaction and intraoperative undesired incidents by using multivariable proportional odds model 131
Table 4.2.28 Estimated results on the association between periop awareness and intraoperative undesired incidents by using multivariable proportional odds model 132
Table 4.3.1 The association between postoperative adverse events and Intraoperative undesired incidents using multivariate GEE model 133
Table 4.3.2 The association between postoperative adverse events and subtypes of intraoperative undesired incidents using multivariate GEE model 135
Table 4.4.1 The association between summary postoperative adverse events and intraoperative undesired incidents using multivariate proportional-odds cumulative logit regression 136
Table 4.4.2 The association between summary postoperative adverse events and subtypes of intraoperative undesired incidents using multivariate proportional-odds cumulative logit regression 138
Table 5.1.1. Summary of intraoperative undesirable incidents associated with postoperative anesthesia adverse events with different statistical analysis methods 139
Figure 3.1. Web-based list for collecting the items of quality indices. 141
Figure 3.2. Web-based system for collecting information on the occurrence of defined unanticipated events by post-operative interview. 142
Figure 4.5.1 Estimated results of using confirmatory factor analysis for the elucidation of the path of adverse events. 143
Figure 4.5.2 Estimated results of using confirmatory factor analysis for the elucidation of the path of adverse events. 144
Figure 4.5.3 Estimated results of using confirmatory factor analysis for the elucidation of the path of adverse events. 145
Figure 5.1 Conceptual diagram on modelling the influences of quality indices on the path to postoperative adverse events 146

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