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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/26263
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor陳秀熙(Tony Hsiu-Hsi Chen)
dc.contributor.authorShih-Pin Linen
dc.contributor.author林世斌zh_TW
dc.date.accessioned2021-06-08T07:04:28Z-
dc.date.copyright2011-10-03
dc.date.issued2011
dc.date.submitted2011-08-14
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/26263-
dc.description.abstract靜脈式病患自控止痛器(Intravenous Patient Controlled Analgesia; IVPCA) 對於急性手術後傷口疼痛是一個有效的治療方法。病患可以自己控制按鈕來決定給予止痛藥的次數,並且由此決定止痛劑的劑量,然而由於每個人在使用劑量上的差異極大,目前沒有單一的配方,可以完美的適合每個人的需要。於是我們應用群集分析來觀察使用者在各個時段上使用劑量,並且分類成三個使用劑量分類。這三個分類不僅可以幫助我們了解不同術後疼痛的行為模式的成因,也可以方便應用於臨床管理IVPCA的劑量。
本研究為回溯性觀察實驗,收集了總共3284的使用人次。由於IVPCA電腦紀錄每個時間的使用劑量歷程,我們以每六個小時當作一個時段來表示。由於一次使用三天,每個人次總共有連續12個時段的使用劑量。首先參考cubic clustering criterion (CCC), R-square, semi-partial R-square root and mean square standard derivation選擇群集數目的標準,我們以這12個時段的使用劑量為隨機變數使用Ward’s minimal variance的方法來聚集成三個使用劑量分類。接下來,我們分析影響使用劑量分類的因子,並且使用羅吉式辨識法來辨識這三種使用劑量分類。
三種使用劑量分類可以很容易的應用在臨床。同一個使用劑量分類中的病患在12個時段上具有相似的疼痛行為模式和使用劑量。我們發現性別、年齡、手術方式(腹部手術、產科手術)、癌症病患、初始設定(按壓劑量、四小時限制劑量、背景劑量)是影響三種使用劑量分類的獨立因子。使用羅吉式辨識方程式來進行辨識分析並且分類這三種使用劑量分類,利用收集的3284的IVPCA資料當作訓練集(training set),並且使用這些特徵來訓練,得到最後的錯誤率為37.9%。
本研究以靜脈式病患自控式止痛器為研究對象,建立了連續時間上的使用劑量並區分出三種使用劑量分類,利用這三種使用劑量分類進行手術後病患的行為模式和因子討論,最後利用自動化的辨識方程式,進行分類使用劑量分類的方法,建立個人化的靜脈式病患自控式止痛器的使用劑量分類。
zh_TW
dc.description.abstractIntravenous patient-controlled analgesia (IVPCA) is a useful approach to relieving acute postoperative pain, by using self administered small dose of analgesia. Due to high variation across individuals, there is lacking of standard regimen. We applied cluster analysis to classifying time series analgesic consumption of IVPCA as three categories. These classifications can help us not only elucidate the etiologies of different pain behavior but also apply to clinical practice.
We conducted a retrospective observational study by enrolling a total of 3284 IVPCA users. Microprocessor of IVPCA recorded a consecutive series of analgesic consumptions every six hours. Every patient had used IVPCA for three days, which has twelve time interval analgesic consumptions. After the determination of cluster numbers by cubic clustering criterion (CCC), R-square, semi-partial R-square root and mean square standard derivation, we used Ward’s minimal variance method to aggregate classifications through twelve sequential analgesic consumptions. We evaluated the possible putative factors and applied logistic discrimination to classifying three consumption classifications.
Three consumption classifications are classified and applied to clinical practice. Patients in the same consumption classifications have similar pain behavior and consumption dosages during twelve time intervals. We found sex, age , surgery (abdominal and obstetric), cancer patient and initial setting of IVPCA (bolus, lockout, background rate) were independent factors of three consumption classifications, By using logistic discrimination, the total error rate was 37.9%.
In summary, we used analgesic consumption dose of twelve time intervals to establish three consumption classifications. Possible factors responsible for three consumption classifications were identified. We used logistic discrimination to recognize three consumption classifications for assessing the error rate of logistic discrimination.
en
dc.description.provenanceMade available in DSpace on 2021-06-08T07:04:28Z (GMT). No. of bitstreams: 1
ntu-100-R98842010-1.pdf: 1285540 bytes, checksum: b736c140c21e111a63007bd7e8652317 (MD5)
Previous issue date: 2011
en
dc.description.tableofcontents口試委員會審定書 #
摘要 ii
ABSTRACT iii
CONTENTS v
LIST OF TABLES vii
LIST OF FIGURES viii
Chapter 1 Introduction 1
Chapter 2 文獻探討 3
2.1 靜脈式病患自控止痛器的醫學文獻回顧 3
2.2 統計分類法 7
2.3 無監督式統計分類 9
2.3.1 Projection methods 9
2.3.2 Cluster analysis---Ward’s minimal variance analysis 11
2.3.3 如何決定可能群集的數目 13
2.4 監督式統計分類 14
2.4.1 貝式決策理論 14
2.4.2 參數模型(parametric models) 17
2.4.3 Logistic discrimination 17
2.4.4 模型選擇 19
Chapter 3 研究材料與方法 21
3.1 資料來源 21
3.2 變項收集 21
3.2.1 病患自控式止痛器電腦記錄資料收集 21
3.2.2 紙本資料的收集 22
3.2.3 統計方法 22
Chapter 4 結果 25
4.1 描述性結果 25
4.2 主成分分析IVPCA的使用劑量 25
4.3 群集分析IVPCA的使用劑量分類 25
4.4 判別分析IVPCA的使用劑量分類 27
Chapter 5 討論 30
5.1 主要方法與結果 30
5.2 主成分分析 31
5.3 群集分析 32
5.4 影響使用劑量分類的決定因子 33
5.5 辨識分析 34
5.6 研究限制 35
5.7 結論 36
參考文獻 37
dc.language.isozh-TW
dc.subject監督式學習zh_TW
dc.subject靜脈式病患自控止痛器zh_TW
dc.subject群集分析zh_TW
dc.subject非監督式學習zh_TW
dc.subject辨識分析zh_TW
dc.subjectIntravenous patient controlled analgesiaen
dc.subjectsupervised learningen
dc.subjectdiscriminant analysisen
dc.subjectunsupervised learningen
dc.subjectcluster analysisen
dc.title術後三天靜脈式病患自控止痛器連續使用劑量分類之統計方法zh_TW
dc.titleStatistical Methods for Classification of Intravenous Patient-Controlled Analgesia Series Consumption during Postoperative Three Daysen
dc.typeThesis
dc.date.schoolyear99-2
dc.description.degree碩士
dc.contributor.oralexamcommittee戴政(John Jen Tai),張淑惠(Shu-Hui Chang)
dc.subject.keyword靜脈式病患自控止痛器,群集分析,非監督式學習,辨識分析,監督式學習,zh_TW
dc.subject.keywordIntravenous patient controlled analgesia,cluster analysis,unsupervised learning,discriminant analysis,supervised learning,en
dc.relation.page58
dc.rights.note未授權
dc.date.accepted2011-08-15
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept流行病學與預防醫學研究所zh_TW
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