目的1)發現與中風相闋的視網膜特徵2) 利用視網膜特徵建立統計模型對老年人中風風險進行分類。 / 方法:配對病例對照研究。病例為中風患者，一部分中風患者來自於糖尿病眼病的篩查項目，另外一部分是腦內科的中風患者。對照是沒有中風的老年人。對照來自糖尿病眼病篩查項目內沒有患中風的患者及在眼科門診沒有中風及特殊眼病的患者。對照與病例在年齡及是否患有糖尿病進行匹配。所有研究對象均來自香港威爾斯親王醫院。我們收集所有研究對象的中風危險因素，包括年齡，性別，吸煙，及是否患有糖尿病，高血壓，缺血性心髒病，心房顫動，高血脂。所有研究對象的彩色視網膜照片都被採集。我們應用軟件“ImageJ"分析並記錄視網膜動靜脈直徑，血管分叉係數，分叉角度，分叉對稱性，視乳頭周長。我們也記錄其他視網膜特徵，如動靜脈壓跡，出血，硬性滲出，動脈阻塞及血管彎曲性。獨立t檢驗用於對連續變量的單因素分析，卡方檢驗用於對分類變量的單因素分析。Logistic 回歸用於建立統計模型對中風風險進行分類。所有統計方法均應用SPSS16.0 軟件。 / 結果:本研究納入122 中風患者及122 例患者做對照。每組分別有81 例糖尿病患者， 41 例非糖尿病患者。視網膜特徵包括動靜脈直徑，血管彎曲度，出血，硬性滲出，動靜脈壓跡在兩組中有顯著性差異。我們建立風險模型對兩組患者進行風險分類。分類準確度最高達的模型裡面包括的因子有：1)中風相關危險因素包括:高血壓，糖尿病，心房顫動2) 視網膜特徵包括:動脈直徑，血管彎曲性，出血，動靜脈壓跡跟靜脈對稱性；3) 視網膜特徵間的交立作用包括:動脈直徑與靜脈對稱性，動脈直徑與出血，靜脈對稱性與血管彎曲度。分類的準確度為80 .4%。只包括視網膜特徵的分類模型的準確度為74.5% 。 / 結論:彩色視網膜照相可成為中風風險的分類工具。與中風相關的視網膜特徵包括血管直徑，血管彎曲度，血管對稱性，出血，動靜脈壓跡。視網膜特徵與中風之間的聯繫存在交互作用。 / Objective: 1) To detect retina characteristics that associated with stroke; 2) To develop a statistics model with variables of retina characteristics for classifying patients with stroke from those without stroke in aged population. / Method: Matched case control study. Patients with stroke from the diabetic retinopathy screening program and stroke patients from Acute Stroke Unit were selected as stroke cases. Controls (patients without history of stroke) with matched diabetes status and age were selected from the diabetic retinopathy screening program and eye outpatient clinics. All subjects in this study were from Prince of Wales Hospital, Hong Kong. Risk factors of stroke from all subjects were collected, including age, gender, diabetes, hypertension, hyperlipidemia, history of ischemic heart disease, atrial fibrillation and smoking. Color retina images of each subject were collected and analyzed. The retina characteristics, including diameters of arterioles and venules, bifurcation coefficients, bifurcation angles, branch symmetry, optic disc perimeter were extracted from the color retina images by software "ImageJ". Other retina characteristics including arteriole-venule nicking, hemorrhages, exudates, arteriole occlusion, and vessel tortuosity were also recorded. Independent t test and Chi-squire test were used to compare the continuous and categorical retina characteristics respectively between patients with stroke and those without stroke. Logistic model combining the risk factors of stroke and retina characteristics was established to classify patients with stroke from those without stroke. All data analysis was by SPSS 16.0. / Results: there were 122 stroke cases and 122 controls recruited in this study. There were 41 patients without diabetes and 81 patients with diabetes in each group. Retina characteristics including diameters of arterioles and venules, vessel tortuosity, hemorrhages, exudates, arteriole-venule nicking were significantly different between the two groups. We established risk models to classify patients with stroke from those without stroke. The risk model with highest accuracy of classification included 1) stroke risk factors including hypertension, diabetes and atrial fibrillation; 2) retina characteristics, including arteriole diameters, vessel tortuosity, hemorrhages, arteriolevenule nicking and venule symmetry; 3)interaction between retina characteristics, including arteriole diameters by venule symmetry, arteriole diameters by hemorrhage,and venule symmetry by vessel tortuosity. The accuracy of classification was 80.4%. Using retinal characteristics alone achieved an accuracy of 74.5%. / Conclusion: color retina images are a potential tool for stroke risk stratification. Useful characteristics found in the retinal images included vessel diameters, vessel tortuosity, vessel symmetry, hemorrhage, arteriole-venule nicking. The association between the retinal characteristic and stroke was modified by other retinal characteristics. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Li, Qing. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 139-148). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.iii / Acknoledgements --- p.v / Chapter Chapter 1 --- Introduction and review of the Literature --- p.1 / Chapter Section 1: --- Stroke prevention and risk assessment tools --- p.1 / Chapter Section 2: --- Rationale of relationship of vascular circulation between retina and brain --- p.9 / Chapter Section 3: --- Manifestation of hypertensive retinopathy and diabetic retinopathy --- p.12 / Chapter Section 4: --- Retina characteristics related to stroke --- p.15 / Chapter Section 5: --- How to make retina as a tool of risk stratification for stroke --- p.28 / Chapter Section 6: --- Rationale to do study to further explore the useful information in color retina images to make it as tool for stroke risk stratification --- p.31 / Chapter Chapter 2 --- Research hypothesis and general design --- p.33 / Chapter Chapter 3 --- Methods of retia characteristics extraction --- p.34 / Chapter Chapter 4 --- A Study of the Reliability of manual measurement of Retinal characteristics using ImageJ --- p.46 / Chapter Chapter 5 --- A study of comparison of retina characteristics between patients with stroke and patients without stroke --- p.55 / Chapter Section 1: --- Method --- p.56 / Chapter Section 2: --- Result-univariate analysis --- p.62 / Chapter Section 3: --- Results-stratification analysis --- p.68 / Chapter Section 4: --- Result-risk model building for stroke risk stratification --- p.79 / Chapter Chapter 6: --- Discussion --- p.118 / Chapter Chapter 7: --- Limitation of this study --- p.133 / Chapter Chapter 8: --- Future development and application of the study results --- p.134 / Appendix --- p.136 / Reference --- p.139
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328179 |
| Date | January 2012 |
| Contributors | Li, Qing, Chinese University of Hong Kong Graduate School. Division of Public Health. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (vi, 148 leaves) : ill. (some col.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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