OBSTETRICS & GYNECOLOGY

1. OBSTETRICS & GYNECOLOGY LIQIAN QIU 邱丽倩 Women’s Hospital Zhejiang University School of Medicine

2. Women’s reproductive system diseases 女性生殖系统疾病 Epidemiology for the Gynecology 妇产科疾病流行病学

3. 妇产科学科研究什么？What is topic 怎样学好这门学科? How to learn?

4. 妇产科是专门研究女性特有的生理、病理及生育调节方面的学科妇产科是专门研究女性特有的生理、病理及生育调节方面的学科 • 产科（Obstetrics) • 妇科 (Gynecology) • 计划生育 (Family Planning) • 妇女保健 (Women’s Health, ~Maternal Health)

5. 妇产科发展史 • 发展起源于产科：产科最早是一门技术（类似于工匠），民间叫接生婆（birth attendant)。 • 现代妇产科的发展是伴随着解剖学，麻醉学、药理学的发展而发展。 • 剖宫产技术（Caesarean section帝王切开)，子宫和附件的手术随现代医学的发展而发展。

6. 近代妇产科学的突破 • 内窥镜技术 Endoscopy • 辅助生育技术 Reproductive assistant technology • 产前诊断技术 Prenatal diagnosis technology • 宫颈癌筛查技术 Cervical cancer screening

7. 产科：研究妊娠、分娩和产褥的生理和病理。 • 妇科：女性生理，内分泌，肿瘤，炎症、生殖器官发育和损伤，辅助生育等。 • 计划生育：生育的调控。 • 妇女保健：妇女各年龄段的预防保健、常见疾病预防。

8. How to learn? • 与任何医学学科一样最基础的从解剖，生理特点开始。 解剖上注重盆腔的解剖，生理上强调丘脑下部－垂体－卵巢轴神经内分泌反馈调节。 • 把厚的书读薄，抓住主要的关节点，融会贯通。 • 作为一个好医生，首先的素质在于仔细，判断正确后果断处理。妇产科疾病相对单纯。 • 规范化的从医。

9. 在实际工作中面对每一位患者诊治的思维包括对病因、病理、病变部位、疾病症状，演变过程及转归的认识。在实际工作中面对每一位患者诊治的思维包括对病因、病理、病变部位、疾病症状，演变过程及转归的认识。 • 确定一个疾病诊断需要认真细致的诊察，作出正确的判断。 • 手段：通过病史，系统检查，辅助检查资料进行归纳、分析、鉴别和综合评价。

10. 近年来医疗理念的发展 • 循证医学（Evidence based medicine) 强调有证据，有科学道理 • 人文医学 （Humanistic medicine) 强调诊疗规范，临床路径.

11. 妇产科学习的特点 • 产科和妇科疾病互相关联，相互影响，这种相关性随着现代妇产科理论的不断更新，越来越显现。分科越来越细，关联越来越密，交叉性学科的需求凸显。 • 与预防医学不可分割：围产保健技术，肿瘤筛查 • 妇产科特有的特点：性别单一性，男医生参与的不便性等。

12. 妇产科流行病学Epidemiology

13. 基本概念 • 定义（Definition）流行病学是研究人群健康事件的学科（Health events in human populations）. • 多数妇产科医生不懂流行病学。 • 高级的医学生和医生应该了解这个学科才能了解有关科学研究。 should learn the interpretation and discussion the relevant Epi study finding. • 了解流行病学才能了解研究结果是否有重要意义。Reading literature with critical Epi principle knowledge.

14. The key questions: Why everyone wants to read your study/paper • What exactly did you measure (definitions) • What has worked? • Has bias been eliminated? • Can the study be generalised to a larger population? • Can the program be reproduced somewhere else? (“Pilot”becomes “program”) • So what – how will this changebest practice? Does it have significant advantages over existing practices? Cost, culture, efficacy etc • Do these results have a “use by” date? How long will this advice lastbefore conditions change?

15. 常用术语 1 • Age-specific incidence • Attributable risk（归因危险度） • Clinical trial • Cohort • Confidence interval (CI) • Confounder

16. 常用术语2 • Incidence & Prevalence • Predictive value of a negative test • Prevalence • bias • Relative risk & Odds ratio

17. 常用术语 3 • Sensitivity • Specificity • Statistical significance • Yield (RR, OR…..)

18. Ratios, proportions and rates These are combinations of two numbers: Numerator （分子） Denominator （分母） (Errors in either cause errors in final result) Ratio – a general term. A relationship between two quantities. Ratio = a:b or a/b (no relationship necessary between “a” and “b”, eg beds per 1000 population) (eg SMR, Odds Ratio)

19. Proportion – a specific ratio where ‘numerator’ is included in ‘denominator’. Eg 杭州人抽烟比例 = No. Smokers/total population (which includes smokers) a/(a+b)

20. Rate A proportion. A rate is a ratio with a specific relationship between ‘n’ and ‘d’ and time period in denominator. Eg. Incidence Lung cancer cases /population/year CDR, age specific death rates.

21. Rates include cases in denominator a/a+b Ratios a/b

22. Incidence The rate at which new cases occur in a population during a specified period. No. cases measles/100,000/year

23. Prevalence The prevalence of a disease is the proportion of a population that are cases at a point in time. Point prevalence Period prevalence

24. Acute disease. High incidence, low prevalence Chronic disease. low incidence, High prevalence Examples: URTI （上呼吸道感染） Diabetes (eg kwashiorkor) with chronic diseases (eg obesity).

25. Study Designs • Descriptive Studies: It is the basic for any study for description of general characteristics. (surveys, case studies etc) • Case Report or Series

26. Cross-sectional Studies Incidence Age-specific incidence Prevalence

27. Analytic Studies • Test a hypothesis the relationship between exposure and no exposure. 2 types of studies: Nonexperimental: Cohort, case-control Experimental: Clinical trials

28. Cohort study • Longitudinal study, using survival analysis to describe mortality. • Yield: evaluation the association between exposure and illness. (Fig 4.2) • Strengths: Obtain both attributable and relative risk, less susceptible and recall bias • Weakness: long time, high cost, lost cases

29. Case control study • Comparing difference to exposure between cases and controls. • Yield: Odds ratio, similar to relative risk. No attributable risk could gotten. • Strengths: low cost, easy to do. • Weaknesses: selection bias, information bias, confounding variable.

30. Observational Studies • Descriptive (surveys, case studies etc) • Case-Control, • Cohort studies (usually longitudinal, can be retrospective)

31. Intervention studies • Laboratory Studies • Cell biology • Genetics • Chemistry and Biochemistry. • Clinical trials

32. Clinic trials: prospective cohort study. Good design is sufficient number of subjects. • Field and community intervention trails: vaccines, dietary intervention. Need large number participants.

33. Test • Significance • Degree of conflict • Confidence interval • Bias • Confounding • Biologic credibility

34. Risk: probability of an individual of experiencing a specific event, in a specific time, under specific conditions. We estimate individual risks from populations. Risk can be negative (ie protects) or positive (ie causal).

35. ‘Risk’ and ‘Odds’ The risk of an event happening is simply the number of those whoexperience the event divided by the total number of people at risk of having that event. It is usually expressed as a proportion or as a percentage. a/a+b The odds of an event is the number of those who experience theevent divided by the number of those who do not. It is expressed as a number from zero (event will never happen) to infinity (event is certain to happen). a:b

36. Measures of effect We compare outcomes in two groups – those who are exposed and those who are not exposed (controls) Odds ratio = a:b/c:d Risk ratio = a/(a+b)/c(c+d) OR and RR are different – but approximate each other in rare events. RR is a better indication of risk, but requires prospective studies. See BMJ 1998;316:989-991

37. Cohort Study Exposed Outcomes Not Exposed TIME T1 T2 Cohort Study, recruit at exposure, measure Outcome Advantage - Measures risk ratio (RR). Disadvantages - Time, n, cost.

38. Risk ratio (RR) = Rate exposed Rate unexposed Cohort Study (relative risk) A direct measure of risk Make sure 95% CI is given (Cases included in denominator)

39. Case-Control Study Cases Exposed Outcomes Controls No or Less Exposure TIME T1 Case-Control Study, recruit on outcome, measure exposure (odds ratio OR). Advantages – time, n, cost. Disadvantage – no direct risk measurement.

40. Case-Control Study Odds ratio (OR). = Odds in exposed Odds in unexposed (Cases not included in denominator)

41. Sensitivity - proportion ofthe true cases detected. • a/a +c

42. Specificity- • A specific test has few false positives, and this quality is measured by d/b + d.

43. Calculation－1 Proportion Survival Analysis Life table analysis (Always present 95% confidence intervals)

44. Calculation－2 • Crude Rates • Adjusted Rates (standardised rates) • Errors • Random error • Systematic errors (bias)

45. Calculation－3 • Life Expectancy • Person years of life lost • Disability adjusted life expectancy (DALES) • Bias • Sample • Representative • Size • Controls • Validity

46. Describing Data Mean Standard Deviation (SD = Z) Z Score – a Z score of +1 is one standard deviation above the mean a Z score of -2 is two standard deviations below the mean

47. 100 80 60 40 20 10 Studyometer: Hierarchy of studies: Truth Pooled data analysis, Meta – analysis of all studies, systematic reviews Randomised Controlled Trials Cohort Case – control Surveys, ecological studies, case reports

48. Minimising Confounding Impossible to be sure eliminated Match the controls to the exposed subjects so that they have a similar pattern of exposure to the confounder, or by measuring exposure to the confounder in each group and adjusting for any difference in the statistical analysis. Eg Standardisation to adjust for age and sex, Can be applied to others eg SES class, Education adjust for confounding, eg mathematical modelling techniques such as logistic regression. These assume that a person's risk of disease is a specified mathematical function of his exposure to different risk factors and confounders. They should be used with caution, however, as the mathematical assumptions in the model may not always reflect the realities of biology. Models must make sense!

49. 定义的认定 Nutrition studies – always check definitions as they can vary a lot from study to study. Eg Obesity Undernutrition Breastfeeding

50. Gynecologic Events （可以做流行病调查的妇产科事件） • Reproductive history Menarche, Menstrual cycle, Num of pregnancies, contraception, hormone using. • Contraception barrier, IUD, Oral pill, Sterilization