婦產(chǎn)科學(xué)習(xí)的特點

1、,,,,OBSTETRICS & GYNECOLOGY,LIQIAN QIU 邱麗倩Women’s Hospital Zhejiang University School of Medicine,Women’s reproductive system diseases 女性生殖系統(tǒng)疾病,Epidemiology for the Gynecology 婦產(chǎn)科疾病流行病學(xué),,,婦產(chǎn)科學(xué)科研究什么？What is topic

2、 怎樣學(xué)好這門學(xué)科? How to learn?,婦產(chǎn)科是專門研究女性特有的生理、病理及生育調(diào)節(jié)方面的學(xué)科,產(chǎn)科（Obstetrics)婦科 (Gynecology)計劃生育 (Family Planning)婦女保健 (Women’s Health, ~Maternal Health),婦產(chǎn)科發(fā)展史,發(fā)展起源于產(chǎn)科：產(chǎn)科最早是一門技術(shù)（類似于工匠），民間叫接生婆（birth attendant)。 現(xiàn)代婦產(chǎn)科的發(fā)展是伴隨著解

3、剖學(xué)，麻醉學(xué)、藥理學(xué)的發(fā)展而發(fā)展。剖宮產(chǎn)技術(shù)（Caesarean section帝王切開)，子宮和附件的手術(shù)隨現(xiàn)代醫(yī)學(xué)的發(fā)展而發(fā)展。,近代婦產(chǎn)科學(xué)的突破,內(nèi)窺鏡技術(shù) Endoscopy輔助生育技術(shù) Reproductive assistant technology產(chǎn)前診斷技術(shù) Prenatal diagnosis technology宮頸癌篩查技術(shù) Cervical cancer screening,,產(chǎn)科：研究妊娠、分娩和產(chǎn)褥

4、的生理和病理。婦科：女性生理，內(nèi)分泌，腫瘤，炎癥、生殖器官發(fā)育和損傷，輔助生育等。計劃生育：生育的調(diào)控。婦女保?。簨D女各年齡段的預(yù)防保健、常見疾病預(yù)防。,How to learn?,與任何醫(yī)學(xué)學(xué)科一樣最基礎(chǔ)的從解剖，生理特點開始。 解剖上注重盆腔的解剖，生理上強(qiáng)調(diào)丘腦下部－垂體－卵巢軸神經(jīng)內(nèi)分泌反饋調(diào)節(jié)。把厚的書讀薄，抓住主要的關(guān)節(jié)點，融會貫通。作為一個好醫(yī)生，首先的素質(zhì)在于仔細(xì)，判斷正確后果斷處理。婦產(chǎn)科疾病相對單純。規(guī)范

5、化的從醫(yī)（遵循臨床路徑）。,,在實際工作中面對每一位患者診治的思維包括對病因、病理、病變部位、疾病癥狀，演變過程及轉(zhuǎn)歸的認(rèn)識。確定一個疾病診斷需要認(rèn)真細(xì)致的診察，作出正確的判斷。手段：通過病史，系統(tǒng)檢查，輔助檢查資料進(jìn)行歸納、分析、鑒別和綜合評價。,近年來醫(yī)療理念的發(fā)展,循證醫(yī)學(xué)（Evidence based medicine) 強(qiáng)調(diào)有證據(jù)，有科學(xué)道理人文醫(yī)學(xué) （Humanistic medicine) 強(qiáng)調(diào)

6、診療規(guī)范，臨床路徑.,婦產(chǎn)科學(xué)習(xí)的特點,產(chǎn)科和婦科疾病互相關(guān)聯(lián)，相互影響，這種相關(guān)性隨著現(xiàn)代婦產(chǎn)科理論的不斷更新，越來越顯現(xiàn)。分科越來越細(xì)，關(guān)聯(lián)越來越密，交叉性學(xué)科的需求凸顯。與預(yù)防醫(yī)學(xué)不可分割：圍產(chǎn)保健技術(shù)，腫瘤篩查婦產(chǎn)科特有的特點：性別單一性，男醫(yī)生參與的不便性等。,婦產(chǎn)科流行病學(xué)Epidemiology,基本概念,定義（Definition） 流行病學(xué)是研究人群健康事件的學(xué)科（Health events in human

7、populations）.多數(shù)婦產(chǎn)科醫(yī)生不懂流行病學(xué)。高級的醫(yī)學(xué)生和醫(yī)生應(yīng)該了解這個學(xué)科才能了解有關(guān)科學(xué)研究。 should learn the interpretation and discussion the relevant Epi study finding.了解流行病學(xué)才能了解研究結(jié)果是否有重要意義。Reading literature with critical Epi principle knowledge.,寫文

8、章讓別人了解自己研究的目的：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 “p

9、rogram”)So what – how will this change best practice? Does it have significant advantages over existing practices? Cost, culture, efficacy etcDo these results have a “use by” date? How long will this advice last befor

10、e conditions change?,流行病學(xué)常用術(shù)語 1,Age-specific incidenceAttributable risk（歸因危險度）Clinical trialCohort Confidence interval (CI)Confounder,常用術(shù)語2,Incidence & PrevalencePredictive value of a negative testPrevalenceb

11、iasRelative risk & Odds ratio,常用術(shù)語 3,SensitivitySpecificityStatistical significanceYield (RR, OR…..),Ratios, proportions and rates These are combinations of two numbers:Numerator （分子）Denominator （分母）(Erro

12、rs in either cause errors in final result)Ratio ：a general term. A relationship between two quantities. Ratio ： a/b (no relationship necessary between “a” and “b”, eg beds per 1000 population) (e

13、g SMR, Odds Ratio),Proportion – a specific ratio where ‘numerator’ is included in ‘denominator’. Eg 杭州人抽煙比例 =No. Smokers/total population (which includes smokers) a/(a+b),Rate A proportion.,A rate is a rat

14、io with a specific relationship between ‘n’ and ‘d’ and time period in denominator.Eg. Incidence Lung cancer cases /population/yearCDR, age specific death rates.,,Rates include cases in denominator a

15、/a+bRatios a/b,Incidence,The rate at which new cases occur in a population during a specified period.No. cases measles/100,000/year,Prevalence,The prevalence of a disease is the proportion of a popul

16、ation that are cases at a point in time. Point prevalencePeriod prevalence,,Acute disease. High incidence, low prevalenceChronic disease. low incidence, High prevalenceExamples:URTI （上呼吸道感染）Diabetes(eg kwashiork

17、or) with chronic diseases (eg obesity).,Study Designs,Descriptive Studies: It is the basic for any study for description of general characteristics. (surveys, case studies etc)Case Report or Series,,Cross-sectional Stud

18、iesIncidenceAge-specific incidencePrevalence,Analytic Studies,Test a hypothesis the relationship between exposure and no exposure. 2 types of studies: Nonexperimental: Cohort, case-control E

19、xperimental: Clinical trials,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 a

20、nd relative risk, less susceptible and recall biasWeakness: long time, high cost, lost cases,Case control study,Comparing difference to exposure between cases and controls.Yield: Odds ratio, similar to relative risk.

21、 No attributable risk could gotten.Strengths: low cost, easy to do.Weaknesses: selection bias, information bias, confounding variable.,Observational Studies Descriptive (surveys, case studies etc) Case-Control,

22、Cohort studies (usually longitudinal, can be retrospective),,Intervention studies Laboratory StudiesCell biologyGeneticsChemistry and Biochemistry. Clinical trials,,Clinic trials: prospective cohort study. Good desi

23、gn is sufficient number of subjects.Field and community intervention trails: vaccines, dietary intervention. Need large number participants.,Test,SignificanceDegree of conflictConfidence intervalBiasConfoundingBio

24、logic credibility,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

25、positive (ie causal).,‘Risk’ and ‘Odds’,The risk of an event happening is simply the number of those who experience the event divided by the total number of people at risk of having that event. It is usually expressed as

26、 a proportion or as a percentage.a/a+bThe odds of an event is the number of those who experience the event divided by the number of those who do not. It is expressed as a number from zero (event will never happen) to

27、 infinity (event is certain to happen).a:b,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:dRisk ratio = a/(a+b)/c(c+d)OR an

28、d 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,,,Cohort Study, recruit at exposure, measure OutcomeAdvanta

29、ge - Measures risk ratio (RR). Disadvantages - Time, n, cost.,Cohort Study,T1,T2,Cohort Study,,Risk ratio (RR) = Rate exposedRate unexposed,,A direct measure of riskMake sure 95% CI is given,(Cases included in deno

30、minator),(relative risk),,Case-Control Study, recruit on outcome, measure exposure (odds ratio OR). Advantages – time, n, cost. Disadvantage – no direct risk measurement.,Case-Control Study,T1,,Odds ratio (OR) = Odds

31、 in exposedOdds in unexposed,Case-Control Study,,(Cases not included in denominator),Sensitivity - proportion ofthe true cases detected.,a/a +c,Specificity-,A specific test has few false positives, and this quality

32、 is measured by d/b + d.,Calculation－1,ProportionSurvival AnalysisLife table analysis(Always present 95% confidence intervals),Calculation－2,Crude RatesAdjusted Rates (standardised rates)ErrorsRandom errorSyste

33、matic errors (bias),Calculation－3,Life ExpectancyPerson years of life lostDisability adjusted life expectancy (DALES)BiasSample RepresentativeSizeControlsValidity,Describing Data,Mean Standard Deviation (SD =

34、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,TruthPooled data analysis, Meta – analysis of all studies, systematic reviewsR

35、andomised Controlled TrialsCohortCase – controlSurveys, ecological studies, case reports,,1008060402010,Studyometer: Hierarchy of studies,Minimising Confounding,Impossible to be sure eliminated Matc

36、h 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 analy

37、sis.Eg Standardisation to adjust for age and sex,,Can be applied to others adjust for confounding, eg mathematical modelling techniques such as logistic regression. These assume that a person's risk of disease

38、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

39、 of biology.,定義的認(rèn)定,Nutrition studies – always check definitions as they can vary a lot from study to study.Eg ObesityUndernutritionBreastfeeding,Gynecologic Events （可以做流行病調(diào)查的婦產(chǎn)科事件）,Reproductive historyMenarche, M