資料的評(píng)讀II診斷與篩檢.ppt

資料的評(píng)讀(II) 診斷與篩檢,神經(jīng)內(nèi)科 王志弘,診斷的過程,Initiation of diagnosis hypothesis 初步診斷 我想這病人可能有 。 Refinement of the diagnostic causes 修正診斷 他可能不是X 或 Y ，但到底是何種感染呢？ Narrowing the possibilities Defining the final diagnosis 最終診斷 我們應(yīng)該再做個(gè)XX 切片確定，再來(lái)治療,初步診斷,目前有上萬(wàn)種的診斷疾病 如果我們不認(rèn)識(shí)這個(gè)疾病，我們就不可能考慮到這個(gè)診斷 關(guān)於疾病發(fā)生比例的文獻(xiàn)，讓我們了解各種診斷的可能性（pretest probability）,修正診斷,根據(jù) Symptoms, 癥狀 Signs, 徵象 Laboratory tests, 實(shí)驗(yàn)室檢查 Imaging, 影像檢查,診斷性試驗(yàn)的實(shí)證,Evidence about “diagnostic tests” Is this evidence about the accuracy of diagnostic test valid? Is this (valid) evidence show that the test is useful at all? How can I apply this valid, accurate diagnostic test to a specific patient?,文獻(xiàn)評(píng)讀,治療性 Validity (closeness to the truth) Impact (size of the effect) Applicability (usefulness in our clinical practice),診斷性 Is this evidence about the accuracy of diagnostic test valid? Is this (valid) evidence show that the test is useful at all? How can I apply this valid, accurate diagnostic test to a specific patient?,Valid Useful Apply,什麼是正常,BNP vs LV dysfunction,Is this evidence about the accuracy of a diagnostic test valid?,Validity about Diagnostic Tests,Diagnostic Test in Question Reference (gold) standard,常見的 GOLD STANDARDS,外科或是病理標(biāo)本 血液培養(yǎng)的菌株 風(fēng)溼熱， Jones Criteria DSM IV (精神疾病) X 光 長(zhǎng)期追蹤,代表性,該檢查是否在適當(dāng)?shù)牟』甲迦褐斜辉u(píng)估過（尤其是那些在臨床上會(huì)使用此一檢查的對(duì)象） Representative common presentation of the target disorder confusing presentations include patients, with mild and severe, early and late, treated and untreated cases.,確定性,無(wú)論檢查結(jié)果如何，參考標(biāo)準(zhǔn)（reference standard）是否經(jīng)過確認(rèn) 如何達(dá)到確定診斷? 另一個(gè)參考標(biāo)準(zhǔn) 長(zhǎng)期追蹤 確定不會(huì)延誤治療,測(cè)量,Independent and blind measurement Psychiatric disorders,Is this (valid) evidence show that the test is useful at all?,Sensitivity, Specificity, Likelihood ratios,整體盛行率,Prevalence = ( a + c) / ( a + b + c +d ) = 809 / 2579 = 31% Pre-test probability,Positive predictive value,陽(yáng)性預(yù)測(cè)值= a / (a + b) = 731 / 1001 = 73% 檢查陽(yáng)性（ferritin 65）的人當(dāng)中，真正有?。ㄈ辫F性貧血）的人的比例,Negative predictive value,陰性預(yù)測(cè)值= d / (c + d) = 1500 / 1578 = 95% 檢查陰性（ferritin 65）的人當(dāng)中，真正沒有病（缺鐵性貧血）的人的比例,Positive vs Negative Predictive Value,Pre-test probability: 測(cè)前機(jī)率 Post-test probability: 測(cè)後機(jī)率 根據(jù)前兩張slide： Positive predictive value: 73% Negative predictive value: 95% 假設(shè)抽血檢查前病人(有病)的測(cè)前機(jī)率：50% 如果陽(yáng)性反應(yīng) 測(cè)後機(jī)率：73% 如果陰性反應(yīng) 測(cè)後機(jī)率： 1-95% = 5%,Sensitivity,敏感度= a / (a + c) = 731 / 809 = 90% 真正有病的人當(dāng)中，檢查有問題（陽(yáng)性）的比例,Specificity,特異度= d / (b + d) = 1500 / 1700 = 85% 真正沒病的人當(dāng)中，檢查沒問題（陰性）的比例,Likelihood Ratio,可能性比率 陽(yáng)性結(jié)果的可能性比率 LR+ = (出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陽(yáng)性的可能性） / (沒有出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陽(yáng)性的可能性） = 敏感度 / (1- 特異度) = 90% / (1-85%) = 6,Likelihood Ratio,陰性結(jié)果的可能性比率 LR- = (出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陰性的可能性） / (沒有出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陰性的可能性） = (1-敏感度) / 特異度 = (1-90%) / 85% = 0.12,勝算 vs 機(jī)率,Odds vs Probability 假設(shè)有病與沒病的機(jī)率分別是 31%，69% 則有病的勝算為：31%/69% = 0.45 Study pre-test odds = prevalence / (1-prevalence),Post-test Odds 測(cè)後勝算,LR+ = (出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陽(yáng)性的可能性） / (沒有出現(xiàn)目標(biāo)疾病的病人中，檢查結(jié)果為陽(yáng)性的可能性） LR+(ferritin)= sensitivity/(1-specificity) = 90%/15%=6 測(cè)後勝算(陽(yáng)性反應(yīng)) = 測(cè)前勝算 * LR+ =1 * 6 = 6 測(cè)後勝算(陰性反應(yīng)) = 測(cè)前勝算 * LR-,Post-test Odds vs Probability,測(cè)後機(jī)率 = 測(cè)後勝算 / (測(cè)後勝算+1) Study pre-test odds = 0.45 Study post-test odds = 0.45 *6 = 2.7 Study post-test probability = 2.7 /(2.7+1) = 73%,Post-test Odds , Probability (陰性),測(cè)後機(jī)率 = 測(cè)後勝算 / (測(cè)後勝算+1) Study pre-test odds = 0.45 Study post-test odds = 0.45 *0.12 = 0.054 Study post-test probability(有病) = 0.054/(0.054+1) = 5% 測(cè)後沒病機(jī)率 = 1-5% = 95% negative predictive value,個(gè)人化調(diào)整,病患測(cè)後勝算 = 研究測(cè)後勝算 * (病患測(cè)前勝算/研究測(cè)前勝算),檢查是否有用,Sensitivity 敏感度, Specificity 特異度 兩者相加減掉100% (Youden Index) 至少要大於 0, 最好要大於 50%, 理想值是 100%,Rule in / Rule out,SnNout: high sensitivity, negative result rule out the diagnosis SpPin: high specificity, positive result rule in the diagnosis LR+ = sensitivity / (1-specificity) LR- = (1-sensitivity) /specificity,D-dimer vs Deep Vein Thrombosis Sensitivity: 97.7% Specificity: 46%,Ferritin vs Iron deficiency anemia Sensitivity: 90%, specificity: 85%,How can I apply this valid, accurate diagnostic test to a specific patient?,Is the diagnostic tests,Available Affordable Accurate Precise In our setting,Patients Pre-Test Probability,From personal experience, prevalence statistics, practice database, primary studies The study patients similar to our own ? If the disease probability changes after the evidence,Results Affect our management?,Move us across a test-treatment threshold Our patient willing to carry it out The consequence of the test help the patient reach his/her goal,Multilevel likelihood ratios,Multiple Tests,Prediction rule,SCREENING,Screening Early diagnosis of pre-symptomatic disease among well individual in public,Case-finding Early diagnosis of pre-symptomatic disease among patients who came to us for other unrelated diseases,Harm of Early Diagnosis,Label: high risk for developing