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  • 學位論文

一個衛生所全細胞型百日咳疫苗不良事件預測模型之建立

Prediction models for adverse events of whole-cell pertussis vaccine in a public health center

指導教授 : 簡國龍 季瑋珠

摘要


背景:全細胞型百日咳疫苗可以有效預防百日咳,但因為不良事件發生率高,易發生醫療糾紛。不良事件分為常見及嚴重兩類,文獻上常見不良事件包含局部及全身性反應:局部反應(紅、腫、痛)發生率介於三成到五成之間,全身性反應(發燒、哭泣、躁動)發生率介於三成到四成之間;而常見不良事件又與嚴重不良事件相關,故如能建立與嚴重不良事件相關的常見不良事件的預測模型,就可以間接預測嚴重不良事件的發生。 方法:本研究是一個世代型研究,以來台中縣某衛生所接種全細胞型百日咳疫苗的民眾為收案對象,透過問卷的方式收集疫苗副作用、個案家族史、社經狀況、個人病史、身體檢查記錄等資料,以多重邏輯氏回歸及廣義估計值方程式分析,找出常見不良事件的預測模型,並估計與嚴重不良事件的相關性。 結果:自95年7月至96年2月共收案121人:男性63人,平均月齡2.7±1.1個月;女性58人。平均月齡2.4±0.6個月。第一劑發生常見不良事件66.1%,嚴重不良事件6.6%;第二劑95人(78.5%)繼續於本所接種全細胞型百日咳疫苗,常見不良事件81.1%,嚴重不良事件7.4%。母親年齡是第一劑全細胞型百日咳疫苗常見不良事件的最重要的正相關因子,母親懷孕數是最重要的負相關因子;在與第一劑嚴重不良事件相關之常見不良事件的預測模型中,全身性反應相關(包括第一劑全身性反應、第一劑躁動不安、第一劑食慾下降、第一劑嘔吐)的預測模型是較理想的模型。第一劑發生相同的常見不良事件及父親喝酒,是第二劑發生常見不良事件最重要的正相關因子,父親嚼檳榔、家庭收入、加固體食物是最重要的負相關因子;本研究並未找到合適的與第二劑嚴重不良事件相關之常見不良事件的預測模型。在同時考慮前後劑疫苗不良事件及相關因子相關性的重複測量模式分析中,母親喝酒、母親懷個案時罹患子癲(前)症、體重是最重要的正相關因子,母親懷孕時抽菸是最重要的負相關因子。第一劑局部發紅、第一劑活力下降、母親懷孕數、家庭收入、打第一劑前兩個月因病住院(非因出生時入住病嬰室或嬰兒加護病房)及隂囊水腫,是第二劑漏失最重要的預測因子。 結論:母親年齡是第一劑全細胞型百日咳疫苗常見不良事件的最重要的正相關因子;第一劑全身性反應相關的預測模型是與嚴重不良事件相關較理想的預測模型。第一劑發生相同的常見不良事件是第二劑發生常見不良事件最重要的正相關因子。全細胞型百日咳疫苗是一個不良事件發生率高的疫苗,容易發生預防接種受害救濟申訴事件,建議在國家經費許可的情況下,全面改用非細胞型百日咳疫苗為民眾施打。

並列摘要


Background:Whole-cell pertussis vaccines have been demonstrated to effectively protect against pertussis. However, the vaccines induced high rates of adverse events (AEs) so that it’s easy to commit litigation. Two kinds of AEs for vaccine were reported: one is common AE, including local and systemic reactions, and another is severe AE, which is accompanied with common AE. We investigated the risk factors and constructed prediction models for common and severe AEs among participants from a public health center. Methods: A total of 121 participants receiving whole-cell pertussis vaccine inoculation was enrolled from a center at Taichung County in this prospective cohort study. We collected basic demographic data from questionnaires and follow-up the AEs through telephone after vaccine. Multiple logistic regression and generalized estimation equation (GEE) were used to construct prediction models for AEs. Results: During the period of July 06 till Feb. 07, we enrolled 121 infants (63 males and 58 females), mean age 2.59±0.91 months old. The occurrence rates of 1st dose were 66.1% for common and 6.6% for severe AEs. Ninty-five enrollee (78.5%) continued the 2nd dose at the same clinic 2 months later. The 2nd dose rates increased to 81.1% for common and 7.4% for severe AEs. The significant positive predictor for 1st dose common AEs is maternal age. Moreover, maternal gestation number is the significant inverse predictor. Occurrence of common AEs at 1st dose is the most important predictor for the 2nd dose (OR=5.41, 95%CI=1.74-16.8). With regard to repeated measurement analysis, maternal drinking habit, being suffered from preeclampsia at pregnancy, and infants’ body weight are the significant predictors for vaccine common AEs, smoking at pregnancy the most significant inverse predictor at this model. Prediction model for systemic reactions after 1st dose have good prediction ability (area under ROC: 0.80, sensitivity: 0.76, specificity: 0.56). Conclusions: Whole-cell pertussis vaccine is related to high rates of AEs among young participants. We suggested acellular pertussis vaccine in specific high-risk children who are predicted from the prediction model.

參考文獻


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被引用紀錄


賴素真(2012)。新住民對疫苗注射之知識、態度及其相關影響因素探討〔碩士論文,中臺科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0099-0905201314440229

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