Prediction models for adverse events of whole-cell pertussis vaccine in a public health center
碩士 === 國立臺灣大學 === 預防醫學研究所 === 95 === 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 c...
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ndltd-TW-095NTU057220072015-12-07T04:04:29Z http://ndltd.ncl.edu.tw/handle/87867627013289880811 Prediction models for adverse events of whole-cell pertussis vaccine in a public health center 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 Ching-Jen Chang 張敬仁 碩士 國立臺灣大學 預防醫學研究所 95 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. Kuo-Liong Chien Wei-Chu Chie 簡國龍 季瑋珠 2007 學位論文 ; thesis 95 zh-TW |
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碩士 === 國立臺灣大學 === 預防醫學研究所 === 95 === 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.
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author2 |
Kuo-Liong Chien |
author_facet |
Kuo-Liong Chien Ching-Jen Chang 張敬仁 |
author |
Ching-Jen Chang 張敬仁 |
spellingShingle |
Ching-Jen Chang 張敬仁 Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
author_sort |
Ching-Jen Chang |
title |
Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
title_short |
Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
title_full |
Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
title_fullStr |
Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
title_full_unstemmed |
Prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
title_sort |
prediction models for adverse events of whole-cell pertussis vaccine in a public health center |
publishDate |
2007 |
url |
http://ndltd.ncl.edu.tw/handle/87867627013289880811 |
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