Intraclass correlation coefficients in the Brazilian network for surveillance of severe maternal morbidity study
Intraclass correlation coefficients in the Brazilian network for surveillance of severe maternal morbidity study
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DOI：
10.1186/1471-2393-12-101
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发表时间：
2012-09-21
影响因子：
3.1
通讯作者：
Souza, Joao P.
中科院分区：
文献类型：
--
作者：
Haddad, Samira M.;Sousa, Maria H.;Souza, Joao P.
背景：本研究的目的是评估巴西严重孕产妇发病率监测网络研究中有关个人特征、结构、结果和过程的变量的组内相关系数 (ICC)，该研究旨在使用世界卫生组织的标准识别严重孕产妇发病率/未遂病例。方法：这是一项横断面、多中心研究，涉及巴西 27 家为孕妇提供护理的医院。描述了聚类大小和初级抽样单位的平均大小。给出了每个变量的估计患病率、ICC、各自的 95% 置信区间、设计效果和平均聚类大小。 结果：总体而言，该研究纳入了 9,555 例严重孕产妇发病病例（入院时患有潜在危及生命状况、险些发生事件或死亡的妇女）。 ICC 范围为 < 0.001 至 0.508，中位数为 0.035。大约 75% 的变量的 ICC < 0.1。对于与过程相关的变量，中位 ICC 为 0.09，与结果相关的变量为 0.021。这些发现证实了之前研究的数据。同质性可能被认为很小，从而提高了这些研究结果的可靠性。结论：这些结果可用于设计孕产妇和围产期健康的新集群试验，并帮助计算样本量。
Background: The purpose of the study was to evaluate intraclass correlation coefficients (ICC) of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria.Method: It was a cross-sectional, multicenter study involving 27 hospitals providing care for pregnant women in Brazil. Cluster size and the mean size of the primary sampling unit were described. Estimated prevalence rates, ICC, their respective 95% confidence intervals, the design effect and the mean cluster size were presented for each variable.Results: Overall, 9,555 cases of severe maternal morbidity (woman admitted with potentially life-threatening conditions, near miss events or death) were included in the study. ICC ranged from < 0.001 to 0.508, with a median of 0.035. ICC was < 0.1 for approximately 75% of the variables. For process-related variables, median ICC was 0.09, with 0.021 for those related to outcome. These findings confirm data from previous studies. Homogeneity may be considered minor, thus increasing reliability of these findings.Conclusions: These results may be used to design new cluster trials in maternal and perinatal health and to help calculate sample sizes.