首页> 外文期刊>Acta Obstetricia et Gynecologica Scandinavica: Official Publication of the Nordisk Forening for Obstetrik och Gynekologi >Validation of data in the Medical Birth Registry of Norway on delivery after a previous cesarean section
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Validation of data in the Medical Birth Registry of Norway on delivery after a previous cesarean section

机译:在先前的剖宫产后挪威医学出生登记处的数据验证

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Introduction Trial of labor (TOL) is an option in most deliveries after a previous cesarean section (CS). The Medical Birth Registry of Norway (MBRN) has received compulsory notification of all deliveries in the country since 1967, including data that could identify TOL in epidemiologic research. The objective of this study was to validate MBRN data for identification of TOL deliveries after a previous cesarean section (CS). Material and methods The MBRN provided a random national sample of 500 birth order two deliveries during 1989-2012 in women with a registered birth order one CS delivery. The reporting maternity units were asked to complete a questionnaire on data items in both deliveries, using hospital record data as the gold standard. Results Completed questionnaires were returned for 477 women (95.5%) with data on both deliveries. An algorithm to identify TOL using MBRN data from the birth order two delivery had a positive predictive value of 93.2%, a negative predictive value of 93.5%, a sensitivity of 96.1%, and a specificity of 88.8%. Validity of MBRN data on mode and onset of delivery, CS subtype, and planned mode of delivery is also reported. Conclusions MBRN data on planned and actual mode of delivery, CS subtype, and the algorithm to identify TOL in deliveries after a previous CS had satisfactory quality for a registry-based study of TOL.
机译:简介劳动力试验(Tol)是在先前的剖宫产(CS)后大多数交付的选项。自1967年以来,挪威的医疗出生登记处已收到全国所有交付的强制性通知,包括可以识别流行病学研究中的TOL的数据。本研究的目的是验证MBRN数据以识别先前的剖宫产(CS)后的甲状腺产量。 MBRN的材料和方法在1989 - 2012年期间,MBRN提供了500名出生令两次交付中的随机国家样本,妇女在注册出生命1 CS交付中。要求报告产妇单位在两次交付中的数据项上填写问卷,使用医院记录数据作为黄金标准。结果已完成调查问卷,返回477名妇女(95.5%),两种交付数据有关。使用来自出生阶数的MBRN数据识别Tol的算法两次输送的阳性预测值为93.2%,负预测值为93.5%,灵敏度为96.1%,特异性为88.8%。还报道了MBRN数据的有效性,CS子类型和计划的交付方式的模式和发作。结论在先前的CS后,CS子类型的递送和实际交付模式,CS子类型和算法识别交付中的算法的算法对基于注册表的研究进行了令人满意的质量。

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