Pharmacoepidemiology and drug safety · 2008
Validation of neural tube defects in the full featured--general practice research database.
СтатьяПоддержка службы здравоохранения СШАВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Devine Scott, West Suzanne L, Andrews Elizabeth, Tennis Pat, Eaton Susan, Thorp John, Olshan Andrew
Аннотация
BACKGROUND: The General Practice Research Database (GPRD) has been used to identify associations between pregnancy medication exposures and birth defects, but experts have argued that databases such as this one cannot provide detailed information for the valid identification of complicated congenital anomalies. Our objective was to determine if the GPRD could be used to identify cases of neural tube defects (NTDs).
METHODS: First, we created algorithms for anencephaly, encephalocele, meningocele, and spina bifida and used them to identify potential cases. We used the algorithms to identify 217 potential NTD cases in either a child's or a mother's record. We validated cases by querying general practitioners (GPs) via questionnaire. Where cases of NTD were identified in the mother's record, in addition to confirming the diagnosis, we asked the GPs if the diagnosis was for the mother or that of her fetus or offspring.
RESULTS: Two hundred seventeen cases were identified, and 165 GP questionnaires were returned. We validated an NTD diagnosis for 117 cases, giving our algorithms a positive predictive value (PPV) of 0.71. The PPVs varied by NTD type: 0.81 for anencephaly, 0.83 for cephalocele, 0.64 for meningocele, and 0.47 for spina bifida.
CONCLUSIONS: Our identification algorithm was useful in identifying three of the four types of NTDs studied. Additional information is necessary to accurately identify cases of spina bifida.
METHODS: First, we created algorithms for anencephaly, encephalocele, meningocele, and spina bifida and used them to identify potential cases. We used the algorithms to identify 217 potential NTD cases in either a child's or a mother's record. We validated cases by querying general practitioners (GPs) via questionnaire. Where cases of NTD were identified in the mother's record, in addition to confirming the diagnosis, we asked the GPs if the diagnosis was for the mother or that of her fetus or offspring.
RESULTS: Two hundred seventeen cases were identified, and 165 GP questionnaires were returned. We validated an NTD diagnosis for 117 cases, giving our algorithms a positive predictive value (PPV) of 0.71. The PPVs varied by NTD type: 0.81 for anencephaly, 0.83 for cephalocele, 0.64 for meningocele, and 0.47 for spina bifida.
CONCLUSIONS: Our identification algorithm was useful in identifying three of the four types of NTDs studied. Additional information is necessary to accurately identify cases of spina bifida.