Paediatric and Perinatal Epidemiology · 2016 · 30 citations · 20 references
MedicineMaternal HealthObstetricsMaternal-fetal MedicineObstetric ComplicationsPreterm BirthBirth RegistrationEtiology Of Preterm BirthPregnancyPreterm Birth EpidemiologyPreterm Premature Rupture Of MembranesScreening For Preterm BirthAetiological SurveillanceInitiating Event FrequencyPreterm Birth IncidencePreterm Birth SurveillanceSpontaneous Preterm Birth Prediction
BACKGROUND: Determining whether initiation of preterm birth was spontaneous, or through labour induction or caesarean without labour or membrane rupture is critical in surveillance and aetiological research on preterm birth, although this information is not explicitly included on the US Birth Certificate. Algorithms combining several fields from birth certificates have been developed to infer the initiating event, but none has been validated against manual review of original obstetric records. Our objective was to develop a birth certificate-based algorithm to determine initiation of preterm birth and validate it by manual review of original records. METHODS: We developed an algorithm from the 2003 US Standard Birth Certificate to determine spontaneous vs. indicated preterm birth. The algorithm was first tested on obstetrical records from 80 preterm (<37 weeks) births in Columbus OH (2006-12) abstracted by an obstetrics research nurse and reviewed by an obstetrician-gynecologist. Onset of delivery was spontaneous if the initiating event was premature rupture of membranes (PROM) or contractions, or indicated if the initiating event was induction or caesarean without labour or PROM. The algorithm was validated in an independent sample of 100 preterm births from four hospitals. RESULTS: Codes for tocolysis, fetal intolerance of labour, and anaesthesia during labour did not predict labour and were dropped. The final algorithm correctly classified 73/80 cases, kappa = 0.83. In the validation, 86/100 cases were correctly classified. The kappa statistic was 0.68 (0.52, 0.83); predictive values for spontaneous and indicated onset were 85% (75%, 92%) and 89% (71%, 98%). CONCLUSIONS: The algorithm distinguished spontaneous from indicated preterm birth, using birth certificates, with good accuracy.
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