The estimation of gestational age at birth in database studies

Epidemiology

Volumn 28, Issue 6, 2017, Pages 854-862

  Eberg, Maria ^a   Platt, Robert W ^b,c   Filion, Kristian B ^a,b,c  

^a MCGILL UNIVERSITY   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIDEPRESSANT AGENT;

ADULT; ALCOHOL CONSUMPTION; ARTICLE; BIRTH; BIRTH WEIGHT; BODY MASS; COHORT ANALYSIS; DATA BASE; FEMALE; FETUS WEIGHT; GESTATIONAL AGE; GOLD STANDARD; HUMAN; INFANT; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MATERNAL AGE; MATERNAL HYPERTENSION; MATERNAL SMOKING; MULTIPLE PREGNANCY; PARITY; POPULATION RESEARCH; PREECLAMPSIA; PREGNANCY DIABETES MELLITUS; PREMATURE LABOR; PRENATAL EXPOSURE; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SIMULATION; SPONTANEOUS ABORTION; STILLBIRTH; EPIDEMIOLOGY; FACTUAL DATABASE; INFORMATION PROCESSING; NEWBORN; PREGNANCY; PREMATURITY; TIME FACTOR; YOUNG ADULT;

ADULT; ANTIDEPRESSIVE AGENTS; BIRTH WEIGHT; COHORT STUDIES; DATA COLLECTION; DATABASES, FACTUAL; FEMALE; GESTATIONAL AGE; HUMANS; INFANT, NEWBORN; INFANT, PREMATURE; MALE; PREGNANCY; PRENATAL EXPOSURE DELAYED EFFECTS; TIME FACTORS; YOUNG ADULT;

EID: 85022212319     PISSN: 10443983     EISSN: 15315487     Source Type: Journal    
DOI: 10.1097/EDE.0000000000000713     Document Type: Article

References (25)

1. Grzeskowiak LE, Gilbert AL, Morrison JL. Exposed or not exposed? Exploring exposure classification in studies using administrative data to investigate outcomes following medication use during pregnancy. Eur J Clin Pharmacol. 2012;68:459-467.
2. Raebel MA, Ellis JL, Andrade SE. Evaluation of gestational age and admission date assumptions used to determine prenatal drug exposure from administrative data. Pharmacoepidemiol Drug Saf. 2005;14:829-836.
3. Margulis AV, Setoguchi S, Mittleman MA, Glynn RJ, Dormuth CR, Hernández-Díaz S. Algorithms to estimate the beginning of pregnancy in administrative databases. Pharmacoepidemiol Drug Saf. 2013;22:16-24.
4. Andrade SE, Raebel MA, Morse AN, et al. Use of prescription medications with a potential for fetal harm among pregnant women. Pharmacoepidemiol Drug Saf. 2006;15:546-554.
5. Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the General Practice Research Database: a systematic review. Br J Clin Pharmacol. 2010;69:4-14.
6. Khan NF, Harrison SE, Rose P W. Validity of diagnostic coding within the General Practice Research Database: a systematic review. Br J Gen Pract. 2010;60:e128-e136.
7. Herrett E, Gallagher AM, Bhaskaran K, et al. Data resource profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol. 2015;44:827-836.
8. El-Metwally D, Vohr B, Tucker R. Survival and neonatal morbidity at the limits of viability in the mid 1990s: 22 to 25 weeks. J Pediatr. 2000;137:616-622.
9. Kramer MS, Platt RW, Wen S W, et al; Fetal/Infant Health Study Group of the Canadian Perinatal Surveillance System. A new and improved population-based Canadian reference for birth weight for gestational age. Pediatrics. 2001;108:E35.
10. Diggle PJ, Heagerty PK, Liang KY, Zeger SL. Analysis of Longitudinal Data. 2nd ed. New York, NY: Oxford University Press; 2002.
11. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York, NY: Wiley; 1987.
12. Heitjan DF, Little RJA. Multiple imputation for the fatal accident reporting system. J R Stat Soc Series C Appl Stat. 1991;40:13-29.
13. Piper JM, Mitchel EF Jr, Ray WA. Presumptive eligibility for pregnant Medicaid enrollees: its effects on prenatal care and perinatal outcome. Am J Public Health. 1994;84:1626-1630.
14. Burton A, Altman DG, Royston P, Holder RL. The design of simulation studies in medical statistics. Stat Med. 2006;25:4279-4292.
15. Rai D, Lee BK, Dalman C, Golding J, Lewis G, Magnusson C. Parental depression, maternal antidepressant use during pregnancy, and risk of autism spectrum disorders: population based case-control study. BMJ. 2013;346:f2059.
16. Callaghan WM, MacDorman MF, Rasmussen SA, Qin C, Lackritz EM. The contribution of preterm birth to infant mortality rates in the United States. Pediatrics. 2006;118:1566-1573.
17. Sowards KA. What is the leading cause of infant mortality? A note on the interpretation of official statistics. Am J Public Health. 1999;89:1752-1754.
18. Margulis AV, Palmsten K, Andrade SE, et al. Beginning and duration of pregnancy in automated health care databases: review of estimation methods and validation results. Pharmacoepidemiol Drug Saf. 2015;24:335-342.
19. Cea-Soriano L, García Rodríguez LA, Fernández Cantero O, Hernández-Díaz S. Challenges of using primary care electronic medical records in the UK to study medications in pregnancy. Pharmacoepidemiol Drug Saf. 2013;22:977-985.
20. Toh S, Mitchell AA, Werler MM, Hernández-Díaz S. Sensitivity and specificity of computerized algorithms to classify gestational periods in the absence of information on date of conception. Am J Epidemiol. 2008;167:633-640.
21. Hardy JR, Holford TR, Hall GC, Bracken MB. Strategies for identifying pregnancies in the automated medical records of the General Practice Research Database. Pharmacoepidemiol Drug Saf. 2004;13:749-759.
22. National Health Service. Premature Labour and Birth. 2016. Available at: http://www.nhs.uk/conditions/pregnancy-and-baby/pages/premature-early-labour.aspx. Accessed 21 July 2016.
23. Micali N, Stemann Larsen P, Strandberg-Larsen K, Nybo Andersen AM. Size at birth and preterm birth in women with lifetime eating disorders: a prospective population-based study. BJOG. 2016;123:1301-1310.
24. Vandentorren S, Bois C, Pirus C, Sarter H, Salines G, Leridon H; Elfe Team. Rationales, design and recruitment for the Elfe longitudinal study. BMC Pediatr. 2009;9:58.
25. Rappazzo KM, Warren JL, Meyer RE, et al. Maternal residential exposure to agricultural pesticides and birth defects in a 2003 to 2005 North Carolina birth cohort. Birth Defects Res A Clin Mol Teratol. 2016;106:240-249.