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Assessment of the Validity of Administrative Data for Gestational Diabetes Ascertainment.
Hsu, Sarah; Selen, Daryl J; James, Kaitlyn; Li, Sijia; Camargo, Carlos A; Kaimal, Anjali; Powe, Camille E.
Afiliação
  • Hsu S; Diabetes Unit, Massachusetts General Hospital, Boston, MA (Ms Hsu and Drs Selen and Powe); Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA (Ms Hsu and Dr Powe).
  • Selen DJ; Diabetes Unit, Massachusetts General Hospital, Boston, MA (Ms Hsu and Drs Selen and Powe); Harvard Medical School, Boston, MA (Drs Selen, James, Camargo, Kaimal, and Powe).
  • James K; Harvard Medical School, Boston, MA (Drs Selen, James, Camargo, Kaimal, and Powe); Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA (Drs James, Kaimal, and Powe).
  • Li S; Department of Medicine, Division of Endocrinology, Warren Alpert Medical School of Brown University, Providence, RI (Dr. Selen), Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA (Ms Li and Dr Camargo).
  • Camargo CA; Harvard Medical School, Boston, MA (Drs Selen, James, Camargo, Kaimal, and Powe); Department of Medicine, Division of Endocrinology, Warren Alpert Medical School of Brown University, Providence, RI (Dr. Selen), Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA (Ms Li and D
  • Kaimal A; Harvard Medical School, Boston, MA (Drs Selen, James, Camargo, Kaimal, and Powe); Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA (Drs James, Kaimal, and Powe).
  • Powe CE; Diabetes Unit, Massachusetts General Hospital, Boston, MA (Ms Hsu and Drs Selen and Powe); Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA (Ms Hsu and Dr Powe); Harvard Medical School, Boston, MA (Drs Selen, James, Camargo, Kaimal, and Powe); Department of Obstetrics and Gynecolo
Am J Obstet Gynecol MFM ; 5(2): 100814, 2023 02.
Article em En | MEDLINE | ID: mdl-36396038
BACKGROUND: Administrative data, including International Classification of Diseases codes and birth certificate records, are often used for retrospective gestational diabetes research investigations to describe associations of gestational diabetes with perinatal complications and long-term outcomes, and to determine gestational diabetes prevalence. Research investigating the validity of using International Classification of Diseases codes and birth certificates for gestational diabetes ascertainment shows varying degrees of reliability. OBJECTIVE: This study aimed to evaluate the accuracy of both International Classification of Diseases codes and birth certificate diagnosis for gestational diabetes ascertainment in a large hospital-based cohort of pregnant individuals, using laboratory criteria for gestational diabetes mellitus as the reference. STUDY DESIGN: We studied individuals who received prenatal care at an academic hospital and affiliated community health centers between 1998 and 2016. In the setting of universal 2-step screening for gestational diabetes, pregnant individuals were classified as having gestational diabetes if ≥2 oral glucose tolerance test values met or exceeded National Diabetes Data Group thresholds. We calculated the sensitivity, specificity, positive predictive value, and negative predictive value for International Classification of Diseases code and birth certificate ascertainment of gestational diabetes, and their exact binomial 95% confidence intervals. RESULTS: In a cohort of 51,059 pregnancies with complete glucose screening, 1303 (2.6%) met National Diabetes Data Group laboratory criteria for gestational diabetes. Gestational diabetes International Classification of Diseases codes had moderate sensitivity of 70.5% (95% confidence interval, 67.9-72.9), high specificity of 99.3% (95% confidence interval, 99.3-99.4), a positive predictive value of 73.3% (95% confidence interval, 70.8-75.8), and a negative predictive value of 99.2% (95% confidence interval, 99.1-99.3). In the 46,512 pregnancies linked to birth certificate data, birth certificate diagnosis had moderate sensitivity (66.3% [95% confidence interval, 63.6-69.0]), high specificity (98.9% [95% confidence interval, 98.8-99.0]), moderate positive predictive value (62.1% [95% confidence interval, 59.8-64.4]), and high negative predictive value (99.1% [95% confidence interval, 99.0-99.2]). CONCLUSION: Ascertainment of gestational diabetes using administrative data, including International Classification of Diseases codes or birth certificates, has moderate sensitivity, moderate positive predictive value, high specificity, and high negative predictive value. Our findings provide context for interpreting the validity of studies that depend on administrative data for ascertainment of gestational diabetes and comparing them with prospective studies that use laboratory-based gestational diabetes criteria.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Gestacional Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Am J Obstet Gynecol MFM Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Gestacional Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Am J Obstet Gynecol MFM Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos