Validation of obstetric estimate of gestational age on US birth certificates.

OBJECTIVE: The birth certificate variable obstetric estimate of gestational age (GA) has not been previously validated against GA based on estimated date of delivery from medical records. STUDY DESIGN: We estimated sensitivity, specificity, positive predictive value, negative predictive value and the corresponding 95% confidence intervals (CIs) for preterm delivery (<37 weeks' gestation) based on obstetric estimate using estimated date of delivery-based GA as the gold standard. Trained abstractors obtained the estimated date of delivery from the prenatal record (64.8% in New York City, and 94.6% in Vermont), or, when not available, from the hospital delivery record for 2 population-based samples: 586 live births delivered in New York City and 649 live births delivered in Vermont during 2009. Weights were applied to account for nonresponse and sampling design. RESULTS: In New York City, the preterm delivery rate based on estimated date of delivery was 9.7% (95% CI, 7.6-12.4) and 8.2% (95% CI, 6.3-10.6) based on obstetric estimate; in Vermont, it was 6.8% (95% CI, 5.4-8.4) based on estimated date of delivery and 6.3% (95% CI, 5.1-7.8) based on obstetric estimate. In New York City, sensitivity of obstetric estimate-based preterm delivery was 82.5% (95% CI, 69.4-90.8), specificity 98.1% (95% CI, 96.4-99.1), positive predictive value 98.0% (95% CI, 95.2-99.2), and negative predictive value 98.8% (95% CI, 99.6-99.9). In Vermont, sensitivity of obstetric estimate-based preterm delivery was 93.8% (95% CI, 81.8-98.1), specificity 99.6% (95% CI, 98.5-99.9), positive predictive value 100%, and negative predictive value 100%. CONCLUSION: Obstetric estimate-based preterm delivery had excellent specificity, positive predictive value and negative predictive value. Sensitivity was moderate in New York City and excellent in Vermont. These results suggest obstetric estimate-based preterm delivery from the birth certificate is useful for the surveillance of preterm delivery.

Validation of self-reported maternal and infant health indicators in the Pregnancy Risk Assessment Monitoring System.

To assess the validity of self-reported maternal and infant health indicators reported by mothers an average of 4 months after delivery. Three validity measures-sensitivity, specificity and positive predictive value (PPV)-were calculated for pregnancy history, pregnancy complications, health care utilization, and infant health indicators self-reported on the Pregnancy Risk Assessment Monitoring System (PRAMS) questionnaire by a representative sample of mothers delivering live births in New York City (NYC) (n = 603) and Vermont (n = 664) in 2009. Data abstracted from hospital records served as gold standards. All data were weighted to be representative of women delivering live births in NYC or Vermont during the study period. Most PRAMS indicators had >90 % specificity. Indicators with >90 % sensitivity and PPV for both sites included prior live birth, any diabetes, and Medicaid insurance at delivery, and for Vermont only, infant admission to the NICU and breastfeeding in the hospital. Indicators with poor sensitivity and PPV (<70 %) for both sites (i.e., NYC and Vermont) included placenta previa and/or placental abruption, urinary tract infection or kidney infection, and for NYC only, preterm labor, prior low-birth-weight birth, and prior preterm birth. For Vermont only, receipt of an HIV test during pregnancy had poor sensitivity and PPV. Mothers accurately reported information on prior live births and Medicaid insurance at delivery; however, mothers' recall of certain pregnancy complications and pregnancy history was poor. These findings could be used to prioritize data collection of indicators with high validity.

High Concentration of Medium-Sized HDL Particles and Enrichment in HDL Paraoxonase 1 Associate With Protection From Vascular Complications in People With Long-standing Type 1 Diabetes.

OBJECTIVE: A subset of people with long-standing type 1 diabetes (T1D) appears to be protected from microvascular and macrovascular complications. Previous studies have focused on improved abilities to respond to glucose and its downstream effects as protective mechanisms. It is unclear whether lipoproteins play a role in the vascular health of these people. We therefore determined whether HDL particle concentration, size, function, and/or protein composition associate with protection from vascular complications. RESEARCH DESIGN AND METHODS: We studied two independent cross-sectional cohorts with T1D: the T1D Exchange Living Biobank (n = 47) and the Joslin Medalist Study (n = 100). Some of the subjects had vascular complications, whereas others never exhibited vascular complications, despite an average duration of diabetes in the cohorts of 45 years. We assessed HDL particle size and concentration by calibrated ion mobility analysis, the HDL proteome by targeted mass spectrometry, and HDL function ex vivo by quantifying cholesterol efflux capacity and inhibition of monocyte adhesion to endothelial cells. RESULTS: In both cohorts, people without vascular complications exhibited significantly higher concentrations of medium-sized HDL particles (M-HDL) independently of total and HDL cholesterol levels. While no consistent differences in HDL functions were observed ex vivo, people without vascular complications had higher levels of HDL-associated paraoxonase 1 (PON1), an enzyme that inhibits atherosclerosis in animal models. CONCLUSIONS: Elevated concentrations of M-HDL particles and elevated levels of HDL-associated PON1 may contribute to long-term protection from the vascular complications of diabetes by pathways that are independent of total cholesterol and HDL cholesterol.

Validation of selected items on the 2003 U.S. standard certificate of live birth: New York City and Vermont.

OBJECTIVE: We assessed the validity of selected items on the 2003 revised U.S. Standard Certificate of Live Birth to understand the accuracy of new and existing items. METHODS: We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of select variables reported on the birth certificate using the medical record as the gold standard for a representative sample of live births in New York City (n=603) and Vermont (n=664) in 2009. RESULTS: In both sites, sensitivity was excellent (>90%) for Medicaid coverage at delivery, any previous live births, and current method of delivery; sensitivity was moderate (70%-90%) for gestational diabetes; and sensitivity was poor (<70%) for premature rupture of the membranes and gestational hypertension. In both sites, PPV was excellent for Medicaid coverage, any previous live births, previous cesarean delivery, and current method of delivery, and poor for premature rupture of membranes. In both sites, almost all items had excellent (>90%) specificity and NPV. CONCLUSION: Further research is needed to determine how best to improve the quality of data on the birth certificate. Future revisions of the birth certificate may consider removing those items that have consistently proven difficult to report accurately.

A general framework for modeling growth and division of mammalian cells.

BACKGROUND: Modeling the cell-division cycle has been practiced for many years. As time has progressed, this work has gone from understanding the basic principles to addressing distinct biological problems, e.g., the nature of the restriction point, how checkpoints operate, the nonlinear dynamics of the cell cycle, the effect of localization, etc. Most models consist of coupled ordinary differential equations developed by the researchers, restricted to deal with the interactions of a limited number of molecules. In the future, cell-cycle modeling--and indeed all modeling of complex biologic processes--will increase in scope and detail. RESULTS: A framework for modeling complex cell-biologic processes is proposed here. The framework is based on two constructs: one describing the entire lifecycle of a molecule and the second describing the basic cellular machinery. Use of these constructs allows complex models to be built in a straightforward manner that fosters rigor and completeness. To demonstrate the framework, an example model of the mammalian cell cycle is presented that consists of several hundred differential equations of simple mass action kinetics. The model calculates energy usage, amino acid and nucleotide usage, membrane transport, RNA synthesis and destruction, and protein synthesis and destruction for 33 proteins to give an in-depth look at the cell cycle. CONCLUSIONS: The framework presented here addresses how to develop increasingly descriptive models of complex cell-biologic processes. The example model of cellular growth and division constructed with the framework demonstrates that large structured models can be created with the framework, and these models can generate non-trivial descriptions of cellular processes. Predictions from the example model include those at both the molecular level--e.g., Wee1 spontaneously reactivates--and at the system level--e.g., pathways for timing-critical processes must shut down redundant pathways. A future effort is to automatically estimate parameter values that are insensitive to changes.