The validity of hospital diagnostic and procedure codes reflecting morbidity in preterm neonates born <32 weeks gestation.

OBJECTIVE: To determine the validity of diagnostic hospital billing codes for complications of prematurity in neonates <32 weeks gestation. STUDY DESIGN: Retrospective cohort data from discharge summaries and clinical notes (n = 160) were reviewed by trained, blinded abstractors for the presence of intraventricular hemorrhage (IVH) grades 3 or 4, periventricular leukomalacia (PVL), necrotizing enterocolitis (NEC), stage 3 or higher, retinopathy of prematurity (ROP), and surgery for NEC or ROP. Data were compared to diagnostic billing codes from the neonatal electronic health record. RESULTS: IVH, PVL, ROP and ROP surgery had strong positive predictive values (PPV > 75%) and excellent negative predictive values (NPV > 95%). The PPVs for NEC (66.7%) and NEC surgery (37.1%) were low. CONCLUSION: Diagnostic hospital billing codes were observed to be a valid metric to evaluate preterm neonatal morbidities and surgeries except in the instance of more ambiguous diagnoses such as NEC and NEC surgery.

The Association of Polymorphisms in Circadian Clock and Lipid Metabolism Genes With 2nd Trimester Lipid Levels and Preterm Birth.

Deregulation of the circadian system in humans and animals can lead to various adverse reproductive outcomes due to genetic mutations and environmental factors. In addition to the clock, lipid metabolism may also play an important role in influencing reproductive outcomes. Despite the importance of the circadian clock and lipid metabolism in regulating birth timing few studies have examined the relationship between circadian genetics with lipid levels during pregnancy and their relationship with preterm birth (PTB). In this study we aimed to determine if single nucleotide polymorphisms (SNPs) in genes from the circadian clock and lipid metabolism influence 2nd trimester maternal lipid levels and if this is associated with an increased risk for PTB. We genotyped 72 SNPs across 40 genes previously associated with various metabolic abnormalities on 930 women with 2nd trimester serum lipid measurements. SNPs were analyzed for their relationship to levels of total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL) and triglycerides (TG) using linear regression. SNPs were also evaluated for their relationship to PTB using logistic regression. Five SNPs in four genes met statistical significance after Bonferroni correction (p < 1.8 × 10-4) with one or more lipid levels. Of these, four SNPs were in lipid related metabolism genes: rs7412 in APOE with total cholesterol, HDL and LDL, rs646776 and rs599839 in CELSR2-PSRC1-SORT1 gene cluster with total cholesterol, HDL and LDL and rs738409 in PNPLA3 with HDL and TG and one was in a circadian clock gene: rs228669 in PER3 with TG. Of these SNPs only PER3 rs228669 was marginally associated with PTB (p = 0.02). In addition, PER3 rs228669 acts as an effect modifier on the relationship between TG and PTB.

Characteristics and risk factors of preterm births in a tertiary center in Lagos, Nigeria.

INTRODUCTION: Preterm birth is a dire complication of pregnancy that poses huge long-term medical and financial burdens for affected children, their families, and the health care system. The aim of the present study was to identify characteristics associated with preterm births at the Lagos University Teaching Hospital (LUTH), Lagos, Nigeria from 2011 to 2013. METHODS: We obtained Information from 5,561 maternal, fetal/neonatal and obstetric records from the labor ward. We excluded delivery at less than 22 weeks (0.25%), post-term birth at ≥42 weeks gestation (1.3%), and unknown gestation (1.4%). Additionally, we excluded records of multiple births (5.4%) and stillbirths (8.3%) leaving 4,691 records of singleton live-births for analysis. Logistic regression analysis was performed comparing preterm birth (22-36 weeks gestation) to term birth (37-41 weeks gestation). Multiple variable models adjusting for maternal age, parity, fetal position, delivery method and booking status were also evaluated. Multinomial regression was used to identify characteristics associated with preterm birth (PTB) defined as early PTB (22-31 weeks gestation), moderate PTB (32-34 weeks gestation), late PTB (35-36 weeks gestation), compared to term birth (37-41 completed weeks gestation). RESULTS: From our data, 16.8% of the singleton live-birth deliveries were preterm (<37 weeks gestation). Of these, 4.7% were early (22-31 weeks), 4.5% were moderate (32-34 weeks) and 7.7% were late (35-36) PTBs. Older maternal age (≥35 years) [odds ratio (OR) = 1.41], hypertension (OR = 3.44) and rupture of membranes (OR = 4.03) were significantly associated with increased odds of PTB. Women being treated for the prevention of mother-to-child transmission of HIV were at a significantly decreased risk for PTB (OR = 0.70). Sixteen percent of women in this cohort were not registered for antenatal care in LUTH. These non-registered subjects had significantly greater odds of all categories of PTB, including early (odds ratio (OR) = 20.8), moderate (OR = 8.68), and late (OR = 2.15). CONCLUSION: PTB and risks for PTB remain high in Nigeria. We recommend that any high risk pregnancy should be referred to a tertiary center for prenatal care in order to significantly reduce adverse birth outcomes such as PTBs.

Quality of EHR data extractions for studies of preterm birth in a tertiary care center: guidelines for obtaining reliable data.

BACKGROUND: The use of Electronic Health Records (EHR) has increased significantly in the past 15 years. This study compares electronic vs. manual data abstractions from an EHR for accuracy. While the dataset is limited to preterm birth data, our work is generally applicable. We enumerate challenges to reliable extraction, and state guidelines to maximize reliability. METHODS: An Epic™ EHR data extraction of structured data values from 1,772 neonatal records born between the years 2001-2011 was performed. The data were directly compared to a manually-abstracted database. Specific data values important to studies of perinatology were chosen to compare discrepancies between the two databases. RESULTS: Discrepancy rates between the EHR extraction and the manual database were calculated for gestational age in weeks (2.6 %), birthweight (9.7 %), first white blood cell count (3.2 %), initial hemoglobin (11.9 %), peak total and direct bilirubin (11.4 % and 4.9 %), and patent ductus arteriosus (PDA) diagnosis (12.8 %). Using the discrepancies, errors were quantified in both datasets using chart review. The EHR extraction errors were significantly fewer than manual abstraction errors for PDA and laboratory values excluding neonates transferred from outside hospitals, but significantly greater for birth weight. Reasons for the observed errors are discussed. CONCLUSIONS: We show that an EHR not modified specifically for research purposes had discrepancy ranges comparable to a manually created database. We offer guidelines to minimize EHR extraction errors in future study designs. As EHRs become more research-friendly, electronic chart extractions should be more efficient and have lower error rates compared to manual abstractions.