Validation of claims-based algorithms to identify non-live birth outcomes.

PURPOSE: Perinatal epidemiology studies using healthcare utilization databases are often restricted to live births, largely due to the lack of established algorithms to identify non-live births. The study objective was to develop and validate claims-based algorithms for the ascertainment of non-live births. METHODS: Using the Mass General Brigham Research Patient Data Registry 2000-2014, we assembled a cohort of women enrolled in Medicaid with a non-live birth. Based on ≥1 inpatient or ≥2 outpatient diagnosis/procedure codes, we identified and randomly sampled 100 potential stillbirth, spontaneous abortion, and termination cases each. For the secondary definitions, we excluded cases with codes for other pregnancy outcomes within ±5 days of the outcome of interest and relaxed the definitions for spontaneous abortion and termination by allowing cases with one outpatient diagnosis only. Cases were adjudicated based on medical chart review. We estimated the positive predictive value (PPV) for each outcome. RESULTS: The PPV was 71.0% (95% CI, 61.1-79.6) for stillbirth; 79.0% (69.7-86.5) for spontaneous abortion, and 93.0% (86.1-97.1) for termination. When excluding cases with adjacent codes for other pregnancy outcomes and further relaxing the definition, the PPV increased to 80.6% (69.5-88.9) for stillbirth, 86.6% (80.5-91.3) for spontaneous abortion and 94.9% (91.1-97.4) for termination. The PPV for the composite outcome using the relaxed definition was 94.4% (92.3-96.1). CONCLUSIONS: Our findings suggest non-live birth outcomes can be identified in a valid manner in epidemiological studies based on healthcare utilization databases.

Validation of algorithms to identify adverse perinatal outcomes in the Medicaid Analytic Extract database.

BACKGROUND: The Medicaid Analytic eXtract (MAX) is a health care utilization database from publicly insured individuals that has been used for studies of drug safety in pregnancy. Claims-based algorithms for defining many important maternal and neonatal outcomes have not been validated. OBJECTIVE: To validate claims-based algorithms for identifying selected pregnancy outcomes in MAX using hospital medical records. METHODS: The medical records of mothers who delivered between 2000 and 2010 within a single large healthcare system were linked to their claims in MAX. Claims-based algorithms for placental abruption, preeclampsia, postpartum hemorrhage, small for gestational age, and noncardiac congenital malformation were defined. Fifty randomly sampled cases for each outcome identified using these algorithms were selected, and their medical records were independently reviewed by two physicians to confirm the presence of the diagnosis of interest; disagreements were resolved by a third physician reviewer. Positive predictive values (PPVs) and 95% confidence intervals (CIs) of the claims-based algorithms were calculated using medical records as the gold standard. RESULTS: The linked cohort included 10,899 live-birth pregnancies. The PPV was 92% (95% CI, 82%-97%) for placental abruption, 82% (95% CI, 70%-91%) for preeclampsia, 74% (95% CI, 61%-85%) for postpartum hemorrhage, 92% (95% CI, 82%-97%) for small for gestational age, and 86% (95% CI, 74%-94%) for noncardiac congenital malformation. CONCLUSIONS: Across the perinatal outcomes considered, PPVs ranged between 74% and 92%. These PPVs can inform bias analyses that correct for outcome misclassification.

When ultrasound anomalies are present: An estimation of the frequency of chromosome abnormalities not detected by cell-free DNA aneuploidy screens.

OBJECTIVES: This study characterizes cytogenetic abnormalities with ultrasound findings to refine counseling following negative cell-free DNA (cfDNA). METHODS: A retrospective cohort of pregnancies with chromosome abnormalities and ultrasound findings was examined to determine the residual risk following negative cfDNA. Cytogenetic data was categorized as cfDNA detectable for aneuploidies of chromosomes 13, 18, 21, X, or Y or non-cfDNA detectable for other chromosome abnormalities. Ultrasound reports were categorized as structural anomaly, nuchal translucency (NT) ≥3.0 mm, or other "soft markers". Results were compared using chi squared and Fishers exact tests. RESULTS: Of the 498 fetuses with cytogenetic abnormalities and ultrasound findings, 16.3% (81/498) had non-cfDNA detectable results. In the first, second, and third trimesters, 12.4% (32/259), 19.5% (42/215), and 29.2% (7/24) had non-cfDNA detectable results respectively. The first trimester non-cfDNA detectable results reduced to 7.7% (19/246) if triploidy was detectable by cfDNA testing. For isolated first trimester NT of 3.0-3.49 mm, 15.8% (6/38) had non-cfDNA detectable results, while for NT ≥3.5 mm, it was 12.3% (20/162). For cystic hygroma, 4.3% (4/94) had non-cfDNA detectable results. CONCLUSIONS: Counseling for residual risk following cfDNA in the presence of an ultrasound finding is impacted by gestational age, ultrasound finding, and cfDNA detection of triploidy.

Neutral effect of body mass index on implantation rate after frozen-thawed blastocyst transfer.

OBJECTIVE: To examine the effects of body mass index (BMI) on implantation rate after uniform protocol frozen-thawed blastocyst transfer in women with a homogenous uterine environment. DESIGN: Retrospective cohort study. SETTING: Single IVF clinic at a large academic institution. PATIENT(S): Four hundred sixty-one infertile women treated at a large academic institution from January 2007 to January 2014. INTERVENTION(S): All women underwent standardized slow frozen-thawed blastocyst transfers with good-quality day 5-6 embryos, following an identical hormonal uterine preparation, with comparison groups divided according to BMI category: underweight (<18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥30.0 kg/m2). MAIN OUTCOME MEASURE(S): Implantation rate. RESULT(S): There were no statistically significant differences identified when comparing implantation rates among the four BMI cohorts. The implantation rate was 38.2% in normal weight patients, 41.7% in underweight patients, 45.1% in overweight patients, and 34.7% in obese patients. Adjusted odds ratios (OR) demonstrated no association between the main outcome, implantation rate, and BMI. Compared with the normal weight patients, the adjusted OR of implantation was 1.70 (95% confidence interval [CI], 0.40-7.72) for underweight patients, 1.61 (95% CI, 0.97-2.68) for overweight patients, and 0.92 (95% CI, 0.49-1.72) for obese patients. Secondary outcomes, including rates of miscarriage, clinical pregnancy, ongoing pregnancy, and live birth, were not significantly different between cohorts. While powered to detect a 16% difference between overweight and normal weight women, the study was underpowered to detect differences in the underweight and obese women, and no definitive conclusions can be drawn for these small cohorts. Patients with transfers that required the longest amount of time, greater than 200 seconds, had the highest average BMI of 27.5 kg/m2. CONCLUSION(S): Under highly controlled circumstances across 7 years of data from a single institution, using a uniform uterine preparation, following a precise transfer technique with high-quality day 5-6 slow frozen-thawed blastocysts, a BMI in the overweight range of 25-29.9 kg/m2 is not associated with a poorer implantation rate or live-birth rate, nor is it associated with an increased risk of miscarriage when compared with a normal BMI range. The increased length of time required during transfer for women with higher BMI suggests body habitus may contribute to difficult transfers, although this may not translate into poorer implantation rates. By using a standardized protocol for slow freezing and thawing of embryos, using identical hormonal preparation and a uniform ET protocol, a homogenous uterine environment was created in this carefully selected cohort of women, thereby minimizing confounders and uniquely highlighting the neutral effect of overweight BMI on implantation rate.