Preterm premature rupture of the membranes (PPROM) is responsible for one-third of all preterm births and affects 120,000 pregnancies in the United States each year. Effective treatment relies on accurate diagnosis and is gestational age dependent. The diagnosis of PPROM is made by a combination of clinical suspicion, patient history and some simple tests. PPROM is associated with significant maternal and neonatal morbidity and mortality from infection, umbilical cord compression, placental abruption and preterm birth. Subclinical intrauterine infection has been implicated as a major aetiological factor in the pathogenesis and subsequent maternal and neonatal morbidity associated with PPROM. The frequency of positive cultures obtained by transabdominal amniocentesis at the time of presentation with PPROM in the absence of labour is 25 -40%. The majority of amniotic fluid infection in the setting of PPROM does not produce the signs and symptoms traditionally used as diagnostic criteria for clinical chorioamnionitis. Any evidence of infection by amniocentesis should be considered carefully as an indication for delivery. Documentation of amniotic fluid infection in women who present with PPROM enables us to triage our therapeutic decision making rationally. In PPROM, the optimal interval for delivery occurs when the risks of immaturity are outweighed by the risks of pregnancy prolongation (infection, abruption and cord accident). Lung maturity assessment may be a useful guide when planning delivery in the 32-to 34-week interval. A gestational age approach to therapy is important and should be adjusted for each hospital's neonatal intensive care unit. Antenatal antibiotics and corticosteroid therapies have clear benefits and should be offered to all women without contraindications. During conservative management, women should be monitored closely for placental abruption, infection, labour and a non-reassuring fetal status. Women with PPROM after 32 weeks of gestation should be considered for delivery, and after 34 weeks the benefits of delivery clearly outweigh the risks.

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We performed karyotype and array comparative genomic hybridization (aCGH) analyses on 177 prenatal samples, including 162 (92%) samples from fetuses with sonographic anomalies. Overall 12 fetuses (6.8%) had abnormal karyotype and 42 (23.7%) fetuses had abnormal microarray results: 20 (11.3%) with pathogenic copy number variations (CNVs), 16 with CNVs of uncertain clinical significance, 4 with CNVs establishing carrier status for recessive, X-linked, or susceptibility to late onset dominant disease, and two CNVs with pseudomosaicism due to in vitro cultural artifacts. For 23 pregnancies (13%), aCGH contributed important new information. Our results highlight the interpretation challenges associated with CNVs of unclear significance, incidental findings, as well as technical aspects. Array CGH analysis significantly improved the detection of genomic imbalances in prenatal diagnosis of pregnancies with structural birth defects.

ObjectivesTo develop new fetal weight prediction models using automated fractional limb volume (FLV).MethodsA prospective multicenter study measured fetal biometry within 4 to 7 days of delivery. Three‐dimensional data acquisition included the automated FLV that was based on 50% of the humerus diaphysis (fractional arm volume [AVol]) or 50% of the femur diaphysis (fractional thigh volume [TVol]) length. A regression analysis provided population sample–specific coefficients to develop 4 weight estimation models. Estimated and actual birth weights (BWs) were compared for the mean percent difference ± standard deviation of the percent differences. Systematic errors were analyzed by the Student t test, and random errors were compared by the Pitman test.ResultsA total of 328 pregnancies were scanned before delivery (BW range, 825–5470 g). Only 71.3% to 72.6% of weight estimations were within 10% of actual BW using original published models by Hadlock et al (Am J Obstet Gynecol 1985; 151:333–337) and INTERGROWTH‐21st (Ultrasound Obstet Gynecol 2017; 49:478–486). All predictions were accurate by using sample‐specific model coefficients to minimize bias in making these comparisons (Hadlock, 0.4% ± 8.7%; INTERGROWTH‐21st, 0.5% ± 10.0%; AVol, 0.3% ± 7.4%; and TVol, 0.3% ± 8.0%). Both AVol‐ and TVol‐based models improved the percentage of correctly classified BW ±10% in 83.2% and 83.9% of cases, respectively, compared to the INTERGROWTH‐21st model (73.8%; P < .01). For BW of less than 2500 g, all models slightly overestimated BW (+2.0% to +3.1%). For BW of greater than 4000 g, AVol (–2.4% ± 6.5%) and TVol (–2.3% ± 6.9%) models) had weight predictions with small systematic errors that were not different from zero (P > .05). For these larger fetuses, both AVol and TVol models correctly classified BW (±10%) in 83.3% and 87.5% of cases compared to the others (Hadlock, 79.2%; INTERGROWTH‐21st, 70.8%) although these differences did not reach statistical significance.ConclusionsIn this cohort, the inclusion of automated FLV measurements with conventional 2‐dimensional biometry was generally associated with improved weight predictions.