Biomedical subjects

Rebecca Smith-Bindman

Publications and source records attributed to Rebecca Smith-Bindman.

21 records · Page 2Linked to original sources

PubMed2002

US evaluation of fetal growth: prediction of neonatal outcomes.

PURPOSE: To determine whether fetal growth measured at serial ultrasonographic (US) examinations can predict neonatal morbidity, independent of whether gestational age is known. MATERIALS AND METHODS: Women (n = 321) who had singleton pregnancies and underwent two or more second- or third-trimester obstetric US examinations were included in a retrospective cohort analysis. Inadequate fetal growth was defined as growth at or below the 10th percentile. The relative risk of each poor outcome was calculated for fetuses with inadequate growth, compared with the risk for fetuses with normal growth. RESULTS: Inadequate fetal growth was associated with 3.9 times the risk of a birth weight less than 2,500 g, 17.7 times the risk of a birth weight less than the 3rd percentile for gestational age, 2.3 times the risk of preterm birth, 2.6 times the risk of a long newborn hospital stay, and 3.6 times the risk of neonatal intensive care unit admission. After adjusting for confounding variables, including fetal weight, fetal growth remained a significant predictor of small birth size and poor outcomes. Inadequate growth predicted the risk of poor outcomes, even when gestational age was unknown. When inadequate growth was used to identify fetuses at risk, 21%-67% of neonates who were small at birth or had poor outcomes were identified at false-positive rates of only 5%-9%. For all outcomes, inadequate growth enabled identification of more fetuses with poor birth outcomes than low estimated fetal weight. CONCLUSION: Morbidity is significantly increased among fetuses who demonstrate less than expected growth. Growth between two US examinations can be used to estimate the risk of neonatal morbidity, even when gestational age is unknown.

Adult↗

PubMed2002

Measurement of breast density with dual X-ray absorptiometry: feasibility.

Dual x-ray absorptiometry (DXA) was used to quantify breast density with a phantom and with cadaveric breasts. With DXA, percentage of fat correlated with percentage of glandular density of the phantom (r > 0.998) and with density at mammography (r(adjusted) = 0.83). DXA precision (SD) was 0.5% without and 1.1% with breast repositioning. DXA devices can be used to accurately and precisely estimate breast tissue density.

Absorptiometry, Photon↗

PubMed2002

Accuracy of mammographic breast density analysis: results of formal operator training.

Mammographic density is a major risk factor for breast cancer. Breast density is not routinely quantified for research studies because present methods are time intensive and manual, and require expert training. We investigated whether individuals with and without backgrounds in radiology or medicine can achieve sufficient accuracy when compared with an expert (gold standard) reader of mammographic breast density. Nine readers (three radiologists, two non-radiology physicians, and four nonphysicians) assessed breast density on 144 digitized films (60 contralateral films of breast cancer cases and 84 controls) on a computer workstation with custom software. Readings were compared with a radiologist with training in mammography and density reading that read the same films. A correlation of r = 0.9 or higher with the gold standard reading was met by three of three radiologists, one of two nonradiology physicians, and one of four nonphysicians. Intrareader reproducibility measured as the residual sum of mean errors averaged 10% mammographic density for all readers and 9% for readers with a correlation of 0.9 or higher with the gold standard. The odds ratios associated with breast cancer when films with mammographic breast density of 50% or greater are considered "dense" ranged from 3.1 to 3.9 or a 1.9-2.4-per-population-SD increase in percentage density. Although it is advantageous to have a radiological background when quantifying mammographic density, it is not a prerequisite. Applying strict validation criteria to qualify readers to quantify mammographic breast density for research studies will enhance the chance of accurately assessing breast density and discriminating women at high and low risk of breast cancer.

Adult↗