The association between maternal use of spermicides, condoms, intra-uterine devices or progesterone and major structural birth defects

Birth defects occur in 1 of every 33 babies born in the United States, and are the leading cause of infant death. Mothers using contraceptives that become pregnant may continue to use their contraceptives after their first missed menstrual period, thus exposing their baby in utero to the contraceptive product. Progesterone is also sometimes prescribed during the first trimester of pregnancy to mothers with a history of miscarriages or infertility problems. To ensure the safety of these products, it is important to investigate whether there is an increased occurrence of babies born with birth defects to mothers using various contraceptive methods or progesterone in early pregnancy. Using data from the National Birth Defects Prevention Study (NBDPS), an ongoing multi-state, population based case-control study, this study assessed maternal exposures to IUDs, spermicides, condoms and progesterone in early pregnancy. ^ Progesterone used for threatened miscarriage during the first three months of pregnancy was associated with an increased occurrence of hypoplastic left heart (adjusted odds ratios (OR) 2.24, 95% CI 1.13-4.21), perimembranous ventricular septal defects (OR 1.64, 95% CI 1.10-2.41), septal associations (OR 2.52, 95% CI 1.45-4.24), esophageal atresia (OR 1.82, 95% CI 1.04-3.08), and hypospadias (OR 2.12, 95% CI 1.41-3.18). Mothers using progesterone for injectable contraception had increased (OR > 2.5), but insignificant odds ratios for anencephaly, septal associations, small intestinal atresias and omphalocel. Progesterone used for fertility was not associated with an increased occurrence of any birth defects examined. ^ Mothers using progesterone for fertility assistance and threatened miscarriage were very similar with respect to their demographics and pregnancy history. They also both reported similar types of progesterone. Thus, if progesterone was a causal risk factor for birth defects we would have expected to observe similar increases in risk among mothers using progesterone for both indications. Because we predominantly observed increased associations among mothers using progesterone for threatened miscarriage but not fertility assistance, it is possible the increased associations we observed were confounded by indication (i.e. progesterone was administered for vaginal bleeding which occurred as a sequelae to the formation of a congenital anomaly. ^ No significant increased associations were observed between maternal spermicide use during pregnancy and 26 of 27 types of structural malformations. While multiple statistical tests were performed we observed first trimester maternal spermicide use to be associated with a significant increased occurrence of perimembranous ventricular septal defects (OR 2.21, 95% CI 1.16-4.21). A decreased occurrence (OR < 1.0) was observed for several categories of birth defects among mothers who conceived in the first cycle after discontinuing the use of spermicides (22 of 28) or male condoms (23 of 33). ^ Overall the percent of IUD use was similar between mothers of controls and mothers of all cases in aggregate (crude OR 1.05, 95% CI 0.61-1.84). Power was limited to detect significant associations between IUD use and birth defects, however mothers using an IUD in the month immediately prior to conception or during pregnancy were not associated with an increase of birth defects. Limb defects and amniotic band sequence previously reported to be associated with IUD use during pregnancy were not found to occur among any mothers reporting the use of an IUD during pregnancy.^

Non-staphylococcal infections of cardiac implantable electronic devices

Background. The number of infections of cardiac implantable electronic devices (CIED) continues to escalate out of proportion to the increase rate of device implantation. Staphylococcal organisms account for 70% to 90% of all CIED infections. However, little is known about non-staphylococcal infections, which have been described only in case reports, small case series or combined in larger studies with staphylococcal CIED infections, thereby diluting their individual impact. ^ Methods. A retrospective review of hospital records of patients admitted with a CIED-related infections were identified within four academic hospitals in Houston, Texas between 2002 and 2009. ^ Results. Of the 504 identified patients with CIED-related infection, 80 (16%) had a non-staphylococcal infection and were the focus of this study. Although the demographics and comorbities of subjects were comparable to other reports, our study illustrates many key points: (a) the microbiologic diversity of non-staphylococcal infections was rather extensive, as it included other Gram-positive bacteria like streptococci and enterococci, a variety of Gram-negative bacteria, atypical bacteria including Nocardia and Mycobacteria, and fungi like Candida and Aspergillus; (b) the duration of CIED insertion prior to non-staphylococcal infection was relatively prolong (mean, 109 ± 27 weeks), of these 44% had their device previously manipulated within a mean of 29.5 ± 6 weeks; (c) non-staphylococcal organisms appear to be less virulent, cause prolonged clinical symptoms prior to admission (mean, 48 ± 12.8 days), and are associated with a lower mortality (4%) than staphylococcal organisms; (d) thirteen patients (16%) presented with CIED-related endocarditis; (e) although not described in prior reports, we identified 3 definite and 2 suspected cases of secondary Gram-negative bacteremia seeding of the CIED; and (f) inappropriate antimicrobial coverage was provided in approximately 50% of patients with non-staphylococcal infections for a mean period of 2.1 days. ^ Conclusions. Non-staphylococcal CIED-related infections are prevalent and diverse with a relatively low virulence and mortality rate. Since non-staphylococcal organisms are capable of secondarily seeding the CIED, a high suspicion for CIED-related infection is warranted in patients with bloodstream infection. Additionally, in patients with suspected CIED infection, adequate Gram positive and -negative antibacterial coverage should be administered until microbiologic data become available.^

Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

Analyzing left-truncated right-censored data with uncertain onset time with parametric models

Prevalent sampling is an efficient and focused approach to the study of the natural history of disease. Right-censored time-to-event data observed from prospective prevalent cohort studies are often subject to left-truncated sampling. Left-truncated samples are not randomly selected from the population of interest and have a selection bias. Extensive studies have focused on estimating the unbiased distribution given left-truncated samples. However, in many applications, the exact date of disease onset was not observed. For example, in an HIV infection study, the exact HIV infection time is not observable. However, it is known that the HIV infection date occurred between two observable dates. Meeting these challenges motivated our study. We propose parametric models to estimate the unbiased distribution of left-truncated, right-censored time-to-event data with uncertain onset times. We first consider data from a length-biased sampling, a specific case in left-truncated samplings. Then we extend the proposed method to general left-truncated sampling. With a parametric model, we construct the full likelihood, given a biased sample with unobservable onset of disease. The parameters are estimated through the maximization of the constructed likelihood by adjusting the selection bias and unobservable exact onset. Simulations are conducted to evaluate the finite sample performance of the proposed methods. We apply the proposed method to an HIV infection study, estimating the unbiased survival function and covariance coefficients. ^