Juvenile onset central nervous system folate deficiency and rheumatoid arthritis.

Isolated cerebral folate deficiency was detected in a 13-year-old girl with cognitive and motor difficulties and juvenile rheumatoid arthritis. Her serum contains autoantibodies that block membrane-bound folate receptors that are on the choroid plexus and diminish the uptake of folate into the spinal fluid. Whereas her serum folate exceeded 21 ng/mL, her spinal fluid contained 3.2 ng/mL of 5-methyltetrahydrofolate as a consequence of the autoantibodies diminishing the uptake of this folate.

Maternal and neonatal outcomes by labor onset type and gestational age.

OBJECTIVE: We sought to determine maternal and neonatal outcomes by labor onset type and gestational age. STUDY DESIGN: We used electronic medical records data from 10 US institutions in the Consortium on Safe Labor on 115,528 deliveries from 2002 through 2008. Deliveries were divided by labor onset type (spontaneous, elective induction, indicated induction, unlabored cesarean). Neonatal and maternal outcomes were calculated by labor onset type and gestational age. RESULTS: Neonatal intensive care unit admissions and sepsis improved with each week of gestational age until 39 weeks (P < .001). After adjusting for complications, elective induction of labor was associated with a lower risk of ventilator use (odds ratio [OR], 0.38; 95% confidence interval [CI], 0.28-0.53), sepsis (OR, 0.36; 95% CI, 0.26-0.49), and neonatal intensive care unit admissions (OR, 0.52; 95% CI, 0.48-0.57) compared to spontaneous labor. The relative risk of hysterectomy at term was 3.21 (95% CI, 1.08-9.54) with elective induction, 1.16 (95% CI, 0.24-5.58) with indicated induction, and 6.57 (95% CI, 1.78-24.30) with cesarean without labor compared to spontaneous labor. CONCLUSION: Some neonatal outcomes improved until 39 weeks. Babies born with elective induction are associated with better neonatal outcomes compared to spontaneous labor. Elective induction may be associated with an increased hysterectomy risk.

Risk of adult-onset asthma in Mexican-American women employed in food preparation or food service

Existing literature examining the association between occupation and asthma has not been adequately powered to address this question in the food preparation or food service industries. Few studies have addressed the possible link between occupational exposure to cooking fumes and asthma. This secondary analysis of cohort study data aimed to investigate the association between adult-onset asthma and exposure to: (a) cooking fumes at work or (b) longest-held employment in food preparation or food service (e.g. waiters and waitresses, food preparation workers, non-restaurant food servers, etc.). Participants arose from a cohort of Mexican-American women residing in Houston, TX, recruited between July 2001 and June 2007. This analysis used Cox proportional-hazards regression to estimate the hazard ratio of adult-onset asthma given the exposures of interest, adjusting for age, BMI, smoking status, acculturation, and birthplace. We found a strong association between adult-onset asthma and occupational exposure to cooking fumes (hazard ratio [HR] = 1.77; 95% confidence interval [CI], 1.15, 2.72), especially in participants whose longest-held occupation was not in the food-related industry (HR = 2.12; 95% CI, 1.21, 3.60). In conclusion, adult-onset asthma is a serious public health concern for food industry workers. ^

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. ^