The impact of gestational age and fetal weight on the risk of failure of spinal anesthesia for cesarean delivery.

BACKGROUND: There are limited data about spinal dosing for cesarean delivery in preterm parturients. We investigated the hypothesis that preterm gestation is associated with an increased incidence of inadequate spinal anesthesia for cesarean delivery compared with term gestation. METHODS: We searched our perioperative database for women who underwent cesarean delivery under spinal or combined spinal-epidural anesthesia with hyperbaric bupivacaine ⩾10.5mg. The primary outcome was the incidence of inadequate surgical anesthesia needing conversion to general anesthesia or repetition or supplementation of the block. We divided patients into four categories: <28, 28 to <32, 32 to <37 and ⩾37weeks of gestation. The chi-square test was used to compare failure rates and a multivariable regression analysis was performed to investigate potential confounders of the relationship between gestational age and failure. RESULTS: A total of 5015 patients (3387 term and 1628 preterm) were included. There were 278 failures (5.5%). The incidence of failure was higher in preterm versus term patients (6.4% vs. 5.1%, P=0.02). Failure rates were 10.8%, 7.7%, 5.3% and 5% for <28, 28 to <32, 32 to <37 and ⩾37weeks of gestation, respectively. In the multivariable model, low birth weight (P<0.0001), gestational age (P=0.03), ethnicity (P=0.02) and use of combined spinal-epidural anesthesia (P<0.0001) were significantly associated with failure. CONCLUSIONS: At standard spinal doses of hyperbaric bupivacaine used in our practice (⩾10.5mg), there were higher odds of inadequate surgical anesthesia in preterm parturients. When adjusting for potential confounders, low birth weight was the main factor associated with failure.

Mainland size variation informs predictive models of exceptional insular body size change in rodents.

The tendency for island populations of mammalian taxa to diverge in body size from their mainland counterparts consistently in particular directions is both impressive for its regularity and, especially among rodents, troublesome for its exceptions. However, previous studies have largely ignored mainland body size variation, treating size differences of any magnitude as equally noteworthy. Here, we use distributions of mainland population body sizes to identify island populations as 'extremely' big or small, and we compare traits of extreme populations and their islands with those of island populations more typical in body size. We find that although insular rodents vary in the directions of body size change, 'extreme' populations tend towards gigantism. With classification tree methods, we develop a predictive model, which points to resource limitations as major drivers in the few cases of insular dwarfism. Highly successful in classifying our dataset, our model also successfully predicts change in untested cases.

CPAG: software for leveraging pleiotropy in GWAS to reveal similarity between human traits links plasma fatty acids and intestinal inflammation.

Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn's disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.

Adaptive intervention design in mobile health: Intervention design and development in the Cell Phone Intervention for You trial.

BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.