Preventing Congenital Syphilis-Opportunities Identified by Congenital Syphilis Case Review Boards.

BACKGROUND: Louisiana has had the highest rates of congenital syphilis (CS) in the nation since 2012. Congenital syphilis case review boards were established statewide in 2016 to study CS cases and identify interventions. METHODS: We summarized the findings of CS review boards, assessed which cases were preventable by prenatal care providers, reviewed recommended interventions, and assessed subsequent improvement in provider practices. RESULTS: All 79 CS cases reported from January 2016 to July 2017 were reviewed by boards during August 2016 to August 2017. Twenty-six (33%) cases that could have been prevented by prenatal care providers had: lack of rescreening at 28 to 32 weeks (n = 15), lack of any screening (n = 5), treatment delay (n = 4), or incorrect interpretation of test results (n = 2). Twenty-one (27%) cases were possibly preventable by providers including: mother did not return for follow-up and treatment (n = 19), late third trimester reactive test with premature delivery (n = 1), or incomplete treatment and lack of follow-up by health department staff (n = 1). Thirty-two (40%) cases that were unlikely to be prevented by providers had: nonreactive test at 28-32 weeks then reactive test <30 days before delivery (n = 10), no prenatal care (n = 9), mother adequately treated, case by infant criteria (n = 8), first/second trimester nonreactive, reactive at preterm delivery (n = 4), or mother adequately treated, reinfected before delivery (n = 1). Providers were advised to adhere to CDC recommended syphilis screening and treatment protocols and rapidly report pregnant women with syphilis. Many providers changed their procedures. CONCLUSIONS: Congenital syphilis case review boards identified practices with inadequate screening, treatment, or reporting. Sharing these findings with providers changed practices and may prevent future cases.

A fully coupled space-time multiscale modeling framework for predicting tumor growth.

Most biological systems encountered in living organisms involve highly complex heterogeneous multi-component structures that exhibit different physical, chemical, and biological behavior at different spatial and temporal scales. The development of predictive mathematical and computational models of multiscale events in such systems is a major challenge in contemporary computational biomechanics, particularly the development of models of growing tumors in humans. The aim of this study is to develop a general framework for tumor growth prediction by considering major biological events at tissue, cellular, and subcellular scales. The key to developing such multiscale models is how to bridge spatial and temporal scales that range from 10-3 to 103 mm in space and from 10-6 to 107 s in time. In this paper, a fully coupled space-time multiscale framework for modeling tumor growth is developed. The framework consists of a tissue scale model, a model of cellular activities, and a subcellular transduction signaling pathway model. The tissue, cellular, and subcellular models in this framework are solved using partial differential equations for tissue growth, agent-based model for cellular events, and ordinary differential equations for signaling transduction pathway as a network at subcellular scale. The model is calibrated using experimental observations. Moreover, this model is biologically-driven from a signaling pathway, volumetrically-consistent between cellular and tissue scale in terms of tumor volume evolution in time, and a biophysically-sound tissue model that satisfies all conservation laws. The results show that the model is capable of predicting major characteristics of tumor growth such as the morphological instability, growth patterns of different cell phenotypes, compact regions of the higher cell density at the tumor region, and the reduction of growth rate due to drug delivery. The predicted treatment outcomes show a reduction in proliferation at different rates in response to different drug dosages. Moreover, the results of several 3D applications to tumor growth and the evolution of cellular and subcellular events are presented.