Matching the Bipolar Patient and the Mood Stabilizer

Bipolar disorder poses many treatment challenges, including "matching" a particular patient with the optimal treatment regimen. Although there are a number of extant guidelines to assist the clinician in selecting treatment, these recommendations are largely based on general variables and fail to take into account the subtleties and complications that confront a clinician in practice. An analysis of predictors of medication response in bipolar disorder provides a basis for matching patients with optimal medication regimens. Response to treatment may depend on the polarity of an episode or on clinical features such as mixed or psychotic symptomatology and rate of cycling. Comorbid psychiatric disorders such as substance abuse, anxiety disorders, or attention-deficit/hyperactivity disorder should also be considered in designing a treatment regimen. Similarly, medical conditions, especially metabolic abnormalities or kidney insufficiency, must be taken into account. Selection of medication may also involve an analysis of demographic factors, including family and personal history of response to a particular agent. When selecting the most appropriate mood stabilizer for a patient--particularly when polypharmacy is required--the clinician should keep potential side effects and drug interactions in mind. Randomized, controlled studies in bipolar populations are needed to further characterize optimal matching of patient and medication.     

The "deep structure" of clinical medicine and prescribing privileges for psychologists

Clinical medicine in general and psychiatry in particular have their roots in the Hippocratic tradition. It is this tradition that defines the "deep structure" of the medical profession. Although the field of clinical psychology has a similar "surface structure" to that of psychiatry and general medicine, it has evolved from a wholly different set of deep structural antecedents. These issues relate directly to the question of "prescribing privileges" for psychologists. The addition of course work in psychopharmacology to the psychology curriculum would not alter the deep structure of the profession nor would it equip psychologists to prescribe psychotropic medication. There are, however, ways in which the disciplines of medicine and psychology can cooperate in the education of clinicians.     

Integrating the Life Course Perspective into a Local Maternal and Child Health Program

For many decades, early access to prenatal care has been considered the gold standard for improving birth outcomes. In Contra Costa County, a diverse urban and suburban county of over one million people in the San Francisco Bay Area, the Family Maternal and Child Health Programs of Contra Costa Health Services (CCHS) have seen high rates of early entry into prenatal care since 2000. Yet despite our best efforts to increase access to quality prenatal care, our rates of low birth weight and infant mortality, especially among African Americans, continue to be high. When we were introduced to the Life Course Perspective in 2003 as an organizational framework for our programmatic activities, we recognized that emerging scientific evidence in the literature demonstrated the importance of social and environmental factors in determining health and health equity, and supported a general impression in the field that prenatal care was not enough to improve birth outcomes. The Life Course Perspective suggests that many of the risk and protective factors that influence health and wellbeing across the lifespan also play an important role in birth outcomes and in health and quality of life beyond the initial years. In this article, we describe the Life Course Perspective and how one local Maternal and Child Health Program adopted and adapted this paradigm by creating and launching a Life Course Initiative to guide our programs and services. The Life Course Initiative implemented by CCHS is designed to reduce inequities in birth outcomes, improve reproductive potential, and change the health of future generations by introducing a longitudinal, integrated, and ecological approach to implementing maternal and child health programs.     

An Ecological Study to Identify Census Blocks Supporting a Higher Burden of Disease: Infant Mortality in the Lille Metropolitan Area, France

In France, reducing social health inequalities has become an explicit goal of health policies over the past few years, one of its objectives is specifically the reduction of the perinatal mortality rate. This study investigates the association between infant mortality and social deprivation categories at a small area level in the Lille metropolitan area, in the north of France, to identify census blocks where public authorities should prioritize appropriate preventive actions. We used census data to establish a neighbourhood deprivation index whose multiple dimensions encompass socioeconomic characteristics. Infant mortality data were obtained from the Lille metropolitan area municipalities to estimate a death rate at the census tract level. We used Bayesian hierarchical models in order to reduce the extra variability when computing relative risks (RR) and to assess the associations between infant mortality and deprivation. Between 2000 and 2009, 668 cases of infant death occurred in the Lille metropolitan area (4.2 per 1,000 live births). The socioeconomic status is associated with infant mortality, with a clear gradient of risk from the most privileged census blocks to the most deprived ones (RR = 2.62, 95 % confidence interval [1.87; 3.70]). The latter have 24.6 % of families who were single parents and 29.9 % of unemployed people in the labor force versus 8.5 % and 7.7 % in the former. Our study reveals socio-spatial disparities in infant mortality in the Lille metropolitan area and highlights the census blocks most affected by the inequalities. Fine spatial analysis may help inform the design of preventive policies tailored to the characteristics of the local communities.