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Background: Identification of the biological markers of anorexia nervosa (AN) is crucial for the development of new treatments. We aimed to determine whether AN is associated with disturbances in the nonconscious neural processing of innate signals of emotion and whether these disturbances persist after weight gain. Methods: In a retest design, 28 adolescent females with AN were tested at first admission to hospital and again after they had gained weight. Matched healthy control participants were tested at the same times. We assessed emotion-elicited event-related potentials (ERPs) during overt and covert presentation of emotion expressions, scores on an emotion-identification behavioural task, and symptom measures. We performed between and within group analyses. Results: Individuals with AN had a marked alteration in ERPs relative to healthy controls. Irrespective of the form of stimulus, early and late ERP components were significantly reduced in AN patients at baseline (when underweight) and on retest (after weight gain), especially in the temporo-occipital regions, suggesting a persistent disruption of the early automatic appraisal of salient emotional signals. Limitations: This study could have been improved with a longer standardized retest interval. Conclusion: There is likely a core, generic disturbance in AN in the early 'automatic' neural processing of emotion irrespective of weight or nutritional status. New innovative emotion-based psychologic or pharmacologic treatments targeting these nonconscious processes may prove beneficial., Introduction Anorexia nervosa (AN) is an eating disorder characterized by low body weight, an intense fear of weight gain, body image distortion and a disruption of menstrual function. (1) There [...]

Purpose: To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension.Methods: Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV).Results: The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001).Conclusion: Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications. [ABSTRACT FROM AUTHOR]

Purpose: To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension., Methods: Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV)., Results: The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001)., Conclusion: Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications., Competing Interests: Disclosure: The authors reports no commercial or financial interest in regard to this article.

Objectives: To quantify how adherence mismeasurement affects the estimated impact of adherence on inpatient costs among patients with serious mental illness (SMI)., Study Design: Proportion of days covered (PDC) is a common claims-based measure of medication adherence. Because PDC does not measure medication ingestion, however, it may inaccurately measure adherence. We derived a formula to correct the bias that occurs in adherence-utilization studies resulting from errors in claims-based measures of adherence., Methods: We conducted a literature review to identify the correlation between gold-standard and claims-based adherence measures. We derived a bias-correction methodology to address claims-based medication adherence measurement error. We then applied this methodology to a case study of patients with SMI who initiated atypical antipsychotics in 2 large claims databases., Results: Our literature review identified 6 studies of interest. The 4 most relevant ones measured correlations between 0.38 and 0.91. Our preferred estimate implies that the effect of adherence on inpatient spending estimated from claims data would understate the true effect by a factor of 5.3, if there were no other sources of bias. Although our procedure corrects for measurement error, such error also may amplify or mitigate other potential biases. For instance, if adherent patients are healthier than nonadherent ones, measurement error makes the resulting bias worse. On the other hand, if adherent patients are sicker, measurement error mitigates the other bias., Conclusions: Measurement error due to claims-based adherence measures is worth addressing, alongside other more widely emphasized sources of bias in inference.