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BACKGROUND: Socioeconomic factors can affect healthcare management. AIMS: The aim was to investigate if patient educational attainment is associated with management of bipolar disorder. METHOD: We included patients with bipolar disorder type 1 (n = 4289), type 2 (n = 4020) and not otherwise specified (n = 1756), from the Swedish National Quality Register for Bipolar Disorder (BipoläR). The association between patients' educational level and pharmacological and psychological interventions was analysed by binary logistic regression. We calculated odds ratios after adjusting for demographic and clinical variables. RESULTS: Higher education was associated with increased likelihood of receiving psychotherapy (adjusted odds ratio 1.34, 95% CI 91.22-1.46) and psychoeducation (adjusted odds ratio 1.18, 95% CI 1.07-1.46), but with lower likelihood of receiving first-generation antipsychotics (adjusted odds ratio 0.76, 95% CI 0.62-0.94) and tricyclic antidepressants (adjusted odds ratio 0.76, 95% CI 0.59-0.97). Higher education was also associated with lower risk for compulsory in-patient care (adjusted odds ratio 0.79, 95% CI 0.67-0.93). CONCLUSIONS: Pharmacological and psychological treatment of bipolar disorder differ depending on patients' educational attainment. The reasons for these disparities remain to be explained.
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BACKGROUND: Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need. STRUCTURE: The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/ ) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants' response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence. CONCLUSIONS: The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.
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BACKGROUND: Data on dietary intake, meal patterns, and eating attitudes from women with polycystic ovary syndrome (PCOS) is limited despite the fact that PCOS is associated with obesity. We aimed to test the hypothesis that women with PCOS display altered dietary intakes and eating behaviors compared to controls. METHODS: Women with PCOS (n = 72) as defined according to the modified Rotterdam criteria were compared with healthy controls (n = 30). Anthropometry included measurement of waist circumference and determination of the resting metabolic rate via indirect calorimetry. All women completed questionnaires regarding eating behavior; Three-Factor Eating Questionnaire (TFEQ-R21) and eating attitudes; Eating Attitudes Test (EAT). Group comparisons were done by Mann-Whitney U test and logistic regression analysis was used for adjustments of age and BMI in a non-parametric way. RESULTS: BMI was higher in women with PCOS compared to controls. Resting metabolic rate did not differ between women with women with and without PCOS after adjustment for age and BMI [1411 ± 229 kcal/day versus 1325 ± 193 kcal per day (P = 0.07)], whereas the respiratory exchange ratio was higher in women with PCOS than in controls [0.83 ± 0.07 versus 0.78 ± 0.08 (P = 0.02 after adjustments for age and BMI)]. Energy percent (E%) carbohydrates was higher in women with PCOS compared to controls (P = 0.017), but E% alcohol was lower (P = 0.036) after adjustment for age and BMI. The average total EAT scores and EAT dieting subscale scores were higher in women with PCOS compared with controls (P = 0.001 and P = 0.024, respectively) after adjustment for age and BMI. No difference was found for previous or current symptoms of bulimia nervosa. CONCLUSIONS: Independent of BMI and age, the resting metabolic rate did not differ between women with and without PCOS indicating that women with PCOS should have equal abilities in terms of energy metabolism to lose weight as women without PCOS. Women with PCOS showed greater concerns about their weight and dieting, and this indicates that anxiety about weight is one of the psychological symptoms of PCOS.
