The association between mixed symptoms, irritability and functioning measured using smartphones in bipolar disorder.

OBJECTIVE: To (i) validate patient-evaluated mixed symptoms and irritability measured using smartphones against clinical evaluations; (ii) investigate associations between mixed symptoms and irritability with stress, quality of life and functioning, respectively, in patients with bipolar disorder. METHODS: A total of 84 patients with bipolar disorder used a smartphone-based system for daily evaluation of mixed symptoms and irritability for nine months. Clinically evaluated symptoms, stress, quality of life and clinically rated functioning were collected multiple times during follow-up. RESULTS: Patients presented mild affective symptoms. Patient-reported mixed symptoms and irritability correlated with clinical evaluations. In analyses including confounding factors there was a statistically significant association between both mixed symptoms and irritability and stress (P < 0.0001) and between irritability and both quality of life and functioning (P < 0.0001) respectively. There was no association between mixed mood and both quality of life and functioning. CONCLUSION: Mixed symptoms and irritability can be validly self-reported using smartphones in patients with bipolar disorder. Mixed symptoms and irritability are associated with increased stress even during full or partial remission. Irritability is associated with decreased quality of life and functioning. The findings emphasize the clinical importance of identifying inter-episodic symptoms including irritability pointing towards smartphones as a valid tool.

Voice analysis as an objective state marker in bipolar disorder.

Changes in speech have been suggested as sensitive and valid measures of depression and mania in bipolar disorder. The present study aimed at investigating (1) voice features collected during phone calls as objective markers of affective states in bipolar disorder and (2) if combining voice features with automatically generated objective smartphone data on behavioral activities (for example, number of text messages and phone calls per day) and electronic self-monitored data (mood) on illness activity would increase the accuracy as a marker of affective states. Using smartphones, voice features, automatically generated objective smartphone data on behavioral activities and electronic self-monitored data were collected from 28 outpatients with bipolar disorder in naturalistic settings on a daily basis during a period of 12 weeks. Depressive and manic symptoms were assessed using the Hamilton Depression Rating Scale 17-item and the Young Mania Rating Scale, respectively, by a researcher blinded to smartphone data. Data were analyzed using random forest algorithms. Affective states were classified using voice features extracted during everyday life phone calls. Voice features were found to be more accurate, sensitive and specific in the classification of manic or mixed states with an area under the curve (AUC)=0.89 compared with an AUC=0.78 for the classification of depressive states. Combining voice features with automatically generated objective smartphone data on behavioral activities and electronic self-monitored data increased the accuracy, sensitivity and specificity of classification of affective states slightly. Voice features collected in naturalistic settings using smartphones may be used as objective state markers in patients with bipolar disorder.

Daily electronic self-monitoring in bipolar disorder using smartphones - the MONARCA I trial: a randomized, placebo-controlled, single-blind, parallel group trial.

BACKGROUND: The number of studies on electronic self-monitoring in affective disorder and other psychiatric disorders is increasing and indicates high patient acceptance and adherence. Nevertheless, the effect of electronic self-monitoring in patients with bipolar disorder has never been investigated in a randomized controlled trial (RCT). The objective of this trial was to investigate in a RCT whether the use of daily electronic self-monitoring using smartphones reduces depressive and manic symptoms in patients with bipolar disorder. METHOD: A total of 78 patients with bipolar disorder according to ICD-10 criteria, aged 18-60 years, and with 17-item Hamilton Depression Rating Scale (HAMD-17) and Young Mania Rating Scale (YMRS) scores ≤17 were randomized to the use of a smartphone for daily self-monitoring including a clinical feedback loop (the intervention group) or to the use of a smartphone for normal communicative purposes (the control group) for 6 months. The primary outcomes were differences in depressive and manic symptoms measured using HAMD-17 and YMRS, respectively, between the intervention and control groups. RESULTS: Intention-to-treat analyses using linear mixed models showed no significant effects of daily self-monitoring using smartphones on depressive as well as manic symptoms. There was a tendency towards more sustained depressive symptoms in the intervention group (B = 2.02, 95% confidence interval -0.13 to 4.17, p = 0.066). Sub-group analysis among patients without mixed symptoms and patients with presence of depressive and manic symptoms showed significantly more depressive symptoms and fewer manic symptoms during the trial period in the intervention group. CONCLUSIONS: These results highlight that electronic self-monitoring, although intuitive and appealing, needs critical consideration and further clarification before it is implemented as a clinical tool.

Predictors of body composition changes during tuberculosis treatment in Mwanza, Tanzania.

BACKGROUND/OBJECTIVES: Gains in fat mass and lean mass during tuberculosis (TB) treatment may determine functional recovery and survival; yet, data are scarce. We aimed to assess predictors of fat and fat-free mass during 2 months of intensive TB treatment in a cohort in Mwanza, Tanzania. SUBJECTS/METHODS: Fat and fat-free mass were determined at the start of TB treatment and repeated after 2 months using the deuterium dilution technique. Gains in fat and fat-free mass were determined and predictors assessed using regression analysis. RESULTS: Data for 116 patients were available at baseline and during follow-up. Of these, 38.8% were females, mean age was 37.3 (s.d. 13.5) years, 69% (81) had sputum-positive TB, 45.7% (53) were HIV infected and 25% (29) were current smokers. The mean weight gain was 3.3 kg (95% confidence interval: 2.7; 3.8), and it did not differ by sex. However, compared with females, males had 1.0 (0.4; 1.6) kg/m(2) lower fat mass but 0.7 (0.2; 1.3) kg/m(2) higher fat-free mass gain. Current smoking was associated with higher fat mass (0.7 kg/m(2), 0.04; 1.4) but lower fat-free mass (-0.5 kg/m(2), -1.2; 0.07) gain. Among HIV-infected patients, antiretroviral therapy (ART) led to a lower fat gain (-1.2 kg/m(2), -2.2; -0.2) but to a higher fat-free mass among sputum-negative (2.9 kg/m(2), 0.8; 5.1) but not sputum-positive patients. CONCLUSIONS: During intensive phase of TB treatment, sex, smoking and ART were predictors of body composition. Larger studies are needed to further understand predictors of body composition during recovery, to help design interventions to improve treatment outcomes.

The use of combined heart rate response and accelerometry to assess the level and predictors of physical activity in tuberculosis patients in Tanzania.

SUMMARY: We assessed the role of tuberculosis (TB) disease and HIV infection on the level of physical activity. A combined heart rate and movement sensor was used to assess habitual physical activity in TB patients and non-TB controls. The association between sputum-negative TB, sputum-positive TB, HIV and physical activity estimates were assessed in multivariable linear regression models adjusted for age, sex, haemoglobin and alpha-1-acid glycoprotein (AGP). Sputum-positive [eB 0·43, 95% confidence interval (CI) 0·29-0·64] and sputum-negative (eB 0·67, 95% CI 0·47-0·94) TB as well as HIV infection (eB 0·59, 95% CI 0·46-0·75) were associated with reduced activity compared to controls. Anaemia accounted for a substantial part of the effects of HIV, while elevated AGP primarily mediated the TB effect. The level of physical activity is highly influenced by TB and HIV, and mainly mediated through anaemia of infection and associated with elevated acute phase response.

The role of anthropometric and other predictors for diabetes among urban Tanzanians with tuberculosis.

BACKGROUND: As diabetes impairs tuberculosis (TB) treatment outcomes, it is essential to identify diabetes among TB patients. While little is known about predictors of diabetes among healthy individuals in Africa, predictors among TB patients are almost non-existent. OBJECTIVE: To assess potential predictors for diabetes among newly diagnosed pulmonary TB patients in Tanzania. METHODS: TB patients were tested for diabetes using an oral glucose tolerance test, demographic information was collected and anthropometric measurements taken. The association between diabetes and possible predictors were examined using logistic regression analyses. RESULTS: Of 1205 TB patients, 16.4% (n = 197) had diabetes, 9.0% (n = 108) were aged ≥55 years, 3.3% (n = 40) were overweight (body mass index [BMI] ≥ 25 kg/m(2)) and 12.7% (n = 152) severely underweight (BMI < 16 kg/m(2)). Diabetes was most prevalent in the 45-55 year age group, and increasing weight, BMI and waist circumference were associated with diabetes. Severe underweight (BMI < 16 kg/m(2)) among male TB patients (sex-BMI interaction, P = 0.02) was associated with diabetes (OR 2.52, P = 0.004). CONCLUSION: Diabetes is a common comorbidity among TB patients. Although diabetes was associated with obesity and was more prevalent among the middle-aged, the majority of TB patients with diabetes comorbidity were young and lean. With diabetes as a major risk factor for TB, and with the lack of strong predictors for diabetes, universal diabetes screening should be implemented in the TB programme.