Association between lifetime and recent stressful life events and the early course and psychopathology in patients with newly diagnosed bipolar disorder, first-degree unaffected relatives and healthy controls: Cross-sectional results from a prospective study.

OBJECTIVE: There is an accumulation of stressful life events prior to the first mood episode, but the impact of previous severe life events on psychopathology in patients with bipolar disorder (BD) is not well studied. We aimed to examine the number of recent and lifetime life events in patients with newly diagnosed BD, their unaffected relatives (UR), and healthy controls (HC) as well as the impact of severe lifetime life events on the early course of BD. METHODS: We compared the number of recent and lifetime life events in 398 patients with newly diagnosed BD, 109 UR, and 214 HC. We subsequently dichotomized the patients with BD by >2 lifetime life events to investigate the associations of severe lifetime life events with clinical characteristics and affective symptoms. RESULTS: Patients with newly diagnosed BD reported significantly more life events in the last 12 months and lifetime before compared with UR and HC. Patients who reported >2 lifetime life events (n = 160) compared with patients with 0-2 life events (n = 238) had a significantly longer diagnostic delay (9.5 years ± 8.2 vs. 6.2 years ± 6.9), presented with more anxiety and depressive symptoms and had at least one previous suicide attempt (30.6% vs. 15.6%) and one previous admission (51.3% vs. 36.6%). CONCLUSION: The experience of severe lifetime life events seems to impact the early course in BD in terms of longer diagnostic delay, more severe psychopathology including more admissions and a more than doubled risk for previous suicide attempts.

Mood, activity, and sleep measured via daily smartphone-based self-monitoring in young patients with newly diagnosed bipolar disorder, their unaffected relatives and healthy control individuals.

Diagnostic evaluations and early interventions of patients with bipolar disorder (BD) rely on clinical evaluations. Smartphones have been proposed to facilitate continuous and fine-grained self-monitoring of symptoms. The present study aimed to (1) validate daily smartphone-based self-monitored mood, activity, and sleep, against validated questionnaires and clinical ratings in young patients with newly diagnosed BD, unaffected relatives (UR), and healthy controls persons (HC); (2) investigate differences in daily smartphone-based self-monitored mood, activity, and sleep in young patients with newly diagnosed BD, UR, and HC; (3) investigate associations between self-monitored mood and self-monitored activity and sleep, respectively, in young patients with newly diagnosed BD. 105 young patients with newly diagnosed BD, 24 UR and 77 HC self-monitored 2 to 1077 days (median [IQR] = 65 [17.5-112.5]). There was a statistically significantly negative association between the mood item on Hamilton Depression Rating Scale (HAMD) and smartphone-based self-monitored mood (B = - 0.76, 95% CI - 0.91; - 0.63, p < 0.001) and between psychomotor item on HAMD and self-monitored activity (B = - 0.44, 95% CI - 0.63; - 0.25, p < 0.001). Smartphone-based self-monitored mood differed between young patients with newly diagnosed BD and HC (p < 0.001), and between UR and HC (p = 0.008) and was positively associated with smartphone-based self-reported activity (p < 0.001) and sleep duration (p < 0.001). The findings support the potential of smartphone-based self-monitoring of mood and activity as part of a biomarker for young patients with BD and UR. Smartphone-based self-monitored mood is better to discriminate between young patients with newly diagnosed BD and HC, and between UR and HC, compared with smartphone-based activity and sleep.Trial registration clinicaltrials.gov NCT0288826.

Aberrant cognition in newly diagnosed patients with bipolar disorder and their unaffected relatives.

BACKGROUND: Patients with bipolar disorder (BD) experience persistent impairments in both affective and non-affective cognitive function, which is associated with a worse course of illness and poor functional outcomes. Nevertheless, the temporal progression of cognitive dysfunction in BD remains unclear and the identification of objective endophenotypes can inform the aetiology of BD. METHODS: The present study is a cross-sectional investigation of cognitive baseline data from the longitudinal Bipolar Illness Onset-study. One hundred seventy-two remitted patients newly diagnosed with BD, 52 of their unaffected relatives (UR), and 110 healthy controls (HC) were compared on a large battery of behavioural cognitive tasks tapping into non-affective (i.e. neurocognitive) and affective (i.e. emotion processing and regulation) cognition. RESULTS: Relative to HCs, patients with BD exhibited global neurocognitive deficits (ps < 0.001), as well as aberrant emotion processing and regulation (ps ⩽ 0.011); including decreased emotional reactivity to positive social scenarios, impaired ability to down-regulate positive emotion, as well as a specific deficit in the ability to recognise surprised facial expressions. Their URs also showed a trend towards difficulties identifying surprised faces (p = 0.075). No other differences in cognitive function were found for URs compared to HCs. CONCLUSIONS: Neurocognitive deficits and impairments within emotion processing and regulation may be illness-related deficits of BD that present after illness-onset, whereas processing of emotional faces may represent an early risk marker of BD. However, longitudinal studies are needed to examine the association between cognitive impairments and illness progression in BD.

Thirty-year cardiovascular risk score in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives.

OBJECTIVES: Bipolar disorder is associated with a decreased life expectancy of 8-12 years. Cardiovascular disease is the leading cause of excess mortality. For the first time, we investigated the Framingham 30-year risk score of cardiovascular disease in patients with newly diagnosed/first-episode bipolar disorder, their unaffected first-degree relatives and healthy individuals. METHODS: In a cross-sectional study, we compared the Framingham 30-year risk score of cardiovascular disease in 221 patients with newly diagnosed/first-episode bipolar disorder, 50 of their unaffected first-degree relatives and 119 healthy age- and sex-matched individuals with no personal or first-degree family history of affective disorder. Among patients with bipolar disorder, we further investigated medication- and illness-related variables associated with cardiovascular risk. RESULTS: The 30-year risk of cardiovascular disease was 98.5% higher in patients with bipolar disorder (p = 0.017) and 85.4% higher in unaffected first-degree relatives (p = 0.042) compared with healthy individuals in models adjusted for age and sex. When categorizing participants in low cardiovascular risk without considering age and sex distribution among participants, 81% of patients were at low risk, versus 92% of unaffected relatives and 89% of healthy individuals. Of the patients 209 (94.6%) were diagnosed within the preceding 2 years. Smoking was more prevalent among patients with bipolar disorder (45.2%) and their unaffected first-degree relatives (20.4%) compared with healthy individuals (12.8%). Similarly, dyslipidemia was more common among patients with bipolar disorder compared with healthy individuals. Treatment with psychotropic medication with metabolic adverse effects was associated with higher 30-year cardiovascular disease risk score, whereas we did not find illness-related variables associated with cardiovascular risk among patients with bipolar disorder. CONCLUSION: We found an enhanced cardiovascular disease risk score in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives, which points to a need for specific primary preventive interventions against smoking and dyslipidemia in these populations.

Socio-economic status and functioning in patients newly diagnosed with bipolar disorder and their unaffected siblings - Results from a cross-sectional clinical study.

BACKGROUND: Few studies have reported socio-economic status and functioning in patients newly diagnosed with bipolar disorder (BD) and their unaffected siblings (US). METHODS: Socio-economic status and functioning were compared in a cross-sectional clinical study including 382 patients newly diagnosed with BD, 129 of their US, and 200 healthy control individuals (HC). RESULTS: Socio-economic status was lower in patients newly diagnosed with BD compared with HC within educational achievement, employment status, workability and relationship status (p < 0.001, OR between 0.02 and 0.53). Regarding US and HC, US had lower educational achievement (p < 0.001, OR = 0.27 [0.16; 0.46]), as the only affected socio-economic outcome. Functioning was substantially impaired according to the Functional Assessment Short Test (FAST) (p < 0.001, Cohen's d = 2.12) and Work and Social Adjustment Scale (WSAS) (p < 0.001, Cohen's d = 2.76) in patients newly diagnosed with BD compared with HC. US expressed the same pattern with impaired overall functioning. Within patients, the impaired functioning was associated with a longer illness duration. LIMITATIONS: Patients had an illness duration of 10.5 [IQR: 6.1; 16.2] years, even though they were included shortly after a diagnosis of BD (0.3 [IQR: 0.1; 0.7] years), highlighting the obstacles of research in illness onset of BD. CONCLUSIONS: Patients newly diagnosed with BD, and to a lesser degree their US, exhibit lower socio-economic status and impaired overall functioning. These findings emphasise the importance of early diagnosis, treatment and focus on functional recovery and stress that intervention strategies and further research in high-risk individuals are needed.

Automatically Generated Smartphone Data in Young Patients With Newly Diagnosed Bipolar Disorder and Healthy Controls.

Background: Smartphones may facilitate continuous and fine-grained monitoring of behavioral activities via automatically generated data and could prove to be especially valuable in monitoring illness activity in young patients with bipolar disorder (BD), who often present with rapid changes in mood and related symptoms. The present pilot study in young patients with newly diagnosed BD and healthy controls (HC) aimed to (1) validate automatically generated smartphone data reflecting physical and social activity and phone usage against validated clinical rating scales and questionnaires; (2) investigate differences in automatically generated smartphone data between young patients with newly diagnosed BD and HC; and (3) investigate associations between automatically generated smartphone data and smartphone-based self-monitored mood and activity in young patients with newly diagnosed BD. Methods: A total of 40 young patients with newly diagnosed BD and 21 HC aged 15-25 years provided daily automatically generated smartphone data for 3-779 days [median (IQR) = 140 (11.5-268.5)], in addition to daily smartphone-based self-monitoring of activity and mood. All participants were assessed with clinical rating scales. Results: (1) The number of outgoing phone calls was positively associated with scores on the Young Mania Rating Scale and subitems concerning activity and speech. The number of missed calls (p = 0.015) and the number of outgoing text messages (p = 0.017) were positively associated with the level of psychomotor agitation according to the Hamilton Depression Rating scale subitem 9. (2) Young patients with newly diagnosed BD had a higher number of incoming calls compared with HC (BD: mean = 1.419, 95% CI: 1.162, 1.677; HC: mean = 0.972, 95% CI: 0.637, 1.308; p = 0.043) and lower self-monitored mood and activity (p's < 0.001). (3) Smartphone-based self-monitored mood and activity were positively associated with step counts and the number of outgoing calls, respectively (p's < 0.001). Conclusion: Automatically generated data on physical and social activity and phone usage seem to reflect symptoms. These data differ between young patients with newly diagnosed BD and HC and reflect changes in illness activity in young patients with BD. Automatically generated smartphone-based data could be a useful clinical tool in diagnosing and monitoring illness activity in young patients with BD.

Higher systemic oxidatively generated DNA and RNA damage in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives.

BACKGROUND: Prior studies in bipolar disorders (BD) have suggested that oxidative stress and cellular ageing play a key role in the pathophysiology of BD. Nevertheless, oxidative stress has not been investigated in patients with newly diagnosed BD and in their unaffected first-degree relatives (UR), compared with healthy control individuals (HC). METHODS: We investigated the level of systemic oxidative damage to DNA and RNA measured by urinary excretion of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo) levels, respectively, in 360 patients with newly diagnosed BD, 92 of their UR and 197 HC. RESULTS: Independent of lifestyle and demographic variables, levels of both 8-oxoGuo and 8-oxodG was 17.1% (B = 1.171, 95%CI = 1.125-1.219, p < 0.001) and 21.2% (B = 1.212, 95%CI = 1.145-1.283, p < 0.001) higher, respectively, in patients with BD compared with HC and 13.3% (B = 1.133, 95%CI = 1.069-1.200, p < 0.001) and 26.6% (B = 1.266, 95%CI = 1.167-1.374, p < 0.001) higher, respectively, in UR compared with HC. Neither 8-oxoGuo nor 8-oxodG levels differed between patients with BD and UR. These findings were replicated in patients in full or partial remission and were consistent both in BD type I and II. CONCLUSION: Overall, the findings of higher oxidative stress in patients with newly diagnosed BD and their UR suggest that systemic nucleoside damage by oxidative stress is present prior to onset and in the early stages of BD thereby potentially representing trait markers of BD.

Impact of modification to DSM-5 criterion A for hypomania/mania in newly diagnosed bipolar patients: findings from the prospective BIO study.

BACKGROUND: DSM-IV states that criterion A for diagnosing hypomania/mania is mood change. The revised DSM-5 now states that increased energy or activity must be present alongside mood changes to diagnose hypomania/mania, thus raising energy/activity to criterion A. We set out to investigate how the change in criterion A affects the diagnosis of hypomanic/manic visits in patients with a newly diagnosed bipolar disorder. RESULTS: In this prospective cohort study, 373 patients were included (median age = 32; IQR, 27-40). Women constituted 66% (n = 245) of the cohort and 68% of the cohort (n = 253) met criteria for bipolar type II, the remaining patients were diagnosed bipolar type I. Median number of contributed visits was 2 per subject (IQR, 1-3) and median follow-up time was 3 years (IQR, 2-4). During follow-up, 127 patients had at least one visit with fulfilled DSM-IV criterion A. Applying DSM-5 criterion A reduced the number of patients experiencing a hypomanic/manic visit by 62% at baseline and by 50% during longitudinal follow-up, compared with DSM-IV criterion A. Fulfilling DSM-5 criterion A during follow-up was associated with higher modified young mania rating scale score (OR = 1.51, CL [1.34, 1.71], p < 0.0001) and increased number of visits contributed (OR = 1.86, CL [1.52, 2.29], p < 0.0001). CONCLUSION: Applying the stricter DSM-5 criterion A in a cohort of newly diagnosed bipolar patients reduced the number of patients experiencing a hypomanic/manic visit substantially, and was associated with higher overall young mania rating scale scores, compared with DSM-IV criterion A. Consequently, fewer hypomanic/manic visits may be detected in newly diagnosed bipolar patients with applied DSM-5 criterion A, and the upcoming ICD-11, which may possibly result in longer diagnostic delay of BD as compared with the DSM-IV.

Affective and non-affective cognition in patients with bipolar disorder type I and type II in full or partial remission: Associations with familial risk.

BACKGROUND: The upcoming conversion of the ICD-11 will subdivide patients with bipolar disorder (BD) into BD type I (BD-I) and BD type II (BD-II). This study aimed to investigate whether cognitive impairments could aid as objective cognitive biomarkers for recently diagnosed BD subtypes by comparing cognitive profiles between BD subtypes, their unaffected relatives (UR), and healthy controls (HC). METHODS: The sample included 76 patients with BD-I, 149 patients with BD-II, 28 UR of patients with BD-I (UR-I), 50 UR of patients with BD-II (UR-II) and 168 HC from the Bipolar Illness Onset study, who were assessed with an extensive non-affective and affective cognitive test battery. RESULTS: The results showed no significant differences in affective or non-affective cognition between BD-I and BD-II. Compared to HC, patients with BD-I (but not BD-II) showed worse performance in verbal fluency (p = .01) and were slower at recognising fearful faces (p = .045), while patients with BD-II (but not BD-I) displayed generally poorer recognition of facial expressions (p = .02). Only UR-I showed lower performance on verbal fluency (p = .049) and aberrant affective cognition (ps≤.047) compared to HC. LIMITATIONS: The potential confounding effects of medication were not explored. CONCLUSIONS: The lack of significant differences in cognitive profiles between recently diagnosed BD-I and BD-II suggests that neither affective nor non-affective cognition are indicative of BD subtype.

Brain-derived neurotrophic factor levels in newly diagnosed patients with bipolar disorder, their unaffected first-degree relatives and healthy controls.

BACKGROUND: Brain-derived neurotrophic factor (BDNF), which facilitates neuroplasticity and synaptogenesis, may be decreased in bipolar disorder, but has not been systematically investigated in people with newly diagnosed bipolar disorder and unaffected first-degree relatives. AIMS: To compare BDNF levels in patients with newly diagnosed bipolar disorder, their unaffected first-degree relatives and healthy controls. METHOD: The study investigated plasma BDNF levels in patients (n = 371) with newly diagnosed bipolar disorder, their unaffected first-degree relatives (n = 98) and healthy controls (n = 200) using enzyme-linked immunosorbent assay. We further investigated associations between BDNF levels and illness-related variables and medication status. RESULTS: BDNF levels were found to be 22.0% (95% CI 1.107-1.343) higher in patients with bipolar disorder compared with healthy controls (P < 0.001) and 15.6% higher in unaffected first-degree relatives compared with healthy controls (95% CI 1.007-1.327, P = 0.04), when adjusting for age and gender. Further, BDNF levels were positively associated with duration of illness at a trend level (P = 0.05), age (P = 0.001) and use of anti-epileptic medication (P = 0.05). CONCLUSIONS: These findings suggest that BDNF levels are not decreased in the early stages of bipolar disorder and in unaffected first-degree relatives contrasting with prior findings during later stages of the illness.

The effect of smartphone-based monitoring and treatment on the rate and duration of psychiatric readmission in patients with unipolar depressive disorder: The RADMIS randomized controlled trial.

BACKGROUND: Patients with unipolar depressive disorder are frequently hospitalized, and the period following discharge is a high-risk-period. Smartphone-based treatments are receiving increasing attention among researchers, clinicians, and patients. We aimed to investigate whether a smartphone-based monitoring and treatment system reduces the rate and duration of readmissions, more than standard treatment, in patients with unipolar depressive disorder following hospitalization. METHODS: We conducted a pragmatic, investigator-blinded, randomized controlled trial. The intervention group received a smartphone-based monitoring and treatment system in addition to standard treatment. The system allowed patients to self-monitor symptoms and access psycho-educative information and cognitive modules. The patients were allocated a study-nurse who, based on the monitoring data, guided and supported them. The control group received standard treatment. The trial lasted six months, with outcome assessments at 0, 3, and 6 months. RESULTS: We included 120 patients with unipolar depressive disorder (ICD-10). Intention-to-treat analyses showed no statistically significant differences in time to readmission (Log-Rank p=0.9) or duration of readmissions (B=-16.41,95%CI:-47.32;25.5,p=0.3) (Primary outcomes). There were no differences in clinically rated depressive symptoms (p=0.6) or functioning (p=0.1) (secondary outcomes). The intervention group had higher levels of recovery (B=7,29, 95%CI:0.82;13,75,p=0.028) and a tendency towards higher quality of life (p=0.07), wellbeing (p=0,09) satisfaction with treatment (p=0.05) and behavioral activation (p=0.08) compared with the control group (tertiary outcomes). LIMITATIONS: Patients and study-nurses were unblinded to allocation. CONCLUSIONS: We found no effect of the intervention on primary or secondary outcomes. In tertiary outcomes, patients in the intervention group reported higher levels of recovery compared to the control group.

Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review.

BACKGROUND: Psychiatric disorders often have an onset at an early age, and early identification and intervention help improve prognosis. A fine-grained, unobtrusive, and effective way to monitor symptoms and level of function could help distinguish severe psychiatric health problems from normal behavior and potentially lead to a more efficient use of clinical resources in the current health care system. The use of smartphones to monitor and treat children, adolescents, and young adults with psychiatric disorders has been widely investigated. However, no systematic review concerning smartphone-based monitoring and treatment in this population has been published. OBJECTIVE: This systematic review aims at describing the following 4 features of the eligible studies: (1) monitoring features such as self-assessment and automatically generated data, (2) treatment delivered by the app, (3) adherence to self-monitoring, and (4) results of the individual studies. METHODS: We conducted a systematic literature search of the PubMed, Embase, and PsycInfo databases. We searched for studies that (1) included a smartphone app to collect self-monitoring data, a smartphone app to collect automatically generated smartphone-based data, or a smartphone-based system for treatment; (2) had participants who were diagnosed with psychiatric disorders or received treatment for a psychiatric disorder, which was verified by an external clinician; (3) had participants who were younger than 25 years; and (4) were published in a peer-reviewed journal. This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias in each individual study was systematically assessed. RESULTS: A total of 2546 unique studies were identified through literature search; 15 of these fulfilled the criteria for inclusion. These studies covered 8 different diagnostic groups: psychosis, eating disorders, depression, autism, self-harm, anxiety, substance abuse, and suicidal behavior. Smartphone-based self-monitoring was used in all but 1 study, and 11 of them reported on the participants' adherence to self-monitoring. Most studies were feasibility/pilot studies, and all studies on feasibility reported positive attitudes toward the use of smartphones for self-monitoring. In 2 studies, automatically generated data were collected. Three studies were randomized controlled trials investigating the effectiveness of smartphone-based monitoring and treatment, with 2 of these showing a positive treatment effect. In 2 randomized controlled trials, the researchers were blinded for randomization, but the participants were not blinded in any of the studies. All studies were determined to be at high risk of bias in several areas. CONCLUSIONS: Smartphones hold great potential as a modern, widely available technology platform to help diagnose, monitor, and treat psychiatric disorders in children and adolescents. However, a higher level of homogeneity and rigor among studies regarding their methodology and reporting of adherence would facilitate future reviews and meta-analyses.

Daily self-reported and automatically generated smartphone-based sleep measurements in patients with newly diagnosed bipolar disorder, unaffected first-degree relatives and healthy control individuals.

OBJECTIVES: (1) To investigate daily smartphone-based self-reported and automatically generated sleep measurements, respectively, against validated rating scales; (2) to investigate if daily smartphone-based self-reported sleep measurements reflected automatically generated sleep measurements and (3) to investigate the differences in smartphone-based sleep measurements between patients with bipolar disorder (BD), unaffected first-degree relatives (UR) and healthy control individuals (HC). METHODS: We included 203 patients with BD, 54 UR and 109 HC in this study. To investigate whether smartphone-based sleep calculated from self-reported bedtime, wake-up time and screen on/off time reflected validated rating scales, we used the Pittsburgh Sleep Quality Index (PSQI) and sleep items on the Hamilton Depression Rating Scale 17-item (HAMD-17) and the Young Mania Rating Scale (YMRS). FINDINGS: (1) Self-reported smartphone-based sleep was associated with the PSQI and sleep items of the HAMD and the YMRS. (2) Automatically generated smartphone-based sleep measurements were associated with daily self-reports of hours slept between 12:00 midnight and 06:00. (3) According to smartphone-based sleep, patients with BD slept less between 12:00 midnight and 06:00, with more interruption and daily variability compared with HC. However, differences in automatically generated smartphone-based sleep were not statistically significant. CONCLUSION: Smartphone-based data may represent measurements of sleep patterns that discriminate between patients with BD and HC and potentially between UR and HC. CLINICAL IMPLICATION: Detecting sleep disturbances and daily variability in sleep duration using smartphones may be helpful for both patients and clinicians for monitoring illness activity. TRIAL REGISTRATION NUMBER: clinicaltrials.gov (NCT02888262).

Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals.

BACKGROUND: In DSM-5 activity is a core criterion for diagnosing hypomania and mania. However, there are no guidelines for quantifying changes in activity. The objectives of the study were (1) to investigate daily smartphone-based self-reported and automatically-generated activity, respectively, against validated measurements of activity; (2) to validate daily smartphone-based self-reported activity and automatically-generated activity against each other; (3) to investigate differences in daily self-reported and automatically-generated smartphone-based activity between patients with bipolar disorder (BD), unaffected relatives (UR) and healthy control individuals (HC). METHODS: A total of 203 patients with BD, 54 UR, and 109 HC were included. On a smartphone-based app, the participants daily reported their activity level on a scale from -3 to + 3. Additionally, participants owning an android smartphone provided automatically-generated data, including step counts, screen on/off logs, and call- and text-logs. Smartphone-based activity was validated against an activity questionnaire the International Physical Activity Questionnaire (IPAQ) and activity items on observer-based rating scales of depression using the Hamilton Depression Rating scale (HAMD), mania using Young Mania Rating scale (YMRS) and functioning using the Functional Assessment Short Test (FAST). In these analyses, we calculated averages of smartphone-based activity measurements reported in the period corresponding to the days assessed by the questionnaires and rating scales. RESULTS: (1) Smartphone-based self-reported activity was a valid measure according to scores on the IPAQ and activity items on the HAMD and YMRS, and was associated with FAST scores, whereas the majority of automatically-generated smartphone-based activity measurements were not. (2) Daily smartphone-based self-reported and automatically-generated activity correlated with each other with nearly all measurements. (3) Patients with BD had decreased daily self-reported activity compared with HC. Patients with BD had decreased physical (number of steps) and social activity (more missed calls) but a longer call duration compared with HC. UR also had decreased physical activity compared with HC but did not differ on daily self-reported activity or social activity. CONCLUSION: Daily self-reported activity measured via smartphone represents overall activity and correlates with measurements of automatically generated smartphone-based activity. Detecting activity levels using smartphones may be clinically helpful in diagnosis and illness monitoring in patients with bipolar disorder. Trial registration clinicaltrials.gov NCT02888262.

Mood instability in patients with newly diagnosed bipolar disorder, unaffected relatives, and healthy control individuals measured daily using smartphones.

OBJECTIVES: To investigate whether mood instability (MI) qualify as a trait marker for bipolar disorder (BD) we investigated: 1) differences in smartphone-based self-reported MI between three groups: patients with newly diagnosed BD, unaffected first-degree relatives (UR), and healthy control individuals (HC); 2) the correlation between MI and functioning, stress, and duration of illness, respectively; and 3) the validity of smartphone-based self-evaluated mood ratings as compared to observer-based ratings of depressed and manic mood. METHODS: 203 patients with newly diagnosed BD, 54 UR and 109 HC were included as part of the longitudinal Bipolar Illness Onset study. Participants completed daily smartphone-based mood ratings for a period of up to two years and were clinically assessed with ratings of depression, mania and functioning. RESULTS: Mood instability scores were statistically significantly higher in patients with BD compared with HC (mean=1.18, 95%CI: 1.12;1.24 vs 1.05, 95%CI: 0.98;1.13, p = 0.007) and did not differ between patients with BD and UR (mean=1.17, 95%CI: 1.07;1.28, p = 0.91). For patients, increased MI scores correlated positively with impaired functioning (p<0.001), increased stress level (p<0.001) and increasing number of prior mood episodes (p<0.001). Smartphone-based mood ratings correlated with ratings of mood according to sub-item 1 on the Hamilton Depression Rating Scale 17-items and the Young Mania Rating Scale, respectively (p´s<0.001). LIMITATION: The study had a smaller number of UR than planned. CONCLUSION: Mood instability is increased in patients with newly diagnosed BD and unaffected relatives and associated with decreased functioning. The findings highlight MI as a potential trait marker for BD.

High-sensitive C-reactive protein and homocysteine levels in patients with newly diagnosed bipolar disorder, their first-degree relatives, and healthy control persons-Results from a clinical study.

BACKGROUND: Changes in inflammatory and metabolic markers are implicated in the pathogenesis in both the development and progression of bipolar disorder (BD). Notwithstanding, these markers have not been investigated in newly diagnosed BD. METHODS: We compared high-sensitive C-reactive protein (hs-CRP) and homocysteine (Hcy) levels in 372 patients with newly diagnosed BD, 106 unaffected first-degree relatives (URs), and 201 healthy control persons (HCs). Within the patient group, we also investigated possible associations between hs-CRP and Hcy, respectively, with illness-related characteristics and psychotropic medication. RESULTS: No statistically significant differences in Hcy and hs-CRP levels were found when comparing BD and URs with HCs. Similarly, there were no differences when comparing only patients in remission or patients with affective symptoms, respectively, with HCs. Hcy levels were found to be 11.9% (95% CI: 1.030-1.219) higher in patients with BD when compared with their URs (p = 0.008), when adjusting for folate and cobalamin status, age, sex, and self-reported activity levels. Hcy levels were significantly associated with folate, cobalamin, gender, and age in all models (p < 0.05). CONCLUSION: Our results do not support hs-CRP or Hcy as markers in newly diagnosed BD.

Sleep and physical activity in patients with newly diagnosed bipolar disorder in remission, their first-degree unaffected relatives and healthy controls.

BACKGROUND: Sleep disturbances are a central feature in bipolar disorder (BD) that often persist in remission and seem to be present also in unaffected first-degree relatives (UR) of patients with BD, presenting a possible risk factor for later onset of BD. However, it is unknown if these disturbances are associated with unhealthy life-style as reflected in low levels of physical activity. We investigated sleep disturbances and physical activity levels in patients with newly diagnosed BD in full or partial remission, their UR and healthy controls (HC). METHODS: Sleep patterns and physical activity were compared in 227 patients with newly diagnosed BD, 76 UR and 148 HC. The Pittsburgh Sleep Quality Index (PSQI) and the International Physical Activity Questionnaire (IPAQ) were used to assess sleep disturbances and physical activity, respectively. RESULTS: In sex- and age-adjusted analyses, patients with BD exhibited more sleep disturbances and lower physical activity compared with UR and HC, respectively. Unaffected relatives reported significantly longer sleep latency and a non-significant trend towards more overall sleep disturbances compared with HC. CONCLUSIONS: Sleep disturbances and less physical activity are present in patients with newly diagnosed BD in partial or full remission. Individuals at familiar risk of BD reported longer sleep latency and similar physical activity compared with HC. Further prospective studies are needed to clarify whether these discrete sleep disturbances act as risk factor for later onset of BD and whether increased physical activity in high-risk individuals may act as a protective factor against development of psychiatric illness.

Mobile videoconferencing for enhanced emergency medical communication - a shot in the dark or a walk in the park? ‒‒ A simulation study.

BACKGROUND: Videoconferencing on mobile phones may enhance communication, but knowledge on its quality in various situations is needed before it can be used in medical emergencies. Mobile phones automatically activate loudspeaker functionality during videoconferencing, making calls particularly vulnerable to background noise. The aim of this study was to investigate if videoconferencing can be used between lay bystanders and Emergency Medical Dispatch (EMD) operators for initial emergency calls during medical emergencies, under suboptimal sound and light conditions. METHODS: Videoconferencing was tested between 90 volunteers and an emergency medical dispatcher in a standardized scenario of a medical emergency. Three different environments were used for the trials: indoors with moderate background noise, outdoors with daylight and much background noise, and outdoors during nighttime with little background noise. Thirty participants were recruited for each of the three locations. After informed consent, each participant was asked to use a video mobile phone to communicate with an EMD operator. During the video call the EMD operator gave instructions for tasks to be performed by the participant. The video quality from the caller to the EMD was evaluated by the EMD operator and rated on a five step scale ranging from "not able to see" to "good video quality". Sound quality between participants and EMD operators was assessed by a method developed for this trial. Kruskal - Wallis and Chi-square tests were used for statistical analysis. RESULTS: Video quality was significantly different between the groups (p <0.001), and the nighttime group had lower video quality. For most sessions in the nighttime group it was still possible to see actions done at the simulated emergency site. All participants were able to perform their tasks according to the instructions given by dispatchers, although with a need for more repetitions during sessions with much background noise. No calls were rated by dispatchers as incomprehensible due to low sound quality and only 3% of the calls were considered somewhat difficult or very difficult to understand. CONCLUSIONS: Videoconferencing on mobile phones can be used for the initial emergency call during medical emergencies also in suboptimal conditions.