A higher score on our composite measure was associated with being female, being unemployed, having greater medication load and lower mania symptomatology. Similarly, studies in BD show that poor sleep is associated with worsening BD symptoms , among other correlates. Based upon LASSO regression, TST and NA most contributed to the correlation with medication load which may be reflective of the sedating properties of many psychotropic medications . PS contributed most to the correlations with employment, and mania symptoms, which may relate to sleep fragmentation and variability that has previously been shown to be associated with these variables . Because wrist actigraphy is easily administered and is less invasive compared to an inlab sleep evaluation and is easier to get longitudinal measures over the span of weeks, it is important for future research to identify other approaches that could reduce these voluminous data to actionable insights, especially for treating patients with BD where management of sleep is paramount. Clinicians could utilize a composite measure to identify patients with poor sleep overall and triage these patients to appropriate sleep treatment options based upon their individual sleep metrics. In the future, as such accelerometry data becomes available in many different populations, it may soon be possible to identify when poor sleep begins to emerge with the possibility of predicting a mood episode to offer just-in-time clinical interventions. More research is needed to develop tools using these data for future prediction of events for clinical monitoring. Our study has some limitations. First, our analysis was cross-sectional and retrospective. Research should explore ways that changes in sleep quality longitudinally may be incorporated in this composite measure. Second, we focused on the means of sleep parameters as our main purpose was to examine an intuitive composite score for poor sleep. Future studies may want to identify whether night-to-night variability in sleep or circadian patterns can improve a composite measure . Third, in the absence of published norms for actigraphic sleep measures for healthy individuals of comparable age to our BD sample, we used our own HC sample as the normative group.

To the extent that our HC sample was relatively small and participants were not selected on the basis of having no reported sleep abnormalities,grow trays 4×4 this may have introduced some bias into the composite scores. It may be important for future studies to compare this method to other approaches which do not use a normative sample . Fourth, our sample size was small and given the number of correlates assessed with the composite score, there is a possibility of significant findings due to chance alone. However, our study evaluates a potential way to combine actigraphic measurements, and future studies with larger samples may help examine this further. Finally, we did not have measures of sleep apnea which may contribute to disturbed sleep . However, sleep apnea is often undiagnosed , and in a clinical setting, clinicians may need to base their assessment of sleep on wrist actigraphy alone. In conclusion, we found that while a sleep composite measure based upon actigraphy measures was correlated with patient characteristics similar to that in other studies, it does not add more information beyond individual sleep metrics alone and future research might benefit from selecting individual sleep metrics based on theory rather than use a composite measure approach. While our approach may have limited utility in BD, it may be important for research to examine this in other clinical groups, including those with other serious mental illnesses. As sleep becomes more frequently measured by actigraphy, efforts to improve the use and applicability of these unique data will be important for understanding the dynamics of sleep in those with BD.With the introduction of combination antiretroviral therapy mortality among HIV-infected patients diminished significantly. However, some patient subgroups have different survival patterns, and have shown less decline in death rates.These include patients with psychiatric or substance use disorders, which are highly prevalent among patients treated for HIV/AIDS.There is also a high cooccurrence between psychiatric and substance use disorders among the HIV-infected,as in other populations; and severity is greater in each type of disorder when there is cooccurrence.Together they place individuals at elevated risk for poor health outcomes. Because psychiatric and substance use disorders frequently co-occur, it is important to examine the combined impact of these disorders among people with HIV infection. Research among HIV-infected patients has shown an association between depression symptoms, HIV disease progression and mortality; and mental illness and substance abuse are barriers to optimal adherence to combination antiretroviral regimens.

One study of U.S. veterans found that survival was associated with greater number of mental health visits.Yet few studies have examined survival patterns for HIV-infected individuals who use alcohol or illicit drugs, but are generally not injection drug users, and have been diagnosed with psychiatric or SU disorders from a private health plan; nor have studies examined both psychiatric and SU disorders in relation to mortality. Previous research has shown that access to psychiatric and SU disorder care among HIV-infected patients varies based on sociodemographic factors and HIV illness severity.The current study compares mortality in HIV-infected patients diagnosed with psychiatric disorders and/or SU disorders to patients without either diagnosis receiving medical care from a private, fully integrated health plan where access to care andability to pay for care are not significant factors. We also examine the effects of accessing psychiatric or SU treatment services. Improvement in depression has been associated with better adherence to combination antiretroviral therapy and increased CD4 cell counts.Therefore, we hypothesize that accessing services is associated with decreased mortality among patients with HIV infection.We conducted a retrospective observational cohort study for years 1996 to 2007 among HIV-infected patients who were members of the Kaiser Permanente Northern California health plan. The KPNC is an integrated health care system with a membership of 3.5 million individuals, representing 34% of the insured population in Northern California. The membership is representative of the northern California population with respect to race/ethnicity, gender, and socioeconomic status, except for some under representation of both extremes of the economic spectrum.HIV infected patients are seen at medical centers throughout the KPNC 17-county catchment region. The study population consisted of 11,132 HIV-infected patients who received health care at KPNC at some time between January 1, 1996 and December 31, 2006. The study sample included all HIV-infected patients who were 14 years of age or older on or after January 1, 1996 and had at least 6 months membership during the first year of study observation .

This minimum age was chosen because the KPNC membership has very few HIV patients under age 14, children are likely to receive different psychiatric diagnoses than adolescents and adults , diagnosis of SU problems generally occurs later than age 13, and children are likely to receive services for these disorders in pediatrics departments rather than in the health plan’s specialty psychiatry and SU treatment programs. Patients could enter the study until December 31, 2006. In the data analyses, we also excluded 83 patients whose SU disorder diagnosis status was unclear . This resulted in a study analysis sample of 9751 patients.Since 1988, the KPNC Division of Research has maintained a surveillance system of patients who are HIV-1– seropositive,horticulture products ascertained through monitoring electronic inpatient, outpatient, laboratory testing, and pharmacy dispensing databases for sentinel indicators of probable HIV infection. HIV-1 seropositivity is then confirmed through review of patient medical records. Ascertainment of HIV infected patients by this registry has been shown to be at least 95% complete. The HIV registry contains information on patient demographics , HIV transmission risk group , dates of known HIV infection, and AIDS diagnoses. KPNC also maintains complete and historical electronic databases on hospital admission/discharge/transfer data, prescription dispensing, outpatient visits, and laboratory tests results, including CD4 T-cell counts and HIV-1 RNA levels. Mortality information including date and cause of death are obtained from hospitalization records, membership files, California death certificates, and Social Security Administration databases. Mortality data were complete through December 31, 2007. Antiretroviral medication prescription data were obtained from KPNC pharmacy databases. Approximately 97% of members fill their prescriptions at KPNC pharmacies, including patients whose prescriptions are obtained through the Ryan White AIDS Drug Assistance Program. ARV medication data included date of first fill, dosage, and days supply, as well as data on all refills. Patients were classified as: currently receiving combination-ARV , current dual NNRTI/NRTI ARV use, past ARV use, or never users .Psychiatric diagnoses were assigned by providers. One or more diagnoses can be coded by ICD-9 in the KPNC administrative databases.Psychiatric diagnoses selected for this study were the most common and serious psychiatric disorders diagnosed among health plan members including schizophrenic disorders , major depressive disorder, bipolar affective disorder, neurotic disorders , hysteria, phobic disorders, obsessive-compulsive disorder, anorexia nervosa, and bulimia. We examined the impact of having one or more of these psychiatric disorders in aggregate, as in prior HIV studies.31 Within the health plan, psychiatry can be accessed directly by patients. Mild cases of depression and anxiety may be addressed in primary care with medication but moderate to severe cases are referred to psychiatry. Treatment in psychiatry includes assessment, psychotherapy and medication management. Patients diagnosed with a psychiatric disorder generally return to psychiatry for individual and/or group psychotherapy and/or medication evaluations. Our measure of psychiatric treatment was whether or not a patient had visits to a psychiatric clinic after a psychiatric diagnosis,obtained from automated databases.A diagnosis of ICD-9 substance dependence or abuse can be made by the patient’s clinician in primary care, SU disorder treatment, or psychiatry as a primary or secondary diagnosis.Diagnostic categories include all alcoholic psychoses, drug psychoses, alcohol dependence syndrome, drug dependence , alcohol abuse, cannabis abuse, hallucinogen abuse, barbiturate abuse, sedative/tranquilizer abuse, opioid abuse, cocaine abuse, and amphetamine abuse; as well as multiple substance abuse and unspecified substance abuse. In our analyses we classified patients as having one or more diagnoses of substance abuse and/or dependence versus no diagnosis.KPNC provides comprehensive outpatient SU treatment available to all members of the health plan. Services include both day hospital and traditional outpatient programs,both of which include eight weeks of individual and group therapy, education, relapse prevention, family therapy, with aftercare visits once a week for ten months. In addition to these primary services, ambulatory detoxification and residential services are available, as needed. A small proportion of patients engage in residential SU treatment, conducted by contractual agreement with outside institutions. These data are available in the KPNC referrals and claims databases. As with psychiatric treatment, in the current study SU treatment initiation was measured as having one or more visits to an outpatient program or a stay in a residential SU treatment unit following diagnosis.Analyses focused on diagnoses of psychiatric disorders with and without co-occurring SU diagnoses as the primary predictors of interest. The distribution of demographic, clinical and behavioral characteristics was compared between patients with and without a major psychiatric diagnosis; statistical significance was assessed using the w2 test. The distribution of cause of death was examined by psychiatric diagnostic status ; statistical significance was assessed using the w2 test or Fisher’s exact test where table cells were sparsely populated. Cox proportional hazards regression was used to obtain point and interval estimates of mortality relative hazards associated with psychiatric diagnosis/treatment status and SU problems diagnosis/treatment status, with each of these two time dependent covariates measured at three levels: no diagnosis, diagnosis with treatment, diagnosis without treatment. With the goal of examining the joint effects of these two covariates on mortality, results are expressed as hazard ratios for combinations of psychiatric diagnosis/treatment and SU diagnosis/treatment levels, with no diagnosis of either comorbidity as the referent. These estimates were adjusted for an a priori chosen set of available covariates, including age at entry into study, race/ethnicity, gender, HIV transmission risk group, CD4 T-cell counts and HIV RNA levels and ARV treatment modeled as time-dependent covariates, year of known HIV infection, AIDS diagnosis prior to entry into study, and evidence of hepatitis C viral infection. Initial modeling results demonstrated a significant interaction between psychiatric and SU diagnosis/treatment status in Cox regression models . Therefore, relative hazard estimates of interest were obtained via appropriate linear combinations of parameter estimates from a fully saturated model .