Life Engagement Improvement Following Initiation of Brexpiprazole Treatment in Patients with MDD: A Naturalistic, Retrospective Real-World Study.

Purpose: Life engagement encompasses concepts such as life fulfillment, well-being, and participation in meaningful activities, encompassing cognitive, physical, social, and emotional dimensions. Patients with MDD experience impaired functioning across multiple domains of life engagement and have ranked concepts related to life engagement and fulfillment as important predictors of treatment success. Post-hoc analyses of three clinical trials of patients with MDD treated adjunctively with brexpiprazole have reported a significantly greater improvement in life engagement. This study investigated improvements in life engagement among patients with MDD following initiation of brexpiprazole treatment using a real-world dataset. Patients and Methods: Information was extracted from semi-structured clinical notes of the Mental Status Examination (MSE) of patients in a real-world setting to develop an outcome measure for quantifying life engagement of psychiatric patients. Measures of life engagement and its four sub-domains (emotional, physical, social, and cognitive) were calculated at each clinical visit for 624 adult patients with MDD during the 6 months following brexpiprazole initiation. Paired t-tests assessed differences between the index event and time periods within 6 months of the index event. Kaplan-Meier survival analyses were used to quantify the improvement in life engagement scores following brexpiprazole initiation. Results: The study identified 54 clinical features associated with life engagement. Statistically significant improvements were observed from as early as 1 month following brexpiprazole initiation, with 20.6%, 37.9%, and 53.9% of the patients demonstrating improved life engagement scores within 1, 3, and 6 months, respectively. The improvements were particularly apparent for the emotional and social sub-domains. Conclusion: The results of this study provide evidence of improved life engagement following brexpiprazole initiation in a real-world dataset.

Early trajectory of clinical global impression as a transdiagnostic predictor of psychiatric hospitalisation: a retrospective cohort study.

BACKGROUND: Identifying patients most at risk of psychiatric hospitalisation is crucial to improving service provision and patient outcomes. Existing predictors focus on specific clinical scenarios and are not validated with real-world data, limiting their translational potential. This study aimed to determine whether early trajectories of Clinical Global Impression Severity are predictors of 6 month risk of hospitalisation. METHODS: This retrospective cohort study used data from the NeuroBlu database, an electronic health records network from 25 US mental health-care providers. Patients with an ICD-9 or ICD-10 code of major depressive disorder, bipolar disorder, generalised anxiety disorder, post-traumatic stress disorder, schizophrenia or schizoaffective disorder, ADHD, or personality disorder were included. Using this cohort, we assessed whether clinical severity and instability (operationalised using Clinical Global Impression Severity measurements) during a 2-month period were predictors of psychiatric hospitalisation within the next 6 months. FINDINGS: 36 914 patients were included (mean age 29·7 years [SD 17·5]; 21 156 [57·3%] female, 15 748 [42·7%] male; 20 559 [55·7%] White, 4842 [13·1%] Black or African American, 286 [0·8%] Native Hawaiian or other Pacific Islander, 300 [0·8%] Asian, 139 [0·4%] American Indian or Alaska Native, 524 (1·4%) other or mixed race, and 10 264 [27·8%] of unknown race). Clinical severity and instability were independent predictors of risk of hospitalisation (adjusted hazard ratio [HR] 1·09, 95% CI 1·07-1·10 for every SD increase in instability; 1·11, 1·09-1·12 for every SD increase in severity; p<0·0001 for both). These associations were consistent across all diagnoses, age groups, and in both males and females, as well as in several robustness analyses, including when clinical severity and clinical instability were based on the Patient Health Questionnaire-9 rather than Clinical Global Impression Severity measurements. Patients in the top half of the cohort for both clinical severity and instability were at an increased risk of hospitalisation compared with those in the bottom half along both dimensions (HR 1·45, 95% CI 1·39-1·52; p<0·0001). INTERPRETATION: Clinical instability and severity are independent predictors of future risk of hospitalisation, across diagnoses, age groups, and in both males and females. These findings could help clinicians make prognoses and screen patients who are most likely to benefit from intensive interventions, as well as help health-care providers plan service provisions by adding additional detail to risk prediction tools that incorporate other risk factors. FUNDING: National Institute for Health and Care Research, National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Medical Research Council, Academy of Medical Sciences, and Holmusk.

Building a Longitudinal National Integrated Cardiovascular Database　- Lessons Learnt From SingCLOUD.

Background: Real world data on clinical outcomes and quality of care for patients with coronary artery disease (CAD) are fragmented. We describe the rationale and design of the Singapore Cardiovascular Longitudinal Outcomes Database (SingCLOUD). Methods and Results: We designed a health data grid to integrate clinical, administrative, laboratory, procedural, prescription and financial data from all public-funded hospitals and primary care clinics, which provide 80% of health care in Singapore. Here, we explain our approach to harmonize real-world data from diverse electronic medical and non-medical platforms to develop a robust and longitudinal dataset. We present pilot data on patients with myocardial infarction (MI) treated with percutaneous coronary intervention (PCI) between 2012 and 2014. The initial data set had 53,395 patients. Of these, 35,203 had CAD confirmed on coronary angiography, of whom 21,521 had PCI. Eventually, limiting to 2012-2014, 3,819 patients had MI with PCI, while 5,989 had MI. Compared with the quality improvement registry, Singapore Cardiac Data Bank, which had 189 fields for analysis, the SingCLOUD platform generated an additional 313 additional data fields, and was able to identify an additional 250 heart failure events, 664 major adverse cardiovascular events at 2 years, and low-density lipoprotein levels to 1 year for 3,747 patients. Conclusions: By integrating multiple incongruent data sources, SINGCLOUD enables in-depth analysis of real-world cardiovascular "big data".