Cardiovascular disease (CVD) is excessively prevalent and premature in bipolar disorder (BD), even after controlling for traditional cardiovascular risk factors. The increased risk of CVD in BD may be subserved by microvascular dysfunction. We examined coronary microvascular function in relation to youth BD.

Participants were 86 youth, ages 13–20 years (n = 39 BD, n = 47 controls). Coronary microvascular reactivity (CMVR) was assessed using quantitative T2 magnetic resonance imaging during a validated breathing-paradigm. Quantitative T2 maps were acquired at baseline, following 60-s of hyperventilation, and every 10-s thereafter during a 40-s breath-hold. Left ventricular structure and function were evaluated based on 12–15 short- and long-axis cardiac-gated cine images. A linear mixed-effects model that controlled for age, sex, and body mass index assessed for between-group differences in CMVR (time-by-group interaction).

The breathing-paradigm induced a significant time-related increase in T2 relaxation time for all participants (i.e. CMVR; β = 0.36, p < 0.001). CMVR was significantly lower in BD v. controls (β = −0.11, p = 0.002). Post-hoc analyses found lower T2 relaxation time in BD youth after 20-, 30-, and 40 s of breath-holding (d = 0.48, d = 0.72, d = 0.91, respectively; all pFDR < 0.01). Gross left ventricular structure and function (e.g. mass, ejection fraction) were within normal ranges and did not differ between groups.

Youth with BD showed evidence of subclinically impaired coronary microvascular function, despite normal gross cardiac structure and function. These results converge with prior findings in adults with major depressive disorder and post-traumatic stress disorder. Future studies integrating larger samples, prospective follow-up, and blood-based biomarkers are warranted.

Many clinical trials leverage real-world data. Typically, these data are manually abstracted from electronic health records (EHRs) and entered into electronic case report forms (CRFs), a time and labor-intensive process that is also error-prone and may miss information. Automated transfer of data from EHRs to eCRFs has the potential to reduce data abstraction and entry burden as well as improve data quality and safety.

We conducted a test of automated EHR-to-CRF data transfer for 40 participants in a clinical trial of hospitalized COVID-19 patients. We determined which coordinator-entered data could be automated from the EHR (coverage), and the frequency with which the values from the automated EHR feed and values entered by study personnel for the actual study matched exactly (concordance).

The automated EHR feed populated 10,081/11,952 (84%) coordinator-completed values. For fields where both the automation and study personnel provided data, the values matched exactly 89% of the time. Highest concordance was for daily lab results (94%), which also required the most personnel resources (30 minutes per participant). In a detailed analysis of 196 instances where personnel and automation entered values differed, both a study coordinator and a data analyst agreed that 152 (78%) instances were a result of data entry error.

An automated EHR feed has the potential to significantly decrease study personnel effort while improving the accuracy of CRF data.

There has been a notable increase in requests for psychiatric reports from District Courts for persons remanded to Ireland’s main remand prison, Cloverhill. We aimed to identify if reports were prepared for persons with severe mental illness and if they led to therapeutic benefits such as diversion to healthcare. Measures of equitability between Cloverhill and other District Courts were explored.

For District Court-requested reports completed by the Prison Inreach and Court Liaison Service (PICLS) at Cloverhill Prison from 2015 to 2017, we recorded clinical variables and therapeutic outcomes such as diversion to inpatient psychiatric settings.

Of 236 cases, over half were diverted to inpatient or outpatient psychiatric care. One-third of remand episodes were admitted to a psychiatric hospital, mainly in non-forensic settings. Nearly two-thirds had major mental illness, mainly schizophrenia and related conditions. Almost half had active psychosis. Cases in Cloverhill District Court and other District Courts were similarly likely to have active psychosis (47% overall) and hospital admission (33% overall). Voluntary reports were more likely to identify active psychosis, with over 90% diverted to inpatient or outpatient community treatment settings.

This is the first large scale study of diversion outcomes following requests for psychiatric advice from District Courts in Ireland. Requests were mainly appropriate. Over half led to diversion from the criminal justice system to healthcare settings. There is a need for a complementary network of diversion initiatives at every stage of the criminal justice system to effectively divert mentally ill individuals to appropriate settings at the earliest possible stage.