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Compulsivity can be seen across various mental health conditions and refers to a tendency toward repetitive habitual acts that are persistent and functionally impairing. Compulsivity involves dysfunctional reward-related circuitry and is thought to be significantly heritable. Despite this, its measurement from a transdiagnostic perspective has received only scant research attention. Here we examine both the psychometric properties of a recently developed compulsivity scale, as well as its relationship with compulsive symptoms, familial risk, and reward-related attentional capture.
Two-hundred and sixty individuals participated in the study (mean age = 36.0 [SD = 10.8] years; 60.0% male) and completed the Cambridge-Chicago Compulsivity Trait Scale (CHI-T), along with measures of psychiatric symptoms and family history thereof. Participants also completed a task designed to measure reward-related attentional capture (n = 177).
CHI-T total scores had a normal distribution and acceptable Cronbach’s alpha (0.84). CHI-T total scores correlated significantly and positively (all p < 0.05, Bonferroni corrected) with Problematic Usage of the Internet, disordered gambling, obsessive-compulsive symptoms, alcohol misuse, and disordered eating. The scale was correlated significantly with history of addiction and obsessive-compulsive related disorders in first-degree relatives of participants and greater reward-related attentional capture.
These findings suggest that the CHI-T is suitable for use in online studies and constitutes a transdiagnostic marker for a range of compulsive symptoms, their familial loading, and related cognitive markers. Future work should more extensively investigate the scale in normative and clinical cohorts, and the role of value-modulated attentional capture across compulsive disorders.
Many patients with advanced serious illness or at the end of life experience delirium, a potentially reversible form of acute brain dysfunction, which may impair ability to participate in medical decision-making and to engage with their loved ones. Screening for delirium provides an opportunity to address modifiable causes. Unfortunately, delirium remains underrecognized. The main objective of this pilot was to validate the brief Confusion Assessment Method (bCAM), a two-minute delirium-screening tool, in a veteran palliative care sample.
This was a pilot prospective, observational study that included hospitalized patients evaluated by the palliative care service at a single Veterans’ Administration Medical Center. The bCAM was compared against the reference standard, the Diagnostic and Statistical Manual of Mental Disorders, fifth edition. Both assessments were blinded and conducted within 30 minutes of each other.
We enrolled 36 patients who were a median of 67 years (interquartile range 63–73). The primary reasons for admission to the hospital were sepsis or severe infection (33%), severe cardiac disease (including heart failure, cardiogenic shock, and myocardial infarction) (17%), or gastrointestinal/liver disease (17%). The bCAM performed well against the Diagnostic and Statistical Manual of Mental Disorders, fifth edition, for detecting delirium, with a sensitivity (95% confidence interval) of 0.80 (0.4, 0.96) and specificity of 0.87 (0.67, 0.96).
Significance of Results
Delirium was present in 27% of patients enrolled and never recognized by the palliative care service in routine clinical care. The bCAM provided good sensitivity and specificity in a pilot of palliative care patients, providing a method for nonpsychiatrically trained personnel to detect delirium.
OBJECTIVES/SPECIFIC AIMS: Opioid prescribing is common and increasing in certain areas of the country with known risk of misuse and dependence. Our study examined the association of opioid prescription at discharge after hospitalization for acute coronary syndrome (ACS) or acute decompensated heart failure (ADHF) with emergency department (ED) care or all-cause readmission, intended healthcare utilization (follow-up with physician within 30 d of discharge and cardiac rehab participation), and all-cause mortality. METHODS/STUDY POPULATION: The Vanderbilt Inpatient Cohort Study is a prospective cohort of hospitalized patients age >18 enrolled with either ACS or ADHF between 2011 and 2015 (index hospitalization). We then excluded those who died during the index hospitalization, patients with hospitalization <24 hours, patients discharged to hospice care, or those who underwent coronary artery bypass surgery because of the high probability of receiving opioids. In addition, we limited the analyses to patients whom we had complete covariate data. The primary predictor variable was an opioid prescription at the time of hospital discharge. We collected healthcare utilization behavior for 90 days after discharge, and mortality data until March 8, 2017. Time-to-event analysis using Cox proportional hazard models was performed for both unintended healthcare utilization behavior and mortality outcomes. Logistic regression was performed for intended healthcare utilization (adherence to follow-up appointments and cardiac rehabilitation). All models were adjusted for demographic data, opioid use prior to index hospitalization, severity of illness, and healthcare utilization prior to the index hospitalization. RESULTS/ANTICIPATED RESULTS: There were 501 patients discharged with an opioid prescription and 1994 with no opioid prescription at discharge. Among patients with opioids at discharge 235 (47%) experienced unplanned healthcare events (71 ED visits and 164 readmissions) and among nonopioids patients 775 (39%) experienced unplanned healthcare events (254 ED visits and 521 readmissions) (aHR: 1.06, 95% CI: 0.87, 1.28). Patient mortality in the opioid group was 131 Versus 432 in the nonopioid group (aHR: 1.08, 95% CI 0.84, 1.39). Patients in the opioid at discharge group were less likely to attend follow up visits or participate in cardiac rehab (OR: 0.69, 95% CI 0.52, 0.91, p=0.009) compared with those not discharged on opioid medications. Sensitivity analysis of patients who were prescribed prehospital opioids (including prehospital opioids in the exposure group with postdischarge opioids) did not reveal a statistically significant increase in mortality (aHR: 1.09, 95% CI 0.91, 1.31) or unintended healthcare utilization (aHR: 1.12, 95% CI 0.89, 1.41) among opioid users. DISCUSSION/SIGNIFICANCE OF IMPACT: Morbidity and mortality related to opioid use is a public health concern. Our study demonstrates a statistically significant reduction in physician follow-up and participation in cardiac rehab among opioid users, both of which are known to decrease patient mortality. We did not find a statistically significant increase in unplanned healthcare utilization or mortality. Sensitivity analysis combining prehospital and posthospital opioid prescriptions did not reveal a statistically significant association between opioid use, hospital readmissions, or mortality. The hospital provides unique patient interactions where providers can make significant medical changes based on their patient’s clinical status. Continuing to understand the association between opioid use, healthcare utilization, morbidity, and mortality in recently hospitalized cardiac patients will provide data to support reduction in total opioid dose to improve clinical outcomes.
A symptom of mild cognitive impairment (MCI) and Alzheimer’s disease
(AD) is a flat learning profile. Learning slope calculation methods vary, and
the optimal method for capturing neuroanatomical changes associated with MCI and
early AD pathology is unclear. This study cross-sectionally compared four
different learning slope measures from the Rey Auditory Verbal Learning Test
(simple slope, regression-based slope, two-slope method, peak slope) to
structural neuroimaging markers of early AD neurodegeneration (hippocampal
volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral
prefrontal cortex) across the cognitive aging spectrum [normal
control (NC); (n=198;
age=76±5), MCI (n=370;
age=75±7), and AD (n=171;
age=76±7)] in ADNI. Within diagnostic group,
general linear models related slope methods individually to neuroimaging
variables, adjusting for age, sex, education, and APOE4 status. Among MCI,
better learning performance on simple slope, regression-based slope, and late
slope (Trial 2–5) from the two-slope method related to larger
parahippocampal thickness (all p-values<.01) and
hippocampal volume (p<.01). Better regression-based
slope (p<.01) and late slope
(p<.01) were related to larger ventrolateral
prefrontal cortex in MCI. No significant associations emerged between any slope
and neuroimaging variables for NC (p-values ≥.05) or
AD (p-values ≥.02). Better learning performances
related to larger medial temporal lobe (i.e., hippocampal volume,
parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI
only. Regression-based and late slope were most highly correlated with
neuroimaging markers and explained more variance above and beyond other common
memory indices, such as total learning. Simple slope may offer an acceptable
alternative given its ease of calculation. (JINS, 2015,