Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.

This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.

32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.

Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

To review existing publications using Household Consumption and Expenditure Survey (HCES) data to estimate household dietary nutrient supply to (1) describe scope of available literature, (2) identify the metrics reported and parameters used to construct these metrics, (3) summarise comparisons between estimates derived from HCES and individual dietary assessment data and (4) explore the demographic and socio-economic sub-groups used to characterise risks of nutrient inadequacy.

This study is a systematic review of publications identified from online databases published between 2000 to 2019 that used HCES food consumption data to estimate household dietary nutrient supply. Further publications were identified by ‘snowballing’ the references of included database-identified publications.

Publications using data from low- and lower-middle income countries.

In total, fifty-eight publications were included. Three metrics were reported that characterised household dietary nutrient supply: apparent nutrient intake per adult-male equivalent per day (n 35), apparent nutrient intake per capita per day (n 24) and nutrient density (n 5). Nutrient intakes were generally overestimated using HCES food consumption data, with several studies finding sizeable discrepancies compared with intake estimates based on individual dietary assessment methods. Sub-group analyses predominantly focused on measuring variation in household dietary nutrient supply according to socio-economic position and geography.

HCES data are increasingly being used to assess diets across populations. More research is needed to inform the development of a framework to guide the use of and qualified interpretation of dietary assessments based on these data.

Obesity increases the risk of post-operative arrhythmias in adults undergoing cardiac surgery, but little is known regarding the impact of obesity on post-operative arrhythmias after CHD surgery.

Patients undergoing CHD surgery from 2007 to 2019 were prospectively enrolled in the parent study. Telemetry was assessed daily, with documentation of all arrhythmias. Patients aged 2–20 years were categorised by body mass index percentile for age and sex (underweight <5, normal 5–85, overweight 85–95, and obese >95). Patients aged >20 years were categorised using absolute body mass index. We investigated the impact of body mass index category on arrhythmias using univariate and multivariate analysis.

There were 1250 operative cases: 12% underweight, 65% normal weight, 12% overweight, and 11% obese. Post-operative arrhythmias were observed in 38%. Body mass index was significantly higher in those with arrhythmias (18.8 versus 17.8, p = 0.003). There was a linear relationship between body mass index category and incidence of arrhythmias: underweight 33%, normal 38%, overweight 42%, and obese 45% (p = 0.017 for trend). In multivariate analysis, body mass index category was independently associated with post-operative arrhythmias (p = 0.021), with odds ratio 1.64 in obese patients as compared to normal-weight patients (p = 0.036). In addition, aortic cross-clamp time (OR 1.007, p = 0.002) and maximal vasoactive–inotropic score in the first 48 hours (OR 1.03, p = 0.04) were associated with post-operative arrhythmias.

Body mass index is independently associated with incidence of post-operative arrhythmias in children after CHD surgery.

This report examines between- and within-person associations between youth irritability and concurrent and prospective internalizing and externalizing symptoms from early childhood through adolescence. Distinguishing between- and within-person longitudinal associations may yield distinct, clinically relevant information about pathways to multifinality from childhood irritability.

Children’s irritability and co-occurring symptoms were assessed across five waves between ages 3 and 15 years using the mother-reported Child Behavior Checklist (N = 605, 46% female). Parental history of depressive disorders was assessed with a clinical interview.

Results demonstrated that between- and within-person irritability were uniquely associated with concurrent depressive, anxiety, and defiance symptoms, but not ADHD. Prior wave within-person irritability also predicted next wave depressive, anxiety, and defiance symptoms, controlling for prior symptoms; these prospective associations were bidirectional. Child sex and parental depressive disorders moderated associations.

Findings identify pathways from within- and between-person irritability to later internalizing and externalizing psychopathology. Results demonstrate the importance of parsing within- and between-person effects to understand nuanced relations among symptoms over childhood.

Neuropsychopharmacologic effects of long-term opioid therapy (LTOT) in the context of chronic pain may result in subjective anhedonia coupled with decreased attention to natural rewards. Yet, there are no known efficacious treatments for anhedonia and reward deficits associated with chronic opioid use. Mindfulness-Oriented Recovery Enhancement (MORE), a novel behavioral intervention combining training in mindfulness with savoring of natural rewards, may hold promise for treating anhedonia in LTOT.

Veterans receiving LTOT (N = 63) for chronic pain were randomized to 8 weeks of MORE or a supportive group (SG) psychotherapy control. Before and after the 8-week treatment groups, we assessed the effects of MORE on the late positive potential (LPP) of the electroencephalogram and skin conductance level (SCL) during viewing and up-regulating responses (i.e. savoring) to natural reward cues. We then examined whether these neurophysiological effects were associated with reductions in subjective anhedonia by 4-month follow-up.

Patients treated with MORE demonstrated significantly increased LPP and SCL to natural reward cues and greater decreases in subjective anhedonia relative to those in the SG. The effect of MORE on reducing anhedonia was statistically mediated by increases in LPP response during savoring.

MORE enhances motivated attention to natural reward cues among chronic pain patients on LTOT, as evidenced by increased electrocortical and sympathetic nervous system responses. Given neurophysiological evidence of clinical target engagement, MORE may be an efficacious treatment for anhedonia among chronic opioid users, people with chronic pain, and those at risk for opioid use disorder.

Retrospective self-report is typically used for diagnosing previous pediatric traumatic brain injury (TBI). A new semi-structured interview instrument (New Mexico Assessment of Pediatric TBI; NewMAP TBI) investigated test–retest reliability for TBI characteristics in both the TBI that qualified for study inclusion and for lifetime history of TBI.

One-hundred and eight-four mTBI (aged 8–18), 156 matched healthy controls (HC), and their parents completed the NewMAP TBI within 11 days (subacute; SA) and 4 months (early chronic; EC) of injury, with a subset returning at 1 year (late chronic; LC).

The test–retest reliability of common TBI characteristics [loss of consciousness (LOC), post-traumatic amnesia (PTA), retrograde amnesia, confusion/disorientation] and post-concussion symptoms (PCS) were examined across study visits. Aside from PTA, binary reporting (present/absent) for all TBI characteristics exhibited acceptable (≥0.60) test–retest reliability for both Qualifying and Remote TBIs across all three visits. In contrast, reliability for continuous data (exact duration) was generally unacceptable, with LOC and PCS meeting acceptable criteria at only half of the assessments. Transforming continuous self-report ratings into discrete categories based on injury severity resulted in acceptable reliability. Reliability was not strongly affected by the parent completing the NewMAP TBI.

Categorical reporting of TBI characteristics in children and adolescents can aid clinicians in retrospectively obtaining reliable estimates of TBI severity up to a year post-injury. However, test–retest reliability is strongly impacted by the initial data distribution, selected statistical methods, and potentially by patient difficulty in distinguishing among conceptually similar medical concepts (i.e., PTA vs. confusion).

Nightmares are a hallmark symptom of posttraumatic stress disorder (PTSD). This strong association may reflect a shared pathophysiology in the form of altered autonomic activity and increased reactivity. Using an acoustic startle paradigm, we investigated the interrelationships of psychophysiological measures during wakefulness and PTSD diagnosis, posttraumatic nightmares, and nontraumatic nightmares.

A community sample of 122 trauma survivors were presented with a series of brief loud tones, while heart rate (HRR), skin conductance (SCR), and orbicularis oculi electromyogram (EMGR) responses were measured. Prior to the tone presentations, resting heart rate variability (HRV) was assessed. Nightmares were measured using nightmare logs. Three dichotomous groupings of participants were compared: (1) current PTSD diagnosis (n = 59), no PTSD diagnosis (n = 63), (2) those with (n = 26) or without (n = 96) frequent posttraumatic nightmares, and (3) those with (n = 22) or without (n = 100) frequent nontraumatic nightmares.

PTSD diagnosis was associated with posttraumatic but not with nontraumatic nightmares. Both PTSD and posttraumatic nightmares were associated with a larger mean HRR to loud tones, whereas nontraumatic nightmare frequency was associated with a larger SCR. EMGR and resting HRV were not associated with PTSD diagnosis or nightmares.

Our findings suggest a shared pathophysiology between PTSD and posttraumatic nightmares in the form of increased HR reactivity to startling tones, which might reflect reduced parasympathetic tone. This shared pathophysiology could explain why PTSD is more strongly related to posttraumatic than nontraumatic nightmares, which could have important clinical implications.

Depression and overweight are each associated with abnormal immune system activation. We sought to disentangle the extent to which depressive symptoms and overweight status contributed to increased inflammation and abnormal cortisol levels.

Participants were recruited through the Wellcome Trust NIMA Consortium. The sample of 216 participants consisted of 69 overweight patients with depression; 35 overweight controls; 55 normal-weight patients with depression and 57 normal-weight controls. Peripheral inflammation was measured as high-sensitivity C-Reactive Protein (hsCRP) in serum. Salivary cortisol was collected at multiple points throughout the day to measure cortisol awakening response and diurnal cortisol levels.

Overweight patients with depression had significantly higher hsCRP compared with overweight controls (p = 0.042), normal-weight depressed patients (p < 0.001) and normal-weight controls (p < 0.001), after controlling for age and gender. Multivariable logistic regression showed that comorbid depression and overweight significantly increased the risk of clinically elevated hsCRP levels ⩾3 mg/L (OR 2.44, 1.28–3.94). In a separate multivariable logistic regression model, overweight status contributed most to the risk of having hsCRP levels ⩾3 mg/L (OR 1.52, 0.7–2.41), while depression also contributed a significant risk (OR 1.09, 0.27–2). There were no significant differences between groups in cortisol awakening response and diurnal cortisol levels.

Comorbid depression and overweight status are associated with increased hsCRP, and the coexistence of these conditions amplified the risk of clinically elevated hsCRP levels. Overweight status contributed most to the risk of clinically elevated hsCRP levels, but depression also contributed to a significant risk. We observed no differences in cortisol levels between groups.

The rapid spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) throughout key regions of the United States in early 2020 placed a premium on timely, national surveillance of hospital patient censuses. To meet that need, the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN), the nation’s largest hospital surveillance system, launched a module for collecting hospital coronavirus disease 2019 (COVID-19) data. We present time-series estimates of the critical hospital capacity indicators from April 1 to July 14, 2020.

From March 27 to July 14, 2020, the NHSN collected daily data on hospital bed occupancy, number of hospitalized patients with COVID-19, and the availability and/or use of mechanical ventilators. Time series were constructed using multiple imputation and survey weighting to allow near–real-time daily national and state estimates to be computed.

During the pandemic’s April peak in the United States, among an estimated 431,000 total inpatients, 84,000 (19%) had COVID-19. Although the number of inpatients with COVID-19 decreased from April to July, the proportion of occupied inpatient beds increased steadily. COVID-19 hospitalizations increased from mid-June in the South and Southwest regions after stay-at-home restrictions were eased. The proportion of inpatients with COVID-19 on ventilators decreased from April to July.

The NHSN hospital capacity estimates served as important, near–real-time indicators of the pandemic’s magnitude, spread, and impact, providing quantitative guidance for the public health response. Use of the estimates detected the rise of hospitalizations in specific geographic regions in June after they declined from a peak in April. Patient outcomes appeared to improve from early April to mid-July.