Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Evaluate the association between provider-ordered viral testing and antibiotic treatment practices among children discharged from an ED or hospitalized with an acute respiratory infection (ARI).

Active, prospective ARI surveillance study from November 2017 to February 2020.

Pediatric hospital and emergency department in Nashville, Tennessee.

Children 30 days to 17 years old seeking medical care for fever and/or respiratory symptoms.

Antibiotics prescribed during the child’s ED visit or administered during hospitalization were categorized into (1) None administered; (2) Narrow-spectrum; and (3) Broad-spectrum. Setting-specific models were built using unconditional polytomous logistic regression with robust sandwich estimators to estimate the adjusted odds ratios and 95% confidence intervals between provider-ordered viral testing (ie, tested versus not tested) and viral test result (ie, positive test versus not tested and negative test versus not tested) and three-level antibiotic administration.

4,107 children were enrolled and tested, of which 2,616 (64%) were seen in the ED and 1,491 (36%) were hospitalized. In the ED, children who received a provider-ordered viral test had 25% decreased odds (aOR: 0.75; 95% CI: 0.54, 0.98) of receiving a narrow-spectrum antibiotic during their visit than those without testing. In the inpatient setting, children with a negative provider-ordered viral test had 57% increased odds (aOR: 1.57; 95% CI: 1.01, 2.44) of being administered a broad-spectrum antibiotic compared to children without testing.

In our study, the impact of provider-ordered viral testing on antibiotic practices differed by setting. Additional studies evaluating the influence of viral testing on antibiotic stewardship and antibiotic prescribing practices are needed.

An accurate estimate of the average number of hand hygiene opportunities per patient hour (HHO rate) is required to implement group electronic hand hygiene monitoring systems (GEHHMSs). We sought to identify predictors of HHOs to validate and implement a GEHHMS across a network of critical care units.

Multicenter, observational study (10 hospitals) followed by quality improvement intervention involving 24 critical care units across 12 hospitals in Ontario, Canada.

Critical care patient beds were randomized to receive 1 hour of continuous direct observation to determine the HHO rate. A Poisson regression model determined unit-level predictors of HHOs. Estimates of average HHO rates across different types of critical care units were derived and used to implement and evaluate use of GEHHMS.

During 2,812 hours of observation, we identified 25,417 HHOs. There was significant variability in HHO rate across critical care units. Time of day, day of the week, unit acuity, patient acuity, patient population and use of transmission-based precautions were significantly associated with HHO rate. Using unit-specific estimates of average HHO rate, aggregate HH adherence was 30.0% (1,084,329 of 3,614,908) at baseline with GEHHMS and improved to 38.5% (740,660 of 1,921,656) within 2 months of continuous feedback to units (P < .0001).

Unit-specific estimates based on known predictors of HHO rate enabled broad implementation of GEHHMS. Further longitudinal quality improvement efforts using this system are required to assess the impact of GEHHMS on both HH adherence and clinical outcomes within critically ill patient populations.