Preclinical evidence suggests that diazepam enhances hippocampal γ-aminobutyric acid (GABA) signalling and normalises a psychosis-relevant cortico-limbic-striatal circuit. Hippocampal network dysconnectivity, particularly from the CA1 subfield, is evident in people at clinical high-risk for psychosis (CHR-P), representing a potential treatment target. This study aimed to forward-translate this preclinical evidence.

In this randomised, double-blind, placebo-controlled study, 18 CHR-P individuals underwent resting-state functional magnetic resonance imaging twice, once following a 5 mg dose of diazepam and once following a placebo. They were compared to 20 healthy controls (HC) who did not receive diazepam/placebo. Functional connectivity (FC) between the hippocampal CA1 subfield and the nucleus accumbens (NAc), amygdala, and ventromedial prefrontal cortex (vmPFC) was calculated. Mixed-effects models investigated the effect of group (CHR-P placebo/diazepam vs. HC) and condition (CHR-P diazepam vs. placebo) on CA1-to-region FC.

In the placebo condition, CHR-P individuals showed significantly lower CA1-vmPFC (Z = 3.17, PFWE = 0.002) and CA1-NAc (Z = 2.94, PFWE = 0.005) FC compared to HC. In the diazepam condition, CA1-vmPFC FC was significantly increased (Z = 4.13, PFWE = 0.008) compared to placebo in CHR-P individuals, and both CA1-vmPFC and CA1-NAc FC were normalised to HC levels. In contrast, compared to HC, CA1-amygdala FC was significantly lower contralaterally and higher ipsilaterally in CHR-P individuals in both the placebo and diazepam conditions (lower: placebo Z = 3.46, PFWE = 0.002, diazepam Z = 3.33, PFWE = 0.003; higher: placebo Z = 4.48, PFWE < 0.001, diazepam Z = 4.22, PFWE < 0.001).

This study demonstrates that diazepam can partially restore hippocampal CA1 dysconnectivity in CHR-P individuals, suggesting that modulation of GABAergic function might be useful in the treatment of this clinical group.

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.

Guideline-based tobacco treatment is infrequently offered. Electronic health record-enabled patient-generated health data (PGHD) has the potential to increase patient treatment engagement and satisfaction.

We evaluated outcomes of a strategy to enable PGHD in a medical oncology clinic from July 1, 2021 to December 31, 2022. Among 12,777 patients, 82.1% received a tobacco screener about use and interest in treatment as part of eCheck-in via the patient portal.

We attained a broad reach (82.1%) and moderate response rate (30.9%) for this low-burden PGHD strategy. Patients reporting current smoking (n = 240) expressed interest in smoking cessation medication (47.9%) and counseling (35.8%). As a result of patient requests via PGHD, most tobacco treatment requests by patients were addressed by their providers (40.6–80.3%). Among patients with active smoking, those who received/answered the screener (n = 309 ) were more likely to receive tobacco treatment compared with usual care patients who did not have the patient portal (n = 323) (OR = 2.72, 95% CI = 1.93–3.82, P < 0.0001) using propensity scores to adjust for the effect of age, sex, race, insurance, and comorbidity. Patients who received yet ignored the screener (n = 1024) compared with usual care were also more likely to receive tobacco treatment, but to a lesser extent (OR = 2.20, 95% CI = 1.68–2.86, P < 0.0001). We mapped observed and potential benefits to the Translational Science Benefits Model (TSBM).

PGHD via patient portal appears to be a feasible, acceptable, scalable, and cost-effective approach to promote patient-centered care and tobacco treatment in cancer patients. Importantly, the PGHD approach serves as a real world example of cancer prevention leveraging the TSBM.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Carbapenem-resistant Enterobacterales (CRE) are an urgent threat to healthcare, but the epidemiology of these antimicrobial-resistant organisms may be evolving in some settings since the COVID-19 pandemic. An updated analysis of hospital-acquired CRE (HA-CRE) incidence in community hospitals is needed.

We retrospectively analyzed data on HA-CRE cases and antimicrobial utilization (AU) from two community hospital networks, the Duke Infection Control Outreach Network (DICON) and the Duke Antimicrobial Stewardship Outreach Network (DASON) from January 2013 to June 2023. The zero-inflated negative binomial regression model was used owing to excess zeros.

126 HA-CRE cases from 36 hospitals were included in the longitudinal analysis. The pooled incidence of HA CRE was 0.69 per 100,000 patient days (95% confidence interval [95% CI], 0.57–0.82 HA-CRE rate significantly decreased over time before COVID-19 (rate ratio [RR], 0.94 [95% CI, 0.89–0.99]; p = 0.02), but there was a significant slope change indicating a trend increase in HA-CRE after COVID-19 (RR, 1.32 [95% CI, 1.06–1.66]; p = 0.01). In 21 hospitals participating in both DICON and DASON from January 2018 to June 2023, there was a correlation between HA-CRE rates and AU for CRE treatment (Spearman’s coefficient = 0.176; p < 0.01). Anti-CRE AU did not change over time, and there was no level or slope change after COVID.

The incidence of HA-CRE decreased before COVID-19 in a network of community hospitals in the southeastern United States, but this trend was disrupted by the COVID-19 pandemic.

Assessment of performance validity during neuropsychology evaluation is essential to reliably interpret cognitive test scores. Studies (Webber et al., 2018; Wisdom, et al., 2012) have validated the use of abbreviated measures, such as Trial 1 (T1) of the Test of Memory Malingering (TOMM), to detect invalid performance. Only one study (Bauer et al., 2007) known to these authors has examined the utility of Green’s Word Memory Test (WMT) immediate recall (IR) as a screening tool for invalid performance. This study explores WMT IR as an independent indicator of performance validity in a mild TBI (mTBI) veteran population.

Participants included 211 (Mage = 32.1, SD = 7.4; Medu = 13.1, SD = 1.64; 94.8% male; 67.8% White) OEF/OIF/OND veterans with a history of mTBI who participated in a comprehensive neuropsychological evaluation at one of five participating VA Medical Centers. Performance validity was assessed using validated cut scores from the following measures: WMT IR and delayed recall (DR); TOMM T1; WAIS-IV reliable digit span; CVLT-II forced choice raw score; Wisconsin Card Sorting Test failure to maintain set; and the Rey Memory for Fifteen Items test, combo score. Sensitivity and specificity were calculated for each IR score compared with failure on DR. In addition, sensitivity and specificity were calculated for each WMT IR score compared to failure of at least one additional performance validity measure (excluding DR), two or more measures, and three or more measures, respectively.

Results indicated that 46.8% participants failed to meet cut offs for adequate performance validity based on the standard WMT IR cut score (i.e., 82.5%; M = 81.8%, SD = 17.7%); however, 50.2% participants failed to meet criteria based on the standard WMT DR cut score (M = 79.8% SD = 18.6%). A cut score of 82.5% or below on WMT IR correctly identified 82.4% (i.e., sensitivity) of subjects who performed below cut score on DR, with a specificity of 94.2%. Examination of IR cutoffs compared to failure of one or more other PVTs revealed that the standardized cut score of 82.5% or below had a sensitivity of 78.2% and a specificity of 72.4%; whereas, a cut score of 65% or below had a sensitivity of 41% and a specificity of 91.3%. Similarly, examination of IR cutoffs compared to failure of two or more additional PVTs revealed that the cut score of 60% or below had a sensitivity of 45.7% and specificity of 93.1% ; whereas, a cut score of 57.5% or below had a sensitivity of 57.9% and specificity of 90.9% when using failure of three or more PVTs as the criterion.

Results indicated that a cut score of 82.5% or below on WMT IR may be sufficient to detect invalid performance when considering WMT DR as criterion. Furthermore, WMT IR alone, with adjustments to cut scores, appears to be a reasonable way to assess symptom validity compared to other PVTs. Sensitivity and specificity of WMT IR scores may have been adversely impacted by lower sensitivity of other PVTs to independently identify invalid performance.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Population studies have shown that Black individuals are at higher risk for MCI and dementia than White individuals but are more likely to be underdiagnosed or misdiagnosed. Although multiple contributory factors have been identified in relation to neurocognitive diagnostic disparities among persons of color, few studies have investigated race-associated differences in MCI and dementia classification across diagnostic methods. The current study examined the agreement of cognitive classification made via semi-structured interview and neuropsychological assessment.

Only participants assigned normal cognitive status or cognitive impairment with presumed Alzheimer’s etiology were included in the study. Baseline visit data in the National Alzheimer’s Coordinating Center (NACC) dataset was collected to compare correspondence of cognitive classification (normal cognition, MCI, dementia) via semi-structured interview (Clinical Dementia Rating; CDR) with formal NACC diagnostic determination. NACC diagnostic determination was further separated by single clinician and consensus diagnostic methods. Inter-rater agreement was evaluated using chi-squared tests, and respective analyses were stratified for race (Black vs White), ethnicity (Hispanic vs Non-Hispanic), and education (<12 years vs. >12 years).

The sample size included 4,739 Black and 26,393 White participants across 43 Alzheimer’s Disease Research Centers (ADRCs). Inter-rater analyses between CDR (semi-structured interview) versus single-clinician and formal consensus NACC diagnostic methods showed strong (all (pc>.70) consistency in cognitive diagnoses overall, irrespective of race, ethnicity, and education. The percentage of agreement between diagnostic methods was nearly 100% for those categorized as cognitively normal or with dementia. However, the agreement for MCI was considerably lower (ranging from 28-74%) and revealed a disparity in diagnostic method between Black and White individuals. White individuals diagnosed with MCI via CDR (CDR total =0.5) were more likely to be labeled as having dementia regardless of NACC diagnostic method. However, Black individuals diagnosed with MCI via CDR were equally likely to be diagnosed as cognitively normal or with dementia via the formal consensus method.

Irrespective of race and other demographic variables, diagnostic methods had high agreement for groups labeled with normal cognition and dementia. Agreement was consistently lower for the group labeled with MCI, with Black individuals having greater variability in diagnostic differentials when diagnosed via formal consensus method. The results of the study suggest that neuropsychological assessment continues to be an integral component of diagnosing individuals with MCI, reducing possible sources of bias.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

To estimate the incidence, duration and risk factors for diagnostic delays associated with pertussis.

We used longitudinal retrospective insurance claims from the Marketscan Commercial Claims and Encounters, Medicare Supplemental (2001–2020), and Multi-State Medicaid (2014–2018) databases.

Inpatient, emergency department, and outpatient visits.

The study included patients diagnosed with pertussis (International Classification of Diseases [ICD] codes) and receipt of macrolide antibiotic treatment.

We estimated the number of visits with pertussis-related symptoms before diagnosis beyond that expected in the absence of diagnostic delays. Using a bootstrapping approach, we estimated the number of visits representing a delay, the number of missed diagnostic opportunities per patient, and the duration of delays. Results were stratified by age groups. We also used a logistic regression model to evaluate potential factors associated with delay.

We identified 20,828 patients meeting inclusion criteria. On average, patients had almost 2 missed opportunities prior to diagnosis, and delay duration was 12 days. Across age groups, the percentage of patients experiencing a delay ranged from 29.7% to 37.6%. The duration of delays increased considerably with age from an average of 5.6 days for patients aged <2 years to 13.8 days for patients aged ≥18 years. Factors associated with increased risk of delays included emergency department visits, telehealth visits, and recent prescriptions for antibiotics not effective against pertussis.

Diagnostic delays for pertussis are frequent. More work is needed to decrease diagnostic delays, especially among adults. Earlier case identification may play an important role in the response to outbreaks by facilitating treatment, isolation, and improved contact tracing.