To describe the real-world clinical impact of a commercially available plasma cell-free DNA metagenomic next-generation sequencing assay, the Karius test (KT).

We retrospectively evaluated the clinical impact of KT by clinical panel adjudication. Descriptive statistics were used to study associations of diagnostic indications, host characteristics, and KT-generated microbiologic patterns with the clinical impact of KT. Multivariable logistic regression modeling was used to further characterize predictors of higher positive clinical impact.

We evaluated 1000 unique clinical cases of KT from 941 patients between January 1, 2017–August 31, 2023. The cohort included adult (70%) and pediatric (30%) patients. The overall clinical impact of KT was positive in 16%, negative in 2%, and no clinical impact in 82% of the cases. Among adult patients, multivariable logistic regression modeling showed that culture-negative endocarditis (OR 2.3; 95% CI, 1.11–4.53; P .022) and concern for fastidious/zoonotic/vector-borne pathogens (OR 2.1; 95% CI, 1.11–3.76; P .019) were associated with positive clinical impact of KT. Host immunocompromised status was not reliably associated with a positive clinical impact of KT (OR 1.03; 95% CI, 0.83–1.29; P .7806). No significant predictors of KT clinical impact were found in pediatric patients. Microbiologic result pattern was also a significant predictor of impact.

Our study highlights that despite the positive clinical impact of KT in select situations, most testing results had no clinical impact. We also confirm diagnostic indications where KT may have the highest yield, thereby generating tools for diagnostic stewardship.

The increase in severe acute respiratory coronavirus virus 2 (SARS-CoV-2) cases due to the omicron strain led to reduced acute care hospital beds at the Veterans Administration (VA) Hospital, North Texas; veterans with non-severe coronavirus disease 2019 (COVID-19) disease were managed at a community living center (CLC), a VA nursing home. The management of non-severe COVID-19 in VA nursing homes has not been extensively described.

We describe resident characteristics and outcomes, and infection control practices implemented during 2 COVID-19 outbreak periods (January 12–February 15, 2022, June 28–July 14, 2023). Serial testing of all CLC residents was conducted, and residents with polymerase chain reaction-confirmed SARS-CoV-2 (COVID-19) infection were included in the analysis. Resident data were ascertained from the COVID-19 facility dashboard and medical record system.

From January 12 to February 15, 2022, and June 28–July 14, 2023, 62 adults residing at the CLC were diagnosed with COVID-19. Overall, the median age was 75 years [interquartile range, 71–80], and 57 (91.9%) were men. Residents were cohorted by COVID-19 test results. A multidisciplinary team was convened, and staff were fit tested for appropriate personal protective equipment (PPE) and received refresher training on hand hygiene, donning, and doffing of PPE. Thirty-seven (59.7%) residents were symptomatic. Overall, 55 (88.7%) residents were documented to have received the SARS-CoV-2 primary vaccination series. Most residents were managed at the CLC, while 12 (19.3%) were hospitalized in acute care.

It is feasible to manage high-risk residents with non-severe COVID-19 disease in a CLC utilizing a multidisciplinary approach and implementing Infection Prevention and Control strategies.

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.

This study sought to assess undergraduate students’ knowledge and attitudes surrounding perceived self-efficacy and threats in various common emergencies in communities of higher education.

Self-reported perceptions of knowledge and skills, as well as attitudes and beliefs regarding education and training, obligation to respond, safety, psychological readiness, efficacy, personal preparedness, and willingness to respond were investigated through 3 representative scenarios via a web-based survey.

Among 970 respondents, approximately 60% reported their university had adequately prepared them for various emergencies while 84% reported the university should provide such training. Respondents with high self-efficacy were significantly more likely than those with low self-efficacy to be willing to respond in whatever capacity needed across all scenarios.

There is a gap between perceived student preparedness for emergencies and training received. Students with high self-efficacy were the most likely to be willing to respond, which may be useful for future training initiatives.

Existing guidelines on overviews of reviews and umbrella reviews recommend an assessment of the certainty of evidence but provide limited guidance on how to apply GRADE to such a complex evidence synthesis. We present one approach to applying GRADE to an overview of reviews developed using general principles derived from current GRADE guidelines.

The methods were developed in an iterative and exploratory fashion following discussion with 11 methodologists and health services researchers. Key principles were distilled on the five GRADE domains (risk of bias, inconsistency, imprecision, indirectness, and publication bias) from the relevant GRADE guidelines, particularly those on test accuracy.

A ‘general principles’ approach of applying the five domains of GRADE to an overview of reviews and arriving at an overall summary judgment for outcomes was developed. These methods were successfully applied to an overview of reviews on 18F-prostate specific membrane antigen positron emission tomography and computed tomography in the staging of patients with high-risk or recurrent prostate cancer.

Our approach distilled key principles from relevant GRADE guidelines and allowed us to apply GRADE to a complex body of evidence. Such an approach may be of interest to other researchers working on overviews of reviews or umbrella reviews.

Depression is a common mental health disorder that often starts during adolescence, with potentially important future consequences including ‘Not in Education, Employment or Training’ (NEET) status.

We took a structured life course modeling approach to examine how depressive symptoms during adolescence might be associated with later NEET status, using a high-quality longitudinal data resource. We considered four plausible life course models: (1) an early adolescent sensitive period model where depressive symptoms in early adolescence are more associated with later NEET status relative to exposure at other stages; (2) a mid adolescent sensitive period model where depressive symptoms during the transition from compulsory education to adult life might be more deleterious regarding NEET status; (3) a late adolescent sensitive period model, meaning that depressive symptoms around the time when most adults have completed their education and started their careers are the most strongly associated with NEET status; and (4) an accumulation of risk model which highlights the importance of chronicity of symptoms.

Our analysis sample included participants with full information on NEET status (N = 3951), and the results supported the accumulation of risk model, showing that the odds of NEET increase by 1.015 (95% CI 1.012–1.019) for an increase of 1 unit in depression at any age between 11 and 24 years.

Given the adverse implications of NEET status, our results emphasize the importance of supporting mental health during adolescence and early adulthood, as well as considering specific needs of young people with re-occurring depressed mood.

To determine if the high-level personal protective equipment used in the treatment of high-consequence infectious diseases is effective at stopping the spread of pathogens to healthcare personnel (HCP) while doffing.

Personal protective equipment (PPE) is fundamental to the safety of HCPs. HCPs treating patients with high-consequence infectious diseases use several layers of PPE, forming complex protective ensembles. With high-containment PPE, step-by-step procedures are often used for donning and doffing to minimize contamination risk to the HCP, but these procedures are rarely empirically validated and instead rely on following infection prevention best practices.

A doffing protocol video for a high-containment PPE ensemble was evaluated to determine potential contamination pathways. These potential pathways were tested using fluorescence and genetically marked bacteriophages.

The experiments revealed existing protocols permit contamination pathways allowing for transmission of bacteriophages to HCPs. Updates to the doffing protocols were generated based on the discovered contamination pathways. This updated doffing protocol eliminated the movement of viable bacteriophages from the outside of the PPE to the skin of the HCP.

Our results illustrate the need for quantitative, scientific investigations of infection prevention practices, such as doffing PPE.

The brain can be represented as a network, with nodes as brain regions and edges as region-to-region connections. Nodes with the most connections (hubs) are central to efficient brain function. Current findings on structural differences in Major Depressive Disorder (MDD) identified using network approaches remain inconsistent, potentially due to small sample sizes. It is still uncertain at what level of the connectome hierarchy differences may exist, and whether they are concentrated in hubs, disrupting fundamental brain connectivity.

We utilized two large cohorts, UK Biobank (UKB, N = 5104) and Generation Scotland (GS, N = 725), to investigate MDD case–control differences in brain network properties. Network analysis was done across four hierarchical levels: (1) global, (2) tier (nodes grouped into four tiers based on degree) and rich club (between-hub connections), (3) nodal, and (4) connection.

In UKB, reductions in network efficiency were observed in MDD cases globally (d = −0.076, pFDR = 0.033), across all tiers (d = −0.069 to −0.079, pFDR = 0.020), and in hubs (d = −0.080 to −0.113, pFDR = 0.013–0.035). No differences in rich club organization and region-to-region connections were identified. The effect sizes and direction for these associations were generally consistent in GS, albeit not significant in our lower-N replication sample.

Our results suggest that the brain's fundamental rich club structure is similar in MDD cases and controls, but subtle topological differences exist across the brain. Consistent with recent large-scale neuroimaging findings, our findings offer a connectomic perspective on a similar scale and support the idea that minimal differences exist between MDD cases and controls.

This study investigates the impact of primary care utilisation of a symptom-based head and neck cancer risk calculator (Head and Neck Cancer Risk Calculator version 2) in the post-coronavirus disease 2019 period on the number of primary care referrals and cancer diagnoses.

The number of referrals from April 2019 to August 2019 and from April 2020 to July 2020 (pre-calculator) was compared with the number from the period January 2021 to August 2022 (post-calculator) using the chi-square test. The patients’ characteristics, referral urgency, triage outcome, Head and Neck Cancer Risk Calculator version 2 score and cancer diagnosis were recorded.

In total, 1110 referrals from the pre-calculator period were compared with 1559 from the post-calculator period. Patient characteristics were comparable for both cohorts. More patients were referred on the cancer pathway in the post-calculator cohort (pre-calculator patients 51.1 per cent vs post-calculator 64.0 per cent). The cancer diagnosis rate increased from 2.7 per cent in the pre-calculator cohort to 3.3 per cent in the post-calculator cohort. A lower rate of cancer diagnosis in the non-cancer pathway occurred in the cohort managed using the Head and Neck Cancer Risk Calculator version 2 (10 per cent vs 23 per cent, p = 0.10).

Head and Neck Cancer Risk Calculator version 2 demonstrated high sensitivity in cancer diagnosis. Further studies are required to improve the predictive strength of the calculator.