Patients presenting to hospital with suspected coronavirus disease 2019 (COVID-19), based on clinical symptoms, are routinely placed in a cohort together until polymerase chain reaction (PCR) test results are available. This procedure leads to delays in transfers to definitive areas and high nosocomial transmission rates. FebriDx is a finger-prick point-of-care test (PoCT) that detects an antiviral host response and has a high negative predictive value for COVID-19. We sought to determine the clinical impact of using FebriDx for COVID-19 triage in the emergency department (ED).

We undertook a retrospective observational study evaluating the real-world clinical impact of FebriDx as part of an ED COVID-19 triage algorithm.

Emergency department of a university teaching hospital.

Patients presenting with symptoms suggestive of COVID-19, placed in a cohort in a ‘high-risk’ area, were tested using FebriDx. Patients without a detectable antiviral host response were then moved to a lower-risk area.

Between September 22, 2020, and January 7, 2021, 1,321 patients were tested using FebriDx, and 1,104 (84%) did not have a detectable antiviral host response. Among 1,104 patients, 865 (78%) were moved to a lower-risk area within the ED. The median times spent in a high-risk area were 52 minutes (interquartile range [IQR], 34–92) for FebriDx-negative patients and 203 minutes (IQR, 142–255) for FebriDx-positive patients (difference of −134 minutes; 95% CI, −144 to −122; P < .0001). The negative predictive value of FebriDx for the identification of COVID-19 was 96% (661 of 690; 95% CI, 94%–97%).

FebriDx improved the triage of patients with suspected COVID-19 and reduced the time that severe acute respiratory coronavirus virus 2 (SARS-CoV-2) PCR-negative patients spent in a high-risk area alongside SARS-CoV-2–positive patients.

Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community.

This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or ‘symptom dimensions’ via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records.

Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations.

An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

To determine whether cascade reporting is associated with a change in meropenem and fluoroquinolone consumption.

A quasi-experimental study was conducted using an interrupted time series to compare antimicrobial consumption before and after the implementation of cascade reporting.

A 399-bed, tertiary-care, Veterans’ Affairs medical center.

Antimicrobial consumption data across 8 inpatient units were extracted from the Center for Disease Control and Prevention (CDC) National Health Safety Network (NHSN) antimicrobial use (AU) module from April 2017 through March 2019, reported as antimicrobial days of therapy (DOT) per 1,000 days present (DP).

Cascade reporting is a strategy of reporting antimicrobial susceptibility test results in which secondary agents are only reported if an organism is resistant to primary, narrow-spectrum agents. A multidisciplinary team developed cascade reporting algorithms for gram-negative bacteria based on local antibiogram and infectious diseases practice guidelines, aimed at restricting the use of fluoroquinolones and carbapenems. The algorithms were implemented in March 2018.

Following the implementation of cascade reporting, mean monthly meropenem (P =.005) and piperacillin/tazobactam (P = .002) consumption decreased and cefepime consumption increased (P < .001). Ciprofloxacin consumption decreased by 2.16 DOT per 1,000 DP per month (SE, 0.25; P < .001). Clostridioides difficile rates did not significantly change.

Ciprofloxacin consumption significantly decreased after the implementation of cascade reporting. Mean meropenem consumption decreased after cascade reporting was implemented, but we observed no significant change in the slope of consumption. cascade reporting may be a useful strategy to optimize antimicrobial prescribing.

Registry-based trials have emerged as a potentially cost-saving study methodology. Early estimates of cost savings, however, conflated the benefits associated with registry utilisation and those associated with other aspects of pragmatic trial designs, which might not all be as broadly applicable. In this study, we sought to build a practical tool that investigators could use across disciplines to estimate the ranges of potential cost differences associated with implementing registry-based trials versus standard clinical trials.

We built simulation Markov models to compare unique costs associated with data acquisition, cleaning, and linkage under a registry-based trial design versus a standard clinical trial. We conducted one-way, two-way, and probabilistic sensitivity analyses, varying study characteristics over broad ranges, to determine thresholds at which investigators might optimally select each trial design.

Registry-based trials were more cost effective than standard clinical trials 98.6% of the time. Data-related cost savings ranged from $4300 to $600,000 with variation in study characteristics. Cost differences were most reactive to the number of patients in a study, the number of data elements per patient available in a registry, and the speed with which research coordinators could manually abstract data. Registry incorporation resulted in cost savings when as few as 3768 independent data elements were available and when manual data abstraction took as little as 3.4 seconds per data field.

Registries offer important resources for investigators. When available, their broad incorporation may help the scientific community reduce the costs of clinical investigation. We offer here a practical tool for investigators to assess potential costs savings.

Major depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.

We analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.

We found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.

Our findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.

To examine the feasibility of using social media to assess the consumer nutrition environment by comparing sentiment expressed in Yelp reviews with information obtained from a direct observation audit instrument for grocery stores.

Trained raters used the Nutrition Environment Measures Survey in Stores (NEMS-S) in 100 grocery stores from July 2015 to March 2016. Yelp reviews were available for sixty-nine of these stores and were retrieved in February 2017 using the Yelp Application Program Interface. A sentiment analysis was conducted to quantify the perceptions of the consumer nutrition environment in the review text. Pearson correlation coefficients (ρ) were used to compare NEMS-S scores with Yelp review text on food availability, quality, price and shopping experience.

Detroit, Michigan, USA.

None.

Yelp reviews contained more comments about food availability and the overall shopping experience than food price and food quality. Negative sentiment about food prices in Yelp review text and the number of dollar signs on Yelp were positively correlated with observed food prices in stores (ρ=0·413 and 0·462, respectively). Stores with greater food availability were rated as more expensive on Yelp. Other aspects of the food store environment (e.g. overall quality and shopping experience) were captured only in Yelp.

While Yelp cannot replace in-person audits for collecting detailed information on the availability, quality and cost of specific food items, Yelp holds promise as a cost-effective means to gather information on the overall cost, quality and experience of food stores, which may be relevant for nutrition outcomes.

We investigated whether a higher number of fast-food outlets in an individual’s home neighbourhood is associated with increased prevalence of type 2 diabetes mellitus and related risk factors, including obesity.

Cross-sectional study.

Three UK-based diabetes screening studies (one general population, two high-risk populations) conducted between 2004 and 2011. The primary outcome was screen-detected type 2 diabetes. Secondary outcomes were risk factors for type 2 diabetes.

In total 10 461 participants (mean age 59 years; 53 % male; 21 % non-White ethnicity).

There was a higher number of neighbourhood (500 m radius from home postcode) fast-food outlets among non-White ethnic groups (P<0·001) and in socially deprived areas (P<0·001). After adjustment (social deprivation, urban/rural, ethnicity, age, sex), more fast-food outlets was associated with significantly increased odds for diabetes (OR=1·02; 95 % CI 1·00, 1·04) and obesity (OR=1·02; 95 % CI 1·00, 1·03). This suggests that for every additional two outlets per neighbourhood, we would expect one additional diabetes case, assuming a causal relationship between the fast-food outlets and diabetes.

These results suggest that increased exposure to fast-food outlets is associated with increased risk of type 2 diabetes and obesity, which has implications for diabetes prevention at a public health level and for those granting planning permission to new fast-food outlets.