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Background: Aerosol-generating procedures (AGPs) performed on COVID-19–positive patients raise concerns about the dissemination of SARS-CoV-2 via aerosols and droplets. Infectious aerosols and droplets generated by SARS-CoV-2–positive patient AGPs or through direct COVID-19 patient coughing or exhalation could potentially contaminate surfaces, leading to the indirect spread of SARS-CoV-2 via fomites within the emergency department (ED). We sampled surfaces of ED patient rooms occupied by known SARS-CoV-2–positive patients or patients under investigation for COVID-19 and undergoing an AGP to determine the frequency of room contamination with SARS-CoV-2 RNA. Methods: Swabs were collected from 5 room surfaces in the ED following AGPs performed on patients under investigation for COVID-19 or positive for SARS-CoV-2. High- and low-touch surfaces 6 feet (2 m) from the patient (door handle and return vent, respectively) and reusable medical equipment were swabbed. Swabs were tested for SARS-CoV-2 RNA by RT-qPCR; positive samples were cultured in Vero E6 cells. Patient COVID-19 results were confirmed through the electronic medical record. Results: In total, 203 rooms were sampled: 43 SARS-CoV-2–positive patients with an AGP, 44 SARS-CoV-2–positive patients who did not have an AGP, and 116 SARS-CoV-2–negative patients with an AGP, for a total of 1,015 swabs. Overall, SARS-CoV-2 RNA was detected on 36 (3.5%) surfaces from 29 rooms (14.3%) (Table 1). RNA contamination was detected more frequently in rooms occupied by SARS-CoV-2–positive patients who did not have an AGP than rooms occupied by COVID-19 patients (30% vs 14%). SARS-CoV-2 RNA was also detected in rooms occupied by SARS-CoV-2–negative patients undergoing an AGP (9%). SARS-CoV-2 RNA was most frequently detected on air vents (n = 15), bedrails (n = 10), equipment and vital signs monitors (n = 4 each), and door handles (n = 3). One bedrail was positive by culture and confirmed by an RT-qPCR cycle threshold reduction from >40 to 13. Conclusions: We detected SARS-CoV-2 RNA contamination on room surfaces in the ED, regardless of patient AGP or COVID-19 status; however, RNA contamination of room surfaces was most common in rooms occupied by SARS-CoV-2–positive patients who did not have an AGP, which may be attributable to stage of disease and viral shedding. SARS-CoV-2 RNA contamination was also present in rooms where APGs were performed on SARS-CoV-2–negative patients, suggesting carryover from previous patients. SARS-CoV-2 RNA was found most often on room air-return vents, further emphasizing the importance of aerosols in the spread of SARS-CoV-2.
Time-series cross-section (TSCS) data are prevalent in political science, yet many distinct challenges presented by TSCS data remain underaddressed. We focus on how dependence in both space and time complicates estimating either spatial or temporal dependence, dynamics, and effects. Little is known about how modeling one of temporal or cross-sectional dependence well while neglecting the other affects results in TSCS analysis. We demonstrate analytically and through simulations how misspecification of either temporal or spatial dependence inflates estimates of the other dimension’s dependence and thereby induces biased estimates and tests of other covariate effects. Therefore, we recommend the spatiotemporal autoregressive distributed lag (STADL) model with distributed lags in both space and time as an effective general starting point for TSCS model specification. We illustrate with two example reanalyses and provide R code to facilitate researchers’ implementation—from automation of common spatial-weights matrices (W) through estimated spatiotemporal effects/response calculations—for their own TSCS analyses.
Optimizing needleless connector hub disinfection practice is a key strategy in central-line–associated bloodstream infection (CLABSI) prevention. In this mixed-methods evaluation, 3 products with varying scrub times were tested for experimental disinfection followed by a qualitative nursing assessment of each.
Needleless connectors were inoculated with varying concentrations of Staphylococcus epidermidis, Pseudomonas aeruginosa, and Staphylococcus aureus followed by disinfection with a 70% isopropyl alcohol (IPA) wipe (a 15-second scrub time and a 15-second dry time), a 70% IPA cap (a 10-second scrub time and a 5-second dry time), or a 3.15% chlorhexidine gluconate with 70% IPA (CHG/IPA) wipe (a 5-second scrub time and a 5-second dry time). Cultures of needleless connectors were obtained after disinfection to quantify bacterial reduction. This was followed by surveying a convenience sample of nursing staff with intensive care unit assignments at an academic tertiary hospital on use of each product.
All products reduced overall bacterial burden when compared to sterile water controls, however the IPA and CHG/IPA wipes were superior to the IPA caps when product efficacy was compared. Nursing staff noted improved compliance with CHG/IPA wipes compared with the IPA wipes and the IPA caps, with many preferring the lesser scrub and dry times required for disinfection.
Achieving adequate bacterial disinfection of needleless connectors while maximizing healthcare staff compliance with scrub and dry times may be best achieved with a combination CHG/IPA wipe.
OBJECTIVES/GOALS: Many older sepsis survivors develop chronic critical illness (CCI) with poor outcomes. Sepsis is caused by a dysregulated immune response and biomarkers reflecting PICS. The purpose was to compare serial PICS biomarkers in a) older (versus young) adults and b) older CCI (versus older RAP) patients to gain insight into underlying pathobiology of CCI. METHODS/STUDY POPULATION: Prospective longitudinal study with young (â‰¤ 45 years) and older (â‰¥ 65 years) septic adults who were characterized by a) baseline predisposition, b) hospital outcomes, c) serial SOFA organ dysfunction scores over 14 days, d) Zubrod Performance status at three, six and 12-month follow-up and e) mortality over 12 months. Serial blood samples over 14 days were analyzed for selected biomarkers reflecting PICS. RESULTS/ANTICIPATED RESULTS: Compared to the young, more older adults developed CCI (20% vs 42%) and had markedly worse serial SOFA scores, performance status and mortality over 12 months. Additionally, older (versus young) and older CCI (versus older RAP) patients had more persistent aberrations in biomarkers reflecting inflammation, immunosuppression, stress metabolism, lack of anabolism and anti-angiogenesis over 14 days after sepsis. DISCUSSION/SIGNIFICANCE: Older (versus young) and older CCI (versus older RAP) patient subgroups demonstrate early biomarker evidence of the underlying pathobiology of PICS. The population of older sepsis survivors is need of interventions to lower systemic inflammation and stimulate anabolism to prevent skeletal muscle wasting and disability.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
From 2014 to 2020, we compiled radiocarbon ages from the lower 48 states, creating a database of more than 100,000 archaeological, geological, and paleontological ages that will be freely available to researchers through the Canadian Archaeological Radiocarbon Database. Here, we discuss the process used to compile ages, general characteristics of the database, and lessons learned from this exercise in “big data” compilation.
We describe the incidence of suicidality (2007–2017) in people with depression treated by secondary mental healthcare services at South London and Maudsley NHS Trust (n = 26 412). We estimated yearly incidence of ‘suicidal ideation’ and ‘high risk of suicide’ from structured and free-text fields of the Clinical Record Interactive Search system. The incidence of suicidal ideation increased from 0.6 (2007) to 1 cases (2017) per 1000 population. The incidence of high risk of suicide, based on risk forms, varied between 0.06 and 0.50 cases per 1000 adult population (2008–2017). Electronic health records provide the opportunity to examine suicidality on a large scale, but the impact of service-related changes in the use of structured risk assessment should be considered.
Our objective was to quantify the cross-sectional associations between dietary fatty acid (DFA) patterns and cognitive function among Hispanic/Latino adults. This study included data from 8,942 participants of the Hispanic Community Health Study/Study of Latinos, a population-based cohort study (weighted age 56.2 y and proportion female 55.2%). The NCI (National Cancer Institute) method was used to estimate dietary intake from two 24-hr recalls. We derived DFA patterns using principal components analysis with 26 fatty acid and total plant and animal monounsaturated fatty acid (MUFA) input variables. Global cognitive function was calculated as the average z-score of 4 neurocognitive tests. Survey linear regression models included multiple potential confounders such as age, sex, education, depressive symptoms, physical activity, energy intake, and cardiovascular disease. DFA patterns were characterized by consumption of long-chain saturated fatty acids (SFA), animal-based MUFA, and trans fatty acids (Factor 1); short to medium-chain SFA (Factor 2); very-long-chain omega-3 polyunsaturated fatty acids (PUFA) (Factor 3); very-long-chain SFA and plant-based MUFA and PUFA (Factor 4). Factor 2 was associated with greater scores for global cognitive function (β=0.037 ± 0.012) and the Digit Symbol Substitution (DSS) (β=0.56±0.17), Brief Spanish English Verbal Learning-Sum (B-SEVLT) (β=0.23 ± 0.11), and B-SEVLT-Recall (β=0.11 ± 0.05) tests (P<0.05 for all). Factors 1 (β=0.04 ± 0.01) and 4 (β=0.70 ± 0.18) were associated with the DSS test (P<0.05 for all). Consumption of short to medium-chain SFA may be associated with higher cognitive function among U.S.-residing Hispanic/Latino adults. Prospective studies are necessary to confirm these findings.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Recent cannabis exposure has been associated with lower rates of neurocognitive impairment in people with HIV (PWH). Cannabis’s anti-inflammatory properties may underlie this relationship by reducing chronic neuroinflammation in PWH. This study examined relations between cannabis use and inflammatory biomarkers in cerebrospinal fluid (CSF) and plasma, and cognitive correlates of these biomarkers within a community-based sample of PWH.
263 individuals were categorized into four groups: HIV− non-cannabis users (n = 65), HIV+ non-cannabis users (n = 105), HIV+ moderate cannabis users (n = 62), and HIV+ daily cannabis users (n = 31). Differences in pro-inflammatory biomarkers (IL-6, MCP-1/CCL2, IP-10/CXCL10, sCD14, sTNFR-II, TNF-α) by study group were determined by Kruskal–Wallis tests. Multivariable linear regressions examined relationships between biomarkers and seven cognitive domains, adjusting for age, sex/gender, race, education, and current CD4 count.
HIV+ daily cannabis users showed lower MCP-1 and IP-10 levels in CSF compared to HIV+ non-cannabis users (p = .015; p = .039) and were similar to HIV− non-cannabis users. Plasma biomarkers showed no differences by cannabis use. Among PWH, lower CSF MCP-1 and lower CSF IP-10 were associated with better learning performance (all ps < .05).
Current daily cannabis use was associated with lower levels of pro-inflammatory chemokines implicated in HIV pathogenesis and these chemokines were linked to the cognitive domain of learning which is commonly impaired in PWH. Cannabinoid-related reductions of MCP-1 and IP-10, if confirmed, suggest a role for medicinal cannabis in the mitigation of persistent inflammation and cognitive impacts of HIV.
In March 2020, at the onset of the coronavirus disease 2019 (COVID-19) pandemic in the United States, the Southern California Extracorporeal Membrane Oxygenation (ECMO) Consortium was formed. The consortium included physicians and coordinators from the 4 ECMO centers in San Diego County. Guidelines were created to ensure that ECMO was delivered equitably and in a resource effective manner across the county during the pandemic. A biomedical ethicist reviewed the guidelines to ensure ECMO use would provide maximal community benefit of this limited resource. The San Diego County Health and Human Services Agency further incorporated the guidelines into its plans for the allocation of scarce resources. The consortium held weekly video conferences to review countywide ECMO capacity (including census and staffing), share data, and discuss clinical practices and difficult cases. Equipment exchanges between ECMO centers maximized regional capacity. From March 1 to November 30, 2020, consortium participants placed 97 patients on ECMO. No eligible patients were denied ECMO due to lack of resources or capacity. The Southern California ECMO Consortium may serve as a model for other communities seeking to optimize ECMO resources during the current COVID-19 or future pandemics.
To understand the long-term climate and glaciological evolution of the ice sheet in the region bordering the Weddell Sea, the British Antarctic Survey has undertaken a series of successful ice core projects drilling to bedrock on Berkner Island, James Ross Island and the Fletcher Promontory. A new project, WACSWAIN, seeks to increase this knowledge by further drilling to bedrock on two further ice rises in this region. In a single-season project, an ice core was recovered to bedrock at 651 m on Skytrain Ice Rise using an ice core drill in a fluid-filled borehole. In a second season, a rapid access drill was used to recover ice chips to 323 m on Sherman Island in a dry borehole, though failing to reach the bedrock which was at an estimated depth of 428 m.