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Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.
Methods:
We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.
Results:
Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.
Conclusions:
WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.
The Variables and Slow Transients Survey (VAST) on the Australian Square Kilometre Array Pathfinder (ASKAP) is designed to detect highly variable and transient radio sources on timescales from 5 s to
$\sim\!5$
yr. In this paper, we present the survey description, observation strategy and initial results from the VAST Phase I Pilot Survey. This pilot survey consists of
$\sim\!162$
h of observations conducted at a central frequency of 888 MHz between 2019 August and 2020 August, with a typical rms sensitivity of
$0.24\ \mathrm{mJy\ beam}^{-1}$
and angular resolution of
$12-20$
arcseconds. There are 113 fields, each of which was observed for 12 min integration time, with between 5 and 13 repeats, with cadences between 1 day and 8 months. The total area of the pilot survey footprint is 5 131 square degrees, covering six distinct regions of the sky. An initial search of two of these regions, totalling 1 646 square degrees, revealed 28 highly variable and/or transient sources. Seven of these are known pulsars, including the millisecond pulsar J2039–5617. Another seven are stars, four of which have no previously reported radio detection (SCR J0533–4257, LEHPM 2-783, UCAC3 89–412162 and 2MASS J22414436–6119311). Of the remaining 14 sources, two are active galactic nuclei, six are associated with galaxies and the other six have no multi-wavelength counterparts and are yet to be identified.
Statistical genetics and brain imaging are together at the technological forefront of research into human intelligence. While these approaches have historically had little practical overlap, they are united both conceptually and in several broad methodological challenges. In concept, both areas attempt to explain complex human behavior by understanding its biological origins, and in doing so have faced the problems that arise from this complexity. The prospect of finding large-effect predictors, for example, has shaped both histories: statistical genetics, with its study of candidate genes that were once thought to have outsized influence on the development of many traits, and neuroscience, with its search for localized brain properties underlying complex behaviors. Both of these areas have then had to adjust their scope and methodology to address the issue of making valid and meaningful predictions from a large number of predictors with small effects. A key understanding is that larger samples of participants than originally employed may be necessary for these predictions to be accurate and useful.
Energy deficit is common during prolonged periods of strenuous physical activity and limited sleep, but the extent to which appetite suppression contributes is unclear. The aim of this randomised crossover study was to determine the effects of energy balance on appetite and physiological mediators of appetite during a 72-h period of high physical activity energy expenditure (about 9·6 MJ/d (2300 kcal/d)) and limited sleep designed to simulate military operations (SUSOPS). Ten men consumed an energy-balanced diet while sedentary for 1 d (REST) followed by energy-balanced (BAL) and energy-deficient (DEF) controlled diets during SUSOPS. Appetite ratings, gastric emptying time (GET) and appetite-mediating hormone concentrations were measured. Energy balance was positive during BAL (18 (sd 20) %) and negative during DEF (–43 (sd 9) %). Relative to REST, hunger, desire to eat and prospective consumption ratings were all higher during DEF (26 (sd 40) %, 56 (sd 71) %, 28 (sd 34) %, respectively) and lower during BAL (–55 (sd 25) %, −52 (sd 27) %, −54 (sd 21) %, respectively; Pcondition < 0·05). Fullness ratings did not differ from REST during DEF, but were 65 (sd 61) % higher during BAL (Pcondition < 0·05). Regression analyses predicted hunger and prospective consumption would be reduced and fullness increased if energy balance was maintained during SUSOPS, and energy deficits of ≥25 % would be required to elicit increases in appetite. Between-condition differences in GET and appetite-mediating hormones identified slowed gastric emptying, increased anorexigenic hormone concentrations and decreased fasting acylated ghrelin concentrations as potential mechanisms of appetite suppression. Findings suggest that physiological responses that suppress appetite may deter energy balance from being achieved during prolonged periods of strenuous activity and limited sleep.
With the legalization of marijuana (Cannabis sativa) and increasing use during pregnancy, it is important to understand its impact on exposed offspring. Specifically, the effects of Δ-9-tetrahydrocannabinol (Δ9-THC), the major psychoactive component of cannabis, on fetal ovarian development and long-term reproductive health are not fully understood. The aim of this study was to assess the effect of prenatal exposure to Δ9-THC on ovarian health in adult rat offspring. At 6 months of age, Δ9-THC-exposed offspring had accelerated folliculogenesis with apparent follicular development arrest, but no persistent effects on circulating steroid levels. Ovaries from Δ9-THC-exposed offspring had reduced blood vessel density in association with decreased expression of the pro-angiogenic factor VEGF and its receptor VEGFR-2, as well as an increase in the anti-angiogenic factor thrombospondin 1 (TSP-1). Collectively, these data suggest that exposure to Δ9-THC during pregnancy alters follicular dynamics during postnatal life, which may have long-lasting detrimental effects on female reproductive health.
The Rapid ASKAP Continuum Survey (RACS) is the first large-area survey to be conducted with the full 36-antenna Australian Square Kilometre Array Pathfinder (ASKAP) telescope. RACS will provide a shallow model of the ASKAP sky that will aid the calibration of future deep ASKAP surveys. RACS will cover the whole sky visible from the ASKAP site in Western Australia and will cover the full ASKAP band of 700–1800 MHz. The RACS images are generally deeper than the existing NRAO VLA Sky Survey and Sydney University Molonglo Sky Survey radio surveys and have better spatial resolution. All RACS survey products will be public, including radio images (with
$\sim$
15 arcsec resolution) and catalogues of about three million source components with spectral index and polarisation information. In this paper, we present a description of the RACS survey and the first data release of 903 images covering the sky south of declination
$+41^\circ$
made over a 288-MHz band centred at 887.5 MHz.
Individuals with schizophrenia are at higher risk of physical illnesses, which are a major contributor to their 20-year reduced life expectancy. It is currently unknown what causes the increased risk of physical illness in schizophrenia.
Aims
To link genetic data from a clinically ascertained sample of individuals with schizophrenia to anonymised National Health Service (NHS) records. To assess (a) rates of physical illness in those with schizophrenia, and (b) whether physical illness in schizophrenia is associated with genetic liability.
Method
We linked genetic data from a clinically ascertained sample of individuals with schizophrenia (Cardiff Cognition in Schizophrenia participants, n = 896) to anonymised NHS records held in the Secure Anonymised Information Linkage (SAIL) databank. Physical illnesses were defined from the General Practice Database and Patient Episode Database for Wales. Genetic liability for schizophrenia was indexed by (a) rare copy number variants (CNVs), and (b) polygenic risk scores.
Results
Individuals with schizophrenia in SAIL had increased rates of epilepsy (standardised rate ratio (SRR) = 5.34), intellectual disability (SRR = 3.11), type 2 diabetes (SRR = 2.45), congenital disorders (SRR = 1.77), ischaemic heart disease (SRR = 1.57) and smoking (SRR = 1.44) in comparison with the general SAIL population. In those with schizophrenia, carrier status for schizophrenia-associated CNVs and neurodevelopmental disorder-associated CNVs was associated with height (P = 0.015–0.017), with carriers being 7.5–7.7 cm shorter than non-carriers. We did not find evidence that the increased rates of poor physical health outcomes in schizophrenia were associated with genetic liability for the disorder.
Conclusions
This study demonstrates the value of and potential for linking genetic data from clinically ascertained research studies to anonymised health records. The increased risk for physical illness in schizophrenia is not caused by genetic liability for the disorder.
Inflammatory Bowel Disease (IBD) is associated with co morbid depression and anxiety of up to 42%. Corticosteroids, used commonly in IBD, are known to cause psychiatric side-effects and could be an independent risk factor for affective illness. Recent studies show that depression is also associated with raised CRP and IL6.
Aims
This study aims to show which demographic, clinical, medication and immunological factors are predictors of anxiety and depression in IBD.
Methods
The IBD, Steroids and Affective Disorder (ISA) study is a cross-sectional study of IBD patients in Edinburgh, UK. Out patients underwent assessment including Hospital Anxiety Depression Scale (HADS) past psychiatric history, steroid medication history, inflammatory markers, the Medication Adherence Rating Scale (MARS) and Altman Self Rated Mania Scale (ARSM).
Results
326 patients with Crohns and 256 with Colitis (72% of clinic attendees) were recruited. 251 (43%) patients scored 12 or above on the HADS questionnaire. 45% of patients had previously suffered from affective illness. Patients on Prednisolone and Budesonide scored significantly higher on HADS Depression (p = 0.03 and p = 0.002) as did those who had been on Prednisolone for more than 8 weeks (p = 0.041). Being on prednisolone was not associated with increased Colitis and Crohns activity indices (p = 0.2). HADS scores were measured against other disease and demographic variables.
Conclusion
Affective illness is common in the IBD population and the prescription and duration of systemic corticosteroids are associated with depression. Biological and disease variables may play an important role in co morbid affective illness in IBD
The Minnesota Center for Twin and Family Research (MCTFR) comprises multiple longitudinal, community-representative investigations of twin and adoptive families that focus on psychological adjustment, personality, cognitive ability and brain function, with a special emphasis on substance use and related psychopathology. The MCTFR includes the Minnesota Twin Registry (MTR), a cohort of twins who have completed assessments in middle and older adulthood; the Minnesota Twin Family Study (MTFS) of twins assessed from childhood and adolescence into middle adulthood; the Enrichment Study (ES) of twins oversampled for high risk for substance-use disorders assessed from childhood into young adulthood; the Adolescent Brain (AdBrain) study, a neuroimaging study of adolescent twins; and the Siblings Interaction and Behavior Study (SIBS), a study of adoptive and nonadoptive families assessed from adolescence into young adulthood. Here we provide a brief overview of key features of these established studies and describe new MCTFR investigations that follow up and expand upon existing studies or recruit and assess new samples, including the MTR Study of Relationships, Personality, and Health (MTR-RPH); the Colorado-Minnesota (COMN) Marijuana Study; the Adolescent Brain Cognitive Development (ABCD) study; the Colorado Online Twins (CoTwins) study and the Children of Twins (CoT) study.
Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
Methods:
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Results:
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Conclusions:
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.
To assess variability in antimicrobial use and associations with infection testing in pediatric ventilator-associated events (VAEs).
Design
Descriptive retrospective cohort with nested case-control study.
Setting
Pediatric intensive care units (PICUs), cardiac intensive care units (CICUs), and neonatal intensive care units (NICUs) in 6 US hospitals.
Patients
Children≤18 years ventilated for≥1 calendar day.
Methods
We identified patients with pediatric ventilator-associated conditions (VACs), pediatric VACs with antimicrobial use for≥4 days (AVACs), and possible ventilator-associated pneumonia (PVAP, defined as pediatric AVAC with a positive respiratory diagnostic test) according to previously proposed criteria.
Results
Among 9,025 ventilated children, we identified 192 VAC cases, 43 in CICUs, 70 in PICUs, and 79 in NICUs. AVAC criteria were met in 79 VAC cases (41%) (58% CICU; 51% PICU; and 23% NICU), and varied by hospital (CICU, 20–67%; PICU, 0–70%; and NICU, 0–43%). Type and duration of AVAC antimicrobials varied by ICU type. AVAC cases in CICUs and PICUs received broad-spectrum antimicrobials more often than those in NICUs. Among AVAC cases, 39% had respiratory infection diagnostic testing performed; PVAP was identified in 15 VAC cases. Also, among AVAC cases, 73% had no associated positive respiratory or nonrespiratory diagnostic test.
Conclusions
Antimicrobial use is common in pediatric VAC, with variability in spectrum and duration of antimicrobials within hospitals and across ICU types, while PVAP is uncommon. Prolonged antimicrobial use despite low rates of PVAP or positive laboratory testing for infection suggests that AVAC may provide a lever for antimicrobial stewardship programs to improve utilization.
Prior evolutionary theory provided reason to suspect that measures of development and reproduction would be correlated with antisocial behaviours in human and non-human species. Behavioural genetics has revealed that most quantitative traits are heritable, suggesting that these phenotypic correlations may share genetic aetiologies. We use genome-wide association study data to estimate the genetic correlations between various measures of reproductive development (N = 52 776–318 863) and antisocial behaviour (N = 31 968). Our genetic correlation analyses demonstrate that alleles associated with higher reproductive output (number of children ever born, rg = 0.50, P = 0.0065) were positively correlated with alleles associated with antisocial behaviour, whereas alleles associated with more delayed reproductive onset (age at first birth, rg = −0.64, P = 0.0008) were negatively associated with alleles linked to antisocial behaviour. Ultimately, these findings coalesce with evolutionary theories suggesting that increased antisocial behaviours may partly represent a faster life history approach, which may be significantly calibrated by genes.
We evaluated the utility of vancomycin-resistant Enterococcus (VRE) surveillance by varying 2 parameters: admission versus weekly surveillance and perirectal swabbing versus stool sampling.
Design
Prospective, patient-level surveillance program of incident VRE colonization.
Setting
Liver transplant surgical intensive care unit (SICU) of a tertiary-care referral medical center with a high prevalence of VRE.
Patients
All patients admitted to the SICU from June to August 2015.
Methods
We conducted a point-prevalence estimate followed by admission and weekly surveillance by perirectal swabbing and/or stool sampling. Incident colonization was defined as a negative screen followed by positive surveillance. VRE was detected by culture on Remel Spectra VRE chromogenic agar. Microbiologically-confirmed VRE bloodstream infections (BSIs) were tracked for 2 months. Statistical analyses were calculated using the McNemar test, the Fisher exact test, the t test, and the χ2 test.
Results
In total, 91 patients underwent VRE surveillance testing. The point prevalence of VRE colonization was 60.9%; VRE prevalence on admission was 30.1%. Weekly surveillance identified an additional 7 of 28 patients (25.0%) with incident colonization. VRE BSIs were more common in VRE-colonized patients than in noncolonized patients (8 of 43 vs 2 of 48; P=.028). In a direct comparison, perirectal swabs were more sensitive than stool samples in detecting VRE (64 of 67 vs 56 of 67; P=.023). Compliance with perirectal swabbing was 89% (201 of 226) compared to 56% (127 of 226) for stool collection (P≤0.001).
Conclusions
We recommend weekly VRE surveillance over admission-only screening in high-burden units such as liver transplant SICUs. Perirectal swabs had greater collection compliance and sensitivity than stool samples, making them the preferred methodology. Further work may have implications for antimicrobial stewardship and infection control.
Does general intelligence exist across species, and has it been a target of natural selection? These questions can be addressed with genomic data, which can rule out artifacts by demonstrating that distinct cognitive abilities are genetically correlated and thus share a biological substrate. This work has begun with data from humans and can be extended to other species; it should focus not only on general intelligence but also specific capacities like language and spatial ability.
Adult ventilator-associated event (VAE) definitions include ventilator-associated conditions (VAC) and subcategories for infection-related ventilator-associated complications (IVAC) and possible ventilator-associated pneumonia (PVAP). We explored these definitions for children.
DESIGN
Retrospective cohort
SETTING
Pediatric, cardiac, or neonatal intensive care units (ICUs) in 6 US hospitals
PATIENTS
Patients ≤18 years old ventilated for ≥1 day
METHODS
We identified patients with pediatric VAC based on previously proposed criteria. We applied adult temperature, white blood cell count, antibiotic, and culture criteria for IVAC and PVAP to these patients. We matched pediatric VAC patients with controls and evaluated associations with adverse outcomes using Cox proportional hazards models.
RESULTS
In total, 233 pediatric VACs (12,167 ventilation episodes) were identified. In the cardiac ICU (CICU), 62.5% of VACs met adult IVAC criteria; in the pediatric ICU (PICU), 54.2% of VACs met adult IVAC criteria; and in the neonatal ICU (NICU), 20.2% of VACs met adult IVAC criteria. Most patients had abnormal white blood cell counts and temperatures; we therefore recommend simplifying surveillance by focusing on “pediatric VAC with antimicrobial use” (pediatric AVAC). Pediatric AVAC with a positive respiratory diagnostic test (“pediatric PVAP”) occurred in 8.9% of VACs in the CICU, 13.3% of VACs in the PICU, and 4.3% of VACs in the NICU. Hospital mortality was increased, and hospital and ICU length of stay and duration of ventilation were prolonged among all pediatric VAE subsets compared with controls.
CONCLUSIONS
We propose pediatric AVAC for surveillance related to antimicrobial use, with pediatric PVAP as a subset of AVAC. Studies on generalizability and responsiveness of these metrics to quality improvement initiatives are needed, as are studies to determine whether lower pediatric VAE rates are associated with improvements in other outcomes.
We aimed to evaluate emergency medical services (EMS) data as disaster metrics and to assess stress in surrounding hospitals and a municipal network after the closure of Bellevue Hospital during Hurricane Sandy in 2012.
Methods
We retrospectively reviewed EMS activity and call types within New York City’s 911 computer-assisted dispatch database from January 1, 2011, to December 31, 2013. We evaluated EMS ambulance transports to individual hospitals during Bellevue’s closure and incremental recovery from urgent care capacity, to freestanding emergency department (ED) capability, freestanding ED with 911-receiving designation, and return of inpatient services.
Results
A total of 2,877,087 patient transports were available for analysis; a total of 707,593 involved Manhattan hospitals. The 911 ambulance transports disproportionately increased at the 3 closest hospitals by 63.6%, 60.7%, and 37.2%. When Bellevue closed, transports to specific hospitals increased by 45% or more for the following call types: blunt traumatic injury, drugs and alcohol, cardiac conditions, difficulty breathing, “pedestrian struck,” unconsciousness, altered mental status, and emotionally disturbed persons.
Conclusions
EMS data identified hospitals with disproportionately increased patient loads after Hurricane Sandy. Loss of Bellevue, a public, safety net medical center, produced statistically significant increases in specific types of medical and trauma transports at surrounding hospitals. Focused redeployment of human, economic, and social capital across hospital systems may be required to expedite regional health care systems recovery. (Disaster Med Public Health Preparedness. 2016;10:333–343)
Ree, Carretta, and Teachout's (2015) arguments for recognizing the importance of general factors are mostly on point, but they neglect two broad issues: (a) an important theoretical problem introduced by the presence of multiple factors (general, group, specific) and (b) the criterion validity of group factors in certain settings.
The number of pediatric antimicrobial stewardship programs (ASPs) is increasing and program evaluation is a key component to improve efficiency and enhance stewardship strategies.
OBJECTIVE
To determine the antimicrobials and diagnoses most strongly associated with a recommendation provided by a well-established pediatric ASP.
DESIGN AND SETTING
Retrospective cohort study from March 3, 2008, to March 2, 2013, of all ASP reviews performed at a free-standing pediatric hospital.
METHODS
ASP recommendations were classified as follows: stop therapy, modify therapy, optimize therapy, or consult infectious diseases. A multinomial distribution model to determine the probability of each ASP recommendation category was performed on the basis of the specific antimicrobial agent or disease category. A logistic model was used to determine the odds of recommendation disagreement by the prescribing clinician.
RESULTS
The ASP made 2,317 recommendations: stop therapy (45%), modify therapy (26%), optimize therapy (19%), or consult infectious diseases (10%). Third-generation cephalosporins (0.20) were the antimicrobials with the highest predictive probability of an ASP recommendation whereas linezolid (0.05) had the lowest probability. Community-acquired pneumonia (0.26) was the diagnosis with the highest predictive probability of an ASP recommendation whereas fever/neutropenia (0.04) had the lowest probability. Disagreement with ASP recommendations by the prescribing clinician occurred 22% of the time, most commonly involving community-acquired pneumonia and ear/nose/throat infections.
CONCLUSIONS
Evaluation of our pediatric ASP identified specific clinical diagnoses and antimicrobials associated with an increased likelihood of an ASP recommendation. Focused interventions targeting these high-yield areas may result in increased program efficiency and efficacy.