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To determine the rate of and factors associated with suboptimal discharge antimicrobial prescribing at a tertiary referral children’s hospital.
Tertiary referral children’s hospital.
All enteral antimicrobial discharge prescriptions at Lucile Packard Children’s Hospital Stanford from January 1st, 2021 through December 31st, 2021.
All enteral discharge antimicrobials are routinely evaluated by our antimicrobial stewardship program within 48 hours of hospital discharge. Antimicrobials are determined to be optimal or suboptimal by an antimicrobial stewardship pharmacist after evaluating the prescribed choice of antimicrobial, dose, duration, dosing frequency, and formulation. The rate and factors associated with suboptimal antimicrobial discharge prescribing were evaluated.
Of 2,593 antimicrobial prescriptions ordered at discharge, 19.7% were suboptimal. Suboptimal prescriptions were due to incorrect duration (72.2%), dose (31.0%), dose frequency (23.3%), drug choice (6.5%), or formulation (5.7%). In total, 87.2% of antimicrobials for perioperative prophylaxis and 13.5% of treatment antimicrobials were suboptimal. Antimicrobials with the highest rate of suboptimal prescriptions were amoxicillin-clavulanate (40.7%), clindamycin (36.6%), and cephalexin (36.6%).
Suboptimal antimicrobial discharge prescriptions are common and present an opportunity for antimicrobial stewardship programs during hospital transition of care. Factors associated with suboptimal prescriptions differ by antimicrobial and prescribed indication, indicating that multiple stewardship interventions may be needed to improve prescribing.
Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions.
To compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness.
Data were collected from individuals aged 18–26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown.
Mental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78–36.57) and 15.6% (95% CI 15.39–15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease.
Healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.
To improve contact tracing for healthcare workers, we built and configured a Bluetooth low-energy system. We predicted close contacts with great accuracy and provided an additional contact yield of 14.8%. This system would decrease the effective reproduction number by 56% and would unnecessarily quarantine 0.74% of employees weekly.
We sought to determine whether increased antimicrobial use (AU) at the onset of the coronavirus disease 2019 (COVID-19) pandemic was driven by greater AU in COVID-19 patients only, or whether AU also increased in non–COVID-19 patients.
In this retrospective observational ecological study from 2019 to 2020, we stratified inpatients by COVID-19 status and determined relative percentage differences in median monthly AU in COVID-19 patients versus non–COVID-19 patients during the COVID-19 period (March–December 2020) and the pre–COVID-19 period (March–December 2019). We also determined relative percentage differences in median monthly AU in non–COVID-19 patients during the COVID-19 period versus the pre–COVID-19 period. Statistical significance was assessed using Wilcoxon signed-rank tests.
The study was conducted in 3 acute-care hospitals in Chicago, Illinois.
Facility-wide AU for broad-spectrum antibacterial agents predominantly used for hospital-onset infections was significantly greater in COVID-19 patients versus non–COVID-19 patients during the COVID-19 period (with relative increases of 73%, 66%, and 91% for hospitals A, B, and C, respectively), and during the pre–COVID-19 period (with relative increases of 52%, 64%, and 66% for hospitals A, B, and C, respectively). In contrast, facility-wide AU for all antibacterial agents was significantly lower in non–COVID-19 patients during the COVID-19 period versus the pre–COVID-19 period (with relative decreases of 8%, 7%, and 8% in hospitals A, B, and C, respectively).
AU for broad-spectrum antimicrobials was greater in COVID-19 patients compared to non–COVID-19 patients at the onset of the pandemic. AU for all antibacterial agents in non–COVID-19 patients decreased in the COVID-19 period compared to the pre–COVID-19 period.
People often test changes to see if the change is producing the desired result (e.g., does taking an antidepressant improve my mood, or does keeping to a consistent schedule reduce a child’s tantrums?). Despite the prevalence of such decisions in everyday life, it is unknown how well people can assess whether the change has influenced the result. According to interrupted time series analysis (ITSA), doing so involves assessing whether there has been a change to the mean (‘level’) or slope of the outcome, after versus before the change. Making this assessment could be hard for multiple reasons. First, people may have difficulty understanding the need to control the slope prior to the change. Additionally, one may need to remember events that occurred prior to the change, which may be a long time ago. In Experiments 1 and 2, we tested how well people can judge causality in 9 ITSA situations across 4 presentation formats in which participants were presented with the data simultaneously or in quick succession. We also explored individual differences. In Experiment 3, we tested how well people can judge causality when the events were spaced out once per day, mimicking a more realistic timeframe of how people make changes in their lives. We found that participants were able to learn accurate causal relations when there is a zero pre-intervention slope in the time series but had difficulty controlling for nonzero pre-intervention slopes. We discuss these results in terms of 2 heuristics that people might use.
This study examined how temporal associations between parents’ physiological and behavioral responses may reflect underlying regulatory difficulties in at-risk parenting. Time-series data of cardiac indices (second-by-second estimates of inter-beat intervals – IBI, and respiratory sinus arrhythmia – RSA) and parenting behaviors were obtained from 204 child welfare-involved parents (88% mothers, Mage = 32.32 years) during child-led play with their 3- to 7-year-old children (45.1% female; Mage = 4.76 years). Known risk factors for maltreatment, including parents’ negative social cognitions, mental health symptoms, and inhibitory control problems, were examined as moderators of intra-individual physiology-behavior associations. Results of ordinary differential equations suggested increases in parents’ cardiac arousal at moments when they showed positive parenting behaviors. In turn, higher arousal was associated with momentary decreases in both positive and negative parenting behaviors. Individual differences in these dynamic processes were identified in association with parental risk factors. In contrast, no sample-wide RSA-behavior associations were evident, but a pattern of increased positive parenting at moments of parasympathetic withdrawal emerged among parents showing more total positive parenting behaviors. This study illustrated an innovative and ecologically-valid approach to examining regulatory patterns that may shape parenting in real-time and identified mechanisms that should be addressed in interventions.
This study contributes to the research on central–local relations in China by examining local dynamics and defiance. Drawing on the case of a provincial government's defiance against a central policy – Heilongjiang province's 2016 ban on genetically modified organisms (GMOs) – this study shows that despite the unprecedented recentralization push in recent years, local defiance still exists and persists. In addition, this study finds that the Heilongjiang provincial government managed to reduce potential political backlash by feeding the public distrust of GMOs, exploiting the internal divide and central ambiguity over GMOs and, more importantly, skilfully framing its GMO ban as part of its efforts to implement Xi Jinping's Green Development Concept.
In this paper, we consider the friendship paradox in the context of random walks and paths. Among our results, we give an equality connecting long-range degree correlation, degree variability, and the degree-wise effect of additional steps for a random walk on a graph. Random paths are also considered, as well as applications to acquaintance sampling in the context of core-periphery structure.
Coronavirus infection has shown a significant impact not only on physical health but also on mental health. Among the long-term consequences in the post-COVID period, depressive and anxiety disorders are well observed. A potential mechanism for developing mental disorders after undergoing SARS-CoV-2 is a neuroinflammatory process in the central nervous system.
This study aimed to discover the features of anxiety and depressive disorders in people who suffered from COVID-19.
The study was conducted from October 2021 to September 2022 in outpatient and inpatient conditions of the S. S. Korsakov Psychiatric Clinic of Sechenov University. 58 patients (17 (29.3%) men and 41 (70.7%) women) with a diagnosis of F32, F34.1, F41-F48.0, or F06.3-06.4 according to ICD-10 who underwent COVID-19, mainly of mild and moderate severity (46 (79,3%) and (8 (13,8%) consequently), were examined clinically.
The median age among the respondents was 34 years. Mental illness in the family history had 38 (65.5%) people. Among the examined patients, 21 ((36.2%) people had psychasthenic traits premorbid, 13 (22.4%) – hyperthymic, 9 (15.5%) – hysterical. 15 patients (25.9%) had a history of maternal disorders during pregnancy and childbirth – 16 (27,6%) had neurotic disorders in childhood, 27 (46.6%) had a traumatic brain injury or general anesthesia. 2 patients (3.4%) reported substance abuse, 7 (12.1%) abused alcohol. The median period from somatic well-being after infection to the onset of mental illness was 3 months. The duration from the onset of symptoms of a mental disorder to treatment with a psychiatrist was 3 months. The main symptoms in the clinical picture were impaired concentration (100.0%), decreased productivity (98.3%), sleep disorders (96.6%), decreased mood (98.3%), anxiety (89.7%), anhedonia (75.9%), decreased appetite (65.5%), asthenia (65.5%), emotional lability (44.8%), self-blame ideas (43.1%), obsessive thoughts (39.7%), irritability (37.9%), suicidal thoughts (19.0%).
About two-thirds of respondents were female. The main reasons for consulting a psychiatrist were decreased concentration, sleep disorders, and reduced productivity. In addition, symptoms of anxiety, asthenia, and low mood were revealed, and more than half of the patients complained of apathy. Although the severity of depression was moderate, and the level of anxiety was mild, all these disorders were accompanied by clinically significant fatigue.
As a result of the wildfire that engulfed Fort McMurray (FMM), Alberta, Canada in May 2016, over 90,000 residents were evacuated from the city. Approximately 2400 homes, or 10% of the housing stock, were destroyed in Fort McMurray. About 200,000 hectors of forest were destroyed by the fire, which reached into Saskatchewan. In the aftermath of a major disaster, a community’s infrastructure is disrupted, and psychological, economic, and environmental effects can last for many years.
Intensive research was conducted in Fort McMurray five years after the wildfire disaster to determine the prevalence of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) among residents of the community and to determine the demographic, clinical, and other risk factors of probable MDD and PTSD.
An online questionnaire administered via REDCap was used to collect data in a quantitative cross-sectional study between 24 April and 2 June 2021. Patients were asked to complete the Patient Health Questionnaire (PHQ-9) in order to assess the presence of symptoms associated with MDD. An assessment of likely PTSD in respondents was conducted using the PTSD Checklist for DSM-5 (PCL-C). In this study, descriptive, univariate, and multivariate regression analyses were conducted.
Out of 249 people who accessed the survey link, 186 completed it (74.7% response rate). There was a median age of 42 among the subscribers. A majority of the sample consisted of 159 (85.5%) females; 98 (52.7%) over the age of 40; 136 (71%) in a relationship; and 175 (94.1%) employed. Our study sample had an overall prevalence of 45.0% (76) of MDD symptoms. The multivariate logistic regression model revealed four variables that were independently associated with MDD symptoms, including being unemployed, diagnosed with MDD, taking sedative-hypnotics, and willingness to receive mental health counseling. A total of 39.6% of our respondents (65) reported having likely PTSD. Three independent variables: received a mental health depression diagnosis from a health professional, would like to receive mental health counseling, and have only limited or no support from familycontributed significantly to the model for predicting likely PTSD among respondents while controlling the other factors in the regression model.
The findings of this study indicate that unemployment, the use of sleeping pills, the presence of a previous depression diagnosis, and the willingness to seek mental health counseling are significant factors associated with the increase in the prevalence of MDD and PTSD following wildfires. Support from family members may prevent these conditions from developing.
As a result of the floods in Fort McMurray (FMM) and the surrounding area in 2020, more than $228 million in insured damage was sustained, over 1200 structures were damaged, and more than 13,000 people were evacuated from their homes.
The aim of the study was to determine the prevalence of post-traumatic stress disorder (PTSD)-like symptoms among the population of FMM one year after the flood in 2020 and the risk predictors associated with such symptoms.
In order to collect sociodemographic, clinical, and flood-related information from residents of FMM via REDCap, an online quantitative cross-sectional survey was administered between April 24 and June 02, 2021. Respondents were assessed for probable PTSD using the PTSD Checklist for DSM-5 (PCL-C).
An overall response rate of 74.7% was achieved among 186 of 249 respondents. The prevalence of likely post-traumatic stress disorder was 39.6% (65). There was a significantly increased likelihood of developing PTSD symptoms in respondents with a history of depression (OR= 5.71; 95% CI: 1.68 - 19.36). As well, disaster responders experiencing limited and no family support after the disaster were more likely to report PTSD symptoms (OR= 2.87; 95% CI: 1.02 - 8.05) and (OR= 2.87; 95% CI: 1.06 - 7.74), respectively.
As a result of our study, we found that those who had a history of depression and had sought health counseling were significantly more likely to develop PTSD symptoms following flooding, while those with family support were less likely to suffer from PTSD symptoms. There is a need for further studies to investigate the relationship between the need for counseling and the presentation of potential symptoms of post-traumatic stress disorder.
We present the third data release from the Parkes Pulsar Timing Array (PPTA) project. The release contains observations of 32 pulsars obtained using the 64-m Parkes ‘Murriyang’ radio telescope. The data span is up to 18 yr with a typical cadence of 3 weeks. This data release is formed by combining an updated version of our second data release with $\sim$3 yr of more recent data primarily obtained using an ultra-wide-bandwidth receiver system that operates between 704 and 4032 MHz. We provide calibrated pulse profiles, flux density dynamic spectra, pulse times of arrival, and initial pulsar timing models. We describe methods for processing such wide-bandwidth observations and compare this data release with our previous release.
The National Pediatric Cardiology Quality Improvement Collaborative (NPC-QIC) lacks a rigorous enrollment audit process, unlike other collaborative networks. Most centers require individual families to consent to participate. It is unknown whether there is variation across centers or biases in enrollment.
We used the Pediatric Cardiac Critical Care Consortium (PC4) registry to assess enrollment rates in NPC-QIC for those centers participating in both registries using indirect identifiers (date of birth, date of admission, gender, and center) to match patient records. All infants born 1/1/2018–12/31/2020 and admitted 30 days of life were eligible. In PC4, all infants with a fundamental diagnosis of hypoplastic left heart or variant or who underwent a surgical or hybrid Norwood or variant were eligible. Standard descriptive statistics were used to describe the cohort and center match rates were plotted on a funnel chart.
Of 898 eligible NPC-QIC patients, 841 were linked to 1,114 eligible PC4 patients (match rate 75.5%) in 32 centers. Match rates were lower in patients of Hispanic/Latino ethnicity (66.1%, p = 0.005), and those with any specified chromosomal abnormality (57.4%, p = 0.002), noncardiac abnormality (67.8%, p = 0.005), or any specified syndrome (66.5%, p = 0.001). Match rates were lower for patients who transferred to another hospital or died prior to discharge. Match rates varied from 0 to 100% across centers.
It is feasible to match patients between the NPC-QIC and PC4 registries. Variation in match rates suggests opportunities for improvement in NPC-QIC patient enrollment.
Machine vision has been extensively researched in the field of unmanned aerial vehicles (UAV) recently. However, the ability of Sense and Avoid (SAA) largely limited by environmental visibility, which brings hazards to flight safety in low illumination or nighttime conditions. In order to solve this critical problem, an approach of image enhancement is proposed in this paper to improve image qualities in low illumination conditions. Considering the complementarity of visible and infrared images, a visible and infrared image fusion method based on convolutional sparse representation (CSR) is a promising solution to improve the SAA ability of UAVs. Firstly, the source image is decomposed into a texture layer and structure layer since infrared images are good at characterising structural information, and visible images have richer texture information. Both the structure and the texture layers are transformed into the sparse convolutional domain through the CSR mechanism, and then CSR coefficient mapping are fused via activity level assessment. Finally, the image is synthesised through the reconstruction results of the fusion texture and structure layers. In the experimental simulation section, a series of visible and infrared registered images including aerial targets are adopted to evaluate the proposed algorithm. Experimental results demonstrates that the proposed method increases image qualities in low illumination conditions effectively and can enhance the object details, which has better performance than traditional methods.
Sackett et al. (2022) identified previously unnoticed flaws in the way range restriction corrections have been applied in prior meta-analyses of personnel selection tools. They offered revised estimates of operational validity, which are often quite different from the prior estimates. The present paper attempts to draw out the applied implications of that work. We aim to a) present a conceptual overview of the critique of prior approaches to correction, b) outline the implications of this new perspective for the relative validity of different predictors and for the tradeoff between validity and diversity in selection system design, c) highlight the need to attend to variability in meta-analytic validity estimates, rather than just the mean, d) summarize reactions encountered to date to Sackett et al., and e) offer a series of recommendations regarding how to go about correcting validity estimates for unreliability in the criterion and for range restriction in applied work.
Adolescent substance use, externalizing and attention problems, and early life stress (ELS) commonly co-occur. These psychopathologies show overlapping neural dysfunction in the form of reduced recruitment of reward processing neuro-circuitries. However, it is unclear to what extent these psychopathologies show common v. different neural dysfunctions as a function of symptom profiles, as no studies have directly compared neural dysfunctions associated with each of these psychopathologies to each other.
In study 1, a latent profile analysis (LPA) was conducted in a sample of 266 adolescents (aged 13–18, 41.7% female, 58.3% male) from a residential youth care facility and the surrounding community to investigate substance use, externalizing and attention problems, and ELS psychopathologies and their co-presentation. In study 2, we examined a subsample of 174 participants who completed the Passive Avoidance learning task during functional magnetic resonance imaging to examine differential and/or common reward processing neuro-circuitry dysfunctions associated with symptom profiles based on these co-presentations.
In study 1, LPA identified profiles of substance use plus rule-breaking behaviors, attention-deficit hyperactivity disorder, and ELS. In study 2, the substance use/rule-breaking profile was associated with reduced recruitment of reward processing and attentional neuro-circuitries during the Passive Avoidance task (p < 0.05, corrected for multiple comparisons).
Findings indicate that there is reduced responsivity of striato-cortical regions when receiving outcomes on an instrumental learning task within a profile of adolescents with substance use and rule-breaking behaviors. Mitigating reward processing dysfunction specifically may represent a potential intervention target for substance-use psychopathologies accompanied by rule-breaking behaviors.
Remote patient monitoring (RPM) has emerged as a viable and valuable care delivery method to improve chronic disease management. In light of the high prevalence and substantial economic burden of cardiovascular disease (CVD), this systematic review examines the cost and cost-effectiveness of using RPM to manage CVD in the United States.
We systematically searched databases to identify potentially relevant research. Findings were synthesized for cost and cost-effectiveness by economic study type with consideration of study perspective, intervention, clinical outcome, and time horizon. The methodological quality was assessed using the Joanna Briggs Institute Checklist for Economic Evaluations.
Thirteen articles with fourteen studies published between 2011 and 2021 were included in the final review. Studies from the provider perspective with a narrow scope of cost components identified higher costs and similar effectiveness for the RPM group relative to the usual care group. However, studies from payer and healthcare sector perspectives indicate better clinical effectiveness of RPM relative to usual care, with two cost-utility analysis studies suggesting that RPM relative to usual care is a cost-effective tool for CVD management even at the conservative $50,000 per Quality-Adjusted Life-Year threshold. Additionally, all model-based studies revealed that RPM is cost-effective in the long run.
Full economic evaluations identified RPM as a potentially cost-effective tool, particularly for long-term CVD management. In addition to the current literature, rigorous economic analysis with a broader perspective is needed in evaluating the value and economic sustainability of RPM.
OBJECTIVES/GOALS: Determine if the Conserved Transcriptional Response to Adversity transcriptomic profile established in primary blood mononuclear cells (PBMC) of chronically stress caregivers, is present in individuals with early Alzheimer’s disease. Chronic stress is a risk factor for Alzheimer’s, and may be an untapped biomarker for disease risk and pathology. METHODS/STUDY POPULATION: To collect preliminary data on the Conserved Transcriptional Response to Adversity profile in individuals with Alzheimer’s disease, we were able to utilize primary blood mononuclear cell samples from a small open label pilot study called Senolytic Therapy to Modulate the Progression of Alzheimer’s Disease, designed to clear stressed senescent cells. We hypothesized senolytics may beneficially reverse this stress profile. We developed a NanoString assay (measuring 19 inflammatory, 31 type-1 interferon, and 3 antibody synthesis genes) to compare these transcriptomic changes within 4 individuals measured at baseline, post-treatment with an intermittent 12-week senolytic therapy, and at an optional extended post-treatment follow-up time point > 3 months after their post treatment visit. RESULTS/ANTICIPATED RESULTS: There was relative downregulation of expression in transcription in 7 of 19 measured inflammatory genes (FOS, PTGS2, IL8, FOS, Il1b, JUNB, and JUN) in Alzheimer’s disease participants after receiving senolytic treatment (baseline vs. post-treatment). This is consistent with a decrease in the inflammatory arm of the Conserved Transcriptional Response to Adversity profile. These differences were not significant between baseline and the extended follow-up, indicative of a transient effect of senolytic. There were no changes in type 1 interferon or antibody synthesis genes. This data provides preliminary evidence for larger controlled studies to further establish this profile in Alzheimer’s disease, providing exciting evidence for transcript changes that may be reproducible with senolytic therapy. DISCUSSION/SIGNIFICANCE: Literature relevant to Alzheimer’s disease indicates global increases in inflammation paired with deficits in immune response, capturing some genes associated with the Conserved Transcriptional Response to Adversity. This profile may be a useful biomarker for prediction of disease severity or risk of dementia due to chronic stress.
OBJECTIVES/GOALS: The goal of this study was to develop a clinically applicable technique to increase the precision of in vivo dose monitoring during radiation therapy by mapping the dose deposition and resolving the temporal dose accumulation while the treatment is being delivered in real time. METHODS/STUDY POPULATION: Ironizing radiation acoustic imaging (iRAI) is a novel imaging concept with the potential to map the delivered radiation dose on anatomic structure in real time during external beam radiation therapy without interrupting the clinical workflow. The iRAI system consisted of a custom-designed two-dimensional (2D) matrix transducer array with integrated preamplifier array, driven by a clinic-ready ultrasound imaging platform. The feasibility of iRAI volumetric imaging in mapping dose delivery and real-time monitoring of temporal dose accumulation in a clinical treatment plan were investigated with a phantom, a rabbit model, and a cancer patient. RESULTS/ANTICIPATED RESULTS: The total dose deposition and temporal dose accumulation in 3D space of a clinical C-shape treatment plan in a targeted region were first imaged and optimized in a phantom. Then, semi-quantitative iRAI measurements were achieved in an in vivo rabbit model. Finally, for the first time, real-time visualization of radiation dose delivered deep in a patient with liver metastases was performed with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the radiation dose deposition during treatment. DISCUSSION/SIGNIFICANCE: Described here is the pioneering role of an iRAI system in mapping the 3D radiation dose deposition of a complex clinical radiotherapy treatment plan. iRAI offers a cost-effective and practical solution for real-time visualization of 3D radiation dose delivery, potentially leading to personalized radiotherapy with optimal efficacy and safety.