Clinical guideline highlights for the hospitalist: Management of COVID-19.

GUIDELINE TITLE: 2023 IDSA Guidelines on the Treatment and Management of Patients with COVID-19 RELEASE DATE: 06/26/2023 PRIOR VERSION (S): 2021 DEVELOPER: Infectious Diseases Society of America FUNDING SOURCE: Infectious Diseases Society of America TARGET POPULATION: Patients with COVID-19 Infection.

Spatiotemporally Explicit Epidemic Model for West Nile Virus Outbreak in Germany: An Inversely Calibrated Approach.

Since the first autochthonous transmission of West Nile Virus was detected in Germany (WNV) in 2018, it has become endemic in several parts of the country and is continuing to spread due to the attainment of a suitable environment for vector occurrence and pathogen transmission. Increasing temperature associated with a changing climate has been identified as a potential driver of mosquito-borne disease in temperate regions. This scenario justifies the need for the development of a spatially and temporarily explicit model that describes the dynamics of WNV transmission in Germany. In this study, we developed a process-based mechanistic epidemic model driven by environmental and epidemiological data. Functional traits of mosquitoes and birds of interest were used to parameterize our compartmental model appropriately. Air temperature, precipitation, and relative humidity were the key climatic forcings used to replicate the fundamental niche responsible for supporting mosquito population and infection transmission risks in the study area. An inverse calibration method was used to optimize our parameter selection. Our model was able to generate spatially and temporally explicit basic reproductive number (R0) maps showing dynamics of the WNV occurrences across Germany, which was strongly associated with the deviation from daily means of climatic forcings, signaling the impact of a changing climate in vector-borne disease dynamics. Epidemiological data for human infections sourced from Robert Koch Institute and animal cases collected from the Animal Diseases Information System (TSIS) of the Friedrich-Loeffler-Institute were used to validate model-simulated transmission rates. From our results, it was evident that West Nile Virus is likely to spread towards the western parts of Germany with the rapid attainment of environmental suitability for vector mosquitoes and amplifying host birds, especially short-distance migratory birds. Locations with high risk of WNV outbreak (Baden-Württemberg, Bavaria, Berlin, Brandenburg, Hamburg, North Rhine-Westphalia, Rhineland-Palatinate, Saarland, Saxony-Anhalt and Saxony) were shown on R0 maps. This study presents a path for developing an early warning system for vector-borne diseases driven by climate change.

Wilderness Medical Society Clinical Practice Guidelines for Prevention and Management of Avalanche and Nonavalanche Snow Burial Accidents: 2024 Update.

To provide guidance to the general public, clinicians, and avalanche professionals about best practices, the Wilderness Medical Society convened an expert panel to revise the evidence-based guidelines for the prevention, rescue, and resuscitation of avalanche and nonavalanche snow burial victims. The original panel authored the Wilderness Medical Society Practice Guidelines for Prevention and Management of Avalanche and Nonavalanche Snow Burial Accidents in 2017. A second panel was convened to update these guidelines and make recommendations based on quality of supporting evidence.

Bayesian Models with Spatial Correlation Improve the Precision of EQ-5D-5L Value Sets.

BACKGROUND: Health utilities from value sets for the EQ-5D-5L are commonly used in economic evaluations. We examined whether modeling spatial correlation among health states could improve the precision of the value sets. METHODS: Using data from 7 EQ-5D-5L valuation studies, we compared the predictive precision of the published linear model, a recently proposed cross-attribute level effects (CALE) model, and 2 Bayesian models with spatial correlation. Predictive precision was quantified through the root mean squared error (RMSE) for out-of-sample predictions of state-level mean utilities on omitting individual states, as well as omitting blocks of states. RESULTS: In all 7 countries, on omitting single health states, Bayesian models with spatial correlation improved upon the published linear model: the RMSEs for the originally published models, 0.050, 0.051, 0.060, 0.061, 0.039, 0.050, and 0.087 for Canada, China, Germany, Indonesia, Japan, Korea, and the Netherlands, respectively, could be reduced to 0.043, 0.042, 0.051, 0.054, 0.037, 0.037, and 0.085, respectively. On omitting blocks of health states, Bayesian models with spatial correlation led to smaller RMSEs in 3 countries, while the CALE model led to smaller RMSEs in the remaining 4 countries. DISCUSSION: Bayesian models incorporating spatial correlation and CALE models are promising for improving the precision of value sets for the EQ-5D-5L. The differential performance of the Bayesian models on omitting single states versus blocks of states suggests that designing valuation studies to capture more health states may further improve precision. We suggest that Bayesian and CALE models be considered as candidates when creating value sets and that alternative designs be explored; this is vital as the prediction errors in value sets need to be smaller than the minimal important difference of the instrument. HIGHLIGHTS: The accuracy of value sets of multi-attribute utility instruments is typically of the same order of magnitude as the instrument's minimal important difference and would benefit from improvement.Bayesian models with spatial correlation have been shown to improve value set accuracy in isolated cases.We showed that Bayesian approaches with spatial correlation improved predictive precision in 7 EQ-5D-5L valuation studies.We recommend that Bayesian models incorporating spatial correlation be considered when creating value sets and have provided code for fitting them.

Iterative Development of the Caregiver Wellness After Traumatic Brain Injury Program (CG-Well).

OBJECTIVES: (1) To iteratively design a web/phone-based intervention to support caregivers of adults acutely following traumatic brain injury (TBI), Caregiver Wellness (CG-Well), and (2) to obtain qualitative and quantitative feedback on CG-Well from experts and caregivers to refine the intervention. SETTING: A level I trauma and tertiary medical center. PARTICIPANTS: Convenience sample of a total of 19 caregivers and 25 experts. DESIGN: Multistep prospective study with iterative changes to CG-Well: (1) developed intervention content based on qualitative feedback from a prior study and literature review; (2) obtained qualitative feedback from 10 experts; (3) refined content using a modified Delphi approach involving 4 caregivers and 6 experts followed by qualitative interviews with 9 caregivers; (4) designed CG-Well website and videos; and (5) obtained feedback on program acceptability, appropriateness, and feasibility from 6 caregivers and 9 experts. INTERVENTIONS: CG-Well included content on TBI, self-care and support, and skill-building strategies delivered through a website and telephone calls. MAIN OUTCOME MEASURES: Qualitative data were analyzed using content analysis. Caregivers and experts completed Likert-type scales to rate module relevance, clarity, accuracy, utility and website acceptability, appropriateness, and feasibility (1 = strongly disagree to 5 = strongly agree). Means and standard deviations (SD) characterized ratings. RESULTS: Qualitative findings were instrumental in designing and refining CG-Well. Ratings were positive for modules (means and SD for relevant [4.9, 0.33], clear [4.6, 0.53], accurate [4.9, 0.33], and useful [5, 0]) and the website (means and SD for acceptable [4.8, 0.36], appropriate [4.8, 0.35], and feasible [4.8, 0.36]). CONCLUSIONS: The iterative design process for CG-Well resulted in a highly acceptable program. An early-stage randomized controlled trial is underway to estimate treatment effects for a future well-powered clinical trial.

Medication Safety in Breastfeeding.

Breastfeeding is universally recognized as the preferred method of infant nutrition, but is sometimes abbreviated because of fear of harm to the infant from maternal medication. The amount of medication that enters breast milk varies based on the maternal serum concentration and the pharmacologic properties of the medication. When prescribing medications for a breastfeeding patient, those with the lowest risk to the infant should be selected, and dosing should be before the infant's longest sleep interval. Prescribers should use current, accurate resources. LactMed is a convenient, government-sponsored, authoritative resource that lists safety information for many medications and is available free online. When mental health conditions occur during lactation, priority should be given to effectively treating the mother, often with medications that were effective during pregnancy. Most antidepressants are compatible with breastfeeding. Stimulant medications may decrease milk supply. Insulin, metformin, and second-generation sulfonylureas are generally preferred to treat diabetes mellitus during breastfeeding, but newer agents require caution because they have not been studied in lactation. Inhaled and nasal treatments for asthma and allergic rhinitis are unlikely to affect breastfed infants. Acetaminophen and ibuprofen are preferred analgesics during lactation. Maternal opioid use can cause infant sedation. Herbal supplements are concerning for risk of impurities and lack of study of effects on breastfed infants. Nonhormonal and progestin-only contraceptives are preferred over combination oral contraceptives. Contrast for computed tomography or magnetic resonance imaging is not concerning during lactation, but use of radiopharmaceuticals, such as iodine 131, can accumulate in the lactating breast and increase risk to the infant.

Reproducible changes in the anorexia nervosa gut microbiota following inpatient therapy remain distinct from non-eating disorder controls.

The composition of the gut microbiota in patients with anorexia nervosa (AN), and the ability of this microbial community to influence the host, remains uncertain. To achieve a broader understanding of the role of the intestinal microbiota in patients with AN, we collected fecal samples before and following clinical treatment at two geographically distinct eating disorder units (Center of Excellence for Eating Disorders [UNC-CH] and ACUTE Center for Eating Disorders [Denver Health]). Gut microbiotas were characterized in patients with AN, before and after inpatient treatment, and in non-eating disorder (non-ED) controls using shotgun metagenomic sequencing. The impact of inpatient treatment on the AN gut microbiota was remarkably consistent between eating disorder units. Although weight in patients with AN showed improvements, AN microbiotas post-treatment remained distinct from non-ED controls. Additionally, AN gut microbiotas prior to treatment exhibited more fermentation pathways and a lower ability to degrade carbohydrates than non-ED controls. As the intestinal microbiota can influence nutrient metabolism, our data highlight the complex microbial communities in patients with AN as an element needing further attention post inpatient treatment. Additionally, this study defines the effects of renourishment on the AN gut microbiota and serves as a platform to develop precision nutrition approaches to potentially mitigate impediments to recovery.

Advancing Antiracism in Community-Based Research Practices in Early Childhood and Family Mental Health.

Structural racism-the ways that institutional policies, practices, and other norms operate to create and sustain race-based inequities1-has historically been foundational to the operations of academic medical centers and research institutions. Since its inception, academic medicine has depended on the exploitation of vulnerable communities to achieve medical, educational, and research goals.2 Research practices have long ignored or taken advantage of the individuals purportedly benefiting from the research, a dynamic most manifestly true for Black, Indigenous, and People of Color (BIPOC) communities in the United States. Reflecting current practices in racial justice work, we intentionally use the term "BIPOC" to highlight shared experiences within racially and ethnically minoritized communities, given the history of White supremacy in the United States. We acknowledge limitations of this term, which collapses myriad unique communities and histories into one construct. Specifically, child and adolescent psychiatry has historically been driven by Eurocentric approaches, paradigms, and methodology. These nonparticipatory dominant research practices have contributed to a lack of culturally responsive interventions for BIPOC communities, a paucity of evidence-based practices with demonstrated effectiveness within BIPOC communities, and disparities in access and quality of care.3 Mental health research involving BIPOC communities has been replete with exploitation and inequality.2.

Predicting price intervals under exogenously induced stress.

We present an experimental protocol to examine the relationship between exogenously induced stress and confidence in a setting applicable to financial markets. Confidence will be measured by a prediction interval for a one period ahead price forecast, based on a series of 100 previous prices; narrower (wider) prediction intervals will be indicative of greater (lower) confidence. Stress will be induced using the Cold Pressor Arm Wrap, a variation of the Cold Pressor Test. Risk attitudes, and personality traits are also considered as mediating factors.

Chikungunya Beyond the Tropics: Where and When Do We Expect Disease Transmission in Europe?

Chikungunya virus disease (chikungunya) is a mosquito-borne infectious disease reported in at least 50 countries, mostly in the tropics. It has spread around the globe within the last two decades, with local outbreaks in Europe. The vector mosquito Aedes albopictus (Diptera, Culicidae) has already widely established itself in southern Europe and is spreading towards central parts of the continent. Public health authorities and policymakers need to be informed about where and when a chikungunya transmission is likely to take place. Here, we adapted a previously published global ecological niche model (ENM) by including only non-tropical chikungunya occurrence records and selecting bioclimatic variables that can reflect the temperate and sub-tropical conditions in Europe with greater accuracy. Additionally, we applied an epidemiological model to capture the temporal outbreak risk of chikungunya in six selected European cities. Overall, the non-tropical ENM captures all the previous outbreaks in Europe, whereas the global ENM had underestimated the risk. Highly suitable areas are more widespread than previously assumed. They are found in coastal areas of the Mediterranean Sea, in the western part of the Iberian Peninsula, and in Atlantic coastal areas of France. Under a worst-case scenario, even large areas of western Germany and the Benelux states are considered potential areas of transmission. For the six selected European cities, June-September (the 22th-38th week) is the most vulnerable time period, with the maximum continuous duration of a possible transmission period lasting up to 93 days (Ravenna, Italy).

Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice.

Anorexia nervosa (AN) is a psychiatric disorder that presents with profound weight dysregulation, metabolic disturbances, and an abnormal composition of gut microbial communities. As the intestinal microbiota can influence host metabolism, the impact of enteric microbial communities from patients with AN on host weight and adiposity was investigated. Germ-free (GF) mice were colonized with fecal microbiotas from either patients with AN (n = 4) prior to inpatient treatment (AN T1, n = 50 recipient mice), the same 4 patients following clinical renourishment (AN T2, n = 53 recipient mice), or age- and sex-matched non-AN controls (n = 4 human donors; non-AN, n = 50 recipient mice). Biological and fecal microbiota data were analyzed with linear mixed-effects models. Body weight did not differ significantly between AN recipient mice (T1 and T2) and non-AN recipient mice following 4 weeks of colonization. Enteric microbiotas from recipient mice colonized with AN T1 and AN T2 fecal microbiotas were more similar to each other compared with enteric microbiotas from non-AN recipient mice. Specific bacterial families in the Actinobacteria, Bacteroidetes, and Firmicutes phyla were significantly associated with body weight, fat mass, and cecum weight irrespective of the donor group. These data suggest that body weight, fat mass, and cecum weight of colonized GF mice are associated with human fecal microbes and independent of donor AN status, although additional analyses with larger cohorts are warranted.

Use of the composite asthma severity index in a pediatric subspecialty clinic.

BACKGROUND: The Composite Asthma Severity Index (CASI) is a comprehensive tool to assess asthma severity, which has been applied in the research setting. OBJECTIVE: To evaluate, in an outpatient setting, whether a CASI score accurately predicts asthma severity or control as determined by means of subspecialist assessment. Asthma Control Test (ACT) and childhood ACT (C-ACT) scores were generated to provide additional context for CASI scores in relationship to assessments using another clinical tool. METHODS: Children aged 5 to 18 years with a physician diagnosis of persistent asthma were recruited from a tertiary care center. A pediatric pulmonologist made determinations on each participant's asthma severity and control during a clinic visit. A CASI and ACT/C-ACT score was generated for each patient. Logistic regression and Spearman correlations were used to determine how well CASI scores predicted physician assessments. Agreement between ACT/C-ACT scores and physician assessment of asthma control was determined in supplemental analyses. RESULTS: CASI scores strongly predicted physician assessment of severity (Spearman correlation = 0.61, P < .001); unadjusted odds ratio (OR) equal to 36.67 (95% confidence interval [CI]: 8.83-152.34); and adjusted OR equal to 32.76 (95% CI: 85.70-188.44). In supplemental analyses, ACT/C-ACT scores strongly predicted physician assessment of control (Spearman correlation = 0.72, P < .001) with an unadjusted OR equal to 42.12 (95% CI: 13.34-133.00) and adjusted OR equal to 55.34 (95% CI: 13.62-224.89). CONCLUSION: Use of the CASI was feasible and accurately predicted physician assessments of asthma severity and control in this sample, which are not distinct entities. The CASI is a robust tool that may be used successfully in ambulatory pediatric asthma care.

Immune Profiling Enables Stratification of Patients With Active Tuberculosis Disease or Mycobacterium tuberculosis Infection.

BACKGROUND: Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) infection and is a major public health problem. Clinical challenges include the lack of a blood-based test for active disease. Current blood-based tests, such as QuantiFERON (QFT) do not distinguish active TB disease from asymptomatic Mtb infection. METHODS: We hypothesized that TruCulture, an immunomonitoring method for whole-blood stimulation, could discriminate active disease from latent Mtb infection (LTBI). We stimulated whole blood from patients with active TB and compared with LTBI donors. Mtb-specific antigens and live bacillus Calmette-Guérin (BCG) were used as stimuli, with direct comparison to QFT. Protein analyses were performed using conventional and digital enzyme-linked immunosorbent assay (ELISA), as well as Luminex. RESULTS: TruCulture showed discrimination of active TB cases from LTBI (P < .0001, AUC = .81) compared with QFT (P = .45, AUC = .56), based on an interferon γ (IFNγ) readout after Mtb antigen (Ag) stimulation. This result was replicated in an independent cohort (AUC = .89). In exploratory analyses, TB stratification could be further improved by the Mtb antigen to BCG IFNγ ratio (P < .0001, AUC = .91). Finally, the combination of digital ELISA and transcriptional analysis showed that LTBI donors with high IFNγ clustered with patients with TB, suggesting the possibility to identify subclinical disease. CONCLUSIONS: TruCulture offers a next-generation solution for whole-blood stimulation and immunomonitoring with the possibility to discriminate active and latent infection.

Deriving risk maps from epidemiological models of vector borne diseases: State-of-the-art and suggestions for best practice.

Epidemiological models (EMs) are widely used to predict the temporal outbreak risk of vector-borne diseases (VBDs). EMs typically use the basic reproduction number (R0), a threshold quantity, to indicate risk. To provide an overall view of the risk, these model outputs can be transformed into spatial risk maps, using various aggregation methods (e.g. average R0 over time, cumulative number of days with R0 > 1). However, there is no standardized methodology available for this. Depending on the specific aggregation methods used, the yielded spatial risk maps may have considerably different interpretations. Additionally, the method used to visualize the aggregated data also affects the perceived spatial patterns. In this review, we compare commonly used aggregation and visualization methods and discuss the respective interpretation of risk maps. Research publications using epidemiological modelling methods were drawn from Web of Science. Only publications containing maps of R0 transformed from EMs were considered for the analysis. An example EM was applied to illustrate how aggregation and visualization methods affect the final presentations of risk maps. Risk maps can be generated to show duration, intensity and spatio-temporal dynamics of potential outbreak risk of VBDs. We show that 1) different temporal aggregation methods lead to different interpretations; 2) similar spatial patterns do not necessarily bear the same meaning; 3) visualization methods considerably affect how results are perceived, and thus should be applied with caution. We recommend mapping both intensity and duration of the VBD outbreak risk, using small time-steps to show spatio-temporal dynamics when possible.

A Comprehensive Review of Manifestations of Novel Coronaviruses in the Context of Deadly COVID-19 Global Pandemic.

Since December 2019, the global pandemic caused by the highly infectious novel coronavirus 2019-nCoV (COVID-19) has been rapidly spreading. As of April 2020, the outbreak has spread to over 210 countries, with over 2,400,000 confirmed cases and over 170,000 deaths.1 COVID-19 causes a severe pneumonia characterized by fever, cough and shortness of breath. Similar coronavirus outbreaks have occurred in the past causing severe pneumonia like COVID-19, most recently, severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV). However, over time, SARS-CoV and MERS-CoV were shown to cause extrapulmonary signs and symptoms including hepatitis, acute renal failure, encephalitis, myositis and gastroenteritis. Similarly, sporadic reports of COVID-19 related extrapulmonary manifestations emerge. Unfortunately, there is no comprehensive summary of the multiorgan manifestations of COVID-19, making it difficult for clinicians to quickly educate themselves about this highly contagious and deadly pathogen. What is more, is that SARS-CoV and MERS-CoV are the closest humanity has come to combating something similar to COVID-19, however, there exists no comparison between the manifestations of any of these novel coronaviruses. In this review, we summarize the current knowledge of the manifestations of the novel coronaviruses SARS-CoV, MERS-CoV and COVID-19, with a particular focus on the latter, and highlight their differences and similarities.

3125 steps to perfect health: a nonparametric approach to developing the EQ-5D-5L value set.

PURPOSE: The EQ-5D-5L is a commonly used instrument for assessing the utility of different health states. Health state utility values are a key component of health technology evaluations. Such evaluations are used to support evidence-based decisions surrounding health resource allocations and therefore rely on the accuracy of the valuation set used. This paper takes an alternative approach to developing an EQ-5D-5L value set for Canada. The aim is to introduce a robust method that is likely to generate a value set with improved accuracy and that can be used to generate value sets for other populations without the need for modification. METHODS: The common approach to developing a valuation set for preference-based instruments is to ask a population sample to value a subset of the health states using an established preference elicitation technique. The relationship between the elicited health states and the preferences is used to inform a model to predict the utility values for the unsampled health states described by the instrument. The true relationship is unknown and the functional forms chosen in the modelling process vary across valuation studies. We use nonparametric local constant regression to estimate an EQ-5D-5L value set for Canada and propose this method as an alternative for value set development because it does not require the specification of a functional form at the outset. RESULTS: Compared to the existing valuation model for Canada, the nonparametric method improves in-sample fit, reducing the average squared prediction error by 94.46% and the mean absolute error by 79.37%. In four of five sets of out-of-sample studies, this new approach performs significantly better than 9 comparison models. Despite lacking any restriction on the functional form of the resulting valuations, the valuation set generated by this new approach is logically consistent. 100% of the pairs of health states in which one state is dominant have health state values which respect this ordering. The value set also appears to differ substantially from the comparators. CONCLUSIONS: Overall, the results suggest that nonparametric regression is a promising tool for the estimation of EQ-5D-5L valuation sets and may be a good option in a standardised methodology for value set development.

The Efficacy of the After-visit Summary in Medication Recall Among Glaucoma Patients.

PRéCIS:: To assess the after-visit summary (AVS) as a tool for glaucoma medication recall. Medication recall was associated with level of education and complexity of medication regimen. Receiving an AVS was not associated with better medication recall. PURPOSE: The purpose of this study was to determine whether patients given the AVS have better or worse glaucoma medication recall. MATERIALS AND METHODS: Observational clinical study. Adults on ≥1 glaucoma medications examined between June 30, 2017 and August 2, 2017. DATA COLLECTION: in-person questionnaire and retrospective chart review. Self-reported glaucoma medications compared with prescribed glaucoma medication regimen verified by electronic medical record. Medication recall assessed using 3-point scoring: 1 point each for; (1) name or color of bottle or cap; (2) treatment eye(s); and (3) dosing regimen. DATA ANALYSIS: 2-sample Welch t test, 2-proportion z-test, analysis of variance, univariate, and multivariate regression. RESULTS: A total of 118 patients enrolled: age 69.7±12.9 years (mean±SD), 55.9% of patients had received an AVS at the previous visit. Of these, 33.3% reported receiving an AVS, 51.2% reported not receiving one (15.1% did not recall or respond). Patients who had received AVSs had lower medication recall scores than those who did not (2.4±1.0 vs. 2.7±0.6, P=0.04). Receipt of an AVS was associated with having Nisha Chadha as their provider (P=0.01), fewer days since prior visit (P=0.0001), and medication regimen change at prior visit (P<0.0001). Multivariate analysis revealed completion of associate's degree or higher and fewer prescribed medications to be independent predictors of higher recall score (P=0.0002 and 0.002). CONCLUSIONS: AVSs were conceived to enhance patient care. This study indicates this goal is not achieved consistently. Less education and more complex medication regimens were identified as barriers to medication recall. Additional investigations should explore if modifying this document and enhanced explanation of its use will impact medication recall and health outcomes.

Sequence variant analysis reveals poor correlations in microbial taxonomic abundance between humans and mice after gnotobiotic transfer.

Transplanting human gut microbiotas into germ-free (GF) mice is a popular approach to disentangle cause-and-effect relationships between enteric microbes and disease. Algorithm development has enabled sequence variant (SV) identification from 16S rRNA gene sequence data. SV analyses can identify which donor taxa colonize recipient GF mice, and how SV abundance in humans is replicated in these mice. Fecal microbiotas from 8 human subjects were used to generate 77 slurries, which were transplanted into 153 GF mice. Strong correlations between fecal and slurry microbial communities were observed; however, only 42.15 ± 9.95% of SVs successfully transferred from the donor to the corresponding recipient mouse. Firmicutes had a particularly low transfer rate and SV abundance was poorly correlated between donor and recipient pairs. Our study confirms human fecal microbiotas colonize formerly GF mice, but the engrafted community only partially resembles the input human communities. Our findings emphasize the importance of reporting a standardized transfer rate and merit the exploration of other animal models or in silico tools to understand the relationships between human gut microbiotas and disease.