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Highly pathogenic avian influenza viruses (HPAIVs) of subtype H5 of the Gs/GD/96 lineage remain a major threat to poultry due to endemicity in wild birds. H5N1 HPAIVs from this lineage were detected in 2021 in the United States (U.S.) and since then have infected many wild and domestic birds. We evaluated the pathobiology of an early U.S. H5N1 HPAIV (clade 2.3.4.4b, 2021) and two H5N8 HPAIVs from previous outbreaks in the U.S. (clade 2.3.4.4c, 2014) and Europe (clade 2.3.4.4b, 2016) in chickens and turkeys. Differences in clinical signs, mean death times (MDTs), and virus transmissibility were found between chickens and turkeys. The mean bird infective dose (BID50) of the 2021 H5N1 virus was approximately 2.6 log10 50% embryo infective dose (EID50) in chickens and 2.2 log10 EID50 in turkeys, and the virus transmitted to contact-exposed turkeys but not chickens. The BID50 for the 2016 H5N8 virus was also slightly different in chickens and turkeys (4.2 and 4.7 log10 EID50, respectively); however, the BID50 for the 2014 H5N8 virus was higher for chickens than turkeys (3.9 and ~0.9 log10 EID50, respectively). With all viruses, turkeys took longer to die (MDTs of 2.6–8.2 days for turkeys and 1–4 days for chickens), which increased the virus shedding period and facilitated transmission to contacts. [ABSTRACT FROM AUTHOR]

Background: Given increasing community-based and off-label use of ketamine for psychiatric indications, we examined current informed consent processes from a convenience sample of outpatient ketamine clinics to identify areas of congruence with current evidence and opportunities for growth.Methods: Using a rubric developed from existing practice guidelines, we conducted an exploratory analysis of informed consent documents (IC-Docs) from 23 American clinics offering ketamine as a psychiatric treatment. Domains assessed included clinical content, procedures, and syntax.Results: Participating clinics (23/288) varied widely in their constitution, training, and services provided. We found that IC-Docs addressed a majority of consent elements, though did so variably on an item-level. Areas for improvement included communication around long-term adverse effects, treatment alternatives, medical/psychiatric evaluation prior to treatment, medical/psychological support during treatment, adjunctive psychological interventions, and subjective/dissociative-type effects. All forms were limited by poor readability.Limitations: Our study was limited by convenience sampling along with possible underestimation of verbal consent processes.Conclusions: As ketamine continues to emerge as a psychiatric intervention, both patients and providers will benefit from a deliberate consent process informed by scientific, ethical, and pragmatic factors toward the goal of shared decision-making regarding treatment. [ABSTRACT FROM AUTHOR]

Objective: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. Materials and methods: Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms’ performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. Results: Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. Discussion: The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations. Conclusion: Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC’s autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems. [ABSTRACT FROM AUTHOR]

Drug overdose is the leading cause of unintentional injury-associated death in the United States. Among 70,237 fatal drug overdoses in 2017, prescription opioids were involved in 17,029 (24.2%) (1). Higher rates of opioid-related deaths have been recorded in nonmetropolitan (rural) areas (2). In 2017, 14 rural counties were among the 15 counties with the highest opioid prescribing rates.* Higher opioid prescribing rates put patients at risk for addiction and overdose (3). Using deidentified data from the Athenahealth electronic health record (EHR) system, opioid prescribing rates among 31,422 primary care providers† in the United States were analyzed to evaluate trends from January 2014 to March 2017. This analysis assessed how prescribing practices varied among six urban-rural classification categories of counties, before and after the March 2016 release of CDC's Guideline for Prescribing Opioids for Chronic Pain (Guideline) (4). Patients in noncore (the most rural) counties had an 87% higher chance of receiving an opioid prescription compared with persons in large central metropolitan counties during the study period. Across all six county groups, the odds of receiving an opioid prescription decreased significantly after March 2016. This decrease followed a flat trend during the preceding period in micropolitan and large central metropolitan county groups; in contrast, the decrease continued previous downward trends in the other four county groups. Data from EHRs can effectively supplement traditional surveillance methods for monitoring trends in opioid prescribing and other areas of public health importance, with minimal lag time under ideal conditions. As less densely populated areas appear to indicate both substantial progress in decreasing opioid prescribing and ongoing need for reduction, community health care practices and intervention programs must continue to be tailored to community characteristics. [ABSTRACT FROM AUTHOR]

Objectives: To determine if identifiable hepatic textural features are present at abdominal CT in patients with colorectal cancer (CRC) prior to the development of CT-detectable hepatic metastases.Methods: Four filtration-histogram texture features (standard deviation, skewness, entropy and kurtosis) were extracted from the liver parenchyma on portal venous phase CT images at staging and post-treatment surveillance. Surveillance scans corresponded to the last scan prior to the development of CT-detectable CRC liver metastases in 29 patients (median time interval, 6 months), and these were compared with interval-matched surveillance scans in 60 CRC patients who did not develop liver metastases. Predictive models of liver metastasis-free survival and overall survival were built using regularised Cox proportional hazards regression.Results: Texture features did not significantly differ between cases and controls. For Cox models using all features as predictors, all coefficients were shrunk to zero, suggesting no association between any CT texture features and outcomes. Prognostic indices derived from entropy features at surveillance CT incorrectly classified patients into risk groups for future liver metastases (p < 0.001).Conclusions: On surveillance CT scans immediately prior to the development of CRC liver metastases, we found no evidence suggesting that changes in identifiable hepatic texture features were predictive of their development.Key Points: • No correlation between liver texture features and metastasis-free survival was observed. • Liver texture features incorrectly classified patients into risk groups for liver metastases. • Standardised texture analysis workflows need to be developed to improve research reproducibility. [ABSTRACT FROM AUTHOR]

Rationale: The IFN-γ release assays and tuberculin skin tests are used to support the diagnosis of both latent and active tuberculosis. However, we previously demonstrated that a negative tuberculin test in active tuberculosis is associated with disseminated disease and death. It is unknown whether the same associations exist for IFN-γ release assays.Objectives: To determine the association between these tests and site of tuberculosis and death among persons with active tuberculosis.Methods: We analyzed IFN-γ release assays and tuberculin test results for all persons with culture-confirmed tuberculosis reported to the U.S. National Tuberculosis Surveillance System from 2010 to 2014. We used logistic regression to calculate the association between these tests and site of disease and death.Measurements and Main Results: A total of 24,803 persons with culture-confirmed tuberculosis had either of these test results available for analysis. Persons with a positive tuberculin test had lower odds of disseminated disease (i.e., miliary or combined pulmonary and extrapulmonary disease), but there was no difference in the odds of disseminated disease with a positive IFN-γ release assay. However, persons who were positive to either of these tests had lower odds of death. An indeterminate IFN-γ release assay result was associated with greater odds of both disseminated disease and death.Conclusions: Despite perceived equivalence in clinical practice, IFN-γ release assays and tuberculin test results have different associations with tuberculosis site, yet similar associations with the risk of death. Furthermore, an indeterminate IFN-γ release assay result in a person with active tuberculosis is not unimportant, and rather carries greater odds of disseminated disease and death. Prospective study may improve our understanding of the underlying mechanisms by which these tests are associated with disease localization and death. [ABSTRACT FROM AUTHOR]

Features the environmental science software programs and databases released by the U.S. Environmental Protection Agency. Source Ranking Database on potential indoor air pollution sources; Use Cluster Scoring System for performing comparative analysis for a variety of chemicals used for a single task.

Focuses on workplace exposures to hazardous materials and comments on the key to detecting occupational illness. Possible problems in diagnosis when that ailment results from repetitive motion or from long-term exposures; Obtaining the occupational history; Diagram showing the initial clinical approach to the recognition of illness caused by occupational exposure; Essential elements of the occupational history and questionnaire.