Hot of Not: Physiological versus Meteorological Heatwaves-Support for a Mean Temperature Threshold

The aim of this study was to determine whether a revised heat warning threshold provides an enhanced predictive tool for increases in Emergency Department heat-related presentations in Canberra, Australia. All Emergency Department triage records containing the word "heat", as well as those diagnosing a heat related illness for the summer periods 2013/2014, 2014/2015, and 2015/2016 were searched. Then a medical record review was conducted to confirm that the patient's presentation was related to environmental heat, which was defined by the final clinical diagnosis, presentation complaint and details of the patient's treatment. Researchers then compared this presentation data, to a mean threshold formula. The mean threshold formula included the past three consecutive daily mean temperatures and the last measured temperature upon presentation. This formula was designed to take into account the variance of night-time lows, with concurrent daily ambient temperatures, and was used to determine whether there was a correlation between heat-related presentations and increasing mean temperatures. Heat-related presentations appeared to occur when the mean threshold temperature reached 25 °C (77 °F), with significant increases when the mean threshold reached 30 °C (86 °F). These results confirm that a mean temperature of 30 °C corresponds to a relevant local public health heat-related threat

Text-Speech Alignment: A Robin Hood Approach for Endangered Languages

Forced alignment automatically aligns audio recordings of spoken language with transcripts at the level of individual sounds, greatly reducing the time required to prepare data for linguistic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data on data from a highly endangered language. At least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by automatic alignment with minimal training data. Underutilized legacy data exist for many endangered languages. This creates both a need and an opportunity to leverage new technology

The application of retinal fundus camera imaging in dementia:A systematic review

INTRODUCTION: The ease of imaging the retinal vasculature, and the evolving evidence suggesting this microvascular bed might reflect the cerebral microvasculature, presents an opportunity to investigate cerebrovascular disease and the contribution of microvascular disease to dementia with fundus camera imaging. METHODS: A systematic review and meta-analysis was carried out to assess the measurement of retinal properties in dementia using fundus imaging. RESULTS: Ten studies assessing retinal properties in dementia were included. Quantitative measurement revealed significant yet inconsistent pathologic changes in vessel caliber, tortuosity, and fractal dimension. Retinopathy was more prevalent in dementia. No association of age-related macular degeneration with dementia was reported. DISCUSSION: Inconsistent findings across studies provide tentative support for the application of fundus camera imaging as a means of identifying changes associated with dementia. The potential of fundus image analysis in differentiating between dementia subtypes should be investigated using larger well-characterized samples. Future work should focus on refining and standardizing methods and measurements

A Robin Hood approach to forced alignment: English-trained algorithms and their use on Australian languages

Forced alignment automatically aligns audio recordings of spoken language with transcripts at the segment level, greatly reducing the time required to prepare data for phonetic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data. For at least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by automatic alignment with minimal training data. Consonants provided significantly more challenges for forced alignment

Investigating the Impact of Delivery Routes for Exon Skipping Therapies in the CNS of DMD Mouse Models

Nucleic acid-based therapies have demonstrated great potential for the treatment of monogenetic diseases, including neurologic disorders. To date, regulatory approval has been received for a dozen antisense oligonucleotides (ASOs); however, these chemistries cannot readily cross the blood–brain barrier when administered systemically. Therefore, an investigation of their potential effects within the central nervous system (CNS) requires local delivery. Here, we studied the brain distribution and exon-skipping efficacy of two ASO chemistries, PMO and tcDNA, when delivered to the cerebrospinal fluid (CSF) of mice carrying a deletion in exon 52 of the dystrophin gene, a model of Duchenne muscular dystrophy (DMD). Following intracerebroventricular (ICV) delivery (unilateral, bilateral, bolus vs. slow rate, repeated via cannula or very slow via osmotic pumps), ASO levels were quantified across brain regions and exon 51 skipping was evaluated, revealing that tcDNA treatment invariably generates comparable or more skipping relative to that with PMO, even when the PMO was administered at higher doses. We also performed intra-cisterna magna (ICM) delivery as an alternative route for CSF delivery and found a biased distribution of the ASOs towards posterior brain regions, including the cerebellum, hindbrain, and the cervical part of the spinal cord. Finally, we combined both ICV and ICM injection methods to assess the potential of an additive effect of this methodology in inducing efficient exon skipping across different brain regions. Our results provide useful insights into the local delivery and associated efficacy of ASOs in the CNS in mouse models of DMD. These findings pave the way for further ASO-based therapy application to the CNS for neurological disease

General practitioner referrals to one-stop clinics for symptoms that could be indicative of cancer: a systematic review of use and clinical outcomes.

BACKGROUND: One-stop clinics provide comprehensive diagnostic testing in one outpatient appointment. They could benefit patients with conditions, such as cancer, whose outcomes are improved by early diagnosis, and bring efficiency savings for health systems. OBJECTIVE: To assess the use and outcomes of one-stop clinics for symptoms where cancer is a possible diagnosis. DESIGN AND SETTING: Systematic review of studies reporting use and outcomes of one-stop clinics in primary care patients. METHOD: We searched MEDLINE, Embase, and Cochrane Library for studies assessing one-stop clinics for adults referred after presenting to primary care with any symptom that could be indicative of cancer. Study selection was carried out independently in duplicate with disagreements resolved through discussion. RESULTS: Twenty-nine studies were identified, most were conducted in the UK and observational in design. Few included a comparison arm. A pooled comparison of the cancer conversion rate of one-stop and multi-stop clinics was only possible for breast symptoms, and we found no significant difference. One-stop clinics were associated with significant reductions in the interval from referral to testing (15 versus 75 days) and more patients diagnosed on the same day (79% versus 25%) compared to multi-stop pathways. The majority of patients and GPs found one-stop clinics to be acceptable. CONCLUSION: This review found one-stop clinics were associated with reduced time from referral to testing, increased same day diagnoses, and were acceptable to patients and GPs. Our conclusions are limited by high levels of heterogeneity, scarcity of comparator groups, and the overwhelmingly observational nature of included studies

Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT

Background: Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose: To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods: This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs. Readers used only CT imaging data and provided an estimate of malignancy risk and a management recommendation for each case without and with CAD. The effect of CAD on average reader diagnostic performance was assessed using the Obuchowski-Rockette and Dorfman-Berbaum-Metz method to calculate estimates of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Multirater Fleiss κ statistics were used to measure interobserver agreement for malignancy risk and management recommendations. Results: A total of 300 chest CT scans of IPNs with maximal diameters of 5-30 mm (50.0% malignant) were reviewed by 12 readers (six radiologists, six pulmonologists) (patient median age, 65 years; IQR, 59-71 years; 164 [55%] men). Readers\u27 average AUC improved from 0.82 to 0.89 with CAD (P \u3c .001). At malignancy risk thresholds of 5% and 65%, use of CAD improved average sensitivity from 94.1% to 97.9% (P = .01) and from 52.6% to 63.1% (P \u3c .001), respectively. Average reader specificity improved from 37.4% to 42.3% (P = .03) and from 87.3% to 89.9% (P = .05), respectively. Reader interobserver agreement improved with CAD for both the less than 5% (Fleiss κ, 0.50 vs 0.71; P \u3c .001) and more than 65% (Fleiss κ, 0.54 vs 0.71; P \u3c .001) malignancy risk categories. Overall reader interobserver agreement for management recommendation categories (no action, CT surveillance, diagnostic procedure) also improved with CAD (Fleiss κ, 0.44 vs 0.52; P = .001). Conclusion: Use of computer-aided diagnosis improved estimation of indeterminate pulmonary nodule malignancy risk on chest CT scans and improved interobserver agreement for both risk stratification and management recommendations

Diversity of symptom phenotypes in SARS-CoV-2 community infections observed in multiple large datasets

Variability in case severity and in the range of symptoms experienced has been apparent from the earliest months of the COVID-19 pandemic. From a clinical perspective, symptom variability might indicate various routes/mechanisms by which infection leads to disease, with different routes requiring potentially different treatment approaches. For public health and control of transmission, symptoms in community cases were the prompt on which action such as PCR testing and isolation was taken. However, interpreting symptoms presents challenges, for instance in balancing sensitivity and specificity of individual symptoms with the need to maximise case finding, whilst managing demand for limited resources such as testing. For both clinical and transmission control reasons, we require an approach that allows for the possibility of distinct symptom phenotypes, rather than assuming variability along a single dimension. Here we address this problem by bringing together four large and diverse datasets deriving from routine testing, a population-representative household survey and participatory smartphone surveillance in the United Kingdom. Through use of cutting-edge unsupervised classification techniques from statistics and machine learning, we characterise symptom phenotypes among symptomatic SARS-CoV-2 PCR-positive community cases, making comparisons across datasets and by age bands. While we observe separation due to the total number of symptoms experienced by cases, we also see a separation of symptoms into gastrointestinal, respiratory and other types, and different symptom co-occurrence patterns at the extremes of age. In this way, we are able to demonstrate the deep structure of symptoms of COVID-19 without usual biases due to study design.Comment: 52 pages; 25 figure

Reexamining evidence-based practice in community corrections: beyond 'a confined view' of what works

This article aims to reexamine the development and scope of evidence-based practice (EBP) in community corrections by exploring three sets of issues. Firstly, we examine the relationships between the contested purposes of community supervision and their relationships to questions of evidence. Secondly, we explore the range of forms of evidence that might inform the pursuit of one purpose of supervision—the rehabilitation of offenders—making the case for a fuller engagement with “desistance” research in supporting this process. Thirdly, we examine who can and should be involved in conversations about EBP, arguing that both ex/offenders’ and practitioners’ voices need to be respected and heard in this debate

Standardized Interpretation of Chest Radiographs in Cases of Pediatric Pneumonia From the PERCH Study.

BACKGROUND.: Chest radiographs (CXRs) are a valuable diagnostic tool in epidemiologic studies of pneumonia. The World Health Organization (WHO) methodology for the interpretation of pediatric CXRs has not been evaluated beyond its intended application as an endpoint measure for bacterial vaccine trials. METHODS.: The Pneumonia Etiology Research for Child Health (PERCH) study enrolled children aged 1-59 months hospitalized with WHO-defined severe and very severe pneumonia from 7 low- and middle-income countries. An interpretation process categorized each CXR into 1 of 5 conclusions: consolidation, other infiltrate, both consolidation and other infiltrate, normal, or uninterpretable. Two members of a 14-person reading panel, who had undertaken training and standardization in CXR interpretation, interpreted each CXR. Two members of an arbitration panel provided additional independent reviews of CXRs with discordant interpretations at the primary reading, blinded to previous reports. Further discordance was resolved with consensus discussion. RESULTS.: A total of 4172 CXRs were obtained from 4232 cases. Observed agreement for detecting consolidation (with or without other infiltrate) between primary readers was 78% (κ = 0.50) and between arbitrators was 84% (κ = 0.61); agreement for primary readers and arbitrators across 5 conclusion categories was 43.5% (κ = 0.25) and 48.5% (κ = 0.32), respectively. Disagreement was most frequent between conclusions of other infiltrate and normal for both the reading panel and the arbitration panel (32% and 30% of discordant CXRs, respectively). CONCLUSIONS.: Agreement was similar to that of previous evaluations using the WHO methodology for detecting consolidation, but poor for other infiltrates despite attempts at a rigorous standardization process