3,772 research outputs found

    Audio-based AI classifiers show no evidence of improved COVID-19 diagnosis over simple symptom checkers

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    Recent work has reported that respiratory audio-trained AI classifiers can accurately predict SARS-CoV-2 infection status. However, it has not yet been determined whether such model performance is driven by latent audio biomarkers with true causal links to SARS-CoV-2 infection or by confounding effects present in observational studies, such as recruitment bias. Here, we undertake a large-scale study of audio-based AI classifiers, as part of the UK government’s pandemic response. We collect a dataset of audio recordings from 67,842 individuals, with linked metadata, of whom 23,514 had positive PCR tests for SARS-CoV-2. In an unadjusted analysis, similar to that in previous works, AI classifiers predict SARS-CoV-2 infection status with high accuracy (ROC-AUC=0.846 [0.838–0.854]). However, after matching on measured confounders, such as self-reported symptoms, performance is much weaker (ROC-AUC=0.619 [0.594–0.644]). Upon quantifying the utility of audio-based classifiers in practical settings, we find them to be outperformed by predictions based on user-reported symptoms. We make best-practice recommendations for handling recruitment bias, and for assessing audio-based classifiers by their utility in relevant practical settings. Our work provides novel insights into the value of AI audio analysis and the importance of study design and treatment of confounders in AI-enabled diagnostics

    A worldwide population of Streptococcus pyogenes strains circulating among school-aged children in Auckland, New Zealand: a genomic epidemiology analysisResearch in context

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    Summary: Background: Acute rheumatic fever (ARF) is a serious post-infectious sequala of Group A Streptococcus (GAS, Streptococcus pyogenes). In New Zealand (NZ) ARF is a major cause of health inequity. This study describes the genomic analysis of GAS isolates associated with childhood skin and throat infections in Auckland NZ. Methods: Isolates (n = 469) collected between March 2018 and October 2019 from the throats and skin of children (5–14 years) underwent whole genomic sequencing. Equal representation across three ethnic groups was ensured through sample quotas with isolates obtained from Indigenous Māori (n = 157, 33%), NZ European/Other (n = 149, 32%) and Pacific Peoples children (n = 163, 35%). Using in silico techniques isolates were classified, assessed for diversity, and examined for distribution differences between groups. Comparisons were also made with GAS strains identified globally. Findings: Genomic analysis revealed a diverse population consisting of 65 distinct sequence clusters. These sequence clusters spanned 49 emm-types, with 11 emm-types comprised of several, distinct sequence clusters. There is evidence of multiple global introductions of different lineages into the population, as well as local clonal expansion. The M1UK lineage comprised 35% of all emm1 isolates. Interpretation: The GAS population was characterized by a high diversity of strains, resembling patterns observed in low- and middle-income countries. However, strains associated with outbreaks and antimicrobial resistance commonly found in high-income countries were also observed. This unique combination poses challenges for vaccine development, disease management and control. Funding: The work was supported by the Health Research Council of New Zealand (HRC), award number 16/005

    A randomised phase 2 study of intermittent versus continuous dosing of dabrafenib plus trametinib in patients with BRAFV600 mutant advanced melanoma (INTERIM)

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    Background: BRAF+MEK inhibitors extend life expectancy of patients with BRAFV600 mutant advanced melanoma. Acquired resistance limits duration of benefit, but preclinical and case studies suggest intermittent dosing could overcome this limitation. INTERIM was a phase 2 trial evaluating an intermittent dosing regimen. Methods: Patients with BRAFV600 mutant advanced melanoma due to start dabrafenib+trametinib were randomised to receive either continuous (CONT), or intermittent (INT; dabrafenib d1–21, trametinib d1–14 every 28 days) dosing. A composite primary endpoint included progression-free survival (PFS) and quality of life (QoL). Secondary endpoints included response rate (ORR), overall survival (OS) and adverse events (AEs). Mutant BRAFV600E ctDNA was measured by droplet digital PCR (ddPCR), using mutant allele frequency of > 1 % as the detection threshold. Results: 79 patients (39 INT, 40 CONT) were recruited; median age 67 years, 65 % AJCC (7th ed) stage IV M1c, 29 % had brain metastases. With 19 months median follow-up, INT was inferior in all efficacy measures: median PFS 8.5 vs 10.7mo (HR 1.39, 95 %CI 0.79–2.45, p = 0.255); median OS 18.1mo vs not reached (HR 1.69, 95 %CI 0.87–3.28, p = 0.121), ORR 57 % vs 77 %. INT patients experienced fewer treatment-related AEs (76 % vs 88 %), but more grade > 3 AEs (53 % vs 42 %). QoL favoured CONT. Detection of BRAFV600E ctDNA prior to treatment correlated with worse OS (HR 2.55, 95 %CI 1.25–5.21, p = 0.01) in both arms. A change to undetected during treatment did not significantly predict better OS. Conclusion: INTERIM findings are consistent with other recent clinical trials reporting that intermittent dosing does not improve efficacy of BRAF+MEK inhibitors

    Effects of Face-to-Face and eHealth Blended Interventions on Physical Activity, Diet, and Weight-Related Outcomes among Adults: A Systematic Review and Meta-Analysis

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    An increasing number of studies are blending face-to-face interventions and electronic health (eHealth) interventions to jointly promote physical activity (PA) and diet among people. However, a comprehensive summary of these studies is lacking. This study aimed to synthesize the characteristics of blended interventions and meta-analyze the effectiveness of blended interventions in promoting PA, diet, and weight-related outcomes among adults. Following the PRISMA guidelines, PubMed, SPORTDiscus, PsycINFO, Embase, and Web of Science were systematically searched to identify eligible articles according to a series of inclusion criteria. The search was limited to English language literature and publication dates between January 2002 and July 2022. Effect sizes were calculated as standardized mean difference (SMD) for three intervention outcomes (physical activity, healthy diet, and weight-related). Random effect models were used to calculate the effect sizes. A sensitivity analysis and publication bias tests were conducted. Of the 1561 identified studies, 17 were eligible for the systematic review. Studies varied in participants, intervention characteristics, and outcome measures. A total of 14 studies were included in the meta-analyses. There was evidence of no significant publication bias. The meta-analyses indicated that the blended intervention could lead to a significant increase in walking steps (p p = 0.01), and diet quality (p = 0.044), a significant decrease in energy intake (p = 0.004), weight (p p p = 0.008), but had no influence on more moderate-to-vigorous physical activity (MVPA) or fruit and vegetable intake among adults, compared with a control group. The study findings showed that blended interventions achieve preliminary success in promoting PA, diet, and weight-related outcomes among adults. Future studies could improve the blended intervention design to achieve better intervention effectiveness

    Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

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    Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

    Assessing alternative occupations for truck drivers in an emerging era of autonomous vehicles

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    This study identifies alternative occupations for heavy truck drivers and evaluates the relative attractiveness of these alternatives in terms of compensation, ease of entry and future job growth. We also evaluate the geographic correspondence between truck driving jobs and available alternatives within the same state given research evidence about geographic rigidities in job seekers. We develop two strategies for identifying alternative occupations. One approach suggests that there may not be sufficient job alternatives for a displacement of 35% or more of the truck-driving workforce. The second alternative suggests insufficient job alternatives when displacement levels exceed 50%. Despite these varied pictures, our results present some important trends among job alternatives. Most alternatives were in Job Zones 1 and 2 which require little additional training and/or education for displaced drivers. Unfortunately, the identified alternatives paid lower wages than truck-driving jobs, indicating a potential loss of income. The projected demand for alternative jobs also varied by occupation. Some alternatives are projected to have employment growth, while others are projected to have job losses. Lastly, there were geographic trends in states projected to experience greater losses of driving jobs, and that do not have sufficient alternative jobs for workers. Our findings indicate that this is particularly true for states located in Middle America. Proactive labor policies that are tailored to the regional labor market and available job alternatives will be needed to help truck drivers transition into new occupations. These policies should be particularly mindful of the specific characteristics of the truck-driving workforce
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