Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging

BackgroundThe automatic analysis of medical images has the potential improve diagnostic accuracy while reducing the strain on clinicians. Current methods analyzing 3D-like imaging data, such as computerized tomography imaging, often treat each image slice as individual slices. This may not be able to appropriately model the relationship between slices.MethodsOur proposed method utilizes a mixed-effects model within the deep learning framework to model the relationship between slices. We externally validated this method on a data set taken from a different country and compared our results against other proposed methods. We evaluated the discrimination, calibration, and clinical usefulness of our model using a range of measures. Finally, we carried out a sensitivity analysis to demonstrate our methods robustness to noise and missing data.ResultsIn the external geographic validation set our model showed excellent performance with an AUROC of 0.930 (95%CI: 0.914, 0.947), with a sensitivity and specificity, PPV, and NPV of 0.778 (0.720, 0.828), 0.882 (0.853, 0.908), 0.744 (0.686, 0.797), and 0.900 (0.872, 0.924) at the 0.5 probability cut-off point. Our model also maintained good calibration in the external validation dataset, while other methods showed poor calibration.ConclusionDeep learning can reduce stress on healthcare systems by automatically screening CT imaging for COVID-19. Our method showed improved generalizability in external validation compared to previous published methods. However, deep learning models must be robustly assessed using various performance measures and externally validated in each setting. In addition, best practice guidelines for developing and reporting predictive models are vital for the safe adoption of such models

Are Better Workers Also Better Humans? On Pharmacological Cognitive Enhancement in the Workplace and Conflicting Societal Domains

The article investigates the sociocultural implications of the changing modern workplace and of pharmacological cognitive enhancement (PCE) as a potential adaptive tool from the viewpoint of social niche construction. We will attempt to elucidate some of the sociocultural and technological trends that drive and influence the characteristics of this specific niche, and especially to identify the kind of capabilities and adaptations that are being promoted, and to ascertain the capabilities and potentialities that might become diminished as a result. In this context, we will examine what PCE is, and how and why it might be desirable as a tool for adaptation within the workplace. As human beings are, or at least should be allowed to be, more than merely productive, able-bodied and able-minded workers, we will further examine how adaptation to the workplace niche could result in problems in other domains of modern societal life that require the same or other cognitive capabilities. In this context we will also focus on the concept of responsibility and how it pertains to PCE and the modern workplace niche. This will shed some light on the kind of trends related to workplace niche construction, PCE and capability promotion that we can expect in the future, and on the contexts in which this might be either beneficial or detrimental to the individual as a well-rounded human being, and to other members of society

Rapid evolution of microbe-mediated protection against pathogens in a worm host.

Microbes can defend their host against virulent infections, but direct evidence for the adaptive origin of microbe-mediated protection is lacking. Using experimental evolution of a novel, tripartite interaction, we demonstrate that mildly pathogenic bacteria (Enterococcus faecalis) living in worms (Caenorhabditis elegans) rapidly evolved to defend their animal hosts against infection by a more virulent pathogen (Staphylococcus aureus), crossing the parasitism-mutualism continuum. Host protection evolved in all six, independently selected populations in response to within-host bacterial interactions and without direct selection for host health. Microbe-mediated protection was also effective against a broad spectrum of pathogenic S. aureus isolates. Genomic analysis implied that the mechanistic basis for E. faecalis-mediated protection was through increased production of antimicrobial superoxide, which was confirmed by biochemical assays. Our results indicate that microbes living within a host may make the evolutionary transition to mutualism in response to pathogen attack, and that microbiome evolution warrants consideration as a driver of infection outcome

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Multicentre studies of insecticide-treated durable wall lining in Africa and South-East Asia: entomological efficacy and household acceptability during one year of field use.

BACKGROUND: Indoor residual spraying (IRS) is a primary method of malaria vector control, but its potential impact is constrained by several inherent limitations: spraying must be repeated when insecticide residues decay, householders can tire of the annual imposition and campaign costs are recurrent. Durable lining (DL) can be considered an advanced form of long-lasting IRS where insecticide is gradually released from an aesthetically attractive wall lining material to provide vector control for several years. A multicentre trial was carried out in Equatorial Guinea, Ghana, Mali, South Africa and Vietnam to assess the feasibility, durability, bioefficacy and household acceptability of DL, compared to conventional IRS or insecticide-treated curtains (LLITCs), in a variety of operational settings. METHODS: This study was conducted in 220 households in traditional rural villages over 12-15 months. In all sites, rolls of DL were cut to fit house dimensions and fixed to interior wall surfaces (usually with nails and caps) by trained teams. Acceptability was assessed using a standardized questionnaire covering such topics as installation, exposure reactions, entomology, indoor environment, aesthetics and durability. Bioefficacy of interventions was evaluated using WHO cone bioassay tests at regular intervals throughout the year. RESULTS: The deltamethrin DL demonstrated little to no decline in bioefficacy over 12-15 months, supported by minimal loss of insecticide content. By contrast, IRS displayed a significant decrease in bioactivity by 6 months and full loss after 12 months. The majority of participants in DL households perceived reductions in mosquito density (93%) and biting (82%), but no changes in indoor temperature (83%). Among those households that wanted to retain the DL, 73% cited protective reasons, 20% expressed a desire to keep theirs for decoration and 7% valued both qualities equally. In Equatorial Guinea, when offered a choice of vector control product at the end of the trial (DL, IRS or LLITCs), DL consistently emerged as the most popular intervention regardless of the earlier household allocation. CONCLUSIONS: Just as long-lasting insecticidal nets overcame several of the technical and logistical constraints associated with conventionally treated nets and then went to scale, this study demonstrates the potential of DL to sustain user compliance and overcome the operational challenges associated with IRS