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The COVID-19 pandemic provides an urgent example where a gap exists between availability of state-of-the-art diagnostics and current needs. As assay protocols and primer sequences become widely known, many laboratories perform diagnostic tests using methods such as RT-PCR or reverse transcription loop mediated isothermal amplification (RT-LAMP). Here, we report an RT-LAMP isothermal assay for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and demonstrate the assay on clinical samples using a simple and accessible point-of-care (POC) instrument. We characterized the assay by dipping swabs into synthetic nasal fluid spiked with the virus, moving the swab to viral transport medium (VTM), and sampling a volume of the VTM to perform the RT-LAMP assay without an RNA extraction kit. The assay has a limit of detection (LOD) of 50 RNA copies per μL in the VTM solution within 30 min. We further demonstrate our assay by detecting SARS-CoV-2 viruses from 20 clinical samples. Finally, we demonstrate a portable and real-time POC device to detect SARS-CoV-2 from VTM samples using an additively manufactured three-dimensional cartridge and a smartphone-based reader. The POC system was tested using 10 clinical samples, and was able to detect SARS-CoV-2 from these clinical samples by distinguishing positive samples from negative samples after 30 min. The POC tests are in complete agreement with RT-PCR controls. This work demonstrates an alternative pathway for SARS-CoV-2 diagnostics that does not require conventional laboratory infrastructure, in settings where diagnosis is required at the point of sample collection.

Providing a solid foundation in clinical medicine for optometrists and optometry students, Clinical Medicine for Optometrists covers the systemic medical conditions that have serious impacts on ocular health and function, as well as the ocular exam findings that may be an early indication of significant systemic disease.

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Empirical evaluations have demonstrated that diagnostic accuracy frequently shows significant heterogeneity between subgroups of patients within a study. We propose to use Cochran's Q test to assess heterogeneity in diagnostic likelihood ratios (LRs). We reanalyzed published data of six articles that showed within-study heterogeneity in diagnostic accuracy. We used the Q test to assess heterogeneity in LRs and compared the results of the Q test with those obtained using another method for stratified analysis of LRs, based on subgroup confidence intervals. We also studied the behavior of the Q test using hypothetical data. The Q test detected significant heterogeneity in LRs in all six example data sets. The Q test detected significant heterogeneity in LRs more frequently than the confidence interval approach (38% vs. 20%). When applied to hypothetical data, the Q test would be able to detect relatively small variations in LRs, of about a twofold increase, in a study including 300 participants. Reanalysis of published data using the Q test can be easily performed to assess heterogeneity in diagnostic LRs between subgroups of patients, potentially providing important information to clinicians who base their decisions on published LRs.

Key Points Clinical molecular genetic testing is transforming personalized medicine and is appropriate for a range of applications, such as rare disease diagnostics and predictive testing for common disorders. Whole-exome and whole-genome sequencing may become a first-line clinical test for some naive diagnostic cases, but classic genetic tests will continue to be used for the high analytical sensitivity of specific defects and for the confirmation of genome findings. There remains no single test to detect the wide array of genetic defects that may be inherited or arise de novo ; clinical diagnostics requires multiple approaches to determine a causal genetic defect. Although genome sequencing may transform diagnostic approaches in large academic medical centres, access to expensive and sophisticated tests are not universal. Genetic testing must be available globally through validated simple technologies for molecular diagnostics (such as direct PCR, linkage analysis or multiplex ligation-dependent probe amplification). The greatest challenge to clinical genomics is the reliable interpretation of the multiple and novel variants found through genome sequencing. Pathogenicity of genetic variants can be examined with bioinformatics prediction approaches, protein stability studies, transcriptional activity studies and allele- and/or gene-specific animal models. As broader genomic information becomes available to providers and patients, partnerships will develop to convey patient-centred data, including incidental findings. The regulatory environment must adapt to the coming volume of genomic information to maximize benefit to patients and health-care systems and to match the expectations of the patient population with regard to these technologies. The authors review current technologies for clinical genetic testing. Moves are being made towards whole-genome and whole-exome sequencing in the clinic, although other technologies will continue to be of value. Genomic technologies are reaching the point of being able to detect genetic variation in patients at high accuracy and reduced cost, offering the promise of fundamentally altering medicine. Still, although scientists and policy advisers grapple with how to interpret and how to handle the onslaught and ambiguity of genome-wide data, established and well-validated molecular technologies continue to have an important role, especially in regions of the world that have more limited access to next-generation sequencing capabilities. Here we review the range of methods currently available in a clinical setting as well as emerging approaches in clinical molecular diagnostics. In parallel, we outline implementation challenges that will be necessary to address to ensure the future of genetic medicine.