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Whole genome sequencing to predict gonorrhoea sensitivities
This timely paper from Eyre et al 1 explores whether whole genome sequencing (WGS) can predict for antibiotic resistance. WGS was used to identify potential resistance determinants for nearly 700 Neisseria gonorrhoeae isolates taken as part of national surveillance programmes in the UK, Canada and the USA. Phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline were determined. Any genetic predictors of minimum inhibitory concentration (MIC) value were identified and included the majority of previously reported resistance. Fifty-three per cent of MIC values were predicted to the nearest doubling dilution, 93% within +1 doubling dilutions, and 98% within +2 doubling dilutions, typical variation is +1 doubling dilution and or greater. EUCAST MICs were applied. The overall very major error rate (phenotypically resistant, WGS prediction susceptible) was 21/1577 (1.3%, 95% CI 0.8% to 2.0%) and the major error rate (phenotypically susceptible, WGS prediction resistant) was 20/1186 (1.7%, 95% CI 1.0% to 2.6%). The MIC prediction performance was similar across each of the antibiotics tested.
Chronic obstructive pulmonary disease in the context of HIV
Bigna et al 2 seek to establish …
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