Background: Next-generation sequencing (NGS) is gradually replacing Sanger sequencing for HIV genotypic drug resistance testing (GRT). This work evaluated the concordance among different NGS-GRT interpretation tools in a real-life setting. Methods: Routine NGS-GRT data were generated from viral RNA at 11 Italian laboratories with the AD4SEQ HIV-1 Solution v2 commercial kit. NGS results were interpreted by the SmartVir system provided by the kit and by two online tools (HyDRA Web and Stanford HIVdb). NGS-GRT was considered valid when the coverage was >100 reads (100×) at each PR/RT/IN resistance-associated position listed in the HIVdb 9.5.1 algorithm. Results: Among 629 NGS-GRT, 75.2%, 74.2%, and 70.9% were valid according to SmartVir, HyDRA Web, and HIVdb. Considering at least two interpretation tools, 463 (73.6%) NGS-GRT had a valid coverage for resistance analyses. The proportion of valid samples was affected by viremia 10% showed fair concordance among different interpretation tools. Conclusion: This Italian survey on NGS resistance testing suggests that viremia levels and HIV subtype affect NGS-GRT coverage. Within the current routine method for NGS-GRT, only mutations with frequency >10% seem reliably detected across different interpretation tools.

Several important sex and gender differences in the clinical manifestation of diseases have been known for a long time but are still underestimated. The infectious Coronavirus 2019 disease pandemic has provided evidence of the importance of a sex and gender-based approach; it mainly affected men with worse symptomatology due to a different immune system, which is stronger in women, and to the Angiotensin-converting enzyme 2 and Transmembrane protease serine 2 roles which are differently expressed among the sexes. Additionally, women are more inclined to maintain social distance and smoke less. Analysis of data on the infectious Coronavirus 2019 disease testing from people admitted to the Amedeo di Savoia Hospital, a regional referral center for infectious diseases, has been applied to the whole of 2020 data (254,640 records). A high percentage of data in the dataset was not suitable due to a lack of information or entering errors. Among the suitable samples, records have been analyzed for positive/negative outcomes, matching records for unique subjects (N = 123,542), to evaluate individual recurrence of testing. Data are presented in age and sex-disaggregated ways. Analyses of the suitable sample also concerned the relation between testing and hospital admission motivation and symptoms. Our analysis indicated that a sex and gender-based approach is mandatory for patients and the National Health System’s sustainability.