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Surgical site infection (SSI) is a significant cause of postoperative morbidity and mortality. As oncologic care advances, the use of surgical adjuncts such as intraoperative ultrasound (US), 5-aminolevulinic acid (5-ALA), and neurophysiologic monitoring has increased. This study set out to identify whether the use of surgical adjuncts in supratentorial tumor surgery lead to increased operative time or increased rates of SSI. This is a retrospective study at a large tertiary clinical neurosciences center in the UK. We included all patients who underwent an elective supratentorial craniotomy for a tumor over a 12 month period. We retrospectively assessed whether patients had had a postoperative infection at 30 days or 4 months using our electronic patient record system. A total of 267 patients were included. The median age was 58 years (range: 17–87 years) with roughly equal numbers of men and women (men: 138 of 267, 52%). Most operations were carried out for gliomas (149 of 267, 56%) or metastases (61 of 267, 23%). The median length of surgery was 3 hours 6 minutes, with 24% lasting >4 hours. The overall infection rate was 4.5%. Intraoperative monitoring and 5-ALA was associated with longer operative times although not necessarily larger craniotomy sizes, whereas intraoperative US was associated with a shorter operative time and smaller craniotomy size. These adjuncts were not associated with an increased risk of infection. This study adds reassurance that although some surgical adjuncts lead to increased operative times, in our study there was no apparent increased risk of infection as a result of this. [ABSTRACT FROM AUTHOR]

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management., (© 2021. The Author(s).)