Virtual preoperative anaesthetic assessments can significantly reduce healthcare costs and improve patient convenience. The challenge with virtual consults is often the airway assessments, which screen for potentially difficult airways (PDAs). The objective of this pilot study was to determine the reliability of standard airway screening tests for detecting PDAs when conducted virtually. An observational longitudinal study was conducted between July 2021 and April 2022 at a tertiary hospital in Singapore. We compared the Mallampati score (MS), upper lip bite test (ULBT), thyromental distance, mouth opening test, and neck movements in 94 patients, first during virtual assessments before surgery and subsequently at face-to-face preoperative assessments (gold standard) on the day of surgery by the same team of anaesthesiology trainees. Goodman and Kruskal's gamma coefficient measured concordance between virtual and face-to-face assessment results. Logistic regression (LR) identified virtual predictors of PDAs in clinical practice. AUROC values informed tool performance. LR showed that elevated virtual MS, virtual ULBT, and body mass index (BMI) were potential predictors of clinical PDAs. Termed the "MBBS", this collective score showed good performance with a sensitivity of 95% and an AUROC of 0.79. Importantly, all screening tests performed poorly in virtual assessments when applied individually (sensitivity < 50%). In this pilot study, BMI combined with MS and ULBT could reliably detect PDAs during virtual airway assessments. The data herein support further large multi-centre studies to validate the MBBS for clinical use.
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http://dx.doi.org/10.3390/jcm14020342 | DOI Listing |
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