Airway and Anaesthetic Management of Adult Patients with Mucopolysaccharidoses Undergoing Cardiac Surgery.
David MayhewKenneth PalmerIan WilsonStuart WatsonKarolina M StępieńPetra JenkinsChaitanya GadepalliPublished in: Journal of clinical medicine (2024)
Background: Mucopolysaccharidoses (MPSs) are rare congenital lysosomal storage disorders due to a deficiency of enzymes metabolising glycosaminoglycans, leading to their accumulation in tissues. This multisystem disease often requires surgical intervention, including valvular cardiac surgery. Adult MPSs have complex airways making anaesthesia risky. Methods: We report novel three-dimensional (3D) modelling airway assessments and multidisciplinary peri-operative airway management. Results: Five MPS adults underwent cardiac surgery at the national MPS cardiac centre (type I = 4, type II = 1; ages 20, 24, 33, 35, 37 years; two males, three females). All had complex airway abnormalities. Assessments involved examination, nasendoscopy, imaging, functional studies, 3D reconstruction, virtual endoscopy, virtual reality and simulation using computerised, physical modelling. Awake oral fibre-optic intubation was achieved via airway conduit. Staged extubation was performed on the first post-operative day under laryngo-tracheoscopic guidance. The post-operative period involved chest physiotherapy and occupational therapy. All patients had safe intubation, ventilation and extubation. Four had good cardiac surgical outcomes, one (MPS type I; age 35 years) was inoperable due to endocarditis. None had post-operative airway complications. Conclusions: Expertise from cardiovascular-heart team, multidisciplinary airway management, use of novel techniques is vital. Traditional airway assessments are insufficient, so ENT input, radiology and computerised methods to assess and simulate the airway in 3D by collaboration with clinical engineering is essential.
Keyphrases
- cardiac surgery
- acute kidney injury
- randomized controlled trial
- virtual reality
- heart failure
- quality improvement
- end stage renal disease
- ejection fraction
- left ventricular
- high resolution
- squamous cell carcinoma
- cardiac arrest
- atrial fibrillation
- physical activity
- chronic kidney disease
- machine learning
- intensive care unit
- newly diagnosed
- artificial intelligence
- risk factors
- clinical decision support
- deep learning
- locally advanced
- deep brain stimulation
- young adults