Physiological predictors of Hypoxic Challenge Testing (HCT) outcomes in Interstitial Lung Disease (ILD). (February 2018) - Barratt, Shaney L.; Shaw, Jonathon; Jones, Rachel; Bibby, Anna; Adamali, Huzaifa; Mustfa, Naveed; Cliff, Ian; Stone, Helen; Chaudhuri, Nazia
Abstract: Background: Pre-flight risk assessments are currently recommended for all Interstitial Lung Disease (ILD) patients. Hypoxic challenge testing (HCT) can inform regarding the need for supplemental in-flight oxygen but variables which might predict the outcome of HCT and thus guide referral for assessment, are unknown. Methods: A retrospective analysis of ILD patients attending for HCT at three tertiary care ILD referral centres was undertaken to investigate the concordance between HCT and existing predictive equations for prediction of in-flight hypoxia. Physiological variables that might predict a hypoxaemic response to HCT were also explored with the aim of developing a practical pre-flight assessment algorithm for ILD patients. Results: A total of 106 ILD patients (69 of whom (65%) had Idiopathic Pulmonary Fibrosis (IPF)) underwent HCT. Of these, 54 (51%) patients (of whom 37 (69%) had IPF) failed HCT and were recommended supplemental in-flight oxygen. Existing predictive equations were unable to accurately predict the outcome of HCT. ILD patients who failed HCT had significantly lower resting SpO2, baseline PaO2, reduced walking distance, FEV1, FVC and TLCO, but higher GAP index than those who passed HCT. Conclusions: TLCO >50% predicted and PaO2 >9.42 kPa were independent predictors for passing HCT. Using these discriminators, a novel, practical pre-flight algorithm for evaluation of ILD patients is proposed. Highlights: Pre-flight risk assessments are recommended for all ILD patients. Variables that predict the outcome of HCT and guide referral for assessment, are unknown. Existing predictive equations did not accurately predict the outcome of HCT. TLCO >50% predicted and PaO2 >9.42 kPa were independent predictors for passing HCT. Using these discriminators, a novel pre-flight algorithm for ILD patients is proposed.