Publications by authors named "Michael McGettrick"

Background: Ventricular septal flattening reflects RV pressure overload in pulmonary arterial hypertension. Eccentricity index (EI) and pulmonary artery distensibility (PAD) correlate with pulmonary artery pressure. We assessed the utility of these using cardiac magnetic resonance (CMR) to assess for pulmonary hypertension (PH) in patients with chronic thromboembolic disease.

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Objective: Group II pulmonary hypertension (PH) can be challenging to distinguish from Group I PH without proceeding to right heart catheterisation (RHC). The diagnostic accuracy of the H2FPEF and OPTICS scores was investigated in Scotland.

Methods: Patients were included in the study if they were referred to the Scottish Pulmonary Vascular Unit between 2016 and 2020 and subsequently diagnosed with Group II PH or Group I PH which was either idiopathic, heritable or pulmonary veno-occlusive disease.

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Objectives: To assess for increase in pulmonary thromboembolism (PTE) in hospitalised patients with COVID-19, in both critical care and ward environments.

Setting: We reviewed all CT pulmonary angiograms (CTPA) performed in Scotland between 23 March 2020 and 31 May 2020 and identified those with COVID-19 using either classical radiological appearances or positive COVID-19 PCR swab.

Participants: All hospitalised patients in Scotland with COVID-19 between 23 March 2020 and 31 May 2020 who underwent a CTPA.

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Socioeconomic factors have been shown to have an adverse impact on survival in some respiratory diseases. Studies from the USA and China have suggested worse survival in idiopathic pulmonary arterial hypertension in low socioeconomic groups. We looked at the effect of deprivation on the outcomes in patients with connective tissue disease-associated pulmonary hypertension (CTDPH) and chronic thromboembolic pulmonary hypertension (CTEPH) in a retrospective observational study.

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Introduction: Accurate prognostication is difficult in malignant pleural mesothelioma (MPM). We developed a set of robust computational models to quantify the prognostic value of routinely available clinical data, which form the basis of published MPM prognostic models.

Methods: Data regarding 269 patients with MPM were allocated to balanced training (n=169) and validation sets (n=100).

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