Artificial intelligence to improve the diagnosis of pulmonary hypertension: promises and pitfalls

Challenges in the diagnosis of pulmonary hypertension Pulmonary hypertension (PH) is a clinical–physiological syndrome thought to affect 1% of the global population.1 PH is defined haemodynamically by mean pulmonary artery pressure >20 mm Hg, resulting in right ventricular (RV) overload and often RV failure. Patients with PH experience symptoms including dyspnoea, fatigue and oedema, often associated with physical and psychosocial disability. In some forms of untreated PH, mean survival is less than 3 years, related in part to delays in diagnosis of 1–2 years after clinical onset of disease. Diagnostic delays are due to non-specific symptoms, subtle clinical examination findings and low sensitivity of detection of PH features on imaging, ECG and pulmonary function testing. Indeed, patients are still most often diagnosed at an advanced stage, typically in New York Heart Association (NYHA) functional class 3. Guidelines recommend screening high-risk patients, such as those with scleroderma, with...
Source: Heart - Category: Cardiology Authors: Tags: Editorials Source Type: research