Key result
Risk prediction models in pulmonary arterial hypertension can map and target individual disease trajectories to guide individualized treatment and avoid future morbid and mortal events.
Risk prediction models are essential for mapping individual disease trajectories and targeting therapies to improve outcomes in pulmonary arterial hypertension.
May guide individualized PAH therapy; leaves open prospective validation before practice change.
Significant therapeutic advances in the field of pulmonary arterial hypertension (PAH), increased awareness and diagnosis, and changing patient demographics in the contemporary era have facilitated the development of better prognostic tools for predicting survival. However, overall patient outcomes remain poor, and measurement of most prognostic factors still occurs at the time of initial PAH diagnosis or enrollment into clinical trials. Treatment of PAH patients requires an individualized approach based on disease severity and burden of risk factors to improve patient outcomes. This article will focus on the use of risk prediction models to map and target individual disease trajectories to avoid future morbid and mortal events.
No takes yet. Share an insight, caveat, or question.
Richa Agarwal (2015) conducted a review in Pulmonary Arterial Hypertension (PAH). Risk prediction models was evaluated. Risk prediction models in pulmonary arterial hypertension can map and target individual disease trajectories to guide individualized treatment and avoid future morbid and mortal events.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: