Beat the pain in Sickle Cell Disease

Sickle cell disease (SCD) is the most common inherited red blood cell disorder. It is characterized by polymerization of hemoglobin S, resulting in the formation of rigid sickled-shaped red blood cells. 
These cells can occlude the microvasculature causing hemolytic anemia, irreversible-organ damage and recurrent painful vaso-occlusive crises. In its severe form, these crises require hospitalization for administration of intravenous opioids. When patients are hospitalized for a painful crises, some may develop severe respiratory complications, called Acute Chest Syndrome (ACS). The clinical presentation of SCD is highly variable among patients and there are no adequate (bio)markers available. For this reason, this study is focused on the early prediction of ACS in admitted patients and the prediction of painful crises in ambulant patients. For the prediction, we will measure heart rate based variables (including heart rate variability) using the Apple Watch.

The aim of this proof-of-concept study is to analyze the use of heart rate based variables using the Apple Watch:

A) To predict Acute Chest Syndrome in patients hospitalized patients for painful crises;
B) To predict painful crises in ambulant patients.

Patients with SCD from the age of 16 years old will be included in this study, divided over two study groups: 

A) Hospitalized patients with painful crisis, longitudinal measurements
B) Ambulant patients, longitudinal measurements

N.A.

The burden and the risks associated with participation in this study are low. Subjects will be asked to wear a wearable device on the wrist during the study period. 
The additional burden for study participants in part B (ambulant patients to predict painful crises) is to keep a pain diary for the duration of six months.