The association between idiopathic thrombocytopenic purpura and cardiovascular disease: a retrospective cohort study.
Joht Singh ChandanT ThomasS LeeT MarshallB WillisK NirantharakumarP GillPublished in: Journal of thrombosis and haemostasis : JTH (2018)
Background Idiopathic thrombocytopenic purpura (ITP) is classically characterized by a transient or persistent decrease of platelet count. Mortality is higher in the ITP population than the general population, with a possible association with increased cardiovascular disease (CVD). Objectives The objective was to assess the strength of the association between ITP and CVD, with a secondary aim to assess the impact of splenectomy on CVD. Methods A population-based retrospective, open cohort study using clinical codes was performed using data from 6591 patients with ITP and 24 275 randomly matched controls (up to 1:4 ratio matched by age, sex, body mass index and smoking status). The main outcome was the risk of CVD, which included ischemic heart disease, stroke, trans-ischemic attack and heart failure. Adjusted incidence rate ratios were calculated using Poisson regression. Results During a median 6-year observation period there was a CVD diagnosis recorded in 392 (5.9%) ITP patients and 1114 (4.5%) control patients. There was an increased risk of developing CVD in the ITP cohort (incidence rate ratio [IRR], 1.38; 95% confidence interval [CI], 1.23-1.55), which remained robust even after a sensitivity analysis only including incident cases of ITP. Findings suggested that patients who had undergone splenectomy were at even further increased risk of developing CVD when compared with the ITP population who had not undergone splenectomy (adjusted IRR, 1.69; 95% CI, 1.22-2.34). Conclusion There is an increased risk of developing CVD in patients with ITP and even further increased risk for those patients with ITP who underwent splenectomy.
Keyphrases
- cardiovascular disease
- end stage renal disease
- heart failure
- newly diagnosed
- ejection fraction
- chronic kidney disease
- type diabetes
- risk factors
- peritoneal dialysis
- metabolic syndrome
- minimally invasive
- cerebral ischemia
- big data
- left ventricular
- patient reported outcomes
- ischemia reperfusion injury
- machine learning
- oxidative stress
- deep learning
- subarachnoid hemorrhage
- electronic health record
- artificial intelligence