Platelet count has a U-shaped association with mortality in hemodialysis patients

Abstract

Our previous manuscript showed that thrombocytopenia predicts all-cause mortality in Chinese hemodialysis (HD) patients. Based on the role of platelets in coagulation, clot formation, and systemic inflammation, we speculate that high platelets increase risk of thrombo-embolic events, hence the mortality. However, research evidence is currently lacking. Therefore, we utilized data from a very large international cohort study to explore the association of platelet counts with mortality and cardiovascular (CV) death in hemodialysis (HD) patients. International data from 396 facilities enrolled in the Dialysis Outcomes and Practice Patterns Study (DOPPS) phase 5 (2012-2015) were analyzed. Participants were divided into 3 groups according to their platelet counts (low: <100, normal: 100-300, high: >300*10⁹). Associations between platelet counts and all-cause and CV mortality were analyzed using Cox regression, adjusted for confounders. There were 13,631 patients with median age of 65 years old. Males accounted for 61.2%. Mean platelet count was 205*10⁹/L overall and ranged from 173 *10⁹/L in China to 227 *10⁹/L in Sweden. Overall, 2,348 (17.2%) patients died and 1017 (7.5%) died from CV disease. Both low (HR:1.48, 95% CI 1.21-1.80, p < 0.001) and high (HR:1.17, 95% CI 1.00- 1.35, p = 0.044) platelet counts were associated with higher all-cause mortality after adjustment for covariates; results for CV death were consistent. Platelet count has a U-shaped association with all-cause and CV mortality in HD patients, and thus may be used as an outcome predictor that is readily available among HD patients.

Keywords: Chronic kidney disease; End-stage kidney disease; Hemodialysis; Mortality; Platelet.

Fig. 1

Patients in normal, low, and high platelet groups from 21 countries, A/NZ is for Australia and New Zealand; GCC is for Gulf Cooperation Council (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates). A)

Fig. 2

The Kaplan-Meier curves for different platelet counts groups in HD patients. (A) Survival curves of all-cause mortality; (B) Survival curves of CV mortality among three groups.

Fig. 3

Associations between the platelet counts and all-cause and CV mortality in different Cox regression models. Model: adjusted for age, gender, BMI, vintage, comorbidities (diabetes, coronary artery disease, congestive heart failure, other cardiovascular disease, cerebrovascular disease, hepatitis B and C, cancer (non-skin), peripheral vascular disease, lung disease, hypertension, psychiatric disorder, GI Bleeding, recurrent cellulitis, liver cirrhosis, neurologic disease), hemoglobin, albumin, white blood cells, and serum creatinine, Intradialytic weight loss, fistula use, primary kidney disease, standard kt/v, urine output < 200 ml/d.

Fig. 4

Subgroup analyses for the hazard ratio for patients with low platelets counts (Vs. normal) using Cox regression. The model was adjusted for age, gender, BMI, dialysis vintage and comorbidities (diabetes, coronary artery disease, congestive heart failure, other cardiovascular disease, cerebrovascular disease, hepatitis, cancer (non-skin), peripheral vascular disease, lung disease, hypertension, psychiatric disorder, gastrointestinal bleeding, recurrent cellulitis, fracture, and neurologic disease).

Fig. 5

Subgroup analyses for the hazard ratio for patients with high platelets counts (Vs. normal) using Cox regression. The model was adjusted for age, gender, BMI, dialysis vintage and comorbidities (diabetes, coronary artery disease, congestive heart failure, other cardiovascular disease, cerebrovascular disease, hepatitis, cancer (non-skin), peripheral vascular disease, lung disease, hypertension, psychiatric disorder, gastrointestinal bleeding, recurrent cellulitis, fracture, and neurologic disease).