Chronic kidney disease could be a risk factor for thrombosis in essential thrombocythemia and polycythemia vera

Ivan Krečak1, Hrvoje Holik2,3, Morić Perić Martina4

  • 1Department of Internal Medicine, Šibenik-Knin County General Hospital, Stjepana Radića 83, 22000, Šibenik, Croatia. krecak.ivan@gmail.com.

Insights

Chronic kidney disease (CKD) increases thrombosis risk in essential thrombocythemia (ET) and polycythemia vera (PV) patients. This finding suggests CKD may need inclusion in current risk assessments for these blood disorders.

Area of Science:

  • Nephrology
  • Hematology
  • Cardiovascular Medicine

Background:

  • Chronic kidney disease (CKD) is a known risk factor for venous thromboembolism and cardiovascular disease.
  • The impact of CKD on thrombotic risk in essential thrombocythemia (ET) and polycythemia vera (PV) is not well understood.

Purpose of the Study:

  • To investigate the correlation between CKD and thrombosis development in ET and PV patients.
  • To assess the impact of CKD on thrombosis-free survival in ET and PV cohorts.

Main Methods:

  • Retrospective multicenter study including 167 patients (76 ET, 91 PV).
  • CKD defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² for ≥ 3 months.
  • Analysis of clinical correlations and thrombosis-free survival using univariate and multivariate Cox regression models.

Main Results:

  • 25.7% of patients had CKD at diagnosis.
  • Lower eGFR correlated with advanced age, female sex, higher granulocytes, elevated C-reactive protein, prior thrombosis, CV risk factors, and splenomegaly.
  • CKD was significantly associated with inferior thrombosis-free survival in the overall cohort and in both ET and PV subgroups, even after multivariate adjustment.

Conclusions:

  • Chronic kidney disease may represent an independent risk factor for thrombosis in ET and PV patients.
  • Further research with larger cohorts is necessary to validate these findings.
  • Investigating the addition of CKD to existing risk stratification models may improve prognostication for ET and PV patients.

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