Early decrease in blood platelet count is associated with poor prognosis in COVID-19 patients—indications for predictive, preventive, and personalized medical approach - Zhao, Xiaofang; Wang, Kun; Zuo, Peiyuan; Liu, Yuwei; Zhang, Meng; Xie, Songpu; Zhang, Hao; Chen, Xinglin; Liu, Chengyun (The EPMA journal, 2020)
Background Changes in platelet count are common in COVID-19 patients. The platelet count reflects the thrombocyte turnover, acting as a sensitive indicator of illness severity that is of great clinical utility to monitor a quickly changing health condition of patients affected by aggressive viral infections. This study aims to investigate the significance of platelet count during the progression of the disease in COVID-19 patients. Methods A total of 532 COVID-19 patients were involved in the cohort study from the First People’s Hospital of Jiangxia District in Wuhan from January 7, 2020, to February 28, 2020. We collected the clinical characteristics and laboratory data of patients. Patients still hospitalized before February 29, 2020, died on admission, with malignant tumors, previous gastrointestinal surgery, missing baseline platelet count, or platelet count detected only once, were excluded. We used a generalized additive model and generalized additive mixed model to compare trends in platelet count over time among survivors and non-survivors, with an adjustment for potential confounders. Results During the follow-up, twenty-nine subjects died (mortality rate, 5.45%). The platelets among non-survivors decreased and among survivors increased gradually within 1 week after admission. In addition, the difference between the two groups showed an increasing trend during 1 week after admission. This difference increased by an average of 5.3 × 10^9/L daily. Conclusions In the early stage, platelet count can dynamically reflect the pathophysiological changes in COVID-19 patients. Early decrease in platelet count was associated with mortality in patients with COVID-19. Causality, however, cannot be deduced from our data.