Abstract
Background
Currently, there is a disagreement between guidelines regarding platelet count cut-off values as a sign of maternal organ damage in pre-eclampsia; the American College of Obstetricians and Gynecologists guidelines state a cut-off value of < 100 × 109/L; however, the International Society for the Study of Hypertension in Pregnancy guidelines specify a cut-off of < 150 × 109/L. We evaluated the effect of mild thrombocytopenia: platelet count < 150 × 109/L and ≥ 100 × 109/L on clinical features of pre-eclampsia to examine whether mild thrombocytopenia reflects maternal organ damage in pre-eclampsia.
Methods
A total of 264 women were enrolled in this study. Participants were divided into three groups based on platelet count levels at delivery: normal, ≥ 150 × 109/L; mild thrombocytopenia, < 150 × 109/L and ≥ 100 × 109/L; and severe thrombocytopenia, < 100 × 109/L. Risk of severe hypertension, utero-placental dysfunction, maternal organ damage, preterm delivery, and neonatal intensive care unit admission were analyzed based on platelet count levels. Estimated relative risk was calculated with a Poisson regression analysis with a robust error.
Results
Platelet counts indicated normal levels in 189 patients, mild thrombocytopenia in 51 patients, and severe thrombocytopenia in 24 patients. The estimated relative risks of severe thrombocytopenia were 4.46 [95 % confidence interval, 2.59–7.68] for maternal organ damage except for thrombocytopenia, 1.61 [1.06–2.45] for preterm delivery < 34 gestational weeks, and 1.35 [1.06–1.73] for neonatal intensive care unit admission. On the other hand, the estimated relative risks of mild thrombocytopenia were 0.97 [0.41–2.26] for maternal organ damage except for thrombocytopenia, 0.91 [0.62–1.35] for preterm delivery < 34 gestational weeks, and 0.97 [0.76–1.24] for neonatal intensive care unit admission.
Conclusions
Mild thrombocytopenia was not associated with severe features of pre-eclampsia and would not be suitable as a sign of maternal organ damage.
Predicting hospital mortality for intensive care unit patients: Time-series analysis
