The Use of Platelet Count and Indices as Prognostic Factors for Mortality in Children with Sepsis

• Published in: Iranian journal of medical sciences Vol. 49; no. 8; pp. 494 - 500
• Main Authors: Meliani, Meliani, Siregar, Jelita, Lubis, Inke Nadia Diniyanti
• Format: Journal Article
• Language: English
• Published: Iran Shiraz University of Medical Sciences 01.08.2024
• Subjects: Blood Platelets; Child; Child, Preschool; Cross-Sectional Studies; Female; Humans; Indonesia; Infant; Male; mean platelet volume; Mean Platelet Volume - methods; Mean Platelet Volume - statistics & numerical data; Mortality; Original; platelet count; Platelet Count - methods; Platelet Count - statistics & numerical data; Prognosis; ROC Curve; Sepsis; Sepsis - blood; Sepsis - mortality; Indonesia; Mean platelet volume; Sepsis; Mortality; Platelet count
• ISSN: 0253-0716; 1735-3688; 1735-3688
• DOI: 10.30476/ijms.2023.99084.3113

Sepsis is still one of the leading causes of mortality and morbidity in children worldwide. Consumptive coagulopathy and suppression of thrombopoiesis in the bone marrow resulting from immune dysregulation are pathological mechanisms that cause thrombocytopenia in sepsis. Platelet count (PLT) and indices, such as mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) are markers of platelet activation and are strongly influenced by platelet morphology and proliferation kinetics. We aimed to study the use of platelet count and indices as predictors of mortality in children with sepsis. This is a cross-sectional study of 45 children diagnosed with sepsis on admission at Haji Adam Malik Hospital, Medan, North Sumatra, Indonesia, between October and November 2022. Blood samples were drawn upon admission, and platelet count and indices were then determined for all children. Subjects were followed up till discharge from hospital or death. Receiver Operating Characteristic (ROC) curve analysis of platelet parameters was done to determine the area under the curve (AUC), optimal cut-off value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in predicting mortality in children with sepsis. Using the cut-off values from ROC curve analysis, the odds ratio with 95% confidence interval was calculated using multiple logistic regression analyses. A P value less than 0.05 was considered statistically significant. MPV, PDW, and PDW/PLT were significantly higher in non-survivors than survivors (P=0.04, P=0.02, and P=0.04, respectively). ROC curve analysis showed that PDW had the largest AUC (0.708 [95% CI=0.549-0.866]) with a cut-off value of 14.1%, sensitivity of 63.6%, and specificity of 82.6%. PDW was also the only parameter that significantly affected the outcome of children with sepsis. PDW≥14.1% at admission increases the risk of mortality by 5.7 times. Admission PDW is a fast and specific tool to predict the outcome of children with sepsis.