Neutrophil-lymphocyte ratio and hypersensitive C-reaction protein are associated with miscarriage during the second...

This study investigated whether biomarkers in the second trimester of pregnancy, including the white blood cell (WBC) count, neutrophil-lymphocyte ratio (NLR), hypersensitive C-reactive protein (hs-CRP) concentration, and procalcitonin (PCT) concentration, were associated with miscarriage during the second trimester of pregnancy. Sixty-two asymptomatic patients in their second trimester of pregnancy were included in the control group (group A). Among 67 patients diagnosed with late threatened miscarriage, 46 patients with ongoing pregnancy were included in group B and 21 patients with subsequent miscarriage were included in group C. The serum of these patients was collected and the biomarkers were analyzed. A paired-samples t-test was used for the comparison between the groups before and after the miscarriage. Statistical significance was set at p<0.05. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the predictive value of different biomarkers for miscarriage during the second trimester of pregnancy. WBC count, neutrophil percentage, and hs-CRP levels were significantly higher in group C than in groups A and B (p<0.05). Lymphocyte percentage and albumin levels decreased significantly from group A to group C (p<0.05). In contrast, NLR increased significantly from group A to group C (p<0.05). There was a significant decrease in the WBC count, neutrophil percentage, hemoglobin concentration, and post-miscarriage NLR among the cases with miscarriage (p<0.05). The area under the curve of WBC count, NLR, hs-CRP, and the combination of these three factors for the prediction of late miscarriage varied from 78.0% to 82.6%. The combination of these three factors had the highest specificity of 91.1%, while hs-CRP had the highest sensitivity of 88.9%. WBC count, NLR, and hs-CRP levels are strongly associated with miscarriage during the second trimester of pregnancy, indicating that they are potential predictive biomarkers.