Objects: This study aims to describe the clinical and laboratory characteristics and to evaluate the predictive value of selected biochemical and hematological parameters for adverse pregnancy outcomes.
Subjects and methods: A retrospective study was conducted on 243 medical records of pregnant women diagnosed with preeclampsia without severe features at the National Hospital of Obstetrics and Gynecology from January 2023 to June 2025.
Results: A total of 66.67% (162/243) of women developed adverse pregnancy outcomes. Women with adverse outcomes had an earlier gestational age at disease onset (31.92 ± 3.19 vs. 35.74 ± 1.50 weeks), and significant alterations in biochemical parameters (elevated proteinuria, uric acid, urea, creatinine, AST, LDH; decreased albumin) and coagulation profiles (decreased fibrinogen) (p < 0.05). Platelet count did not differ significantly between the two groups. The multivariate logistic regression model identified five independent prognostic factors: previous SGA births (aOR = 19.03), gestational age at disease onset (aOR = 0.36), systolic blood pressure (aOR = 1.11), serum uric acid level (aOR = 1.01), and APTT (aOR = 1.22). The predictive model achieved an area under the curve (AUC) of 0.9463, with a sensitivity of 86.42%, a specificity of 87.65%, and a positive predictive value (PPV) of up to 93.33%.
Conclusion: A multivariable prediction model integrating five routinely available clinical and laboratory parameters demonstrated excellent performance in predicting adverse pregnancy outcomes among women with preeclampsia without severe features. This model may assist clinicians in risk stratification, timely clinical decision-making, and prevention of severe maternal and perinatal complications while remaining feasible for implementation in resource-limited healthcare settings.