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Scholars International Journal of Obstetrics and Gynecology (SIJOG)
Volume-8 | Issue-10 | 312-317
Original Research Article
Diagnostic Accuracy of Middle Cerebral Artery to Umbilical Artery Resistance Index Ratio in Predicting Adverse Perinatal Outcomes
Mahzabin Husain, Rubab Sarmin, Sheikh Imran Alam, Salma Akter, Jannatul Ferdous Chowdhury, Effat Aziz, Tasnia Sultana
Published : Oct. 10, 2025
DOI : https://doi.org/10.36348/sijog.2025.v08i10.003
Abstract
Background: Despite evidence supporting the use of MCA/UA Doppler ratios in detecting fetal compromise, most studies have focused on high-risk pregnancies or specific populations, with limited data from broader clinical settings, particularly in Bangladesh; therefore, the purpose of the study was to evaluate the diagnostic accuracy of the Middle Cerebral Artery to Umbilical Artery Resistance Index Ratio in predicting adverse perinatal outcomes. Aim of the study: The aim of the study was to evaluate the diagnostic accuracy of the Middle Cerebral Artery to Umbilical Artery Resistance Index Ratio in predicting adverse perinatal outcomes. Methods: A prospective cohort study of 106 pregnant women at 29–38 weeks gestation was conducted at the Department of Obstetrics and Gynecology, BIRDEM General Hospital, Dhaka (Nov 2022–Feb 2024). Maternal and fetal outcomes were recorded, C/U ratio was assessed, participants were grouped by a 1.01 cut-off, and data were analyzed using SPSS v26.0 (p < 0.05). Results: The C/U ratio predicted adverse perinatal outcomes with an ROC AUC of 0.827 (95% CI: 0.749–0.905; p < 0.0001). At a cut-off of 1.01, sensitivity was 77.8%, specificity 84.6%, PPV 46.2%, NPV 95.7%, and accuracy 83.6%. Low C/U (<1.01) was associated with higher rates of complicated outcomes (84.0% vs 21.4%), 5-min APGAR <7 (68.0% vs 19.6%), NICU admission (74.0% vs 21.4%), respiratory distress (60.0% vs 12.5%), and FGR (18.0% vs 0.0%) compared to C/U ≥1.01 (P <0.05). Conclusion: A C/U ratio below 1.01 reliably predicts adverse perinatal outcomes, supporting its use for early identification of at-risk fetuses.
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