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PREDICTIVE ACCURACY OF CERVICAL LENGTH IN MID TRIMESTER ON TRANSABDOMINAL ULTRASOUND FOR CESAREAN SECTION

Asma Khalid, MN Anjum, U Daraaz, K. Hussain, MA Omer

2020Biological and Clinical Sciences Research Journal11 citationsDOIOpen Access PDF

Abstract

The Cesarean section (CS) delivery is a most frequent surgical technique worldwide. The CS increasing rate and its related problems have drawn an attention towards CS related morbidity. As recommended by WHO, C-section could be carried out only when required medically. In mid-pregnancy cervical extended length predicts the probability of CS early in the pregnancy. The objective of the study is to find the predictive accuracy of cervical length (CL) on transabdominal ultrasound for cesarean section in mid trimester taking mode of delivery as gold standard. It was a cross sectional study in which 362 females were enrolled. Females were undergoing transabdominal ultrasonography for assessment of cervical length. A 2x2 contingency table was generated to calculate sensitivity, specificity, positive predictive valve (PPV), negative predictive value (NPV) and diagnostic accuracy of transabdominal ultrasound taking actual mode of delivery as gold standard. The mean age of the females was 27.92 + 5.75 years while mean parity and mean CL were 2.22 + 1.30 and 35.83 + 7.96 mm, respectively. Among 30 females who had cervical length <25 mm, 24 had CS and 6 had spontaneous vaginal delivery (SVD). Among 332 females who had cervical length >25 mm, 96 had CS and 236 had SVD. The sensitivity, specificity, PPV, NPV and diagnostic accuracy of transabdominal ultrasound for cesarean section were 20.0%, 97.5%, 80.0%, 71.1% and 71.8%, respectively. Study concluded that cesarean section takes place among pregnant females when cervical length is ≤25mm on transabdominal ultrasound during mid trimester.

Topics & Concepts

MedicineUltrasoundGold standard (test)ObstetricsPredictive valuePregnancyTransabdominal ultrasoundContingency tableUltrasonographyGynecologySurgeryRadiologyInternal medicineMathematicsStatisticsBiologyGeneticsMaternal and Perinatal Health InterventionsAssisted Reproductive Technology and Twin PregnancyPregnancy-related medical research