Diagnostic efficacy of Striae Gravidarum in predicting intraperitoneal adhesions and uterine scar thickness in women undergoing repeat caesarean section


  • Akanksha Mohanty Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
  • H. P. Anand Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India




Intraperitoneal adhesions, Striae gravidarum, Uterine scar thickness


Background: Striae gravidarum (SG) are stretch marks on the skin which develop during pregnancy. Cesarean section is one of the most common operation performed worldwide which carries a potential risk of complications due to the intra-peritoneal adhesions and thickness of previous uterine scar. The aim of this study was to find the diagnostic efficacy of striae gravidarum in predicting intra-peritoneal adhesions (IPA) and uterine scar thickness in women undergoing repeated caesarean delivery.

Methods: It was a cross-sectional study done over a period of 18 months duration. One hundred women with previous cesarean section scheduled for elective LSCS were enrolled for the study. Striae gravidarum was calculated according to the Atwal numerical scoring system. Presence of intra-peritoneal adhesions were graded intraoperatively according to modified Nair scoring system. After extraction of baby, the thickness of lower uterine segment at midpoint of lower flap of uterine incision was measured by metallic screw gauge.

Results: Significant positive correlation was seen between striae gravidarum and intra-peritoneal adhesions. A negative association was established between striae gravidarum severity and thickness of LUS. Owing to its moderately high sensitivity and low specificity in predicting IPA Grade 3 or 4 and LUS scar thickness<3.74mm, striae gravidarum cannot be used as a diagnostic indicator, but can be a useful mass screening method.

Conclusions: Striae gravidarum is a zero-cost simple quick and easy technique which can be universally used with minimal intra-observer variation to predict perioperative complications in low resource settings.

Author Biography

Akanksha Mohanty, Department of Obstetrics and Gynaecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India

Postgraduate resident in Department of Obstetrics and Gynaecology


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