title: Five year retrospective case series of adnexal torsion.
abstract: OBJECTIVE
  Adnexal torsion is a rare gynaecological emergency that requires an early surgical intervention to save the adnexa from irreversible damage .Our study is about clinical presentation and management approach of adnexal torsion in a tertiary care centre.
  
  
  METHODS
  Retrospective study.
  
  
  METHODS
  Review of case records during the five years of 2008 November -2013 November in Amrita Institute of Medical Sciences, Kochi, India.
  
  
  RESULTS
  Adnexal torsion was found mainly in the reproductive age. Ultrasound was the most commonly used imaging modality. Benign tumours predispose to torsion. Torsion occurred during postovulatory period in many cases. Polycystic ovaries were a risk factor for unexplained torsion in younger age groups. Diagnosis of adnexal torsion was mostly intra operative by direct visualisation of the rotated adnexa. Laparoscopy was the preferred method of surgical intervention. Ovarian conservation was tried in majority of the child bearing age groups.
  
  
  CONCLUSIONS
  Adnexal torsion is a rare emergency which requires a high index of clinical suspicion for diagnosis as the symptoms are non specific. Imaging helps in diagnosis but most of them are diagnosed intra operatively. Laparoscopic conservative surgery is the preferred surgical approach especially in younger age groups. An early surgical intervention helps in salvaging the adnexa and prevents further complications.
authors: Assistant Professor, Department of Obstetrics and Gynaecology, Amrita Institute of Medical Sciences , Kochi, Kerala, India .
authors: Sobha
authors: S
authors: Nair
authors: Assistant Professor, Department of Obstetrics and Gynaecology, Amrita Institute of Medical Sciences , Kochi, Kerala, India .
authors: Smitha
authors: S
authors: Joy
authors: Professor, Department of Obstetrics and Gynaecology, Amrita Institute of Medical Sciences , Kochi, Kerala, India .
authors: Jayashree
authors: J
authors: Nayar
keywords: PCA (principal component analysis); Procustes; Statistical shape analysis
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