PropertyValue
?:abstract
  • Background Antepartum assessment of the fetus is very important to prevent intra-uterine demise, birth asphyxia, neurological defect of newborns and neonatal mortality. Cardiotocography is the best indicator for fetal surveillance during labour in low resource country. Objective To assess on admission cardiotocography and predict perinatal outcome of antenatal mothers admitted to labour room for delivery at Dhulikhel Hospital, Kathmandu University Hospital. Method A prospective, observational study was conducted from 1st January 2016 to 31st December 2017. Antenatal mothers were evaluated in admission cardiotocography for 20 minutes. Cardiotocography studies were interpreted and categorized according to the classification proposed by National Institute of Clinical Excellence (NICE)- clinical guidelines 2007. Result Total 204 mothers were enrolled, the mean age is 24.06±4.331. Cardiotocography interpretation shows, 81.4% of Normal, 13.7% suspected and only 4.9% accounts pathological. Mother having CTG of pathological had more operative delivery 80% compare to normal and suspicious (0.0001). Similarly, more meconium stained liquor fall in pathological group with p value of 0.002. Fetal distress in labour is seen in all groups, showing 13.3% in normal, 32.1% in suspicious and 80% in pathological with p value 0.000. The duration of on admission cardiotocography to occurrence of fetal distress found to be mean hour of 9.57. Conclusion The admission cardiotocography test is useful to detect fetal distress which is already present at the time of test and can predict fetal wellbeing during the next few hours of labour. This test might lead to higher incidence of operative delivery at low resource countries because of lack of fetal blood sampling test to confirm fetal hypoxia during labour.
is ?:annotates of
?:creator
?:journal
  • Kathmandu_Univ_Med_J_(KUMJ)
?:license
  • unk
?:publication_isRelatedTo_Disease
?:source
  • WHO
?:title
  • Admission Cardiotocography in Predicting Perinatal Outcome
?:type
?:who_covidence_id
  • #33305748
?:year
  • 2019

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