Preoperative predictive factors in the surgical treatment of congenital gastrointestinal anomalies
DOI:
https://doi.org/10.5457/ams.v42i1.309Keywords:
gastrointestinal anomalies, treatment, predictorsAbstract
Background: Congenital anomalies of the gastrointestinal tract are a significant cause of perinatal morbidity and mortality. The aim of this study was to identify the preoperative factors which could help to predict the outcome of new-borns who undergo surgery for congenital gastrointestinal anomalies.
Methods: All newborns born between January 1st,1998 to December 31st, 2011. that had anomalies of the gastrointestinal tract and were surgically treated at the University Clinical Centre, Tuzla were included in this study. Seventy-two newborns were included, of which 42 (58.33%) were born at term and 30 (41.67%) were preterm. The preoperative predictive factors were analysed.
Results: The most frequent disorders of gastrointestinal tract were gastroschisis and jejunoileal atresia (20.8%) and the least frequent was omphalocele (4.2%). Twenty six new-borns (36.11%) had associated anomalies, whilst in 46 newborns (63.89%) no associated anomalies were detected in the neonatal period. There was a statistically significant correlation with unfavourable outcome after surgical treatment of newborns where resuscitation procedures were used (p<0.041), or when feeding was delayed (p<0.018) or the time of evacuation of the meconium was extended (p<0.040). An unfavourable outcome may be predicted in those newborns with anomalies of the gastrointestinal who underwent surgery tract in relation to the length of the pregnancy, expressed as gestational age (p=0.041) and perinatal care (p=0.032).
Conclusion: Some unfavourable factors are preventable, such as inadequate perinatal care and its effect on the length of the pregnancy, and also by the lack of prenatal diagnosis. Better organization of health care is an effective and cheap way of preventing the risk factors identified.
Key words: gastrointestinal anomalies, treatment, predictors
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