Diagnostic Accuracy of Lactate Dehydrogenase for Diagnosis of Birth Asphyxia in Preterm Neonates
DOI:
https://doi.org/10.53350/pjmhs020231712826Abstract
Background: Birth asphyxia remains a major cause of neonatal morbidity and mortality, particularly in preterm infants. Serum lactate dehydrogenase (LDH) has been identified as a potential biochemical marker for early detection of hypoxic-ischemic injury. Elevated LDH levels within the first six hours of life have been shown to predict the development of hypoxic-ischemic encephalopathy (HIE) within 6–72 hours after birth.
Objective: To determine the diagnostic accuracy of serum LDH for the diagnosis of birth asphyxia in preterm neonates, using arterial blood gas (ABG) acidosis as the gold standard.
Methods: The study protocol was approved after which the cross-sectional validation study was carried out in the Department of Pediatrics, Jinnah Hospital, Lahore, in a duration of six months from June 2017 to November 2017. Immediately after delivery of the placenta blood samples were taken under aseptic conditions to determine the level of serum LDH. Afterwards, blood samples taken in the arteries were measured to assess pH and base excess. Neonates were identified as positive or negative birth asphyxia according to pre-determined LDH and ABG results. Parameters of diagnostic accuracy such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall accuracy were computed.
Results: Among 320 preterm neonates, the diagnostic accuracy of LDH for identifying birth asphyxia was 76.56%, with a sensitivity of 80%, specificity of 70.83%, PPV of 82.05%, and NPV of 68%.
Conclusion: Serum LDH demonstrates good diagnostic performance for early detection of birth asphyxia in preterm neonates. It can serve as a reliable, cost-effective, and less invasive complement to conventional diagnostic tools such as ABG analysis.
Keywords: Lactate dehydrogenase, Birth asphyxia, Preterm neonates, Arterial blood gases, Acidosis
Downloads
How to Cite
Issue
Section
License
Copyright (c) 2023 Attiba Aslam, Alia Afzal, Javed Tahir

This work is licensed under a Creative Commons Attribution 4.0 International License.
