Fetal Main Pulmonary Artery Doppler and Lamellar Body Count in Amniotic Fluid as Predictors for Respiratory Distress Syndrome Development

Context: Insufficient surfactant in the underdeveloped fetal lungs can cause severe respiratory distress syndrome (RDS), potentially necessitating specialized management during delivery. Aims: Investigate the lamellar body count in amniotic fluid and fetal main pulmonary artery doppler measures as possible markers for the onset of respiratory distress syndrome. Settings and Design: This cross-sectional study included 118 pregnant women scheduled for elective Cesarean sec-tion. Participants were recruited from Menoufia Univer-sity Hospital and El-Tahrir General Hospital in Imbaba. Methods and Material: All the studied cases were sub-jected to: Detailed personal and obstetric histories in-cluded information such as:(Age, BMI, Sex, Gravidity, Parity, Gestational age, Previous CS, Previous PTL, Cor-ticosteroids and Corticosteroids dose time), Ultrasound Examinations, Cesarean section and delivery assessment, Post-Delivery Neonatal Evaluation.Statistical analysis used: Data analysis was conducted using SPSS version 24, which stands for the Statistical Program for the Social Sciences. Results: Patients with respiratory distress syndrome (RDS) can be reliably identified using the pulmonary ar-tery pulsatility index (PI) when the cut off value is more than 2.55. It shows 81.8% sensitivity, 100% specificity, 100% positive predictive value (PPV), and 98.2% nega-tive predictive value (NPV) with an area under the curve (AUC) of 0.96 and a p-value less than 0.001. Also, with a cutoff value higher than 0.89, the pulmonary artery resis-tance index (RI) can distinguish RDS in these patients. It has a 0.9 area under the curve (AUC) and a p-value of less than 0.001, in addition to 81.8% sensitivity, 85% specific-ity, 36% PPV, and 97.8% NPV.Conclusions: A fetal main pulmonary artery Doppler measurement, an amniotic fluid lamellar body count (LBC) and pulmonary artery index can be used to an-ticipate neonatal respiratory distress syndrome (RDS). In conjunction with lower LBC and higher Pulmonary Artery Pulsatility Index (PI) and Resistance Index (RI), these non-invasive methods of fetal lung maturity evaluation are very helpful in assessing the risk of RDS.

Authors

Institutions

Publication Details

Journal
The Egyptian Journal of Fertility of Sterility
Published
2025-05-01
DOI
https://doi.org/10.21608/egyfs.2025.431333
Primary Topic
Neonatal Respiratory Health Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fetal Main Pulmonary Artery Doppler and Lamellar Body Count in Amniotic Fluid as Predictors for Respiratory Distress Syndrome Development

Dena Serag, Heba Farag Mohamed Salama, Mohamed Abdelghani Emaraa, Kerolos Usama Henry Sorial et al.
The Egyptian Journal of Fertility of Sterility
Neonatal Respiratory Health Research
article

Fetal Main Pulmonary Artery Doppler and Lamellar Body Count in Amniotic Fluid as Predictors for Respiratory Distress Syndrome Development

Dena Serag, Heba Farag Mohamed Salama, Mohamed Abdelghani Emaraa, Kerolos Usama Henry Sorial, Mohamed Sabry Ahmed Rawash
article en

Abstract

Context: Insufficient surfactant in the underdeveloped fetal lungs can cause severe respiratory distress syndrome (RDS), potentially necessitating specialized management during delivery. Aims: Investigate the lamellar body count in amniotic fluid and fetal main pulmonary artery doppler measures as possible markers for the onset of respiratory distress syndrome. Settings and Design: This cross-sectional study included 118 pregnant women scheduled for elective Cesarean sec-tion. Participants were recruited from Menoufia Univer-sity Hospital and El-Tahrir General Hospital in Imbaba. Methods and Material: All the studied cases were sub-jected to: Detailed personal and obstetric histories in-cluded information such as:(Age, BMI, Sex, Gravidity, Parity, Gestational age, Previous CS, Previous PTL, Cor-ticosteroids and Corticosteroids dose time), Ultrasound Examinations, Cesarean section and delivery assessment, Post-Delivery Neonatal Evaluation.Statistical analysis used: Data analysis was conducted using SPSS version 24, which stands for the Statistical Program for the Social Sciences. Results: Patients with respiratory distress syndrome (RDS) can be reliably identified using the pulmonary ar-tery pulsatility index (PI) when the cut off value is more than 2.55. It shows 81.8% sensitivity, 100% specificity, 100% positive predictive value (PPV), and 98.2% nega-tive predictive value (NPV) with an area under the curve (AUC) of 0.96 and a p-value less than 0.001. Also, with a cutoff value higher than 0.89, the pulmonary artery resis-tance index (RI) can distinguish RDS in these patients. It has a 0.9 area under the curve (AUC) and a p-value of less than 0.001, in addition to 81.8% sensitivity, 85% specific-ity, 36% PPV, and 97.8% NPV.Conclusions: A fetal main pulmonary artery Doppler measurement, an amniotic fluid lamellar body count (LBC) and pulmonary artery index can be used to an-ticipate neonatal respiratory distress syndrome (RDS). In conjunction with lower LBC and higher Pulmonary Artery Pulsatility Index (PI) and Resistance Index (RI), these non-invasive methods of fetal lung maturity evaluation are very helpful in assessing the risk of RDS.

The Egyptian Journal of Fertility of SterilityVol. 29(3)
Society of Interventional Radiology (US), Hospital Oncológico Docente "Conrado Benítez García" (CU), University Radiology (US), Assiut University (EG)
Openalex Percentile: Top 78%
Neonatal Respiratory Health Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.