outcome were significantly increased in infants with abnormal S/D ratio (P < 0.001). When logistic regression analysis was performed after adjusting for gestational age, the odds ratio for poor perinatal outcome was 3.7 in the group showing abnormal S/D ratio (95% confidence interval 1.42-9.54, P = 0.007). Conclusion: Umbilical artery Doppler velocimetry is shown as a significantly efficient method in predicting perinatal outcome in preterm neonates with small-for-gestational age, and it may be useful in managing preterm patients with small-for-gestational age fetuses.Objectives: To show the role of umbilical artery Doppler examination in the evaluation of fetal growth potential and the quantification of various IUGR forms. Material and methods: The study included 116 single pregnancies with suspicion of IUGR following conventional ultrasound (IUGRE). The patients underwent fetal umbilical artery Doppler examination, measuring the RI value. The pregnant women were assigned to two groups: 54 hypertensive pregnancies and 62 non-hypertensive pregnancies. Results: At birth, there were 80 (68.9%) newborns with a weight deficit. The results obtained in non-hypertensive patients: the incidence of fetal weight deficit at birth was 51.6% (12.9% the moderate form, 38.7% the severe form). The reliability of umbilical Doppler examination was Se =68.7%, Sp =93.3%, PPV =91.6%, NPV =73.6%. The results obtained in hypertensive patients: the incidence of fetal weight deficit at birth was 88.8% (25.9% the moderate form and 62.9% the severe form). The reliability of umbilical Doppler examination in the evaluation of fetal growth disorders was Se = 66.6%, Sp = 100%, PPV = 100%, NPV = 27.2%. A 15.5% error percent (8.6% false negative results and 6.9% false positive results) was obtained.
Conclusions:In the presence of an ultrasound suspicion of IUGR, an abnormal umbilical RI value allows to confirm the alteration of fetal growth potential. A normal RI value in the context of IUGRE has a different significance depending on the presence or the absence of hypertension.
P46.08 Blood flow in pregnancies complicated with IUGR
the starting weights were obtained from a pre-trained model on ImageNet. The model was then trained on our dataset using a supervised learning approach. To classify a WSI, the model was applied in a sliding window fashion with an input tile size of 224x224 and a stride of 128 on a magnification of x10. The maximum probability was then used as a WSI diagnosis. In this study, this established model was validated in 2171 TBLB specimen WSIs (439, 143, 73 and 1516 specimens of ADC, SCC, SCLC and non-neoplastic lesions, respectively).
Results:The model achieved a Receiver Operator Curve Area Under the Curve (ROC-AUC) of 0.9458 (95% confidence interval [CI] 0.9316-0.9575) for non-neoplastic lesions with an accuracy, sensitivity and specificity of 0.8738, 0.8971 and 0.8661, respectively. The ROC-AUCs for ADC, SCC and SCLC were 0.8469 (95% CI 0.8170-0.8725), 0.9141 (95% CI 0.8825-0.9443) and 0.9412 (95% CI 0.905-0.9703), respectively.Conclusions: Our model achieved high ROC-AUCs for the differentiation of ADC, SCC, SCLC and non-neoplastic lesions. Further studies are warranted to refine the established model.Legal entity responsible for the study: The authors.
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