| Autor: |
Andrade Júnior, Valter Lacerda de, França, Marcelo Santucci, Santos, Roberto Angelo Fernandes, Hatanaka, Alan Roberto, Cruz, Jader de Jesus, Hamamoto, Tatiana Emy Kawanami, Traina, Evelyn, Sarmento, Stephanno Gomes Pereira, Elito Júnior, Júlio, Pares, David Baptista da Silva, Mattar, Rosiane, Araujo Júnior, Edward, Moron, Antonio Fernandes |
| Předmět: |
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| Zdroj: |
Journal of Maternal-Fetal & Neonatal Medicine; 2023, Vol. 36 Issue 2, p1-17, 17p |
| Abstrakt: |
The objective of this study is to create a new screening for spontaneous preterm birth (sPTB) based on artificial intelligence (AI). This study included 524 singleton pregnancies from 18th to 24th-week gestation after transvaginal ultrasound cervical length (CL) analyzes for screening sPTB < 35 weeks. AI model was created based on the stacking-based ensemble learning method (SBELM) by the neural network, gathering CL < 25 mm, multivariate unadjusted logistic regression (LR), and the best AI algorithm. Receiver Operating Characteristics (ROC) curve to predict sPTB < 35 weeks and area under the curve (AUC), sensitivity, specificity, accuracy, predictive positive and negative values were performed to evaluate CL < 25 mm, LR, the best algorithms of AI and SBELM. The most relevant variables presented by LR were cervical funneling, index straight CL/internal angle inside the cervix (≤ 0.200), previous PTB < 37 weeks, previous curettage, no antibiotic treatment during pregnancy, and weight (≤ 58 kg), no smoking, and CL < 30.9 mm. Fixing 10% of false positive rate, CL < 25 mm and SBELM present, respectively: AUC of 0.318 and 0.808; sensitivity of 33.3% and 47,3%; specificity of 91.8 and 92.8%; positive predictive value of 23.1 and 32.7%; negative predictive value of 94.9 and 96.0%. This machine learning presented high statistical significance when compared to CL < 25 mm after T-test (p <.00001). AI applied to clinical and ultrasonographic variables could be a viable option for screening of sPTB < 35 weeks, improving the performance of short cervix, with a low false-positive rate. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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