20.500.12556/DiRROS-24655 Uncovering early predictors of cerebral palsy through the application of machine learning a case–control study Objective Cerebral palsy (CP) is a group of neurological disorders with profound implications for children’s development. The identification of perinatal risk factors for CP may lead to improved preventive and therapeutic strategies. This study aimed to identify the early predictors of CP using machine learning (ML). Design This is a retrospective case–control study, using data from the two population-based databases, the Slovenian National Perinatal Information System and the Slovenian Registry of Cerebral Palsy. Multiple ML algorithms were evaluated to identify the best model for predicting CP. Setting This is a population-based study of CP and control subjects born into one of Slovenia’s 14 maternity wards. Participants A total of 382CP cases, born between 2002 and 2017, were identified. Controls were selected at a control-to-case ratio of 3:1, with matched gestational age and birth multiplicity. CP cases with congenital anomalies (n=44) were excluded from the analysis. A total of 338CP cases and 1014 controls were included in the study. Exposure 135 variables relating to perinatal and maternal factors. Main outcome measures Receiver operating characteristic (ROC), sensitivity and specificity. Results The stochastic gradient boosting ML model (271 cases and 812 controls) demonstrated the highest mean ROC value of 0.81 (mean sensitivity=0.46 and mean specificity=0.95). Using this model with the validation dataset (67 cases and 202 controls) resulted in an area under the ROC curve of 0.77 (mean sensitivity=0.27 and mean specificity=0.94). Conclusions Our final ML model using early perinatal factors could not reliably predict CP in our cohort. Future studies should evaluate models with additional factors, such as genetic and neuroimaging data early predictors cerebral palsy true false true Angleški jezik Ni določen Neznano 2025-12-10 13:51:23 2025-12-10 13:51:24 2025-12-11 03:46:38 0000-00-00 00:00:00 2024 0 0 Nasl. z nasl. zaslona; Opis vira z dne 2. 9. 2024; str. 1-7 issue 1, [article no.] e002800 Vol. 8 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616.3-053.2 2399-9772 10.1136/bmjpo-2024-002800 206047747 RAZ_Rapuc_Sara_2024.pdf RAZ_Rapuc_Sara_2024.pdf 1 6BA7C2B427ACB43F535C3A9DE8614D23 cc38749286e298124ba7f6ba9ccc64c9ebdbb1f3249838f50e1a0a747f95c14d 4bdd869d-d5c7-11f0-94a7-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=36804 https://bmjpaedsopen.bmj.com/content/8/1/e002800 0 f1c7302c-d5c6-11f0-94a7-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=36803 Univerzitetni klinični center Ljubljana 0 0 0