Predicting intensive care need in women with preeclampsia using machine learning - a pilot study.

BACKGROUND: Predicting severe preeclampsia with need for intensive care is challenging. To better predict high-risk pregnancies to prevent adverse outcomes such as eclampsia is still an unmet need worldwide. In this study we aimed to develop a prediction model for severe outcomes using routine biomarkers and clinical characteristics. METHODS: We used machine learning models based on data from an intensive care cohort with severe preeclampsia (n=41) and a cohort of preeclampsia controls (n=40) with the objective to find patterns for severe disease not detectable with traditional logistic regression models. RESULTS: The best model was generated by including the laboratory parameters aspartate aminotransferase (ASAT), uric acid and body mass index (BMI) with a cross-validation accuracy of 0.88 and an area under the curve (AUC) of 0.91. Our model was internally validated on a test-set where the accuracy was lower, 0.82, with an AUC of 0.85. CONCLUSION: The clinical routine blood parameters ASAT and uric acid as well as BMI, were the parameters most indicative of severe disease. Aspartate aminotransferase reflects liver involvement, uric acid might be involved in several steps of the pathophysiologic process of preeclampsia, and obesity is a well-known risk factor for development of both severe and non-severe preeclampsia likely involving inflammatory pathways..[Figure: see text].

Prediction of adverse maternal and perinatal outcomes associated with pre-eclampsia and hypertensive disorders of pregnancy: a systematic review and meta-analysis.

Background: Hypertensive disorders of pregnancy are a leading cause of maternal and perinatal morbidity and mortality. If women at high risk for developing complications could be identified early, level of care could be triaged, limited resources could be correctly allocated and targeted interventions to prevent complications could be implemented. Methods: We updated a systematic review and meta-analysis and added single outcomes. Women with hypertensive disorders of pregnancy were included. Exposures were tests predicting adverse maternal and/or perinatal outcomes. We searched Medline, Embase, CINAHL, and Cochrane library from January 2016-February 2024. We included studies identified from the previous review. We calculated effect measures. For similar predictive tests and outcomes, area under the receiver-operating-characteristic curve (AUROC) were pooled. This study was registered by PROSPERO: CRD42022336368. Findings: Of the 2898 studies identified, 80 were included. Thirty were added from the previous review resulting in 110 included studies with 506,178 women. Despite more than 1500 tests being performed, most outcomes could not be pooled due to heterogeneity in populations, tests, and outcome definitions. For maternal outcomes, only studies reporting on the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) model could be pooled. For the composite outcome within 48-h the AUROC was 0.78 (95% CI 0.71-0.86, N = 8). There was significant heterogeneity (I 2  = 95.7%). For perinatal outcomes, data were pooled for pulsatility index in the umbilical artery and soluble FMS-like tyrosine kinase-1 (sFlt-1)/placental growth factor (PlGF) ratio. Biomarkers like the sFlt-1/PlGF ratio showed promising predictive performance for some outcomes but were not externally validated. Interpretation: Despite including over 100 studies with more than 1500 predictors, we were unable to pool any single maternal outcomes and only a few individual perinatal outcomes. The fullPIERS model was externally validated, showing moderate accuracy which varied across studies and should be validated in each new population. Angiogenic biomarkers showed promise but need validation. Future studies should use standardized outcome measures and validate promising tests. Funding: VB is supported by the Swedish Research Council, Grant number 2020-01481. University of Gothenburg.

Intensive care patients with preeclampsia - Clinical risk factors and biomarkers for oxidative stress and angiogenic imbalance as discriminators for severe disease.

BACKGROUND: Approximately 180 mothers are treated in Swedish Intensive Care Units (ICU) due to preeclampsia each year. Although several clinical risk factors are known, prediction of critical disease is challenging. Two scavenger proteins, hemopexin (Hpx) and alpha-1-microglobulin (A1M) have been suggested to be associated with the oxidative stress seen in preeclampsia. The ratio of two other biomarkers, soluble fms-like tyrosine kinase (sFlt-1) to placental growth factor (PIGF), is predictive of adverse pregnancy outcomes. METHODS: In total 121 women were included in this study where we compared risk factors for preeclampsia, plasma levels of Hpx and A1M in ICU-patients with preeclampsia (n = 41) compared to uncomplicated preeclampsia cases (n = 40) and normotensive pregnancies (n = 40), with the objective to identify clinical risk patterns for severe disease. The sFlt-1/PIGF ratio was investigated in early and late onset preeclampsia ICU-patients. Blood samples were collected at admission to ICU and within 27 h postpartum for all groups. RESULTS: Hemopexin and A1M levels were significantly lower in the preeclampsia ICU-cohort compared to uncomplicated preeclampsia patients. The sFlt-1/PIGF-ratio was elevated in the ICU-patients but there was no difference between early and late onset preeclampsia. The ICU-patients had more clinical risk factors, refractory hypertension, and an increased rate of emergency Caesarean section. CONCLUSION: Intensive care patients have more clinical risk factors and a Hpx and A1M profile suggestive of depletion and thereby a reduced capacity to respond to oxidative stress. The ratios of sFlt-1/PIGF were high in the ICU-cohort and in accordance with pre-delivery levels predictive of adverse pregnancy outcomes.

Depth-Resolved FTIR-ATR Imaging Studies of Coating Degradation during Accelerated and Natural Weathering-Influence of Biobased Reactive Diluents in Polyester Melamine Coil Coating.

Improved methods to assess the degradation of coil coatings to approximate lifetime have been an area of academic and industrial interest for decades. This work aims to elucidate the differences in the degradation behavior of two coil coating systems: one standard commercial formulation and one formulation with a significant addition of biorenewable reactive diluents. Depth-resolved degradation behavior of samples exposed to accelerated and natural field weathering is assessed. Focal plane array attenuated total reflection-Fourier transform infrared spectroscopy was used to acquire high-resolution chemical data from a sloping cross section. The results agreed with conventional photoacoustic spectroscopy. Degradation profiles for the two coatings were significantly different, with the biobased samples showing a more durable behavior. This study provides a method for detailed assessment of coating degradation, giving a good estimation of its durability. This is both a way to compare the performance of coating systems and to improve the understanding of the impact of exposure conditions, paving the way for the development of more sustainable coil coatings.