N-terminal pro-brain natriuretic peptide (NT-proBNP) and uric acid are elevated in pregnancies with preeclampsia (PE). Short-term prediction of PE using angiogenic factors has many false-positive results. Our objective was to validate a machine-learning model (MLM) to predict PE in patients with clinical suspicion, and evaluate if the model performed better than the sFlt-1/PlGF ratio alone. A multicentric cohort study of pregnancies with suspected PE between 24⁺⁰ and 36⁺⁶ weeks was used. The MLM included six predictors: gestational age, chronic hypertension, sFlt-1, PlGF, NT-proBNP, and uric acid. A total of 936 serum samples from 597 women were included. The PPV of the MLM for PE following 6 weeks was 83.1% (95% CI 78.5–88.2) compared to 72.8% (95% CI 67.4–78.4) for the sFlt-1/PlGF ratio. The specificity of the model was better; 94.9% vs. 91%, respectively. The AUC was significantly improved compared to the ratio alone [0.941 (95% CI 0.926–0.956) vs. 0.901 (95% CI 0.880–0.921), p < 0.05]. For prediction of preterm PE within 1 week, the AUC of the MLM was 0.954 (95% CI 0.937–0.968); significantly greater than the ratio alone [0.914 (95% CI 0.890–0.934), p < 0.01]. To conclude, an MLM combining the sFlt-1/PlGF ratio, NT-proBNP, and uric acid performs better to predict preterm PE compared to the sFlt-1/PlGF ratio alone, potentially increasing clinical precision.

Background: Methylation markers have shown promise in the early diagnosis of pancreatic carcinoma. The aim of this study was to assess the diagnostic utility of hypermethylation status of candidate genes in combination with KRAS mutation detection in the evaluation of pancreatic masses. Experimental design: Sixty-one fine needle aspirates of pancreatic masses (43 pancreatic adenocarcinomas and 18 chronic pancreatitis) were studied. Methylation status of HRH2, EN1, SPARC, CDH13 and APC were analysed using melting curve analysis after DNA bisulfite treatment. KRAS mutations were also analysed. Results: The methylation panel had a sensitivity of 73% (27 of 37, CI 95% 56 to 86%) and a specificity of 100% whenever two or more promoters were found hypermethylated. KRAS mutations showed a sensitivity of 77% (33 of 43, CI 95% 62 to 88%) and a specificity of 100%. Both molecular analyses added useful information to cytology by increasing the number of informative cases. When genetic and epigenetic analyses were combined sensitivity was 84% (36 of 43 CI 95% 69 to 93%) maintaining a 100% specificity. Conclusions: Analysis of hypermethylation status of a panel of genes and KRAS mutation detection offer a similar diagnostic yield in the evaluation of pancreatic masses. The combined molecular analysis increases the number of informative cases without diminishing specificity.

Deregulation of small non-coding RNAs (sncRNAs) has been associated with the onset of metastasis. We evaluated the expression of sncRNAs in patients with early-stage breast cancer, performing RNA sequencing in 60 patients for whom tumor and sentinel lymph node (SLN) samples were available, and conducting differential expression, gene ontology, enrichment and survival analyses. Sequencing annotation classified most of the sncRNAs into small nucleolar RNA (snoRNAs, 70%) and small nuclear RNA (snRNA, 13%). Our results showed no significant differences in sncRNA expression between tumor or SLNs obtained from the same patient. Differential expression analysis showed down-regulation (n = 21) sncRNAs and up-regulation (n = 2) sncRNAs in patients with locoregional metastasis. The expression of SNHG5, SNORD90, SCARNA2 and SNORD78 differentiated luminal A from luminal B tumors, whereas SNORD124 up-regulation was associated with luminal B HER2+ tumors. Discriminating analysis and receiver-operating curve analysis revealed a signature of six snoRNAs (SNORD93, SNORA16A, SNORD113-6, SNORA7A, SNORA57 and SNORA18A) that distinguished patients with locoregional metastasis and predicted patient outcome. Gene ontology and Reactome pathway analysis showed an enrichment of biological processes associated with translation initiation, protein targeting to specific cell locations, and positive regulation of Wnt and NOTCH signaling pathways, commonly involved in the promotion of metastases. Our results point to the potential of several sncRNAs as surrogate markers of lymph node metastases and patient outcome in early-stage breast cancer patients. Further preclinical and clinical studies are required to understand the biological significance of the most significant sncRNAs and to validate our results in a larger cohort of patients.

Objectives: Several multivariate algorithms for preeclampsia (PE) screening in the first trimester have been developed over the past few years. These models include maternal factors, mean arterial pressure (MAP), uterine artery Doppler (UtA-PI), and biochemical markers (pregnancy-associated plasma protein-A (PAPP-A) or placental growth factor (PlGF)). Treatment with low-dose aspirin (LDA) has shown a reduction in the incidence of preterm PE in women with a high-risk assessment in the first trimester. An important barrier to the implementation of first-trimester screening is the cost of performing tests for biochemical markers in the whole population. Theoretical contingent strategies suggest that two-stage screening models could also achieve high detection rates for preterm PE with lower costs. However, no data derived from routine care settings are currently available. This study was conducted to validate and assess the performance of a first-trimester contingent screening process using PlGF for PE, with prophylactic LDA, for decreasing the incidence of preterm PE. Methods: This was a two-phase study. In phase one, a contingent screening model for PE was developed using a multivariate validated model and a historical cohort participating in a non-interventional PE screening study (n = 525). First-stage risk assessment included maternal factors, MAP, UtA-PI, and PAPP-A. Several cut-off levels were tested to determine the best screening performance, and three groups were then defined (high-, medium-, and low-risk groups). PlGF was determined in the medium-risk group to calculate the final risk. Phase two included a validation cohort of 847 singleton pregnancies prospectively undergoing first-trimester PE screening using this approach. Women at high risk of PE received prophylactic treatment with 150 mg of LDA. The clinical impact of the model was evaluated by comparing the incidence of early-onset (<34 weeks) and preterm (<37 weeks) PE between groups. Results: Cut-off levels for the contingent screening model were chosen in the first and second stages of screening to achieve a performance with sensitivities of 100% and 80% for early-onset and preterm PE detection, respectively, with a 15% false positive rate. In the development phase, 21.5% (n = 113) of the women had a medium risk of PE and required second-stage screening. In the prospective validation phase, 15.3% (n = 130) of the women required second-stage screening for PlGF, yielding an overall screen-positive rate of 14.9% (n = 126). The incidence of preterm PE was reduced by 68.4% (1.9% vs. 0.6%, p = 0.031) after one year of screening implementation. Conclusions: Implementation of contingent screening for PE using PlGF in a routine care setting led to a significant reduction (68.4%) in preterm PE, suggesting that contingent screening can achieve similar results to protocols using PlGF in the whole population. This could have financial benefits, with a similar reduction in the rate of preterm PE.

Algorithms for first-trimester prediction of pre-eclampsia usually include maternal risk factors, blood pressure, placental growth factor (PlGF), and uterine artery Doppler pulsatility index. However, these models lack sensitivity for the prediction of late-onset pre-eclampsia and other placental complications of pregnancy, such as small for gestational age infants or preterm birth. The aim of this study was to assess the screening performance of PlGF, soluble fms-like tyrosine kinase-1 (sFlt-1), N-terminal pro-brain natriuretic peptide (NT-proBNP), uric acid, and high-sensitivity cardiac troponin T (hs-TnT) in the prediction of adverse obstetric outcomes related to placental insufficiency. This retrospective case–control study was based on a cohort of 1390 pregnant women, among which 210 presented pre-eclampsia, small for gestational age infants, or preterm birth. Two hundred and eight women with healthy pregnancies were selected as controls. Serum samples were collected between weeks 9 and 13 of gestation, and maternal serum concentrations of PlGF, sFlt-1, NT-proBNP, uric acid, and hs-TnT were measured. Multivariate regression analysis was used to generate predictive models combining maternal factors with the above-mentioned biomarkers. Women with placental dysfunction had lower median concentrations of PlGF (25.77 vs. 32.00 pg/mL; p < 0.001), sFlt-1 (1212.0 vs. 1363.5 pg/mL; p = 0.001), and NT-proBNP (51.22 vs. 68.71 ng/L; p < 0.001) and higher levels of uric acid (193.66 µmol/L vs. 177.40 µmol/L; p = 0.001). There was no significant difference between groups regarding the sFlt-1/PlGF ratio. Hs-TnT was not detected in 70% of the maternal serums analyzed. Altered biomarker concentrations increased the risk of the analyzed complications both in univariate and multivariate analyses. The addition of PlGF, sFlt-1, and NT-proBNP to maternal variables improved the prediction of pre-eclampsia, small for gestational age infants, and preterm birth (area under the curve: 0.710, 0.697, 0.727, and 0.697 vs. 0.668, respectively). Reclassification improvement was greater in maternal factors plus the PlGF model and maternal factors plus the NT-p roBNP model (net reclassification index, NRI: 42.2% and 53.5%, respectively). PlGF, sFlt-1, NT-proBNP, and uric acid measurements in the first trimester of pregnancy, combined with maternal factors, can improve the prediction of adverse perinatal outcomes related to placental dysfunction. In addition to PlGF, uric acid and NT-proBNP are two promising predictive biomarkers for placental dysfunction in the first trimester of pregnancy.

Importance: The clinical presentation of hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome is one of the more severe forms of preeclampsia. COVID-19 infection exhibits signs that are shared with preeclampsia and HELLP syndrome, which may lead to needless interventions and iatrogenic preterm delivery. Objective: We evaluated the prevalence of HELLP-like signs in pregnant women admitted for COVID-19 and the value of angiogenic factors to rule out preeclampsia. Methods: a consecutive series of 27 pregnant women beyond 20 weeks of gestation, with symptomatic COVID-19. Clinical and analytical features were recorded and those cases with signs of HELLP syndrome were tested for sFlt-1/PlGF ratio. Results: Seven patients (25.9%) presented at least one sign of suspected HELLP syndrome, of which 2 (7.4%) were diagnosed clinically with PE because of hypertension and high transaminases and 5 (18.5%) had only elevated transaminases. sFlt-1/PlGF ratio was normal in 6 of 7. Conclusion: Symptomatic COVID-19 may simulate severe preeclampsia in pregnancy. Angiogenic factors may be essential to avoid false diagnosis and needless interventions. These data were presented in a Virtual Symposium on Covid-19 and Pregnancy on 17 April: 2020:(http://medicinafetalbarcelona.org/simposiocovid19/ [Spanish] and https://medicinafetalbarcelona.org/symposiumcovid19/ [English]