Circulatory soluble endoglin and its predictive value for preeclampsia in second-trimester pregnancies with abnormal uterine perfusion

Stepan, Holger; Geipel, A.; Schwarz, Friederike; Kramer, Thomas H.; Wessel, Niels; Faber, R.

doi:10.1016/j.ajog.2007.08.052

Cited by 114 publications

(66 citation statements)

References 32 publications

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“…The predictive abilities of sFlt-1 and PlGF for preeclampsia were excellently reviewed by Widmer et al in a systematic review [33]. The test utility for sENG is summarized from 4 most recent studies [35,43,61,62] as shown in Table 2.…”

Section: Soluble Endoglinmentioning

confidence: 99%

Novel Angiogenic Factors for Predicting Preeclampsia: sFlt-1, PlGF, and Soluble Endoglin~!2008-08-29~!2008-12-15~!2009-01-02~!

Chen¹

2009

TOCCHEMJ

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Preeclampsia is a devastating multisystem syndrome and is a major cause of maternal, fetal and neonatal morbidity and mortality. Angiogenic factors contribute to the molecular mechanisms of preeclampsia and its main phenotypes such as hypertension and proteinuria. Very recently, novel anti-angiogenic proteins including soluble fms-like tyrosine kinase-1 (sFlt-1) and soluble endoglin (sEng), and one pro-angiogenic protein placental growth factor (PlGF) have been found to be significantly abnormal several weeks preceding the onset of clinical signs and symptoms. Automatic immunoassays are being developed for sFlt-1 and PlGF. This article will summarize our current knowledge of these markers and their roles on predicting preeclampsia.

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Section: Soluble Endoglinmentioning

confidence: 99%

Novel Angiogenic Factors for Predicting Preeclampsia: sFlt-1, PlGF, and Soluble Endoglin~!2008-08-29~!2008-12-15~!2009-01-02~!

Chen¹

2009

TOCCHEMJ

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“…Screening for Downs's syndrome in the first trimester is a good example where a combination of ultrasound scanning and biochemical markers are used. For instance, the combination of uterine artery Doppler pathological findings with altered biochemical markers in second trimester have shown better than use of the Doppler test or the factors alone for prediction of the PE [59,[76][77][78] . Stepan et al showed that combination of abnormal Doppler findings with sFlt1 increased the sensitivity of Doppler alone for preterm delivery from 67% to 83% and the specificity from 76% to 89% [59].…”

Section: Discussionmentioning

confidence: 99%

“…For instance, the combination of uterine artery Doppler pathological findings with altered biochemical markers in second trimester have shown better than use of the Doppler test or the factors alone for prediction of the PE [59,[76][77][78] . Stepan et al showed that combination of abnormal Doppler findings with sFlt1 increased the sensitivity of Doppler alone for preterm delivery from 67% to 83% and the specificity from 76% to 89% [59]. Crispi et al found 90% sensitivity and 95% specificity for identifying early onset preeclampsia when using the combination of second trimester serum PlGF and uterine artery mean pulsatility index [77].…”

Section: Discussionmentioning

confidence: 99%

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Prediction of the preeclampsia: a view of biochemical markers

Bostancı

Bayram

Cevrioğlu

et al. 2013

RHC

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Preeclampsia is a diverse, multiorgan group of related disease processes that occurs in up to 5%-8% of pregnancies after 20 weeks' gestation and it is one of the leading causes of maternal and fetal morbidity and mortality. Many molecular mechanisms are contributed to the pathogenesis of preeclampsia. Although it is unknown whether the mechanisms act independently or have synergistic effects. This review describes review of primary papers investigating blood based biomarker such as PAP-A, Inhibin A, sFlt1, and PP13 in general and first trimester biochemical markers and combinations of them specifically for preeclampsia.

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“…PE affects healthy nulliparous women in a range between 2 and 7 per cent worldwide [14]. Several strategies are used in order to predict PE, among which we can mention some biochemical markers, such as fms-like tyrosine kinase 1 (sFlt-1), placental growth factor (PlGF), soluble endoglin [15,16], maternal autoantibody, the angiotensin II type I receptor agonistic autoantibody (AT1-AA) [17], the urinary biomarkers [18], ultrasonographic markers [19], non-invasive CV markers [20] or the combination of some of those [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Classification of cardiovascular time series based on different coupling structures using recurrence networks analysis

Ramírez-Ávila

Gapelyuk²,

Marwan

et al. 2013

Phil. Trans. R. Soc. A.

Self Cite

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We analyse cardiovascular time series with the aim of performing early prediction of preeclampsia (PE), a pregnancy-specific disorder causing maternal and foetal morbidity and mortality. The analysis is made using a novel approach, namely the ε -recurrence networks applied to a phase space constructed by means of the time series of the variabilities of the heart rate and the blood pressure (systolic and diastolic). All the possible coupling structures among these variables are considered for the analysis. Network measures such as average path length, mean coreness, global clustering coefficient and scale-local transitivity dimension are computed and constitute the parameters for the subsequent quadratic discriminant analysis. This allows us to predict PE with a sensitivity of 91.7 per cent and a specificity of 68.1 per cent, thus validating the use of this method for classifying healthy and preeclamptic patients.

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Circulatory soluble endoglin and its predictive value for preeclampsia in second-trimester pregnancies with abnormal uterine perfusion

Cited by 114 publications

References 32 publications

Novel Angiogenic Factors for Predicting Preeclampsia: sFlt-1, PlGF, and Soluble Endoglin~!2008-08-29~!2008-12-15~!2009-01-02~!

Novel Angiogenic Factors for Predicting Preeclampsia: sFlt-1, PlGF, and Soluble Endoglin~!2008-08-29~!2008-12-15~!2009-01-02~!

Prediction of the preeclampsia: a view of biochemical markers

Classification of cardiovascular time series based on different coupling structures using recurrence networks analysis

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