scholarly journals Predictive values of multiple serum biomarkers in women with suspected preeclampsia: a prospective study

2020 ◽  
Author(s):  
Jing Wang ◽  
Honghai Hu ◽  
Xiaowei Liu ◽  
Shenglong Zhao ◽  
Yuanyuan Zheng ◽  
...  
Keyword(s):  
Plasminogen Activator Inhibitor ◽  
Serum Levels ◽  
Serum Markers ◽  
Serum Biomarkers ◽  
Operating Characteristics ◽  
Serum Samples ◽  
Predictive Values ◽  
A Prospective Study ◽  
Activator Inhibitor

Abstract Background: Preeclampsia prediction improves maternal and fetal outcomes in pregnancy. We aimed to evaluate the preeclampsia prediction values of a series of serum biomarkers. Methods: Singleton pregnant women with preeclampsia-related clinical and/or laboratory presentations were recruited and had blood drawn at their first visits. The prospective cohort was further divided into preeclampsia-positive and preeclampsia-negative groups based on the follow-up results. The following markers were tested using the collected serum samples: soluble fms-like tyrosine kinase-1 ( sFlt-1); placental growth factor (PlGF); thrombomodulin (TM); tissue plasminogen activator inhibitor complex (tPAI-C); compliment factors C1q, B, and H; glycosylated fibronectin (GlyFn); pregnancy-associated plasma protein-A2 ( PAPP-A2); blood urea nitrogen (BUN); creatinine (Cre); uric acid (UA); and cystatin C (Cysc). Results: A total of 196 women with suspected preeclampsia were recruited with follow-up medical records. Twenty-five percent (n=49) of the recruited subjects developed preeclampsia before delivery, and 75% remained preeclampsia-negative (n=147). The serum levels of sFlt-1, BUN, Cre, UA, Cysc and PAPP-A2 were significantly elevated, and the PlGF level was significantly decreased in the preeclampsia-positive patients. In the receiver operating characteristics (ROC) analyses, the area under the curves were listed in the order of decreasing values: 0.73 (UA), 0.67 (sFlt-1/PlGF), 0.66 (Cysc), 0.65 (GlyFn/PlGF), 0.64 (PAPP-A2/PlGF), 0.63 (BUN), 0.63 (Cre), and 0.60 (PAPP-A2). With the cut-off values obtained from the ROC analyses, the positive predictive values of these serum markers were between 33.1% and 58.5%, and the negative predictive values were between 80.9% and 89.5%. Conclusions: Further studies are warranted to confirm the clinical utilities of the serum markers in preeclampsia prediction

scholarly journals Predictive values of multiple serum biomarkers in women with suspected preeclampsia: a prospective study

2020 ◽  
Author(s):  
Jing Wang ◽  
Honghai Hu ◽  
Xiaowei Liu ◽  
Shenglong Zhao ◽  
Yuanyuan Zheng ◽  
...  
Keyword(s):  
Medical Records ◽  
Serum Levels ◽  
Serum Markers ◽  
Serum Biomarkers ◽  
Serum Samples ◽  
Predictive Values ◽  
Independent Risk Factors ◽  
A Prospective Study ◽  
In Pregnancy

Abstract Background Early preeclampsia (PE) prediction has been shown to improve the maternal and fetal outcomes in pregnancy. We aimed to evaluate the PE prediction values of a series of serum biomarkers. Methods The singleton pregnant women with PE-related clinical and/or laboratory presentations were recruited and had the blood drawn at their first visits. The prospective cohort was further divided into the PE-positive and PE-negative groups based on the follow-up results. The following markers were tested with the collected serum samples: sFlt-1, PlGF, M, tPAI-C, compliment factors C1q, B, H, BUN, GlyFn, PAPP-A2, BUN, Cre, UA and Cysc. Results Totally 196 women suspected for PE were recruited with follow-up medical records. Twenty-five percent of the recruited subjects developed PE before delivery and 75% remained PE-negative. The serum levels of sFlt-1, BUN, Cre, UA, Cysc and PAPP-A2 were significantly elevated and the PlGF was significantly decreased in the PE-positive patients. The AUCs were listed in the order of decreasing values: UA (AUC = 0.73), sFlt-1/PlGF (AUC = 0.67), Cysc (AUC = 0.66), GlyFn/PlGF (AUC = 0.65), PlGF (AUC = 0.64), PAPP-A2/PlGF (AUC = 0.64), sFlt-1 (AUC = 0.63), BUN (AUC = 0.63), Cre (AUC = 0.63), and PAPP-A2 (AUC = 0.60) in the ROC analyses. The Logistic regression analysis showed that UA and PAPP-A2 were independent risk factors for PE development with the odds ratios of 3.3 and 2.2 respectively. Moreover, the PPVs of UA and PAPP-A2 were 48.9%, and 40.4%; the NPVs of UA and PAPP-A2 were 82.1% and 81.9%. Conclusions Further studies are warranted to confirm the clinical utilities of the serum markers in PE prediction.

scholarly journals Predictive values of multiple serum biomarkers in women with suspected preeclampsia: a prospective study

2020 ◽  
Author(s):  
Jing Wang ◽  
Honghai Hu ◽  
Xiaowei Liu ◽  
Shenglong Zhao ◽  
Yuanyuan Zheng ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Prospective Cohort ◽  
Serum Markers ◽  
Serum Biomarkers ◽  
Clinical Implementation ◽  
Operating Characteristics ◽  
Serum Samples ◽  
Multisystem Disorder ◽  
Predictive Values

Abstract Background: Preeclampsia is a common obstetric multisystem disorder causing maternal and fetal morbidity and mortality; it’s been shown that the prediction improves preeclampsia outcomes in pregnancy. However, the current serum biomarkers had low clinical application values and still lack validation studies. Here we aimed to evaluate the preeclampsia prediction values of a series of serum biomarkers in Chinese pregnant women of > 20 weeks of gestation. Methods: Singleton pregnant women with preeclampsia-related clinical and/or laboratory presentations were recruited and had blood drawn at their first visits. The prospective cohort was further divided into preeclampsia-positive and preeclampsia-negative groups based on the follow-up results. The following markers were tested using the collected serum samples: soluble fms-like tyrosine kinase-1 (sFlt-1); placental growth factor (PlGF); thrombomodulin (TM); tissue plasminogen activator inhibitor complex (tPAI-C); compliment factors C1q, B, and H; glycosylated fibronectin (GlyFn); pregnancy-associated plasma protein-A2 (PAPP-A2); blood urea nitrogen (BUN); creatinine (Cre); uric acid (UA); and cystatin C (Cysc). Results: A total of 196 women with suspected preeclampsia were recruited with follow-up medical records. Twenty-five percent (n=49) of the recruited subjects developed preeclampsia before delivery, and 75% remained preeclampsia-negative (n=147). The serum levels of sFlt-1, BUN, Cre, UA, Cysc and PAPP-A2 were significantly elevated, and the PlGF level was significantly decreased in the preeclampsia-positive patients. In the receiver operating characteristics (ROC) analyses, the area under the curves were listed in the order of decreasing values: 0.73 (UA), 0.67 (sFlt-1/PlGF), 0.66 (Cysc), 0.65 (GlyFn/PlGF), 0.64 (PAPP-A2/PlGF), 0.63 (BUN), 0.63 (Cre), and 0.60 (PAPP-A2). With the cut-off values obtained from the ROC analyses, the positive predictive values of these serum markers were between 33.1% and 58.5%, and the negative predictive values were between 80.9% and 89.5%. Conclusions: Although several serum markers were found to be significantly changed with current prospective cohort, their limited predictive values in preeclampsia development posed potential barrier in clinical implementation. Further studies with larger cohort are warranted to further reveal the clinical utilities of the serum markers in preeclampsia prediction.

Performance of the Surprise Question Compared to Prediction Models in Hemodialysis Patients: A Prospective Study

2017 ◽  
Vol 46 (5) ◽  
pp. 390-396 ◽  
Author(s):  
Rakesh Malhotra ◽  
Xia Tao ◽  
Yuedong Wang ◽  
Yuqi Chen ◽  
Rebecca H. Apruzzese ◽  
...  
Keyword(s):  
Linear Models ◽  
Prediction Models ◽  
Clinical Laboratory ◽  
Mortality Prediction ◽  
Operating Characteristics ◽  
Dialysis Treatment ◽  
Mortality Probability ◽  
A Prospective Study ◽  
Surprise Question

Background: The surprise question (SQ) (“Would you be surprised if this patient were still alive in 6 or 12 months?”) is used as a mortality prognostication tool in hemodialysis (HD) patients. We compared the performance of the SQ with that of prediction models (PMs) for 6- and 12-month mortality prediction. Methods: Demographic, clinical, laboratory, and dialysis treatment indicators were used to model 6- and 12-month mortality probability in a HD patients training cohort (n = 6,633) using generalized linear models (GLMs). A total of 10 nephrologists from 5 HD clinics responded to the SQ in 215 patients followed prospectively for 12 months. The performance of PM was evaluated in the validation (n = 6,634) and SQ cohorts (n = 215) using the areas under receiver operating characteristics curves. We compared sensitivities and specificities of PM and SQ. Results: The PM and SQ cohorts comprised 13,267 (mean age 61 years, 55% men, 54% whites) and 215 (mean age 62 years, 59% men, 50% whites) patients, respectively. During the 12-month follow-up, 1,313 patients died in the prediction model cohort and 22 in the SQ cohort. For 6-month mortality prediction, the GLM had areas under the curve of 0.77 in the validation cohort and 0.77 in the SQ cohort. As for 12-month mortality, areas under the curve were 0.77 and 0.80 in the validation and SQ cohorts, respectively. The 6- and 12-month PMs had sensitivities of 0.62 (95% CI 0.35–0.88) and 0.75 (95% CI 0.56–0.94), respectively. The 6- and 12-month SQ sensitivities were 0.23 (95% CI 0.002–0.46) and 0.35 (95% CI 0.14–0.56), respectively. Conclusion: PMs exhibit superior sensitivity compared to the SQ for mortality prognostication in HD patients.

Abstract 43: Association of Plasminogen Activator Inhibitor-1 with Prevalent and Incident Obesity is Independent of Inflammatory Markers: The Multi-Ethnic Study of Atherosclerosis (MESA)

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Sadiya S Khan ◽  
Donald M Lloyd-Jones ◽  
Cheelin Chan ◽  
Kiang Liu ◽  
Mary Cushman ◽  
...  
Keyword(s):  
Plasminogen Activator ◽  
Inflammatory Markers ◽  
Smoking Status ◽  
Plasminogen Activator Inhibitor ◽  
Cox Proportional Hazards ◽  
Plasminogen Activator Inhibitor 1 ◽  
Ethnic Study ◽  
Activator Inhibitor ◽  
Pai 1

Background: In experimental animal models, deficiency of plasminogen activator inhibitor-1 (PAI-1) protects against development of obesity. In addition, elevated circulating levels of PAI-1 are associated in cross-sectional studies with prevalent obesity in humans. However, no studies have investigated the prospective association between PAI-1 and incident obesity. Methods: Plasma PAI-1 levels were measured in a random sample of men and women at baseline (2000-2002) in the Multi-Ethnic Study of Atherosclerosis. Obesity was defined as body mass index (BMI) > 30kg/m2. Incident obesity was identified at four follow-up exams (2002-2011) among those who were not obese at baseline. Logistic regression was used to examine the odds ratios (OR) and 95% confidence intervals (CI) of prevalent obesity at baseline. Cox proportional hazards regression was used to estimate hazard ratios (HR) for time to incident obesity. The covariates used for adjustment included baseline demographics (age, race, sex, center), lifestyle risk factors (physical activity, dietary energy intake, smoking status, alcohol consumption, education), and inflammatory markers (CRP and IL-6). Results: In 839 participants mean age was 59 years old; 59% and 47% of the cohort were female and white, respectively. At baseline, each standard deviation (SD) increase in log(PAI-1) level was associated with an odds ratio (OR) for adjusted prevalent obesity of 2.70 (95% CI: 2.21 - 3.30, p<0.001. This association remained significant after further adjustment for IL-6 and CRP with OR 2.39 (95% CI: 1.94-2.94, p<0.001). Over a median follow-up of 8.5 years, 16% of participants developed obesity. The multivariable adjusted hazard ratio for incident obesity was 1.36 (95% CI 1.09-1.69, p<0.001) per 1 SD increase in log(PAI-1). (Table). Conclusions: Elevated PAI-1 levels are associated with prevalent and incident obesity. These findings are consistent with results from murine studies and provide evidence suggesting a potential role of PAI-1 in the pathogenesis of obesity.

scholarly journals Global Longitudinal Strain in Heart Transplantation Recipients Using Different Vendors: Reliability and Validity in a Tertiary Hospital in Colombia.

2021 ◽  
Author(s):  
Oscar Mauricio Perez Fernandez ◽  
Hector M. Medina ◽  
Mónica López ◽  
Madeleine Barrera ◽  
Azucena Martinez ◽  
...  
Keyword(s):  
Longitudinal Strain ◽  
Global Longitudinal Strain ◽  
Intraclass Correlation ◽  
Reliability And Validity ◽  
Roc Curves ◽  
Tertiary Hospital ◽  
Operating Characteristics ◽  
Predictive Values ◽  
Left Ventricle Function

Abstract Global Longitudinal Strain (GLS) is a useful tool to follow-up heart transplant (HT) recipients. Important inter-vendor variability of GLS measurements has been reported in healthy subjects and different conditions, but there is still limited evidence among HT patients. We assessed the reliability and validity of GLS using two vendors (General Electric and Philips) in a group of consecutive and stable adult HT recipients. Patients underwent two concurrent GLS analyses during their echocardiographic follow-up. We evaluated GLS inter-vendor reliability using Bland-Altman’s limits of agreement (LOA) plots, computing its coverage probability (CP) and the intraclass correlation coefficient (ICC). Validity was assessed though receiver operating characteristics (ROC) curves, predictive values, sensitivity and specificity of GLS for each vendor to detect a normal left ventricle function. 78 pairs of GLS studies in 53 stable HT patients were analyzed. We observed a modest inter-vendor reliability with a broad LOA (less than 50% of values falling out our CP of 2% and an ICC of 0.49). ROC analyses (areas under the curve of 0.824 Vs. 0.631, p<0.05) and diagnosis test indices (Sensitivity of 0.73 Vs. 0.64; and Specificity of 0.79 Vs. 0.50) favored GE over Philips. Inter-vendor variability for GLS analysis exceeded clinically acceptable limits in HT recipients. GLS from GE software seemed to show higher validity as compared to Philips’. The present study provides evidence to consider caution for the interpretation of GLS for clinical management in the follow-up of HT patients, especially when GLS is measured by different vendors.

scholarly journals Menstruation Distress Is Strongly Associated with Hormone-Immune-Metabolic Biomarkers

2020 ◽  
Author(s):  
Chutima Roomruangwong ◽  
Sunee Sirivichayakul ◽  
Andressa Keiko Matsumoto ◽  
Ana Paula Michelin ◽  
Laura de Oliveira Semeao ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Plasminogen Activator Inhibitor ◽  
Serum Levels ◽  
Insulin Growth Factor ◽  
Estimated Blood Loss ◽  
Gi Symptoms ◽  
Daily Record ◽  
Pain Symptoms ◽  
Metabolic Biomarkers ◽  
Activator Inhibitor

Objective: To examine the associations between menstruation features and symptoms and hormone-immune-metabolic biomarkers. Methods: Forty-one women completed questionnaires assessing characteristic menstruation symptoms, duration of menstrual cycle and number of pads used/day and completed the Daily Record of Severity of Problems (DRSP) during the consecutive days of their menstrual cycle. Menses-related symptoms (MsRS) were computed from the sum of 10 pre- and post-menses symptoms and the menstruation blood and duration index (MBDI) was computed based on the daily number of pads and duration of menses. We assayed serum levels of various biomarkers at days 7, 14, 21, and 28 of the subjects&rsquo; menstrual cycle. Results: MBDI was significantly associated with a) MsRS including low abdominal cramps, and gastro-intestinal (GI) and pain symptoms (positively); b) plasma levels of haptoglobin (Hp), CCL5, insulin growth factor (IGF)-1, and plasminogen activator inhibitor (PAI)1 (all positively); and c) estradiol and paraoxonase (PON)1 arylesterase activity (both inversely). MsRS were significantly predicted by CCL5 and IGF-1 (both positively) and progesterone (inversely). Low-abdominal cramps, and gastro-intestinal and pain symptoms were associated with lower progesterone levels. The MBDI+MsRS score was significantly predicted by the cumulative effects of (in descending order of importance): Hp, IGF-1, PON1 arylesterase, estradiol and PAI. Conclusion: Menstruation-related features including estimated blood loss, duration of menses, cramps, pain and GI symptoms are associated with hormone-immune-metabolic biomarkers, which mechanistically may explain those features. Women with an increased MBDI+MsRS index &ge; 0.666 percentile may be considered to have menstruation-related distress, including dysmenorrhea symptoms.

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