The Assessment of High Post-Clopidogrel Platelet Reactivity Using the Vasodilator-Stimulated Phosphoprotein Phosphorylation Index – Comparison with Light Transmittance Aggregometry.

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1093-1093
Author(s):  
In-Suk Kim ◽  
Young-Hoon Jeong ◽  
Arum Kim ◽  
Gyeong-Won Lee
Keyword(s):  
Roc Curve ◽  
Platelet Reactivity ◽  
Flow Cytometric Analysis ◽  
Curve Analysis ◽  
Light Transmittance ◽  
Reactivity Index ◽  
Roc Curve Analysis ◽  
Flow Cytometric ◽  
Light Transmittance Aggregometry ◽  
P Index

Abstract Abstract 1093 Background Flow cytometric analysis of platelet reactivity index of vasodilator-stimulated phosphoprotein-phosphorylation (VASP-P) is a suitable test to evaluate the “high post-treatment platelet reactivity (HPPR)”. A reliable cut-off of VASP-P index is needed to identify the HPPR. However, an ideal cut-off identifying HPPR using the VASP-P index remains undetermined. We aimed to show the comparison between light transmittance aggregometry (LTA) and flow cytometric analysis of VASP-P index and assess the cut-offs of identifying HPPR using VASP-P index. Methods We enrolled consecutively patients undergoing percutaneous coronary intervention (PCI) in real clinical practice (n = 516). They all received clopidogrel and aspirin, performed LTA (5 and 20 μmol/l ADP-induced, and 1.6 nmol/l arachidonic acid (AA)-induced PR) and flow cytometric analysis of VASP-P index simultaneously and compared the different platelet measures. Based on previously suggested cut-offs, 5 μmol/l ADP-induced maximal platelet reactivity (PRmax) > 42.9%, 5 μmol/l ADP-induced PRmax > 50%, 20 μmol/l ADP-induced PRmax > 62%, 20 μmol/l ADP-induced PRmax > 64.5%, and 1.6 mmol/l AA-induced PRmax > 20%, the cut-offs of identifying HPPR using flow cytometric analysis of VASP-P were determined by receiver-operating characteristics (ROC) curve analysis. Results Excellent correlations were observed between LTA with ADP-induced PRmax and flow cytometric analysis of VASP-P according to the ROC curve analyses. The ROC curve analyses demonstrated that 5 μmol/l ADP-induced PRmax > 42.9% could distinguish between patients with and without VASP-P index > 54.9% (area under curve [AUC] 0.926, 95% confidence interval (CI) 0.903–0.949, sensitivity 82.8%, and specificity 88.5%, p < 0.001) and 5 μmol/l ADP-induced PRmax > 50% could distinguish between patients with and without VASP-P index > 57.4% (AUC 0.937, 95% CI 0.914–0.961, sensitivity 91.5%, and specificity 85.2%, p < 0.001). ROC curve analysis demonstrated 20 μmol/l ADP-induced PRmax > 62% could distinguish between patients with and without VASP-P index > 55.2% (AUC 0.948, 95% CI 0.927–0.969, sensitivity 95.7%, and specificity 87.3%, p < 0.001) and 20 μmol/l ADP-induced PRmax > 64.5% could distinguish between patients with and without VASP-P index > 55.9% (AUC 0.925, 95% CI 0.900–0.951, sensitivity 88.3%, and specificity 83.0%, p < 0.001), respectively. However, fair correlation was observed between AA-induced PRmax and VASP-P index and 1.6 nmol/l AA-induced PRmax > 20% could distinguish between patients with and without VASP-P index > 52.4% (AUC 0.761, 95% CI 0.719–0.802, sensitivity 68.5%, and specificity 72.7%, p < 0.001). We defined the ideal threshold of VASP-P index > 56%. The VASP-P index > 56% showed a substantial agreement with 5 μmol/l and 20 μmol/l ADP-induced PRmax (Table 1). However, VASP-P index > 56% showed a moderate agreement with 1.6 nmol/l AA)-induced PRmax > 20% (Table 1). Conclusion There are significant correlations between the suggested cut-offs of HPPR. Because VASP-P index > 56 is well matched with 5 μmol/l ADP-induced PRmax > 42.9%, 5 μmol/l ADP-induced PRmax > 50%, 20 μmol/l ADP-induced PRmax > 62%, and 20 μmol/l ADP-induced PRmax > 64.5%., it might suggest that VASP-P index > 56 has a practical implication for stratification of high-risk ischemic events. Disclosures: No relevant conflicts of interest to declare.

A Comprehensive Analysis on the Agreement and Correlation of Consensual Cut-Offs of High on-Treatment Platelet Reactivity with the Vasodilator-Stimulated Phosphorylation Assay, the VerifyNow P2Y12 Analyzer and Light Transmittance Aggregometry

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2315-2315
Author(s):  
In-Suk Kim ◽  
Young-Hoon Jeong ◽  
Eun Yup Lee ◽  
Gyeong-Won Lee
Keyword(s):  
Platelet Function ◽  
Roc Curve ◽  
Working Group ◽  
Platelet Reactivity ◽  
Comprehensive Analysis ◽  
Curve Analysis ◽  
Light Transmittance ◽  
Roc Curve Analysis ◽  
Light Transmittance Aggregometry ◽  
Consensual Definition

Abstract Abstract 2315 Background: Multiple lines of evidence have demonstrated a relationship between high on-treatment platelet reactivity (HPR) measured by multiple platelet assays and adverse clinical ischemic events. Although the Working Group on High On-Treatment Platelet Reactivity recently provided a consensus opinion on the definition of HPR, correlations between HPR cut-offs have not been validated yet. Therefore, we performed this study to provide a comprehensive analysis on the agreement and correlation of HPR cut-offs based on the consensual definition among the different platelet function measurements. Methods: We analyzed data from coronary intervention-treated patients on dual antiplatelet therapy (n = 962). Platelet measures were concurrently 5 and 20 μM ADP-stimulated light transmittance aggregometry (LTA), the VerifyNow P2Y12 analyzer, and flow cytometric analysis of vasodilator-stimulated phosphoprotein (VASP)-platelet reactivity index (PRI). As the Working Group noted, HPR cut-offs were defined as 5 and 20 μM ADP-induced maximal platelet aggregation (PRmax) > 46% and 59%, the VerifyNow P2Y12 assay > 240 P2Y12 reaction unit (PRU), and the VASP-PRI > 50%, respectively. Agreement between the consensual cut-off points of different tests was determined by kappa statistics, and 95% confidence intervals (CI) were also calculated. Receiver-operating characteristics (ROC) curve analysis was performed to identify the matched points for consensual definition-based cut-offs for HPR. Results: The consensual cut-off as 5μmol/l ADP-induced PRmax >46% showed a substantial agreement with 20 μmol/l ADP-induced PRmax, however, this cut-off showed a moderate agreement with the VerifyNow P2Y12 assay > 240 PRU and the VASP-PRI > 50%, respectively (Table 1). Fair correlations were observed between ADP-induced PRmax, the VerifyNow P2Y12 assay, and VASP-PRI according to the ROC curve analyses (Table 2). The cut-offs for 5μmol/l ADP-induced PRmax >46% based HPR matched well with the VerifyNow P2Y12 assay > 284 PRU (AUC 0.791, 95% CI 0.763–0.819, sensitivity 62.0%, and specificity 80.7%, p < 0.001), and the VASP-PRI > 60.3% (AUC 0.788, 95% CI 0.759–0.816, sensitivity 78.2%, and specificity 70.2%, p < 0.001) by the ROC curve analysis, respectively. The consensus-defined cut-offs of VerifyNow P2Y12 assay and VASP index overestimated HPR risk based on LTA cut-offs. Conclusion: Although the VerifyNow P2Y12 and VASP assay correlated significantly with LTA, there are moderate agreements and fair correlations among the consensual cut-offs of HPR. These data suggest the platelet function measurements need to be improved to become clinically used diagnostic tests and the need for a new cut-offs to balance safety and efficacy of P2Y12 receptor antagonists. Further, it still may be too early to define the gold standard method for assessing platelet reactivity and generally acceptable cut-off values. Disclosures: No relevant conflicts of interest to declare.

Impact of adjunctive cilostazol therapy on platelet function profiles in patients with and without diabetes mellitus on aspirin and clopidogrel therapy

2011 ◽  
Vol 106 (08) ◽  
pp. 253-262 ◽  
Author(s):  
Dominick J. Angiolillo ◽  
Piera Capranzano ◽  
Jose Luis Ferreiro ◽  
Masafumi Ueno ◽  
Davide Capodanno ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Platelet Function ◽  
Thrombin Generation ◽  
Platelet Reactivity ◽  
Flow Cytometric Analysis ◽  
Light Transmittance ◽  
Reactivity Index ◽  
Pharmacodynamic Effects ◽  
Increased Risk ◽  
Clopidogrel Therapy

SummaryCilostazol is a platelet inhibitor which when added to aspirin and clopidogrel has shown to reduce the risk of recurrent ischaemic events without an increase in bleeding. These clinical benefits have shown to be more pronounced in patients with diabetes mellitus (DM). However, it remains unknown whether cilostazol exerts different pharmacodynamic effects in patients with and without DM. This was a randomised, double-blind, placebo-controlled, cross-over pharmacodynamic study comparing platelet function in patients with and without DM on aspirin and clopidogrel therapy. Patients (n=111) were randomly assigned to either cilostazol 100 mg or placebo twice daily for 14 days and afterwards crossed-over treatment for another 14 days. Platelet function was performed at baseline, 14 days post-randomisation, and 14 days post-cross-over. Functional testing to assess P2Y12 signalling included flow cytometric analysis of phosphorylation status of vasodilatorstimulated phosphoprotein measured by P2Y12 reactivity index (PRI), light transmittance aggregometry and VerifyNow. Thrombin generation processes were also studied using thrombelastography. Significantly lower PRI values were observed following treatment with cilostazol compared with placebo both in DM and non-DM groups (p < 0.0001). The absolute between-treatment differences of PRI between groups was a 35.1% lower in patients with DM (p=0.039). Similar results were obtained using all other functional measures assessing P2Y12 signalling. Thrombin generation was not affected by cilostazol. Cilostazol reduces platelet reactivity both in patients with and without DM, although these pharmacodynamic effects are enhanced in patients with DM. Despite the marked platelet inhibition, cilostazol does not alter thrombin-mediated haemostatic processes, which may explain its ischaemic benefit without the increased risk of bleeding.

Acute heart failure: predicting early in-hospital outcomes

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Santos ◽  
S Paula ◽  
I Almeida ◽  
H Santos ◽  
H Miranda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Acute Heart Failure ◽  
Roc Curve ◽  
Real Life ◽  
Study Data ◽  
Curve Analysis ◽  
Older Age ◽  
Invasive Ventilation ◽  
Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p &lt; 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p &lt; 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p &lt; 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

scholarly journals Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuichiro Shimoyama ◽  
Osamu Umegaki ◽  
Noriko Kadono ◽  
Toshiaki Minami
Keyword(s):  
Multivariate Analysis ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Prognostic Nutritional Index ◽  
Early Mortality ◽  
Curve Analysis ◽  
Rank Test ◽  
Roc Curve Analysis ◽  
Log Rank Test ◽  
Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

scholarly journals Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiajia Liu ◽  
Xiaoyi Tian ◽  
Yan Wang ◽  
Xixiong Kang ◽  
Wenqi Song
Keyword(s):  
T Lymphocyte ◽  
Roc Curve ◽  
Cytotoxic T Lymphocyte ◽  
Tumor Grade ◽  
Curve Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Low Grade ◽  
High Grade ◽  
Healthy Individuals ◽  
Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

scholarly journals Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaohua Ban ◽  
Xinping Shen ◽  
Huijun Hu ◽  
Rong Zhang ◽  
Chuanmiao Xie ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Roc Curve ◽  
Multinomial Logistic Regression ◽  
Univariate Analysis ◽  
Ct Imaging ◽  
Squamous Cell Carcinomas ◽  
Curve Analysis ◽  
Imaging Features ◽  
Roc Curve Analysis ◽  
Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

scholarly journals Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

2019 ◽  
Vol 11 ◽  
pp. 1759720X1988555 ◽  
Author(s):  
Wanlong Wu ◽  
Jun Ma ◽  
Yuhong Zhou ◽  
Chao Tang ◽  
Feng Zhao ◽  
...  
Keyword(s):  
Emergency Department ◽  
Prediction Model ◽  
Risk Score ◽  
Roc Curve ◽  
Curve Analysis ◽  
Multivariable Logistic Regression Analysis ◽  
Invasive Infection ◽  
Roc Curve Analysis ◽  
All Cause Mortality ◽  
Qsofa Score

Background: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. Methods: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. Results: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections ( n = 108). Conclusions: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.

scholarly journals Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

2014 ◽  
Vol 5 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Balkishan Sharma ◽  
Ravikant Jain
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Traditional Method ◽  
Statistical Technique ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296      

Assessment of Biomarkers for Clinical Diagnosis of Papillary Thyroid Carcinoma with Distant Metastasis

2010 ◽  
Vol 25 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Huasheng Liang ◽  
Yuhua Zhong ◽  
Zuojie Luo ◽  
Yu Huang ◽  
Huade Lin ◽  
...  
Keyword(s):  
Growth Factor ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Clinical Diagnosis ◽  
Distant Metastasis ◽  
Roc Curve ◽  
Curve Analysis ◽  
Papillary Thyroid ◽  
Roc Curve Analysis ◽  
Thyroid Carcinomas

Early diagnosis and treatment of thyroid cancers are critical for better prognosis and better survival rates. The purpose of this study was to identify potential diagnostic markers for papillary thyroid carcinomas with distant metastasis. Fifty-eight papillary thyroid tumor specimens (27 papillary thyroid carcinomas with distant metastasis and 31 without metastasis) were examined, and protein expression of pituitary tumor-transforming gene (PTTG), E-cadherin, p27kip1, vascular endothelial growth factor (VEGF)-C, metalloproteinase (MMP) 2, MMP9, chemokine receptor CXCR4, and basic fibroblast growth factor (bFGF) in these tumors was assessed by immunohistochemistry. The clinicopathological variables with diagnostic significance were determined by multivariate analysis, and their diagnostic values were evaluated by ROC curve analysis. PTTG, VEGF-C, MMP2, MMP9, CXCR4, and bFGF were overexpressed in metastatic papillary thyroid carcinomas, whereas p27kip1 expression was elevated only in carcinomas lacking metastasis. Multiple-factor binary ordinal logistic regression analysis revealed that PTTG, VEGF-C, MMP2, and bFGF were independently related to biological metastatic behavior in thyroid tumors, suggesting their potential use as biomarkers. ROC curve analysis showed that among these four proteins, VEGF-C and bFGF were the best diagnostic biomarkers. A VEGF-C and bFGF cluster was the most useful factor for the differential diagnosis between metastatic and non-metastatic papillary thyroid cancers. Thus, the combined use of VEGF-C and bFGF as biomarkers may improve the diagnostic accuracy of papillary thyroid carcinoma and may be useful in multimodal screening programs for the clinical diagnosis of papillary thyroid carcinoma and early detection of papillary thyroid carcinoma with distant metastasis.

58 Relationship Between Early Laboratory Measures and Neurological Injury in Neonates Undergoing Therapeutic Hypothermia

2021 ◽  
Vol 26 (Supplement_1) ◽  
pp. e39-e41
Author(s):  
Lilian Kebaya ◽  
Mong Tieng Ee ◽  
Michael Miller ◽  
Soume Bhattacharya
Keyword(s):  
Therapeutic Hypothermia ◽  
Roc Curve ◽  
Base Excess ◽  
Curve Analysis ◽  
Neurological Injury ◽  
Acid Base ◽  
Roc Curve Analysis ◽  
Baseline Characteristics ◽  
Laboratory Measures

Abstract Primary Subject area Neonatal-Perinatal Medicine Background Hypoxic-ischemic encephalopathy (HIE) is a major contributor to morbidity and mortality. Therapeutic hypothermia (TH) is the standard of care for neonates with moderate to severe HIE. Brain magnetic resonance imaging (MRI) is the imaging modality of choice for confirmation of HIE, assessment of injury severity, and prognostication. Reliable, inexpensive and widely available laboratory measures for early identification of risk for neurological injury can play a critical role in the optimal management of neonatal HIE, especially in the resource-limited setting. Our study examined whether derangements in early routine laboratory measures (acid-base, haematological, metabolic) were worse in neonates with MRI findings of neurological injury. Objectives Primary objective: To evaluate the role of early laboratory measures in predicting neurological injury as detected by MRI at 72 hours. Secondary objective: To evaluate the role of early laboratory measures in predicting survival to NICU discharge in patients with HIE. Design/Methods This single-centre, retrospective cohort study included neonates ≥ 35 weeks gestation with moderate to severe HIE, who had undergone therapeutic hypothermia. Based on findings of brain MRI completed within 72 hours of life, our cohort was divided into 2 groups: neonates with, and without, evidence of neurological injury consistent with HIE. Baseline characteristics, as well as laboratory measures, were compared between groups, and a receiver operating characteristic (ROC) curve analysis was conducted to determine the cut-off for prediction of neurological injury based on the highest sensitivity and specificity values. Results 104 neonates were analyzed. Baseline characteristics (Table 1) were similar between both groups, except for cord venous pH and base excess (BE), which were significantly lower in the abnormal MRI group (p = 0.02). In bivariate analysis, pH (at 1 h of age, p = 0.027), BE (at 1 h, p = 0.001, and 6 h of age, p = 0.004), ionized calcium (at 6 h of age, p = 0.02), and platelets (at 1 h of age, p = 0.004) were significantly different in neonates with abnormal MRI. In ROC curve analysis, BE at 1 h of life was the best predictor of abnormal MRI (AUC = 0.71, p = 0.002), with a cut-off value of ≤ -14.95, sensitivity of 67% and specificity of 66% (Figure 1). Conclusion Among neonates with HIE undergoing TH, early laboratory measures such as acid-base status, ionized calcium, and platelet count were worse in neonates with abnormal MRI, in comparison to neonates with normal MRI. Base excess at 1 h of life is a good predictor of abnormal MRI. Future prospective studies to validate these findings are needed

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