scholarly journals B-Type Natriuretic Peptides Help in Cardioembolic Stroke Diagnosis

Stroke ◽  
2015 ◽  
Vol 46 (5) ◽  
pp. 1187-1195 ◽  
Author(s):  
Víctor Llombart ◽  
Albert Antolin-Fontes ◽  
Alejandro Bustamante ◽  
Dolors Giralt ◽  
Natalia S. Rost ◽  
...  
Keyword(s):  
Natriuretic Peptides ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Cardioembolic Stroke ◽  
Blood Levels ◽  
Clinical Value ◽  
Predictive Values ◽  
Pubmed Database ◽  
Integrated Discrimination Improvement ◽  
Improvement Index

Background and Purpose— Determining the underlying cause of stroke is important to optimize secondary prevention treatment. Increased blood levels of natriuretic peptides (B-type natriuretic peptide/N-terminal pro-BNP [BNP/NT-proBNP]) have been repeatedly associated with cardioembolic stroke. Here, we evaluate their clinical value as pathogenic biomarkers for stroke through a literature systematic review and individual participants’ data meta-analysis. Methods— We searched publications in PubMed database until November 2013 that compared BNP and NT-proBNP circulating levels among stroke causes. Standardized individual participants’ data were collected to estimate predictive values of BNP/NT-proBNP for cardioembolic stroke. Dichotomized BNP/NT-proBNP levels were included in logistic regression models together with clinical variables to assess the sensitivity and specificity to identify cardioembolic strokes and the additional value of biomarkers using area under the curve and integrated discrimination improvement index. Results— From 23 selected articles, we collected information of 2834 patients with a defined cause. BNP/NT-proBNP levels were significantly elevated in cardioembolic stroke until 72 hours from symptoms onset. Predictive models showed a sensitivity >90% and specificity >80% when BNP/NT-proBNP were added considering the lowest and the highest quartile, respectively. Both peptides also increased significantly the area under the curve and integrated discrimination improvement index compared with clinical models. Sensitivity, specificity, and precision of the models were validated in 197 patients with initially undetermined stroke with final pathogenic diagnosis after ancillary follow-up. Conclusions— Natriuretic peptides are strongly increased in cardioembolic strokes. Future multicentre prospective studies comparing BNP and NT-proBNP might aid in finding the optimal biomarker, the best time point, and the optimal cutoff points for cardioembolic stroke identification.

scholarly journals Diagnostic and prognostic value of miRNAs in hepatoblastoma: A systematic review with meta-analysis

2021 ◽  
Author(s):  
Bin Wu ◽  
◽  
Lixia Guo ◽  
Kaikai Zhen ◽  
Chao Sun
Keyword(s):  
Systematic Review ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Prognostic Indicator ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Likelihood Ratios ◽  
Clinical Value ◽  
Diagnostic And Prognostic Value

Review question / Objective: Background and aim: Increasing evidence has revealed the valuable diagnostic and prognostic applications of dysregulated microRNAs (miRNAs) in hepatoblastoma (HB), the most common hepatic malignancy during childhood. However, these results are inconsistent and remain to be elucidated. In the present study, we aimed to systematically compile up-to-date information regarding the clinical value of miRNAs in HB. Methods: Articles concerning the diagnostic and prognostic value of single miRNAs for HB were searched from databases. The sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and hazard ratios (HRs) were separately pooled to explore the diagnostic and prognostic performance of miRNA. Subgroup and meta-regression analyses were further carried out only in the event of heterogeneity. Results: In all, 20 studies, involving 264 HB patients and 206 healthy individuals, met the inclusion criteria in the six included literature articles. For the diagnostic analysis of miRNAs in HB, the pooled SEN and SPE were 0.76 (95% CI: 0.72–0.80) and 0.75 (95% CI: 0.70–0.80), respectively. Moreover, the pooled PLR was 2.79 (95% CI: 2.12–3.66), NLR was 0.34 (95% CI: 0.26–0.45), DOR was 10.24 (95% CI: 6.55–16.00), and AUC was 0.83, indicating that miRNAs had moderate diagnostic value in HB. For the prognostic analysis of miRNAs in HB, the abnormal expressions of miR-21, miR-34a, miR-34b, miR-34c, miR-492, miR-193, miR-222, and miR-224 in patients were confirmed to be associated with a worse prognosis. The pooled HR was 1.74 (95% CI: 1.20–2.29) for overall survival (OS) and 1.74 (95% CI: 1.31–2.18) for event-free survival (EFS), suggesting its potential as a prognostic indicator for HB. Conclusion: To the best of our knowledge, this is the first comprehensive systematic review and meta-analysis that examines the diagnostic and prognostic role of dysregulated miRNAs in HB patients. The combined meta-analysis results supported the previous individual finds that miRNAs might provide a new, noninvasive method for the diagnostic and prognostic analyses ofHB.

scholarly journals Associations and prognostic accuracy of electrolyte imbalances in predicting poor COVID-19 outcome: a systematic review and meta-analysis of 28 observational studies

2021 ◽  
Author(s):  
Harris Jun Jie Muhammad Danial Song ◽  
Alys Zhi Qin Chia ◽  
Benjamin Kye Jyn Tan ◽  
Chong Boon Teo ◽  
Horng Ruey Chua ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Observational Studies ◽  
Inflammatory Marker ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Cochrane Library ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Poor Outcome ◽  
Prognostic Accuracy

BACKGROUND: Serum electrolyte imbalances are highly prevalent in COVID-19 patients. However, their associations with COVID-19 outcomes are inconsistent, and of unknown prognostic value. OBJECTIVES: To systematically clarify the associations and prognostic accuracy of electrolyte imbalances (sodium, calcium, potassium, magnesium, chloride and phosphate) in predicting poor COVID-19 clinical outcome. METHODS: PubMed, Embase and Cochrane Library were searched. Odds of poor clinical outcome (a composite of mortality, intensive-care unit (ICU) admission, need for respiratory support and acute respiratory distress syndrome) were pooled using mixed-effects models. The associated prognostic sensitivity, positive and negative likelihood ratios (LR+, LR-) and predictive values (PPV, NPV; assuming 25% pre-test probability), and area under the curve (AUC) were computed. RESULTS: We included 28 observational studies from 953 records with low to moderate risk-of-bias. Hyponatremia (OR=2.08, 95%CI=1.48-2.94, I2=93%, N=8), hypernatremia (OR=4.32, 95%CI=3.17-5.88, I2=45%, N=7) and hypocalcemia (OR=3.31, 95%CI=2.24-4.88, I2=25%, N=6) were associated with poor COVID-19 outcome. These associations remained significant on adjustment for covariates such as demographics and comorbidities. Hypernatremia was 97% specific in predicting poor outcome (LR+ 4.0, PPV=55%, AUC=0.80) despite no differences in CRP and IL-6 levels between hypernatremic and normonatremic patients. Hypocalcemia was 76% sensitive in predicting poor outcome (LR- 0.44, NPV=87%, AUC=0.71). Overall quality of evidence ranged from very low to moderate. CONCLUSION: Hyponatremia, hypernatremia and hypocalcemia are associated with poor COVID-19 clinical outcome. Hypernatremia is 97% specific for a poor outcome and the association is independent of inflammatory marker levels. Further studies should evaluate if correcting these imbalances help improve clinical outcome.

scholarly journals Circulating long non-coding RNAs as potential biomarkers for stomach cancer: A systematic review and meta-analysis

2020 ◽  
Author(s):  
Fang Cao ◽  
Yongwei Hu ◽  
Zaichang Chen ◽  
Wei Han ◽  
Weijie Lu ◽  
...  
Keyword(s):  
Stomach Cancer ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Cochrane Library ◽  
Clinical Value ◽  
Summary Receiver Operating Characteristic ◽  
Non Coding Rna ◽  
Diagnostic Values ◽  
Meta Regression Analysis ◽  
Characteristic Area

Abstract Background: Recent researches have suggested that long non-coding RNA (lncRNA) is involved in the tumorigenesis and development of stomach cancer (SC). This meta-analysis aimed to identify the diagnostic performance of circulating lncRNAs in SC.Methods: All relevant studies were systematically searched through PubMed, Web of Science, Cochrane Library and EMBASE databases. The diagnostic values of lncRNAs were mainly assessed by pooled sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic area under the curve (SROC AUC). Meta-DiSc 1.4, Review Manager 5.3 and STATA 12.0 were used for statistical analysis. Results: A total of 42 eligible studies were included in this meta-analysis. The pooled SEN, SPE, and AUC were 0.78 (95%CI: 0.75-0.81), 0.75 (95%CI: 0.71-0.78), and 0.83 (95%CI: 0.80-0.86) respectively, suggesting that the lncRNAs test had a high accuracy for the diagnosis of SC. Obvious heterogeneity might come from the type of lncRNA through subgroup and meta-regression analysis. Fagan diagram showed the clinical value of lncRNAs test in SC. Conclusions: Abnormal expression of circulating lncRNAs exhibits a high efficacy for diagnosing SC, which is promising in clinical application.

Checkpoint inhibitor-associated immune-related adverse events as harbinger of favorable clinical outcome: Systematic review and meta-analysis.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15129-e15129
Author(s):  
Robin Park ◽  
Laércio Lopes da Silva ◽  
Anwaar Saeed
Keyword(s):  
Adverse Events ◽  
Clinical Outcomes ◽  
Checkpoint Inhibitors ◽  
Metastatic Cancer ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Final Analysis ◽  
Receiver Operating Curve ◽  
Predictive Values ◽  
Favorable Clinical Outcome

e15129 Background: Recent studies have observed an association between immune-related adverse events (irAE) and favorable clinical outcomes in the setting of cancer treatment with immune checkpoint inhibitors (ICI). However, results have been variable and inconclusive. Therefore, we have conducted a pan-cancer meta-analysis evaluating the relationship between irAEs and clinical outcomes. Methods: The search included PubMed, Embase, and Web of Science from conception to 12.28.2019 as well as abstracts published in the ASCO and ESMO meetings from 2015 to 2019. Studies were included if ICI was used in advanced or metastatic cancer settings and excluded if data contained only combination therapy regimens or contained anti-CTLA-4. Pooled sensitivity (SN), specificity (SP), positive (PPV) and negative predictive values (NPV), and odds ratios (ORs) were calculated using the 2 x 2 table and logit transformed proportions; and summary receiver operating curve (sROC) was generated using the bivariate approach for ORR. Pooled HRs were calculated using the means weighted by inverse of the variance for OS and PFS. Heterogeneity was assumed and random effects model was used throughout analyses. Results: Final analysis included 32 studies encompassing non-small cell lung cancer, melanoma, gastric cancer, renal cell carcinoma, urothelial carcinoma, and head and neck cancer. With respect to ORR, pooled SN, SP, PPV and NPV, and OR were 0.522 [0.423-0.619], 0.810 [0.771-0.844], 0.516 [0.413-0.618], 0.819 [0.764-0.864], and 4.59 [3.24-6.50] respectively. The area under the curve (AUC) derived from the sROC was 0.773. HR for OS and PFS were 0.47 [95% CI 0.37-0.60] and 0.46 [95% CI 0.37-0.56] respectively. Between-study publication bias was present for ORR, OS, and PFS but results remained significant after trim-fill analysis. Conclusions: irAEs predict OR, OS, and PFS across different types of cancer and may represent useful biomarkers in the clinical setting. [Table: see text]

scholarly journals MicroRNAs as potential biomarkers for the diagnosis of traumatic brain injury: a systematic review and meta-analysis

2019 ◽  
Author(s):  
Qian Zhou ◽  
Jian Yin ◽  
Yadong Wang ◽  
Xinsuo Zhuang ◽  
Zhiyang He ◽  
...  
Keyword(s):  
Systematic Review ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Diagnostic Accuracy ◽  
Brain Tissue ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Clinical Value ◽  
Mirnas Expression ◽  
Potential Biomarkers

Abstract Background: Traumatic brain injury (TBI) is a sudden trauma on the head, commonly associated with death and long-term disability. MicroRNAs (miRNAs) are potential biomarkers of diverse diseases, including TBI. However, few systematic reviews and meta-analyses have been conducted to determine the clinical value of miRNAs expression in TBI patients.Methods: We did a comprehensive literature search to identify articles that have reported on the diagnostic and prognostic value of miRNAs expression in TBI patients.Results: Six studies investating the diagnostic value of miRNA in TBI were analyzed in this study. The overall sensitivity, specificity and area under the curve (AUC) of miRNAs in diagnosis of TBI were 92% [95% confidence interval (CI): 0.87–0.95]; 92% (95% CI 0.78–0.97) and 96% (95% CI 0.94–0.97), respectively. We found that panels of multiple miRNAs could improve the diagnostic accuracy of TBI. Compared to saliva, detected samples like blood and brain tissue could significantly enhance diagnostic accuracy. Besides, the AUC of miRNAs in severe TBI was 0.97, with 92% sensitivity and 92% specificity.Conclusions: This systematic review and meta-analysis demonstrated that miRNAs could be potential diagnostic markers in TBI patients. MiRNAs detected in blood and brain tissue display high accuracy for TBI diagnosis.

Diagnostic accuracy of E-cadherin for malignanteffusions: a systematic review and meta-analysis

2019 ◽  
Vol 96 (1139) ◽  
pp. 530-536
Author(s):  
Fangying Chen ◽  
Luqi Dai ◽  
Jing An ◽  
Ni Zeng ◽  
Lei Chen ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Relevant Literature ◽  
Geographical Location ◽  
Area Under The Curve ◽  
Cochrane Library ◽  
Malignant Effusion ◽  
Clinical Value ◽  
Summary Receiver Operating Characteristic ◽  
E Cadherin

BackgroundThe differential diagnosis of malignant effusion remains a clinical challenge. We aim to summarise all relevant literature studies in order to determine the overall clinical value of E-cadherin in the diagnosis of malignant effusion by meta-analysis.MethodsPubMed, the Cochrane Library Database, Medline (Ovid), Web of Science, CNKI, WANFANG and WEIPU databases are thoroughly searched up to 15 March2018. The calculated pooled sensitivity, specificity, likelihood ratio (LR), diagnostic OR(DOR) and the summary receiver operating characteristic (SROC) curve were plotted.ResultsA total of 15 studies were included in the analysis. The sensitivity and specificity of E-cadherin in the diagnosis of malignant effusion were determined to be high, with a sensitivity of 0.83(95%CI0.79 to 0.87) and a specificity of 0.96(95%CI0.90 to 0.98). The positive LR was determined to be 21.10(95%CI 8.54 to 52.11), the negative LR was determined to be 0.17(95% CI 0.14 to 0.22) and the DOR was determined to be 121.34(95%CI 49.11 to 299.80). The SROC curve exhibited a high overall diagnostic, with the area under the curve measured to be 0.91(95% CI 0.89 to 0.93). Subgroup analysis showed the method (cell blocks or smears), sample size (≥100 or<100), geographical location (Asia, Europe or USA) and impact factor of each article (≥3 or<3) were not the sources of overall heterogeneity.ConclusionE-cadherin exhibits very good diagnostic accuracy for the diagnosis for malignant effusion; thus, it can be helpful in the process of clinical decisions.

Standalone performance of artificial intelligence for upper GI neoplasia: a meta-analysis

Gut ◽  
2020 ◽  
pp. gutjnl-2020-321922 ◽  
Author(s):  
Julia Arribas ◽  
Giulio Antonelli ◽  
Leonardo Frazzoni ◽  
Lorenzo Fuccio ◽  
Alanna Ebigbo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Likelihood Ratio ◽  
Precancerous Lesions ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Clinical Value ◽  
Predictive Values ◽  
Upper Gi ◽  
Neoplastic Lesion

ObjectiveArtificial intelligence (AI) may reduce underdiagnosed or overlooked upper GI (UGI) neoplastic and preneoplastic conditions, due to subtle appearance and low disease prevalence. Only disease-specific AI performances have been reported, generating uncertainty on its clinical value.DesignWe searched PubMed, Embase and Scopus until July 2020, for studies on the diagnostic performance of AI in detection and characterisation of UGI lesions. Primary outcomes were pooled diagnostic accuracy, sensitivity and specificity of AI. Secondary outcomes were pooled positive (PPV) and negative (NPV) predictive values. We calculated pooled proportion rates (%), designed summary receiving operating characteristic curves with respective area under the curves (AUCs) and performed metaregression and sensitivity analysis.ResultsOverall, 19 studies on detection of oesophageal squamous cell neoplasia (ESCN) or Barrett's esophagus-related neoplasia (BERN) or gastric adenocarcinoma (GCA) were included with 218, 445, 453 patients and 7976, 2340, 13 562 images, respectively. AI-sensitivity/specificity/PPV/NPV/positive likelihood ratio/negative likelihood ratio for UGI neoplasia detection were 90% (CI 85% to 94%)/89% (CI 85% to 92%)/87% (CI 83% to 91%)/91% (CI 87% to 94%)/8.2 (CI 5.7 to 11.7)/0.111 (CI 0.071 to 0.175), respectively, with an overall AUC of 0.95 (CI 0.93 to 0.97). No difference in AI performance across ESCN, BERN and GCA was found, AUC being 0.94 (CI 0.52 to 0.99), 0.96 (CI 0.95 to 0.98), 0.93 (CI 0.83 to 0.99), respectively. Overall, study quality was low, with high risk of selection bias. No significant publication bias was found.ConclusionWe found a high overall AI accuracy for the diagnosis of any neoplastic lesion of the UGI tract that was independent of the underlying condition. This may be expected to substantially reduce the miss rate of precancerous lesions and early cancer when implemented in clinical practice.

scholarly journals Circulating long noncoding RNAs as potential biomarkers for stomach cancer: a systematic review and meta-analysis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Fang Cao ◽  
Yongwei Hu ◽  
Zaichang Chen ◽  
Wei Han ◽  
Weijie Lu ◽  
...  
Keyword(s):  
Systematic Review ◽  
Stomach Cancer ◽  
Noncoding Rna ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Cochrane Library ◽  
Clinical Value ◽  
Summary Receiver Operating Characteristic ◽  
Link Type ◽  
Sensitivity Specificity

Abstract Background Recent researches have suggested that long noncoding RNA (lncRNA) is involved in the tumorigenesis and development of stomach cancer (SC). This meta-analysis aimed to identify the diagnostic performance of circulating lncRNAs in SC. Methods All relevant studies were systematically searched through PubMed, Web of Science, Cochrane Library, and EMBASE databases. The diagnostic values of lncRNAs were mainly assessed by pooled sensitivity, specificity, and summary receiver operating characteristic area under the curve (SROC AUC). Meta-DiSc 1.4, Review Manager 5.3, and STATA 12.0 were used for statistical analysis. The protocol for this systematic review was registered on INPLASY (INPLASY202120079) and is available in full on the inplasy.com (10.37766/inplasy2021.2.0079). Results A total of 42 eligible studies were included in this meta-analysis. The pooled sensitivity, specificity, and SROC AUC were 0.78 (95%CI 0.75–0.81), 0.75 (95%CI 0.71–0.78), and 0.83 (95%CI 0.80–0.86), respectively, suggesting that the lncRNAs test had a high accuracy for the diagnosis of SC. Obvious heterogeneity might come from the type of lncRNA through subgroup and meta-regression analysis. Fagan diagram shows the clinical value of lncRNAs test in SC. Conclusions Abnormal expression of circulating lncRNAs exhibits a high efficacy for diagnosing SC, which is promising in clinical application.

Discriminative value of glial fibrillar acidic protein (GFAP) as a diagnostic tool in acute stroke. Individual patient data meta-analysis

2020 ◽  
Vol 68 (8) ◽  
pp. 1379-1385
Author(s):  
Juan Antonio Cabezas ◽  
Alejandro Bustamante ◽  
Nicola Giannini ◽  
Emilio Pecharroman ◽  
Aristeidis H Katsanos ◽  
...  
Keyword(s):  
Diagnostic Tool ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Data ◽  
Acidic Protein ◽  
Medical Decision ◽  
Blood Levels ◽  
Stroke Severity ◽  
Pubmed Database ◽  
Glial Fibrillar Acidic Protein

Glial fibrillar acidic protein (GFAP) in serum has been evaluated as a promising biomarker to differentiate between intracerebral hemorrhage (ICH) and acute ischemic stroke (AIS). We assessed its value as diagnostic and prognostic tool for ICH through a literature systematic review and individual patient data (IPD) meta-analysis.We performed a systematic search in PubMed database until November 2018 for publications that evaluated GFAP to differentiate AIS and ICH within 4.5 hours after symptoms onset. Thereafter, we invited authors of selected studies to participate in this work by providing IPD from their cohorts. We used standardized individual subject’s data to evaluate the association of GFAP concentrations with stroke subtype, demographics, stroke characteristics and factors related with GFAP measurement.From 4 selected studies, we collected data of 340 patients (236 AIS and 104 ICH). Standardized GFAP blood levels were significantly elevated in ICH compared with those with AIS (median and IQR: 0.84 (0.781–1.24), 0.79 (0.74–0.81); p<0.0001). In both stroke types, GFAP concentrations correlated with baseline stroke severity (r=0.27, p<0.0001; r=0.36, p<0.001; for AIS and ICH, respectively) but no correlation was found regarding time to sampling. Limited data precluded the evaluation of GFAP levels and functional outcome.These findings demonstrate substantially different levels of GFAP in the blood of patients with ICH compared with patients with AIS soon after the event, while no association was found with outcome. In summary, GFAP could be a valuable diagnostic tool to assist in medical decision-making and to optimize management of stroke in the acute setting.

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