scholarly journals Predictive Power of Extubation Failure Diagnosed by Cough Strength: A Systematic Review and Meta-Analysis

2021 ◽  
Author(s):  
Jun Duan ◽  
Xiaofang Zhang ◽  
Jianping Song
Keyword(s):  
Predictive Power ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Extubation Failure ◽  
Diagnostic Odds Ratio ◽  
Receiver Operating Characteristic Curves ◽  
On Line ◽  
Cough Strength ◽  
Sensitivity Specificity

Abstract Background: The predictive power of extubation failure diagnosed by cough strength is various in different studies. We aimed to summarize the diagnostic power of extubation failure tested by cough strength. Methods: A comprehensive on-line search was performed to select any potentially eligible studies that evaluated the predictive power of extubation failure tested by cough strength. A manual research was also performed to identify additional studies. Data were extracted to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and area under the receiver operating characteristic curves (AUC) to evaluate predictive power of extubation failure. I2 was used to test the heterogeneity and deek’s funnel plot was used to detect the publication bias.Results: A total of 35 studies involving 7515 patients were included. Of them, 1113 patients (14.8%) experienced extubation failure. Twenty studies involving 2787 patients assessed cough strength by measure of cough peak flow (CPF) to predict extubation failure. The pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 0.77 (95%CI: 0.72-0.80), 0.75 (0.69-0.80), 2.84 (2.36-3.42), 0.34 (0.29-0.39), 9.16 (6.14-13.67), and 0.81 (0.77-0.84), respectively. Twenty studies involving 5508 patients assessed cough strength by measurement of a semiquantitative cough strength scale (SCSS) to predict extubation failure. The pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 0.54 (95%CI: 0.43-0.65), 0.82 (0.73-0.88), 2.48 (1.92-3.21), 0.63 (0.54-0.74), 4.61 (3.03-7.01), and 0.74 (0.70-0.78), respectively. Conclusions: Cough strength can be measured by CPF and SCSS. The CPF has good predictive power to diagnose extubation failure and SCSS has moderate predictive power.

scholarly journals Predictive power of extubation failure diagnosed by cough strength: a systematic review and meta-analysis

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Jun Duan ◽  
Xiaofang Zhang ◽  
Jianping Song
Keyword(s):  
Predictive Power ◽  
Peak Flow ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Extubation Failure ◽  
Diagnostic Odds Ratio ◽  
Manual Search ◽  
Cough Strength ◽  
Sensitivity Specificity

Abstract Background The predictive power of extubation failure diagnosed by cough strength varies by study. Here we summarise the diagnostic power of extubation failure tested by cough strength. Methods A comprehensive online search was performed to select potentially eligible studies that evaluated the predictive power of extubation failure tested by cough strength. A manual search was also performed to identify additional studies. Data were extracted to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) to evaluate the predictive power of extubation failure. Results A total of 34 studies involving 45 study arms were enrolled, and 7329 patients involving 8684 tests were analysed. In all, 23 study arms involving 3018 tests measured cough peak flow before extubation. The pooled extubation failure was 36.2% and 6.3% in patients with weak and strong cough assessed by cough peak flow, respectively. The pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 0.76 (95% confidence interval [CI]: 0.72–0.80), 0.75 (0.69–0.81), 2.89 (2.36–3.54), 0.37 (0.30–0.45), 8.91 (5.96–13.32), and 0.79 (0.75–0.82), respectively. Moreover, 22 study arms involving 5666 tests measured the semiquantitative cough strength score (SCSS) before extubation. The pooled extubation failure was 37.1% and 11.3%, respectively, in patients with weak and strong cough assessed by the SCSS. The pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 0.53 (95% CI: 0.41–0.64), 0.83 (0.74–0.89), 2.50 (1.93–3.25), 0.65 (0.56–0.76), 4.61 (3.03–7.01), and 0.74 (0.70–0.78), respectively. Conclusions Weak cough is associated with increased extubation failure. Cough peak flow is superior to the SCSS for predicting extubation failure. However, both show moderate power for predicting extubation failure.

scholarly journals Evaluation of alpha-l-fucosidase for the diagnosis of hepatocellular carcinoma based on meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Xi ◽  
Chunqing Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Receiver Operating Characteristic Curves ◽  
Sensitivity Specificity ◽  
Review Manager

AbstractObjectivesThe main aim of the present study was to assess the diagnostic value of alpha-l-fucosidase (AFU) for hepatocellular carcinoma (HCC).MethodsStudies that explored the diagnostic value of AFU in HCC were searched in EMBASE, SCI, and PUBMED. The sensitivity, specificity, and DOR about the accuracy of serum AFU in the diagnosis of HCC were pooled. The methodological quality of each article was evaluated with QUADAS-2 (quality assessment for studies of diagnostic accuracy 2). Receiver operating characteristic curves (ROC) analysis was performed. Statistical analysis was conducted by using Review Manager 5 and Open Meta-analyst.ResultsEighteen studies were selected in this study. The pooled estimates for AFU vs. α-fetoprotein (AFP) in the diagnosis of HCC in 18 studies were as follows: sensitivity of 0.7352 (0.6827, 0.7818) vs. 0.7501 (0.6725, 0.8144), and specificity of 0.7681 (0.6946, 0.8283) vs. 0.8208 (0.7586, 0.8697), diagnostic odds ratio (DOR) of 7.974(5.302, 11.993) vs. 13.401 (8.359, 21.483), area under the curve (AUC) of 0.7968 vs. 0.8451, respectively.ConclusionsAFU is comparable to AFP for the diagnosis of HCC.

Diagnostic value of HOX transcript antisense RNA for cancer detection: a meta-analysis

2020 ◽  
Vol 14 (5) ◽  
pp. 401-411
Author(s):  
Weihao Kong ◽  
Mingwei Yang ◽  
Yunfeng Zhu ◽  
Xiaomin Zuo ◽  
Hengyi Wang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Antisense Rna ◽  
Noncoding Rna ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Sensitivity Specificity

Aim: Numerous studies have investigated the diagnostic role of long noncoding RNA HOX transcript antisense RNA in cancers, but its diagnostic efficacy is inconsistent. Methods: The PubMed, Embase, Web of Science and Cochrane Library databases are used to retrieve relevant studies. The bivariate effect model was used to compute the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve. Results: A total of 13 studies were included in this meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve were: 0.77, 0.83, 4.7, 0.28, 17 and 0.87, respectively. Deeks’ funnel plot test (p = 0.103) indicated no publication bias. Conclusion: Long noncoding RNA HOX transcript antisense RNA may be a useful biomarker for cancer detection.

scholarly journals The Potential Diagnostic Accuracy of Circulating MicroRNAs for Leukemia: A Meta-Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Wen-Ting Zhang ◽  
Guo-Xun Zhang ◽  
Shuai-Shuai Gao
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Circulating Micrornas ◽  
Sensitivity Specificity

Background: Leukemia is a common malignant disease in the human blood system. Many researchers have proposed circulating microRNAs as biomarkers for the diagnosis of leukemia. We conducted a meta-analysis to evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of leukemia. Methods: A comprehensive literature search (updated to October 13, 2020) in PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for diagnosing leukemia were pooled for both overall and subgroup analysis. The meta-regression and subgroup analysis were performed to explore heterogeneity and Deeks’ funnel plot was used to assess publication bias. Results: 49 studies from 22 publications with a total of 3,489 leukemia patients and 2,756 healthy controls were included in this meta-analysis. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve were 0.83, 0.92, 10.8, 0.18, 59 and 0.94, respectively. Subgroup analysis shows that the microRNA clusters of plasma type could carry out a better diagnostic accuracy of leukemia patients. In addition, publication bias was not found. Conclusions: Circulating microRNAs can be used as a promising noninvasive biomarker in the early diagnosis of leukemia.

scholarly journals Systematic Review and Meta-Analysis of the Utility of Circular RNAs as Biomarkers of Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Qingqin Hao ◽  
Yadi Han ◽  
Wei Xia ◽  
Qinghui Wang ◽  
Huizhong Qian
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Clinicopathological Characteristics ◽  
Cochrane Library ◽  
Circular Rnas ◽  
Clinical Value ◽  
Sensitivity Specificity

Emerging studies have reported circRNAs were dysregulated in HCC. However, the clinical value of these circRNAs remains to be clarified. Herein, we aimed to comprehensively explore their association with the diagnosis, prognosis, and clinicopathological characteristics of HCC. PubMed, EMBASE, Web of Science, and Cochrane Library databases were comprehensively searched for eligible studies up to October 30, 2018. The diagnostic effect was evaluated by the pooled sensitivity, specificity, and other indexes. The pooled hazard ratio (HR) for overall survival (OS) and recurrence free survival (RFS) was calculated to assess the prognostic value. Ten studies on diagnosis, 12 on prognosis, and 23 on clinicopathology were identified from the databases. A total of 11 upregulated and 11 downregulated circRNAs showed an association with clinicopathological features of HCC. For the diagnosis analyses, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) of circRNAs for HCC were 0.74 (95%CI: 0.65-0.82) and 0.76 (95%CI: 0.70-0.81), 3.1 (95%CI: 2.5-3.8), 0.34 (95%CI: 0.25-0.47), and 9 (95%CI: 6-14), respectively. The area under SROC curve (AUC) was 0.81 (95% CI: 0.78–0.84), indicating moderate diagnostic accuracy. In stratified analyses, the diagnostic performance of circRNAs varied based on the source of control and specimen type. For the prognosis analyses, increased expression of upregulated circRNAs was associated with worse OS (HR: 3.67, 95%: 2.07-6.48), while high expression of downregulated circRNAs was associated with better OS (HR: 0.38, 95%: 0.30-0.48). In conclusion, this study reveals that circRNAs may serve as promising diagnostic and prognostic biomarkers for HCC. However, further investigations are still required to explore the clinical value of circRNAs.

scholarly journals Prognostic Value of N-terminal Probrain Natriuretic Peptide for Patients with Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Qi Ni ◽  
Chaoqian Li ◽  
Hua Lin
Keyword(s):  
Systematic Review ◽  
Acute Respiratory Distress Syndrome ◽  
Likelihood Ratio ◽  
Odds Ratio ◽  
Distress Syndrome ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Sensitivity Specificity

Objectives. The mortality rate of patients with acute respiratory distress syndrome (ARDS) is high. Hence, it is crucial to identify a reliable biomarker with wide clinical applications for predicting the prognosis of patients with ARDS. This systematic review and meta-analysis was conducted to investigate the value of plasma N-terminal probrain natriuretic peptide (NT-proBNP) for predicting mortality in patients with ARDS. Methods. An electronic search of databases including PubMed, Web of Science, Cochrane Library, and Chinese National Knowledge Infrastructure was conducted up to May 31, 2019, without language restrictions. The quality of the included studies was evaluated using QUADAS-2. Data were extracted and analyzed to obtain pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio. A forest graph was used to evaluate heterogeneity. Potential causes of heterogeneity were further explored by subgroup analysis based on the testing day, testing method, observation endpoint, or cut-off points. A summary receiver operating characteristic curve was drawn to obtain the pooled area under the curve. Results. A total of 7 studies involving 581 patients with ARDS were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were as follows: 0.79 (95% CI: 0.72–0.84), 0.79 (95% CI: 0.66–0.88), 3.68 (95% CI: 2.16–6.28), 0.27 (95% CI: 0.20–0.38), and 13.58 (95% CI: 6.17–29.90), respectively. The results of subgroup analysis showed that the testing day influenced the summary sensitivity and that the cut-off points influenced the summary sensitivity and specificity. Conclusion. Our results indicate that elevated plasma NT-proBNP levels have a moderate value for predicting the mortality of patients with ARDS.

scholarly journals Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5253
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Bruno Andreas Walther ◽  
Ming-Chin Lin ◽  
Yu-Chuan (Jack) Li
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Work Load ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC. We conducted a systematic search in the online databases (e.g., PubMed, Embase, and Web of Science) for all relevant original studies on the subject of CNN in EGC published between January 1, 2010, and March 26, 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Moreover, a summary receiver operating characteristic curve (SROC) was plotted. Of the 171 studies retrieved, 15 studies met inclusion criteria. The application of the CNN model in the diagnosis of EGC achieved a SROC of 0.95, with corresponding sensitivity of 0.89 (0.88–0.89), and specificity of 0.89 (0.89–0.90). Pooled sensitivity and specificity for experts endoscopists were 0.77 (0.76–0.78), and 0.92 (0.91–0.93), respectively. However, the overall SROC for the CNN model and expert endoscopists was 0.95 and 0.90. The findings of this comprehensive study show that CNN model exhibited comparable performance to endoscopists in the diagnosis of EGC using digital endoscopy images. Given its scalability, the CNN model could enhance the performance of endoscopists to correctly stratify EGC patients and reduce work load.

scholarly journals Reliability of circulating fibrinogen in the diagnosis of prosthesis-related infections: a systematic review and meta-analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Xingyang Zhu ◽  
Haitao Zhang ◽  
Xiaobo Sun ◽  
Yijin Li ◽  
Jiahao Li ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Joint Infection ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Small Sample ◽  
Cochrane Library ◽  
Sensitivity Specificity

Abstract Background Fibrinogen (FIB) has recently been used as a biomarker to diagnose periprosthetic joint infection (PJI), but its reliability is still questionable. The aim of this study was to investigate the accuracy of FIB in the diagnosis of PJI after joint replacement. Methods We searched for literatures published in PubMed, EMBASE, and the Cochrane Library from the time of database inception to September 2020 and screened the studies according to the inclusion criteria. Then, we calculated the diagnostic parameters of FIB, including the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), area under the curve (AUC), and diagnostic odds ratio (DOR). In addition, we implemented subgroup analyses to identify the sources of heterogeneity. Results Seven studies including 1341 patients were selected in our meta-analysis. The pooled sensitivity, specificity, PLR, NLR, and DOR of FIB for PJI diagnosis were 0.78 (95% confidence interval [CI], 0.73–0.82), 0.83 (95% CI, 0.81–0.86), 4.60 (95% CI, 3.30–6.42), 0.24 (95% CI, 0.18–0.34), and 20.13 (95% CI, 14.80–27.36), respectively, while the AUC was 0.896. Conclusion The present study indicated that FIB was a reliable detection method and might be introduced into the diagnostic criteria for PJI. However, more robust studies are still needed to confirm the current findings, because most of the included studies were retrospective and had small sample sizes.

scholarly journals MicroRNAs as Biomarkers for the Diagnosis of Ankylosing Spondylitis: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Jiangbi Li ◽  
Xiaoping Xie ◽  
Weibing Liu ◽  
Feng Gu ◽  
Ke Zhang ◽  
...  
Keyword(s):  
Ankylosing Spondylitis ◽  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Good Diagnostic Accuracy ◽  
Sensitivity Specificity

Background: Abnormal expression levels of microRNAs (miRNAs) were observed in ankylosing spondylitis (AS) in recent articles, suggesting that miRNAs may be used as biomarkers for AS diagnoses. In this paper, we conducted a meta-analysis to identify the overall diagnostic accuracy of miRNA biomarkers in AS patients.Methods: An extensive search was undertaken in PubMed, Embase, Cochrane databases, and Wan Fang database up to 30 December 2020 using the following key words: (“microRNAs” or “microRNA” or “miRNA” or “miR” or “RNA, Micro” or “Primary MicroRNA”) and (“Spondylitis Ankylosing” or “Spondyloarthritis Ankylopoietica” or “Ankylosing Spondylarthritis” or “Ankylosing Spondylarthritides” or “Spondylarthritides Ankylosing” or “Ankylosing Spondylitis”) and (“blood” or “serum” or “plasma”). Statistical evaluation of dysregulated miRNAs using the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC).Results: Twenty-nine articles reporting on the miRNAs of AS were included. A total of 42 miRNAs were observed to be up-regulated and 45 miRNAs were down-regulated in the AS cases compared with the controls. Besides, 29 studies from nine articles were included in our meta-analysis. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0. 76 (95% CI, 0.70–0.81), 0.80 (95% CI, 0.74–0.85), 3.75 (95% CI, 2.82–5.01), 0.30 (95% CI, 0.24–0.39), 12.32 (95% CI, 7.65–19.83), 0.85 (95% CI, 0.81–0.88), respectively, suggesting a good diagnostic accuracy of miRNAs for AS.Conclusions: Circulating miRNAs are deregulated in AS patients. miRNAs may be used as a relatively non-invasive biomarkers for the detection of AS.

scholarly journals Hepatic Subcapsular Flow as a Significant Diagnostic Marker for Biliary Atresia: A Meta-Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Chao Sun ◽  
Bin Wu ◽  
Jiang Pan ◽  
Lulu Chen ◽  
Wenxian Zhi ◽  
...  
Keyword(s):  
Biliary Atresia ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Sensitivity Specificity ◽  
Larger Sample

Aim. Increasing evidence indicates that hepatic subcapsular flow (HSF) can serve as a noninvasive ultrasonographic marker for the early diagnosis of biliary atresia (BA). However, results regarding its diagnostic accuracy are inconsistent and inconclusive. We conducted this meta-analysis with an aim to systematically evaluate the diagnostic value of HSF in predicting BA. Methods. A comprehensive literature search of four databases was conducted to identify the eligible studies. All analyses were performed using STATA 12.0. Results. Nine studies from eight articles containing 368 patients and 469 controls were included in our meta-analysis. Briefly, the values for pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were 0.95 (95% CI 0.88-0.98), 0.92 (95% CI 0.85-0.96), 11.6 (95% CI 6.3-21.5), 0.06 (95% CI 0.02-0.14), 201 (95% CI 59-689), and 0.98 (95% CI 0.96-0.99), respectively. Additionally, metaregression along with subgroup analysis based on various covariates revealed the potential sources of heterogeneity and the detailed diagnostic value in each subgroup. Conclusion. Our meta-analysis showed that HSF assay could provide high accuracy in predicting BA patients and non-BA individuals. However, further studies with better design and larger sample size are required to support the results of the present study.

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