The role of serum periostin in the diagnosis of asthma: A meta-analysis

2020 ◽  
Vol 41 (4) ◽  
pp. 240-247
Author(s):  
Lei Yang ◽  
Qingtao Zhao ◽  
Shuyu Wang
Keyword(s):  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Summary Receiver Operating Characteristic ◽  
True Negative ◽  
Negative Results ◽  
Noninvasive Biomarker ◽  
Sensitivity Specificity ◽  
Serum Periostin

Background: Serum periostin has been proposed as a noninvasive biomarker for asthma diagnosis and management. However, its accuracy for the diagnosis of asthma in different populations is not completely clear. Methods: This meta-analysis aimed to evaluate the diagnostic accuracy of periostin level in the clinical determination of asthma. Several medical literature data bases were searched for relevant studies through December 1, 2019. The numbers of patients with true-positive, false-positive, false-negative, and true-negative results for the periostin level were extracted from each individual study. We assessed the risk of bias by using Quality Assessment of Diagnostic Accuracy Studies 2. We used the meta-analysis to produce summary estimates of accuracy. Results: In total, nine studies with 1757 subjects met the inclusion criteria. The pooled estimates of sensitivity, specificity, and diagnostic odds ratios for the detection of asthma were 0.58 (95% confidence interval [CI], 0.38‐0.76), 0.86 (95% CI, 0.74‐0.93), and 8.28 (95% CI, 3.67‐18.68), respectively. The area under the summary receiver operating characteristic curve was 0.82 (95% CI, 0.79‐0.85). And significant publication bias was found in this meta‐analysis (p = 0.39). Conclusion: Serum periostin may be used for the diagnosis of asthma, with moderate diagnostic accuracy.

Usefulness of Nasal Endoscopy for Diagnosing Patients With Chronic Rhinosinusitis: A Meta-Analysis

2019 ◽  
Vol 34 (2) ◽  
pp. 306-314
Author(s):  
Do Hyun Kim ◽  
Youngjun Seo ◽  
Kyung Min Kim ◽  
Seoungmin Lee ◽  
Se Hwan Hwang
Keyword(s):  
Diagnostic Accuracy ◽  
Chronic Rhinosinusitis ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Nasal Endoscopy ◽  
Summary Receiver Operating Characteristic ◽  
True Negative ◽  
Endoscopic Score

Background We evaluated the accuracy of nasal endoscopy in diagnosing chronic rhinosinusitis (CRS) compared with paranasal sinus computed tomography (CT). Methods Two authors independently searched the 5 databases (PubMed, SCOPUS, Embase, the Web of Science, and the Cochrane database) up to March 2019. For all included studies, we calculated correlation coefficients between the endoscopic and CT scores. We extracted data on true-positive and false-positive and true-negative and false-negative results. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool (version 2). Results We included 16 observational or retrospective studies. A high correlation ( r = .8543; 95% confidence interval [CI] [0.7685–0.9401], P < .0001, I2 = 76.58%) between endoscopy and CT in terms of the diagnostic accuracy for CRS was apparent. The odds ratio (Lund–Kennedy endoscopic score ≥1) was 7.915 (95% CI [4.435–14.124]; I2 = 28.361%). The area under the summary receiver operating characteristic curve was 0.765. The sensitivity and specificity were 0.726 (95% CI [0.584–0.834]) and 0.767 (95% CI [0.685–0.849]), respectively. However, high interstudy heterogeneity was evident given the different endoscopic score thresholds used (Lund–Kennedy endoscopic score ≥1 vs 2). In a subgroup analysis of studies using a Lund–Kennedy endoscopic score threshold ≥2, the area under the summary curve was 0.881, and the sensitivity and specificity were 0.874 (95% CI [0.783–0.930]) and 0.793 (95% CI [0.366–0.962]), respectively. Conclusion Nasal endoscopy is a useful diagnostic tool; the Lund–Kennedy score was comparable with that of CT.

scholarly journals Diagnostic accuracy of Mycobacterium tuberculosis cell-free DNA for tuberculosis: A systematic review and meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253658
Author(s):  
Guocan Yu ◽  
Yanqin Shen ◽  
Bo Ye ◽  
Yan Shi
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Meta Analysis ◽  
False Negative ◽  
Summary Receiver Operating Characteristic ◽  
True Negative ◽  
Cell Free Dna ◽  
Free Dna ◽  
Sensitivity Specificity

Background Diagnosis of tuberculosis (TB) is still difficult. The purpose of our study was to evaluate the diagnostic accuracy of Mycobacterium tuberculosis cell-free DNA (cfDNA) for diagnosing of TB. Methods We searched relevant databases for studies that used cfDNA to diagnose TB. We evaluated the accuracy of cfDNA compared with the composite reference standard (CRS) and culture. True positive, false positive, false negative, and true negative values for cfDNA were obtained first, then the estimated pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve (AUC) of cfDNA for diagnosing TB were calculated with 95% confidence intervals (CIs). Heterogeneity was determined using the I2 statistic. When the heterogeneity was obvious, the source of heterogeneity was further discussed. Results We included 14 independent studies comparing cfDNA with the CRS, and 4 studies compared with culture. The pooled sensitivity, specificity, PPV, NPV, DOR, and AUC of the SROC were 68%, 98%,99%, 62%, 83, and 0.97 as compared with the CRS, respectively. The pooled sensitivity, specificity, PPV, NPV, DOR, and AUC of the SROC were 48%, 91%, 92%, 60%, 5, and 0.88 as compared with culture, respectively. The heterogeneity between studies was significant. Conclusions The accuracy of cfDNA testing for TB diagnosis was good compared with CRS and culture. cfDNA can be used for rapid early diagnosis of TB.

Methylene Blue as a Diagnosis and Screening Tool for Oral Cancer and Precancer

2020 ◽  
pp. 019459982094768
Author(s):  
Se Hwan Hwang ◽  
Sung Won Kim ◽  
Eun A. Song ◽  
Junuk Lee ◽  
Do Hyun Kim
Keyword(s):  
Methylene Blue ◽  
Oral Cancer ◽  
Diagnostic Accuracy ◽  
False Positive ◽  
Characteristic Curve ◽  
False Positive Rate ◽  
False Negative ◽  
High Sensitivity ◽  
Summary Receiver Operating Characteristic ◽  
True Negative

Objectives To evaluate the accuracy of methylene blue (MB) for diagnosing oral cancer and precancer. Data Sources PubMed, Cochrane Database, Embase, Web of Science, SCOPUS, and Google Scholar. Review Methods Two authors working independently reviewed 6 databases from their dates of inception until April 2020. Studies exploring oral mucosal disorders as detected by MB were assessed. True-positive, true-negative, false-positive, and false-negative data were extracted for each study. Methodological quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies tool (v 2). Results Seven prospective and retrospective studies (N = 493) were included. The diagnostic odds ratio of MB was 20.017 (95% CI, 10.65-37.63, I2 = 23%). The area under the summary receiver operating characteristic curve was 0.699. Sensitivity was 0.903 (95% CI, 0.84-0.94, I2 = 54%), and specificity was 0.68 (95% CI, 0.60-0.75, I2 = 0%). The correlation between the sensitivity and the false-positive rate was –0.17, indicating an absence of heterogeneity. Conclusions Regarding diagnostic accuracy, MB had high sensitivity but low specificity, suggesting that it cannot be recommended as a replacement for the currently used standard of a scalpel biopsy with histologic assessment. Instead, it should be used as an adjunct to conventional assessment because of its low toxicity and price.

scholarly journals Accuracy of Enzyme-Linked Immunosorbent Assays (ELISAs) in Detecting Antibodies againstMycobacterium lepraein Leprosy Patients: A Systematic Review and Meta-Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Omar Ariel Espinosa ◽  
Silvana Margarida Benevides Ferreira ◽  
Fabiana Gulin Longhi Palacio ◽  
Denise da Costa Boamorte Cortela ◽  
Eliane Ignotti
Keyword(s):  
Diagnostic Accuracy ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Diagnostic Odds Ratio ◽  
Cochrane Library ◽  
Likelihood Ratios ◽  
Summary Receiver Operating Characteristic ◽  
Immunosorbent Assays ◽  
Sensitivity Specificity

IgM againstMycobacterium lepraemay be detected by enzyme-linked immunosorbent assays (ELISAs) based on phenolic glycolipid I (PGL-I) or natural disaccharide octyl bovine serum albumin (ND-O-BSA) as antigens, and the IgG response can be detected by an ELISA based on lipid droplet protein 1 (LID-1). The titers of antibodies against these antigens vary with operational classification. The aim of this study was to compare the accuracy of ELISAs involving PGL-I and ND-O-BSA with that involving LID-1. We included studies that analyze multibacillary and paucibacillary leprosy cases and evaluate the diagnostic accuracy of ELISAs based on LID-1 and/or PGL-I or ND-O-BSA as antigens to measure antibody titers againstM. leprae. Studies were found via PubMed, the Virtual Health Library Regional Portal, Literatura Latino-Americana e do Caribe em Ciências da Saúde, Índice Bibliográfico Espanhol de Ciências de Saúde, the Brazilian Society of Dermatology, National Institute for Health and Clinical Excellence, Cochrane Library, Embase (the Elsevier database), and Cumulative Index to Nursing and Allied Health Literature. The Quality Assessment of Diagnostic Accuracy Studies served as a methodological validity tool. Quantitative data were extracted using the Standards for Reporting of Diagnostic Accuracy. Sensitivity, specificity, and a diagnostic odds ratio were calculated, and a hierarchical summary receiver-operating characteristic curve and forest plots were constructed. The protocol register code for this meta-analysis is PROSPERO 2017: CRD42017055983. Nineteen studies were included. ND-O-BSA showed better overall performance in terms of sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio when compared with PGL-I and LID-1. The multibacillary group showed better performance on these parameters (than the paucibacillary group did), at 94%, 99%, 129, 0.05, and 2293, respectively. LID-1 did not provide any advantage regarding the overall estimate of sensitivity in comparison with PGL-I or ND-O-BSA.

scholarly journals Diagnostic Accuracy of the Quidel Sofia Rapid Influenza Fluorescent Immunoassay in Patients with Influenza-like illness: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Jonghoo Lee ◽  
Jae-Uk Song
Keyword(s):  
Diagnostic Accuracy ◽  
Odds Ratio ◽  
Influenza A ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Diagnostic Odds Ratio ◽  
Influenza B ◽  
Cochrane Central Register ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Abstract Background: Although the Quidel Sofia rapid influenza fluorescent immunoassay (FIA) is widely used to identify influenza A and B, the diagnostic accuracy of this test remains unclear. We compared the diagnostic performances of this test with reverse transcriptase-polymerase chain reaction.Methods: A systematic literature search was performed using MEDLINE, EMBASE, and the Cochrane Central Register. The sensitivity, specificity, diagnostic odds ratio (DOR), and a hierarchical summary receiver-operating characteristic curve (HSROC) of this test for identifying influenza A and B were pooled using meta-analysis. A sensitivity and subgroup analysis was used to identify potential sources of heterogeneity within the selected studies.Results: We identified seventeen studies comprising 8,334 patients. The pooled sensitivity, specificity, and DOR of the Quidel Sofia rapid influenza FIA to identify influenza A were 0.78 (95% CI, 0.71–0.83), 0.99 (95% CI, 0.98–0.99), and 251.26 (95% CI, 139.39–452.89), respectively. The pooled sensitivity, specificity, and diagnostic odds ratio of this test to identify influenza B were 0.72 (95% CI, 0.60–0.82), 0.98 (95% CI, 0.96-0.99), and 140.20 (95% CI, 55.92-351.54), respectively. The area under the HSROC for this test was similar for identification of influenza A and influenza B. Age was considered a probable source of heterogeneity.Conclusions: The pooled sensitivities of the Quidel Sofia rapid influenza FIA did not quite meet the target level (≥80%) for both influenza A and B. The interpretation of data should be carefully considered due to substantial between-study heterogeneity.

scholarly journals Serum CA72-4 as a biomarker in the diagnosis of colorectal cancer: A meta-analysis

Open Medicine ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 164-171 ◽  
Author(s):  
Han Yanqing ◽  
Dong Cheng ◽  
Xu Ling
Keyword(s):  
Colorectal Cancer ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Negative Likelihood Ratio ◽  
Diagnostic Sensitivity ◽  
Published Data ◽  
Summary Receiver Operating Characteristic ◽  
True Negative

AbstractThe purpose of this meta-analysis was to investigate the serum CA72-4 as a biomarker in the diagnosis of colorectal cancer by pooling the open published data. Methods. An electronic search of databases Pubmed, Medline, Web of Science, Cochrane Embase CBM, and CNKI were performed by two reviewers (Han Yanqing, Dong Cheng) independently to identify the studies relevant to serum CA72-4 as a biomarker in the diagnosis of colorectal cancer. The patient number of true positive(tp), false positive(fp), false negative(fn) and true negative(tn) were extracted from each included study. The diagnostic performance of serum CA72-4 as a biomarker in the diagnosis of colorectal cancer was assessed by pooled sensitivity, specificity and hierarchical summary receiver operating characteristic curve (HSROC). All the data was pooled by MetaDiSc 1.4 and Stata/SE 11.0 statistical software. Results A total of 22 studies with 2474 colorectal patients and 1576 controls were included in the present study and meta-analysis. The combined diagnostic sensitivity and specificity were 0.50 (95%CI:0.48-0.52) and 0.86 (95%CI:0.84-0.88) for serum CA72-4 as a biomarker in the diagnosis of colorectal cancer. The pooled positive and negative likelihood ratio were 3.41(95%CI:2.57-4.53) and 0.62(0.55-0.71). The pooled area under the ROC curve (AUC) was 0.73. Deeks’funnel plot and Egger’s line regression test (p=0.49) showed no significant publication bias in the present meta-analysis. Conclusion Due toits low diagnostic sensitivity, the diagnostic performance of serum CA72-4 as a biomarker for colorectal cancer screening is limited.

scholarly journals Blood Procalcitonin Level as A Diagnostic Marker of Pediatric Bacterial Meningitis: A Systematic Review and Meta-Analysis

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 846
Author(s):  
Heeyeon Kim ◽  
Yun-Ho Roh ◽  
Seo-Hee Yoon
Keyword(s):  
Bacterial Meningitis ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Mortality And Morbidity ◽  
Meningitis In Children ◽  
Sensitivity Specificity

Early diagnosis and treatment of bacterial meningitis in children are essential, due to the high mortality and morbidity rates. However, lumbar puncture is often difficult, and cerebrospinal fluid (CSF) culture takes time. This meta-analysis aims to determine the diagnostic accuracy of blood procalcitonin for detecting bacterial meningitis in children. We conducted a systematic search on electronic databases to identify relevant studies. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated, and a hierarchical summary receiver operating characteristic curve and area under the curve (AUC) were determined. Eighteen studies with 1462 children were included in the analysis. The pooled sensitivity, specificity, and the DOR of blood procalcitonin for detecting bacterial meningitis were 0.87 (95% confidence interval (CI): 0.78–0.93); 0.85 (95% CI: 0.75–0.91), and 35.85 (95% CI: 10.68–120.28), respectively. The AUC for blood procalcitonin was 0.921. Blood procalcitonin also showed higher diagnostic accuracy for detecting bacterial meningitis than other conventional biomarkers, including serum C-reactive protein and leukocyte count, CSF leukocyte and neutrophil count, and CSF protein and glucose levels. Blood procalcitonin can be a good supplemental biomarker with high diagnostic accuracy in detecting bacterial meningitis in children.

scholarly journals Predictive value of olfactory and taste symptoms in the diagnosis of COVID-19: A systematic review and meta-analysis

2021 ◽  
Author(s):  
Minbum Kim ◽  
Do Hyun Kim ◽  
So Yeon Yoon ◽  
Sung Won Kim ◽  
Hansol Hong ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Diagnostic Value ◽  
The Other ◽  
Summary Receiver Operating Characteristic ◽  
True Negative ◽  
Predictive Values ◽  
Taste Changes ◽  
Patient Reported

Objectives: This study evaluated the diagnostic value of the various symptoms of COVID-19 in the screening of this disease.Methods: Two authors (working independently) comprehensively reviewed six databases (PubMed, Cochrane database, Embase, Web of Science, SCOPUS, and Google Scholar) from their dates of inception until November 2020. Patient-reported symptoms, including otolaryngologic and general symptoms, were evaluated for their predictive values in adults who underwent testing for COVID-19. True-positive, true-negative, false-positive, and false-negative data were extracted from each study. The methodological quality of included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies tool (ver. 2). Results: Twenty-eight prospective and retrospective studies were included in the meta-analysis. The diagnostic odds ratio (DOR) of a change in olfaction and/or taste was 10.20 (95% confidence interval [CI], 8.43; 12.34). The area under the summary receiver operating characteristic curve was 0.8. Olfactory and/or taste changes had a low sensitivity (0.57, 95%CI: 0.47; 0.66) but moderate negative (0.78, 95%CI: 0.69; 0.85] and positive (0.78, 95%CI: 0.66; 0.87) predictive values and a high specificity (0.91, (95%CI: 0.83; 0.96). Olfactory and/or taste changes had a higher diagnostic value than the other otolaryngologic symptoms, a higher DOR and specificity, and a similar or higher diagnostic value than the other general symptoms. Conclusions: Among otolaryngologic symptoms, olfactory and/or taste dysfunction was the most highly associated with COVID-19 and its general symptoms and should be considered when screening for the disease.

scholarly journals Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Curtis K. Sohn ◽  
Sotirios Bisdas
Keyword(s):  
Machine Learning ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Total Sample ◽  
Low Grade ◽  
Sample Sizes ◽  
Summary Receiver Operating Characteristic ◽  
Pubmed Database ◽  
Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

DIAGNOSTIC VALUE OF ANTI-MÜLLERIAN HORMONE AS A BIOMARKER FOR POLYCYSTIC OVARY SYNDROME: A META-ANALYSIS UPDATE

2019 ◽  
Vol 25 (10) ◽  
pp. 1056-1066 ◽  
Author(s):  
Yang Zhao ◽  
Yinlong Zhao ◽  
Chunpeng Wang ◽  
Zhenzhen Liang ◽  
Xin Liu
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Ovary Syndrome ◽  
Diagnostic Efficacy ◽  
Sensitivity Specificity ◽  
Rotterdam Criteria

Objective: A previous meta-analysis carried out on the predictive ability of anti-Müllerian hormone (AMH) for polycystic ovary syndrome (PCOS) showed that independent AMH may be a useful initial diagnostic test for PCOS. The aims of this study were to update the meta-analysis and to evaluate the diagnostic efficacy of AMH when it replaces polycystic ovary morphology (PCOM) in the Rotterdam criteria. Methods: Two independent reviewers searched PubMed, Cochrane Library, and the Web of Science databases systematically to identify relevant articles by using the key words “anti-Müllerian hormone” and “polycystic ovary syndrome.” The deadline for manuscript inclusion was July 31, 2018. A random effects model was used and subgroup analysis and meta regression were performed to identify possible sources of heterogeneity. The methodologic quality of each study was assessed by QUADAS-2 and funnel plot asymmetry test. Results: According to the inclusion criteria, 29 studies were included in this meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) for AMH alone detecting PCOS were 0.76 (95% confidence interval [CI] 0.71 to 0.81), 0.86 (95% CI 0.82 to 0.90) and 20 (95% CI 12 to 33), respectively. When AMH replaces polycystic ovary morphology (PCOM) for the diagnosis of PCOS, the pooled sensitivity, specificity, and DOR rose to 0.93 (95% CI 0.89 to 0.96), 0.99 (95% CI 0.95 to 1.00), and 1,634 (95% CI 217 to 12,324), respectively. The area under the summary receiver-operating characteristic curve for AMH alone and for AMH replacing PCOM detecting PCOS were 0.88 (95% CI 0.85 to 0.91) and 0.97 (95% CI 0.95 to 0.98), respectively, which was found to be significantly different ( Z = 4.89, P<.01). Conclusion: When AMH replaces PCOM in the Rotterdam criteria, the diagnostic efficacy for polycystic ovary syndrome is better. Abbreviations: AMH = anti-Müllerian hormone; AUC = area under the summary receiver operating characteristic curve; BMI = body mass index; CI = confidence interval; DOR = diagnostic odds ratio; HA = hyperandrogenism; IBC = Immunotech-Beckman Coulter; NLR = negative likelihood ratio; OA = oligo-anovulation; PCOM = polycystic ovary morphology; PCOS = polycystic ovary syndrome; PLR = positive likelihood ratio; QUADAS = the Quality Assessment of Diagnostic Accuracy Studies; SENS = sensitivity; SPEC = specificity

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