Combined Likelihood Ratio Research Articles

Systematic review and meta-analysis of the diagnostic value of computed tomography angiography for severe internal carotid artery stenosis

BackgroundDue to the increasing incidence of ischaemic cerebrovascular diseases, the accurate assessment of internal carotid artery (ICA) stenosis is crucial for the development of treatment plans. This systematic review and meta-analysis aimed to evaluate the diagnostic value of computed tomography angiography (CTA) for severe ICAstenosis, thereby providing support for clinical decision-making and promoting diagnostic updates.MethodsThe PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database for Chinese Technical Periodicals (VIP), and Chinese Biomedical Literature (CBM) electronic databases were searched from inception to March 21, 2024, to identify publicly available research literature on the use of CTA to diagnose severe ICA stenosis. Literature screening, data extraction, and quality assessment were conducted based on the inclusion and exclusion criteria as well as the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) standards. Data analysis was performed using Stata 17.0 and Meta-Disc 1.4 software. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of the included studies were calculated using Stata 17.0 software, and forest plots and summary receiver operating characteristic (SROC) curves were generated. The area under the curve (AUC) was calculated, and funnel plots were constructed to assess publication bias.ResultsA total of 16 studies with 2368 vascular segments were included. The meta-analysis revealed that the combined sensitivity and specificity of CTA for severe ICA stenosis were 0.93 (95% CI: 0.88 ~ 0.96) and 0.99 (95% CI: 0.96 ~ 1.00), respectively. The combined positive likelihood ratio and negative likelihood ratio were 92.0 (95% CI: 24.2 ~ 349.6) and 0.07 (95% CI: 0.04 ~ 0.13), respectively. The diagnostic odds ratio was 1302 (95% CI: 257 ~ 6606), and the AUC of the SROC curve was 0.98. The Deeks funnel plot suggested no publication bias among the included studies.ConclusionCTA demonstrated high sensitivity and specificity for diagnosing severe ICA stenosis. Therefore, this study provided important evidence for the accurate diagnosis and treatment of severe ICA stenosis. However, there was considerable heterogeneity among the included studies, thus indicating the need for additional high-quality prospective studies to confirm the clinical applicability of CTA.

Fusing linguistic and acoustic information for automated forensic speaker comparison

Verifying the speaker of a speech fragment can be crucial in attributing a crime to a suspect. The question can be addressed given disputed and reference speech material, adopting the recommended and scientifically accepted likelihood ratio framework for reporting evidential strength in court. In forensic practice, usually, auditory and acoustic analyses are performed to carry out such a verification task considering a diversity of features, such as language competence, pronunciation, or other linguistic features. Automated speaker comparison systems can also be used alongside those manual analyses. State-of-the-art automatic speaker comparison systems are based on deep neural networks that take acoustic features as input. Additional information, though, may be obtained from linguistic analysis. In this paper, we aim to answer if, when and how modern acoustic-based systems can be complemented by an authorship technique based on frequent words, within the likelihood ratio framework. We consider three different approaches to derive a combined likelihood ratio: using a support vector machine algorithm, fitting bivariate normal distributions, and passing the score of the acoustic system as additional input to the frequent-word analysis. We apply our method to the forensically relevant dataset FRIDA and the FISHER corpus, and we explore under which conditions fusion is valuable. We evaluate our results in terms of log likelihood ratio cost (Cllr) and equal error rate (EER). We show that fusion can be beneficial, especially in the case of intercepted phone calls with noise in the background.

Accuracy of prostigmin tests in the diagnosis of myasthenia gravis: a meta-analysis.

Myasthenia gravis (MG) is an acquired autoimmune disease diagnosed based on clinical manifestations, muscle fatigue tests, prostigmin tests, serum antibody tests, and neuroelectrophysiological examination. This study conducted a comprehensive search of PubMed, Web of Science, Scopus, Ovid, Embase, Cochrane Library, China National Knowledge Infrastructure, WanFang, Chinese Periodical Database, Chinese Bio-Medicine Database, VIP, and DuXiu Database to identify relevant studies on the accuracy of prostigmin tests for diagnosing MG, covering publications from 1941 to 2021. Ten studies met the inclusion criteria and were included in the meta-analysis. The analysis found no heterogeneity caused by threshold effects but identified heterogeneity due to non-threshold effects. The combined sensitivity was 0.861 (95% CI: 0.831-0.888), and the combined specificity was 0.844 (95% CI: 0.816-0.870). The combined positive likelihood ratio was 5.496 (95% CI: 1.454-20.77), and the combined negative likelihood ratio was 0.237 (95% CI: 0.123-0.455). The area under the curve for diagnostic accuracy was 0.88 (95% CI: 0.84-0.90), with Q* = 0.8520. The combined diagnostic odds ratio was 19.344 (95% CI: 4.327-86.488). In conclusion, the prostigmin test demonstrated good diagnostic value for MG.

Calculation of the Weight of Evidence for Combined Single-Cell and Extracellular Forensic DNA.

The weight of DNA evidence for forensic applications is typically assessed through the calculation of the likelihood ratio (LR). In the standard workflow, DNA is extracted from a collection of cells where the cells of an unknown number of donors are mixed. The DNA is then genotyped, and the LR is calculated through well-established methods. Recently, a method for calculating the LR from single-cell data has been presented. Rather than extracting the DNA while the cells are still mixed, single-cell data is procured by first isolating each cell. Extraction and fragment analysis of relevant forensic loci follows such that individual cells are genotyped. This workflow leads to significantly stronger weights of evidence, but it does not account for extracellular DNA that could also be present in the sample. In this paper, we present a method for calculation of an LR that combines single-cell and extracellular data. We demonstrate the calculation on example data and show that the combined LR can lead to stronger conclusions than would be obtained from calculating LRs on the single-cell and extracellular DNA separately.

Evaluation of the diagnostic effectiveness of next generation sequencing in sepsis etiology: a systematic review and meta-analysis.

Systematic evaluation of the diagnostic value of next generation sequencing (NGS) in sepsis etiology. We conducted a systematic search on four databases (Web of Science, Cochrane, PubMed, and Embase) and compiled diagnostic experiments using NGS to evaluate sepsis etiology. Two researchers conducted research and obtained data independently. Nine documents were included comprising 747 patients, 988 blood samples, 175 bronchoalveolar lavage fluid (BALF) samples, 16 cerebrospinal fluid samples, and one urine sample. The combined sensitivity of each study was 0.89 (95% CI: 0.82-0.95). The combined specificity was 0.40 (95% CI: 0.25-0.55). The combined positive likelihood ratio was 1.51 (95% CI: 1.18-1.98). The combined negative likelihood ratio was 0.28 (95% CI: 0.11-0.48). The diagnostic odds ratio (DOR) was 6.38 (95% CI: 2.53-15.32) and the area under the curve (AUC) was 0.84, (95% CI: 0.62-0.94). Based on the data we collected, we found that compared with the blood culture technology, NGS has the advantages of high sensitivity and wide detection range, but its specificity was low. Further study is needed to confirm the value of NGS in the etiological diagnosis of patients with sepsis.

A systematic review and meta-analysis of magnetic resonance and computed tomography enterography in the diagnosis of small intestinal tumors.

To explore the potential value of magnetic resonance (MR) and computed tomography (CT) enterography in the diagnosis of small intestinal tumor (SIT). Articles reporting on the diagnosis of SIT by MR and CT enterography deposited in Chinese and foreign literature databases were identified and evaluated using the quality assessment of diagnostic accuracy studies (QUADAS). The diagnostic data extracted from the articles were adopted for meta-analysis using Meta-disc 1.40 software. Analysis was undertaken to compare the sensitivity, specificity, positive and negative likelihood ratios, and the diagnostic odds ratio (DOR) of MR and CT enterography in the diagnosis of SIT. The diagnostic values of the two imaging methods were analyzed by summary receiver operating characteristic (SROC) curves. The meta-analysis was registered at INPLASY (202380053). A total of eight articles, including 551 cases of SIT were included in this analysis. The pooled sensitivity and specificity of MR enterography were 0.92 (95% CI [0.89-0.95]) and 0.81 (95% CI [0.74-0.86]), respectively, whilst CT enterography had a sensitivity of 0.93 (95% CI [0.90-0.95]) and a specificity of 0.83 (95% CI [0.76-0.88]). For MR enterography, the combined positive likelihood ratio was 4.90 (95% CI [3.50-6.70]), the combined negative likelihood ratio was 0.10 (95% CI [0.07-0.14]), and the area under the receiver operating characteristic curve (AUROC) was 0.940. For CT enterography, the corresponding values were 5.40 (95% CI [3.90-7.40]), 0.08 (95% CI [0.06-0.12]), and 0.950, respectively. When the pretest probability for MR was assumed to be 50%, the posterior probabilities for positive and negative results were calculated as 83% and 9%, respectively. For CT enterography with a pretest probability of 50%, the posterior probabilities of positive and negative results were 84% and 8%, respectively. MR and CT enterography have high accuracy in the diagnosis of SIT and have a valuable role in the diagnosis and management of these tumors.

Proenkephalin as a biomarker correlates with acute kidney injury: a systematic review with meta-analysis and trial sequential analysis

BackgroundProenkephalin A 119-159 (PENK) is freely filtered in the glomerulus with plasma levels correlating with glomerular filtration rate. Therefore, PENK has been proposed as an early indicator of acute kidney injury (AKI) although its performance is dependent on the clinical setting. This meta-analysis aimed to investigate the correlation between PENK levels and the development of AKI.MethodsWe conducted a comprehensive search on the PubMed, Embase, Cochrane databases, the website ClinicalTrials.gov and Cnki.net until June 26, 2023. Summary receiver operating characteristic (SROC) curves were used to amalgamate the overall test performance. Diagnostic odds ratio (DOR) was employed to compare the diagnostic accuracy of PENK with other biomarkers. Quality of the evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria.ResultsWe incorporated 11 observational studies with 3969 patients with an incidence of AKI of 23.4% (929 out of 3969 patients) with the best optimal cutoff value of PENK for early detection of AKI being 57.3 pmol/L. The overall sensitivity and specificity of PENK in identifying AKI were 0.69 (95% CI 0.62–0.75) and 0.76 (95% CI 0.68–0.82), respectively. The combined positive likelihood ratio (LR) stood at 2.83 (95% CI 2.06–3.88), and the negative LR was 0.41 (95% CI 0.33–0.52). The SROC curve showcased pooled diagnostic accuracy of 0.77 (95% CI 0.73–0.81). Interestingly, patients with a history of hypertension or heart failure demonstrated a lower specificity of PENK in correlating the development of AKI.ConclusionOur results indicate that PENK possesses significant potential as a biomarker for the early detection of the development of AKI, using a cutoff point of 57.3 pmol/L for PENK.

Utilization of Radiomics Features Extracted From Preoperative Medical Images to Detect Metastatic Lymph Nodes in Cholangiocarcinoma and Gallbladder Cancer Patients: A Systemic Review and Meta-analysis.

This study aimed to determine the methodological quality and evaluate the diagnostic performance of radiomics features in detecting lymph node metastasis on preoperative images in patients with cholangiocarcinoma and gallbladder cancer. Publications between January 2005 and October 2022 were considered for inclusion. Databases such as Pubmed/Medline, Scopus, Embase, and Google Scholar were searched for relevant studies. The quality of the methodology of the manuscripts was determined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2. Pooled results with corresponding 95% confidence intervals (CIs) were calculated using the DerSimonian-Liard method (random-effect model). Forest plots were used to visually represent the diagnostic profile of radiomics signature in each of the data sets pertaining to each study. Fagan plot was used to determine clinical applicability. Overall sensitivity was 0.748 (95% CI, 0.703-0.789). Overall specificity was 0.795 (95% CI, 0.742-0.839). The combined negative likelihood ratio was 0.299 (95% CI, 0.266-0.350), and the positive likelihood ratio was 3.545 (95% CI, 2.850-4.409). The combined odds ratio of the studies was 12.184 (95% CI, 8.477-17.514). The overall summary receiver operating characteristics area under the curve was 0.83 (95% CI, 0.80-0.86). Three studies applied nomograms to 8 data sets and achieved a higher pooled sensitivity and specificity (0.85 [0.80-0.89] and 0.85 [0.71-0.93], respectively). The pooled analysis showed that predictive models fed with radiomics features achieve good sensitivity and specificity in detecting lymph node metastasis in computed tomography and magnetic resonance imaging images. Supplementation of the models with biological correlates increased sensitivity and specificity in all data sets.

Meta-analysis of the diagnostic value of serum procalcitonin for burn sepsis in adults.

Serum procalcitonin (PCT) reflects the infection status of the organism and the severity of the infection. The purpose of this study was to systematically evaluate the diagnostic value of serum PCT for burn sepsis in adults and to provide a factual basis for future clinical diagnosis and decision-making. On August 16, 2022, six databases were searched in this study and a total of 856 studies were found. The retrieved literature was comprehensively evaluated according to the inclusion and exclusion criteria, and the valid data were extracted and included for analysis. The number of true positives, false positives, true negatives and false negatives were used as indicators to evaluate the diagnostic value of serum PCT for burn sepsis in adults. In total, 15 studies met the inclusion criteria. Meta-analysis showed a combined sensitivity of 0.78 (95% CI: 0.69-0.84), a combined specificity of 0.85 (95% CI: 0.77-0.91), a combined positive likelihood ratio of 5.17 (95% CI: 3.25-8.25), a combined negative likelihood ratio of 0.26 (95% CI: 0.19-0.37), and a combined diagnostic ratio of 19.63 (95% CI: 10.17-37.90). The AUC was 0.88 (95% CI: 0.85-0.90). Serum PCT provides good early diagnostic benefits for burn sepsis in adults. More high-quality studies are required to clarify its specific early diagnostic value.

Improving kinship probability in analysis of ancient skeletons using identity SNPs and MPS technology.

In forensic kinship analysis and human identification cases, analysis of STRs is the gold standard. When badly preserved ancient DNA is used for kinship analysis, short identity SNPs are more promising for successful amplification. In this work, kinship analysis was performed on two skeletons from the Early Middle Ages. The surface contaminants of petrous bones were removed by chemical cleaning and UV irradiation; DNA was isolated through full demineralization and purified in an EZ1 Advanced XL machine. The PowerQuant kit was used to analyze DNA yield and degradation, and on average, 17 ng DNA/g of petrous bone was obtained. Both skeletons were typed in duplicate for STR markers using the Investigator EssplexPlus SE QS kit, and comparison of partial consensus genotypes showed shared allelic variants at most loci amplified, indicating close kinship. After statistical calculation, the full-sibling kinship probability was too low for kinship confirmation, and additional analyses were performed with PCR-MPS using the Precision ID Identity Panel. The HID Ion Chef Instrument was used to prepare the libraries and for templating and the Ion GeneStudio S5 System for sequencing. Analysis of identity SNPs produced full genetic profiles from both skeletons. For combined likelihood ratio (LR) calculation, the product rule was used, combining LR for STRs and LR for SNPs, and a combined LR of 3.3 × 107 (corresponding to a full-sibling probability of 99.999997%) was calculated. Through the SNP PCR-MPS that followed the STR analysis, full-sibling kinship between the ancient skeletons excavated from an early medieval grave was confirmed.

Endometrial Cytology in Diagnosis of Endometrial Cancer: A Systematic Review and Meta-Analysis of Diagnostic Accuracy.

Because the incidence of endometrial cancer has been increasing every year, it is important to identify an effective screening method for it. The endometrial cytology test (ECT) is considered to be the more acceptable technique compared to invasive endometrial sampling. The study followed the Priority Reporting Project for Systematic Evaluation and Meta-Analysis (PRISMA-DTA) protocol. This systematic rating searched EMBASE and Web of Science databases for studies on ECT for endometrial cancer from the databases' dates of inception to 30 September 2022. All literature screening and data extraction were performed by two researchers, while the methodological quality of the included studies was assessed against defined inclusion criteria. And a third researcher resolves the disagreements. Twenty-six studies were eventually included in this final analysis. Meta-analysis results showed that the diagnostic accuracy characteristics of ECT for endometrial cancer were as follows: combined sensitivity = 0.84 [95% confidence interval (CI) (0.83-0.86)], combined specificity = 0.98 [95% CI (0.98-0.98)], combined positive likelihood ratio = 34.65 [95% CI (20.90-57.45)], combined negative likelihood ratio = 0.21 [95% CI (0.15-0.30)], and area under the summary receiver operating characteristic curve = 0.9673. ECT had the ability to detect endometrial cancer with strong specificity, although some studies have demonstrated significant differences in sensitivity.

Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect.

Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error. Approaches to overcome this problem were published recently, such as model-averaging across drug models (MAD), individual model-averaging (IMA), and combined Likelihood Ratio Test (cLRT). This work aimed to assess seven NLMEM approaches in the same framework: treatment effect assessment in balanced two-armed designs using real natural history data with or without the addition of simulated treatment effect. The approaches are MAD, IMA, cLRT, standard model selection (STDs), structural similarity selection (SSs), randomized cLRT (rcLRT), and model-averaging across placebo and drug models (MAPD). The assessment included type I error, using Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores from 817 untreated patients and power and accuracy in the treatment effect estimates after the addition of simulated treatment effects. The model selection and averaging among a set of pre-selected candidate models were driven by the Akaike information criteria (AIC). The type I error rate was controlled only for IMA and rcLRT; the inflation observed otherwise was explained by the placebo model misspecification and selection bias. Both IMA and rcLRT had reasonable power and accuracy except under a low typical treatment effect.

EFMrep: An extension of EuroForMix for improved combination of STR DNA mixture profiles

The EuroForMix model has been extended to create a new open-source software called EFMrep which enables the combination of STR DNA mixture samples from different multiplexes. In addition to calculating combined likelihood ratios and carrying out deconvolution, the software also includes the capability to specify related unknown individuals. A graphical user interface has been implemented to ease the analysis for practitioners in real case work. The effect of combining multiple samples based on the PROVEDIt dataset was investigated, either from the same or different multiplexes. The information gain increases when more samples are combined. A head-to-head comparison against EuroForMix shows the benefit of a more general model. Guidelines are provided. A real case example was used to demonstrate how EFMrep could be used to combine multiple samples when a proposition includes kinship.

Accuracy of Magnetic Resonance Imaging in Diagnosing Placenta Accreta: A Systematic Review and Meta-Analysis

Background The disease burden and incidence of placenta accreta are increasing worldwide. The morbidity and mortality associated with undiagnosed placenta accreta are both high, highlighting the important of early diagnosis and intervention. In recent years, increasing studies are exploring the diagnostic value of magnetic resonance imaging (MRI) for placenta accreta. Compared with traditional ultrasound, MRI has the advantages of high-resolution, multiangle imaging, and less influence by amniotic fluid and intestinal gas. However, the reported diagnostic accuracy among studies was inconsistent. Therefore, this study is aimed at exploring the diagnostic value of MRI for placenta accreta by systematic review and meta-analysis. Methods Relevant literature were systematically searched in PubMed, Ovid, Embase, ScienceDirect database, CNKI, and Wanfang database by using medical subject headings and relevant diagnostic terminologies such as sensitivity, specificity, likelihood ratio, receiver-operating characteristic curve, and area under the curve. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and area under the curve of the included literature were analyzed using stata 17.0 software. Publication bias of the included studies was assessed by Deek's funnel plot. Cochrane Q statistics and I2 statistics were used to test the heterogeneity. Results A total of 10 primary publications, comprising 4 retrospective studies and 6 prospective studies, were included in this meta-analysis. The gestational weeks of pregnant women ranged from 32 to 35 weeks, and the sample size ranged from 37 cases to 575 cases. Only 4 studies used the blind method in the process of clinical diagnosis by MRI. The combined sensitivity, specificity, and area of curve under summary receiver-operating characteristic for the diagnosis of placenta accreta by MRI were 0.88 (95% CI, 0.79-0.93), 0.79 (95% CI, 0.68-0.87), and 0.91 (95% CI, 0.88.-0.93), respectively. The combined positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and diagnostic score were 4.17 (95% CI, 2.62-6.66), 0.16 (95% CI, 0.09-0.29), 26.61 (95% CI, 10.22-69.28), and 3.28 (95% CI, 2.32-4.24), respectively. No publication bias was noted. Conclusion Diagnosis of placenta accreta by MRI has good accuracy and predictive value that warrants clinical promotion.

Test of a Homeopathic Algorithm for COVID-19: the Importance of a Broad Perspective.

Most of the symptoms of coronavirus disease 2019 (COVID-19) are covered by large repertory rubrics and hence many remedies have been proposed as "genus epidemicus". The aim of this study was to combine the information from various data collections to prepare a COVID-19 Bayesian mini-repertory/an algorithm-based application (app) and test it. In July 2021, 1,161 COVID-19 cases from 100 practitioners globally were combined. These data were used to calculate "condition-confined" likelihood ratios (LRs) for 59 symptoms of COVID-19. Out of these, 35 symptoms of the 11 medicines that had at least 20 cases each were considered. The information was entered in a spreadsheet (algorithm) to calculate combined LRs of specific combinations of symptoms. The algorithm contained the medicines Arsenicum album, Belladonna, Bryonia alba, Camphora, Gelsemium sempervirens, Hepar sulphuris, Mercurius solubilis, Nux vomica, Phosphorus, Pulsatilla and Rhus toxicodendron. To test concordance, the doctors were then invited to re-enter the symptoms of their cases into this algorithm. The algorithm was re-tested on 358 cases, and concordance was seen in 288 cases. On analysis of the data, bias was noticed in the Merc group, which was therefore excluded from the algorithm. The remaining 10 medicines, representing 81.8% of all cases, were included in the preparation of the next version of the homeopathic mini-repertory and app. The Bayesian mini-repertory and app is based on qualitative clinical experiences of various doctors in COVID-19 and gives indications for specific medicines for common COVID-19 symptoms. It is freely available [English: https://hpra.co.uk/; Spanish: https://hpra.co.uk/es ] for further testing and utilization by the profession.

Transcranial Sonography as a Diagnostic Tool for Depressive Disorders.

Transcranial sonography (TCS) is an available and noninvasive neuroimaging method that has been found to reduce the echogenicity of the brainstem raphe (BR) in patients with depression. Applying the criteria of the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV), we performed a meta-analysis of the diagnostic accuracy of TCS. A systematic search was conducted in PubMed, EMBASE, The Cochrane Library, and Web of Science. The databases were searched from inception to December 2021. The quality of the included literature was assessed using the QUADAS-2. Heterogeneity analysis was performed. A summary receiver operating characteristic (SROC) curve was generated to evaluate the diagnostic accuracy of TCS. We included 12 studies with 809 patients. The pooled sensitivity was 0.66 (95% confidence interval [CI]: 0.61-0.71), and the specificity was 0.84 (95% CI: 0.80-0.87). The combined positive likelihood ratio (LR) was 3.84 (95% CI: 2.68-5.51), the negative LR was 0.41 (95% CI: 0.29-0.57), and the diagnostic odds ratio (DOR) was 11.45 (95% CI: 5.57-23.02). The area under the curve (AUC) of the plotted SROC curve was 0.86 (95% CI: 0.83-0.89). The meta-regression and subgroup analyses found no source of heterogeneity. TCS has high potential and efficacy in diagnosing depression and may be a reasonable test to perform clinically for the assessment of depression.

Diagnostic accuracy of the visceral adiposity index in patients with metabolic-associated fatty liver disease: a meta-analysis

BackgroundConflicting results on the prognostic value of the visceral adiposity index (VAI) in patients with metabolic-associated fatty liver disease (MAFLD) have been reported. This study aimed to assess the diagnostic value of the VAI in MAFLD patients.MethodsThe Cochrane Library, PubMed, Embase, and other databases were searched to collect all documents that met the inclusion criteria from the establishment of the database to September 2021. The methodological quality of the included studies was assessed using the Newcastle–Ottawa Scale. The heterogeneity among the studies was analysed by the Cochran Q test and I2 test, and the appropriate model was selected according to the heterogeneity results. The diagnostic efficacy of the VAI was evaluated by sensitivity, specificity, and area under the curve, and a Fagan diagram was generated to evaluate the diagnostic ability of the VAI.ResultsA total of 9 studies were included. The overall quality of the included studies was good. Meta-analysis showed that the combined sensitivity of the VAI for the diagnosis of MAFLD was 0.70 [95% CI (0.69–0.71)], the combined specificity was 0.67 [95% CI (0.67–0.68)], the combined positive likelihood ratio was 2.08 [95% CI (1.87–2.31)], the combined negative likelihood ratio was 0.39 [95% CI (0.34–0.44)], and the combined diagnostic odds ratio was 5.81 [95% CI (4.73–7.14)]. The corresponding area under the curve was 0.79 [95% CI (0.75–0.82)]. Meta-regression analysis showed that the diagnostic method was a potential source of heterogeneity (P < 0.05). The Fagan diagram showed that the precision of MAFLD diagnosis was 70% when the pretest probability was set to 50% and then supplemented by the VAI.ConclusionsThe VAI is an independent predictor in the diagnosis of MAFLD and may be helpful in the detection of MAFLD. A VAI > 2.33 suggests that patients have a high probability of having MAFLD.

Diagnostic value of exosome derived long noncoding RNA in gastric cancer in Chinese population: A PRISMA-compliant systematic review and meta-analysis.

Background:Objective to systematically evaluate the diagnostic value of long noncoding RNA (lncRNA) in gastric cancer (GC) in the Chinese population.Methods:PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, and Wanfang Database were searched. According to the search strategy and inclusion and exclusion criteria, 2 staff members screened the relevant kinds of literature from January 2010 to December 2020 and extracted the relevant data. Revman5.3, Meta-Disc1.4, and Stata15.1 software were used to analyze the relationship between lncRNA from exosomes and the diagnosis of GC. The combined values of sensitivity (SEN), specificity (SPE), positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio (DOR) and their corresponding 95% confidence intervals (CIs) were calculated. The summary receiver operating characteristic curve was drawn and the area under the ROC curve (AUC) value was calculated.Results:In 9 studies, 1314 samples were included, including 792 cases in the case group and 522 cases in the control group. The combined SEN was 0.82 (95% CI: 0.77–0.86), the combined SPE was 0.78 (95% CI: 0.72–0.83), the combined positive likelihood ratio was 3.7 (95% CI: 2.9–4.6), the negative likelihood ratio was 0.23 (95% CI: 0.18–0.29), and the DOR was 16 (95% CI: 12–23), AUC was 0.87 (95% CI: 0.84–0.90). Subgroup analysis showed that the SEN, SPE, likelihood ratio, DOR, and AUC of plasma-derived lncRNA in the diagnosis of GC were better than those of serum.Conclusions:Exosome-derived lncRNA may be a new potential biomarker for the clinical diagnosis of GC.

A systematic review and meta-analysis of indirect comparison between miRNA and ctDNA in diagnosis of epithelial ovarian cancer.

BackgroundTo evaluate the clinical value of microRNA (miR) and circulating tumor RNA (ctDNA) in the diagnosis of epithelial ovarian cancer (EOC) by meta-analysis and indirect comparison based on common reference criteria.MethodsThe PubMed, EMBASE, MEDLINE, Cochrane Library, Chinese biology medicine (CBM), China national knowledge infrastructure (CNKI), Wanfang, and Chinese Weipu (VIP) databases were searched by computer. The retrieval time limit was from the date of establishment of the database to September 2020. Two researchers independently screened the literature and extracted the basic data according to the inclusion and exclusion criteria formulated in advance, and evaluated the literature quality according to the quality assessment of diagnostic accuracy research (quadas-2). The Meta disc 1.4 and Stata 12.0 software programs were used for meta-analysis to calculate the combined sensitivity, combined specificity, combined positive likelihood ratio, combined negative likelihood ratio and combined diagnostic odds ratio (DOR). The summary receiver operating characteristic (SROC) curve was drawn using Revman 5.3 software, and the stability of the results was evaluated by sensitivity analysis. The publication bias was evaluated by Deek’s funnel asymmetric test. The relative diagnostic odds ratio (RDOR) results of indirect comparison between microRNA and ctDNA were obtained using R software.ResultsNineteen articles were included, including a total of 1,351 EOC patients and 1,194 controls. The heterogeneity test showed that there was obvious heterogeneity caused by non-threshold effect. The random effects model was used for meta-analysis of microRNA in the diagnosis of EOC. The results showed that there was no significant difference between microRNA and ctDNA in the accuracy of EOC diagnosis. The asymmetric test of Deek’s funnel chart showed that there was no significant publication bias.DiscussionThere are some limitations in this study, there is no blind diagnostic test, and the intensity of indirect comparison evidence is lower than that of direct comparison evidence. The accuracy of diagnostic tests and the imperfection of mesh meta-analysis statistical methods. MicroRNA and ctDNA have similar clinical diagnostic value for EOC.

Systematic review and meta-analysis of the diagnostic value of radionuclide imaging for thyroid nodules.

There are many studies on diagnostic imaging of thyroid nodules, among which radionuclide scanning imaging has been proven to be very effective in identifying malignant lesions of thyroid nodules and is now widely used in the clinical detection of thyroid nodules. Studies on radionuclide imaging in the diagnosis of thyroid nodules were searched in multiple Chinese and English databases, including PubMed, Web of Science, Embase, and The Cochrane Library as of July 1, 2021. The search terms included "clinical experiment", "thyroid nodule", "radionuclide imaging", "thyroid mass", "thyroid masses", "postoperative pathology", and "histopathology". The basic information and evaluation indicators in the literature were screened and extracted. Subsequently, meta-analysis was performed using RevMan 5.3 and Stata 13 software provided by the Cochrane system. In addition, forest plots and summary receiver operating characteristic (SROC) curves were drawn. Seven randomized controlled trails (RCTs) were included in this study. The radionuclide imaging of thyroid nodule showed the area under SROC curve of 0.38. The combined diagnostic sensitivity and specificity were 0.66 [95% confidence interval (CI): 0.46, 0.89] and 0.36 (95% CI: 0.21, 0.59), respectively. The combined positive likelihood ratio (LR) and negative LR were 0.66 (95% CI: 0.53, 0.87) and 0.67 (95% CI: 0.43, 0.95), respectively. In addition, the combined diagnostic odds ratio (OR) was 4.45 (95% CI: 0.25, 10.57). In this study, meta-analysis was used to confirm the application value of radionuclide imaging in the diagnosis of thyroid nodules. In the future, the value of radionuclide imaging in the diagnosis of thyroid nodules should be compared with other imaging detection methods.