Summary Estimates Of Sensitivity Research Articles

Iron deposition in subcortical nuclei of Parkinson's disease: A meta-analysis of quantitative iron-sensitive magnetic resonance imaging studies.

Iron deposition plays a crucial role in the pathophysiology of Parkinson's disease (PD), yet the distribution pattern of iron deposition in the subcortical nuclei has been inconsistent across previous studies. We aimed to assess the difference patterns of iron deposition detected by quantitative iron-sensitive magnetic resonance imaging (MRI) between patients with PD and patients with atypical parkinsonian syndromes (APSs), and between patients with PD and healthy controls (HCs). A systematic literature search was conducted on PubMed, Embase, and Web of Science databases to identify studies investigating the iron content in PD patients using the iron-sensitive MRI techniques (R2* and quantitative susceptibility mapping [QSM]), up until May 1, 2023. The quality assessment of case-control and cohort studies was performed using the Newcastle-Ottawa Scale, whereas diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Standardized mean differences and summary estimates of sensitivity, specificity, and area under the curve (AUC) were calculated for iron content, using a random effects model. We also conducted the subgroup-analysis based on the MRI sequence and meta-regression. Seventy-seven studies with 3192 PD, 209 multiple system atrophy (MSA), 174 progressive supranuclear palsy (PSP), and 2447 HCs were included. Elevated iron content in substantia nigra (SN) pars reticulata (P <0.001) and compacta (P <0.001), SN (P <0.001), red nucleus (RN, P <0.001), globus pallidus (P <0.001), putamen (PUT, P=0.009), and thalamus (P=0.046) were found in PD patients compared with HCs. PD patients showed lower iron content in PUT (P <0.001), RN (P=0.003), SN (P=0.017), and caudate nucleus (P=0.027) than MSA patients, and lower iron content in RN (P=0.001), PUT (P <0.001), globus pallidus (P=0.004), SN (P=0.015), and caudate nucleus (P=0.001) than PSP patients. The highest diagnostic accuracy distinguishing PD from HCs was observed in SN (AUC: 0.85), and that distinguishing PD from MSA was found in PUT (AUC: 0.90). In addition, the best diagnostic performance was achieved in the RN for distinguishing PD from PSP (AUC: 0.84). Quantitative iron-sensitive MRI could quantitatively detect the iron content of subcortical nuclei in PD and APSs, while it may be insufficient to accurately diagnose PD. Future studies are needed to explore the role of multimodal MRI in the diagnosis of PD. PROSPERO; CRD42022344413.

Diagnostic accuracy of cell-free DNA in maternal blood in detecting chromosomal anomalies in twin pregnancies: systematic review and meta-analysis.

To report the diagnostic accuracy of cell-free DNA (cfDNA) in maternal blood in detecting chromosomal anomalies in twin pregnancies. Medline, Embase and Cochrane databases were searched. The inclusion criteria were twin pregnancies undergoing cfDNA screening for Trisomies 13, 18, 21, monosomy X0 and other sex chromosomal anomalies (SCA). The index test was represented by a positive results of cfDNA test. The reference standard was represented by the karyotype results (obtained either pre or postnatally) or, in case of negative cfDNA result, by a normal neonatal phenotype. The quality of the studies was assessed using the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). Summary estimates of sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-) and diagnostic odds ratio (DOR), with the corresponding 95% Confidence Intervals (95% CI), were computed using the bivariate random-effects model. Thirty-five studies were included. cfDNA had an overall high accuracy in detecting Trisomy 21 in twin pregnancies with a sensitivity of 98.8% (95% CI 96.5-100), a specificity of 100% (95% CI 99.9-100). Sensitivity and specificity were of 94.9% (95% CI 75.6-99.1) and 100 (95% CI 99.9-100) for Trisomy 18, and 84.6% (95% C% 54.6-98.1) and 100% (95% CI 99.9-100) for Trisomy 13 . We could not compute the diagnostic accuracy of cfDNA in detecting monosomy X0 in twins, while cfDNA had a sensitivity of 100% (95% CI 71.5-100) and a specificity of 99.8% (95% CI 99.7-99.9) in detecting other SCA (11 cases). The accuracy of cfDNA in detecting Trisomy 21, 18 and 13 was similar in dichorionic and monochorionic twin pregnancies. cfDNA has a high diagnostic accuracy in detecting Trisomy 18 and 21 in twin pregnancies, irrespective of chorionicity. Accuracy in the detection of Trisomy 13 and SCA was limited by the small number of affected cases and the difficulties in the confirmation of false negative cases in case of SCA and requires confirmation in larger studies. This article is protected by copyright. All rights reserved.

Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis.

To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD). The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with NOD were included. Two-by-two tables, coupled forest plots and summary receiver operating characteristic plots were constructed using the number of true positives, false negatives, true negatives and false positives. Diagnostic random effects models were used to estimate summary sensitivity and specificity points. A total of 26,752 individuals from four studies were included. The median follow-up was 3 years and the pooled risk of pancreatic cancer was 0.8% (95% CI 0.6-1.0%). END-PAC score ≥ 3, which classifies the patients as high risk, was associated with better predictive performance (sensitivity: 55.8% (43.9-67%); specificity: 82.0% (76.4-86.5%)) in comparison with END-PAC score 1-2 (sensitivity: 22.2% (16.6-29.2%); specificity: 69.9% (67.3-72.4%)) and END-PAC score < 1 (sensitivity: 18.0% (12.8-24.6%); specificity: 50.9% (48.6-53.2%)) which classify the patients as intermediate and low risk, respectively. The evidence quality was judged to be moderate to high. END-PAC is a promising model for predicting pancreatic cancer risk in individuals with NOD. The score ≥3 should be considered as optimum cut-off value. More studies are needed to assess whether it could improve early pancreatic cancer detection rate, pancreatic cancer re-section rate, and pancreatic cancer treatment outcomes.

The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis

BackgroundWith rising incidence of skin cancer and relatively increased mortality rates, an improved diagnosis of such a potentially fatal disease is of vital importance. Although frequently curable, it nevertheless places a considerable burden upon healthcare systems. Among the various types of skin cancers, non-melanoma skin cancer is most prevalent. Despite such prevalence and its associated cost, scant proof concerning the diagnostic accuracy via Artificial Intelligence (AI) for non-melanoma skin cancer exists. This study meta-analyzes the diagnostic test accuracy of AI used to diagnose non-melanoma forms of skin cancer, and it identifies potential covariates that account for heterogeneity between extant studies.MethodsVarious electronic databases (Scopus, PubMed, ScienceDirect, SpringerLink, and Dimensions) were examined to discern eligible studies beginning from March 2022. Those AI studies predictive of non-melanoma skin cancer were included. Summary estimates of sensitivity, specificity, and area under receiver operating characteristic curves were used to evaluate diagnostic accuracy. The revised Quality Assessment of Diagnostic Studies served to assess any risk of bias.ResultsA literature search produced 39 eligible articles for meta-analysis. The summary sensitivity, specificity, and area under receiver operating characteristic curve of AI for diagnosing non-melanoma skin cancer was 0.78, 0.98, & 0.97, respectively. Skin cancer typology, data sources, cross validation, ensemble models, types of techniques, pre-trained models, and image augmentation became significant covariates accounting for heterogeneity in terms of both sensitivity and/or specificity.ConclusionsMeta-analysis results revealed that AI is predictive of non-melanoma with an acceptable performance, but sensitivity may become improved. Further, ensemble models and pre-trained models are employable to improve true positive rating.

A115 THE PERFORMANCE OF NATURAL LANGUAGE PROCESSING IN INTERPRETING COLONOSCOPY REPORTS: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract Background Screening colonoscopy is integral in the effort to identify and remove potentially cancerous lesions. Important quality indicators include the adenoma detection rate and more recently, the sessile/serrated adenoma detection rate. Natural language processing (NLP) is a computer-based linguistic technique that leverages artificial intelligence to abstract meaningful information from text. This tool carries the potential to automate the task of analyzing large volumes of colonoscopy and pathology reports to generate data on key performance metrics. Purpose The aim of this study is to systematically review the available literature on the performance of NLP in identifying the presence of an adenoma or a sessile/serrated adenoma in colonoscopy reports. Method We performed a systematic review and meta-analysis according to PRISMA recommendations. A comprehensive literature query was conducted on MEDLINE, EMBASE, CINAHL, and CDSR, through July 2022. Studies were included if they evaluated the performance of NLP in extracting data from colonoscopy reports. Our primary outcome was the performance of NLP models in correctly identifying an adenoma reported in a colonoscopy report. Two authors independently screened studies and abstracted data using an a priori designed data collection form. We pooled the sensitivity and specificity of our primary outcome using a univariate analysis first, followed by a bivariate analysis. Using the open-source package ‘mada’ which is written in R, we generated a summary estimate and a summary receiver operating characteristic curve. Result(s) From the 1030 unique studies obtained from our literature search, 13 studies met the inclusion criteria. Eligible studies were used for our meta-analysis. In the univariate analysis, the pooled sensitivity and specificity for detecting an adenoma by the NLP systems was 0.978 (95% CI 0.938-0.992) and 0.997 (95% CI 0.984-0.999), respectively. Similarly, in univariate analysis, the pooled sensitivity and specificity for detecting a sessile/serrated adenoma by the NLP systems was 0.984 (95% CI 0.929-0.996) and 1.0 (95% CI 0.998-1.000), respectively. In the bivariate analysis, the summary estimates for the sensitivity and specificity of the NLP system in detecting an adenoma were 0.973 (95% CI 0.929-0.990) and 0.992 (95%CI 0.978-0.997) respectively. For detecting a sessile/serrated adenoma, the summary estimates for sensitivity and specificity were 0.964 (95% CI 0.895-0.988) and 0.998 (95% CI 0.995-0.999) respectively. Conclusion(s) NLP models have excellent performance in extracting quality metric data from colonoscopy reports. Based on the available literature, we suggest integration of NLP in quality improvement efforts in colonoscopy. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared

Pleural fluid interleukins for diagnosis of tuberculous pleural effusion: A systematic review and meta-analysis.

The diagnostic performance of pleural fluid interleukins as potential biomarkers for tuberculous pleural effusion (TPE) remains unclear. We assessed the diagnostic accuracy of various interleukins in the pleural fluid for TPE and evaluated their ability to differentiate TPE from other effusions. We queried the PubMed and Embase databases for studies indexed till October 2021. We included studies that (a) provided information regarding sensitivity and specificity of pleural fluid interleukins for diagnosing TPE, or (b) compared pleural fluid interleukin levels between TPE and malignant or parapneumonic effusions. We used hierarchical summary receiver operating characteristic plots to model summary sensitivity and specificity. Random effects modeling was employed to pool standardized mean differences (SMD) across descriptive studies comparing TPE and other effusions. We included 80 publications in our review; most were small and of poor quality. All interleukins except interleukin-27 (interleukins 1-beta, 2, 4, 6, 8, 10, 12, 12p40, 13, 18, 33) showed poor diagnostic accuracy and inconsistent discrimination of TPE from other effusions. The summary estimates for sensitivity, specificity, and diagnostic odds ratio were 0.94 (95% CI 0.85-0.98), 0.97 (95% CI 0.93-0.99), and 507.13 (95% CI 130.66-1968.34) respectively for pleural fluid interleukin-27. Mean pleural fluid interleukin-27 levels in TPE were significantly higher than malignant (summary SMD 3.72, 95% CI 2.81-4.63) or parapneumonic (summary SMD 2.45, 95% CI -1.80-3.09) effusions. Pleural fluid interleukins are poor diagnostic biomarkers for TPE. Only pleural fluid interleukin-27 exhibited good accuracy in diagnosing TPE and needs further evaluation.

Comparison of RIPASA and ALVARADO scores for risk assessment of acute appendicitis: A systematic review and meta-analysis.

In the last decades, several clinical scores have been developed and currently used to improve the diagnosis and risk management of patients with suspected acute appendicitis (AA). However, some of them exhibited different values of sensitivity and specificity. We conducted a systematic review and metanalysis of epidemiological studies, which compared RIPASA and Alvarado scores for the diagnosis of AA. This systematic review was conducted using PubMed and Web of Science databases. Selected studies had to compare RIPASA and Alvarado scores on patients with suspected AA and reported diagnostic parameters. Summary estimates of sensitivity and specificity were calculated by the Hierarchical Summary Receiver Operating Curve (HSROC) using STATA 17 (STATA Corp, College Station, TX) and MetaDiSc (version 1.4) software. We included a total of 33 articles, reporting data from 35 studies. For the Alvarado score, the Hierarchical Summary Receiver Operating Curve (HSROC) model produced a summary sensitivity of 0.72 (95%CI = 0.66-0.77), and a summary specificity of 0.77 (95%CI = 0.70-0.82). For the RIPASA score, the HSROC model produced a summary sensitivity of 0.95 (95%CI = 0.92-0.97), and a summary specificity of 0.71 (95%CI = 0.60-0.80). RIPASA score has higher sensitivity, but low specificity compared to Alvarado score. Since these scoring systems showed different sensitivity and specificity parameters, it is still necessary to develop novel scores for the risk assessment of patients with suspected AA.

Xpert MTB/RIF Ultra assay for tuberculosis disease and rifampicin resistance in children.

Xpert MTB/RIF Ultra assay for tuberculosis disease and rifampicin resistance in children.

The Use of Infrared Thermography (IRT) in Burns Depth Assessment: A Diagnostic Accuracy Meta-Analysis

Background: The timely diagnosis of burns depth is crucial to avoid unnecessary surgery and delays in adequate management of patients with burn injuries. Whilst it is mostly a clinical diagnosis, indocyanine green, laser Doppler imaging and infrared thermography have been used alongside clinical findings to support the diagnosis. Infrared thermography is a noninvasive technique which uses temperature differences to diagnose tissue burn depth. Our study aims to assess its use in differentiating between superficial and deep burns. Methods: We conducted a systematic literature review and meta-analysis using electronic databases. We used a mixed-effects logistic regression bivariate model to estimate summary sensitivity and specificity and developed hierarchical summary receiver operating characteristic (HSROC) curves. Results: We identified 6 studies reporting a total of 197 burns, of which 92 were proven to be deep burns. The reference standard was clinical assessment at the time of injury and burn healing time. The pooled estimates for sensitivity and specificity were 0.84 (95% CI 0.71–0.92) and 0.76 (95% CI 0.56–0.89), respectively. Conclusions: IRT is a promising burns assessment modality which may allow surgeons to correctly classify burn injuries at the time of presentation. This will allow a more efficient management of burns and timely surgical intervention.

Diagnostic Accuracy of MRI for Solid Renal Masses: A Systematic Review and Meta-analysis.

Biparametric (bp)-MRI and multiparametric (mp)-MRI may improve the diagnostic accuracy of renal mass histology. To evaluate the available evidence on the diagnostic accuracy of bp-MRI and mp-MRI for solid renal masses in differentiating malignant from benign, aggressive from indolent, and clear cell renal cell carcinoma (ccRCC) from other histology. Systematic review. MEDLINE, EMBASE, and CENTRAL up to January 11, 2022 were searched. 1.5 or 3 Tesla. Eligible studies evaluated the accuracy of MRI (with at least two sequences: T2, T1, dynamic contrast and diffusion-weighted imaging) for diagnosis of solid renal masses in adult patients, using histology as reference standard. Risk of bias and applicability were assessed using QUADAS-2. Meta-analysis using a bivariate logitnormal random effects model. We included 10 studies (1239 masses from approximately 1200 patients). The risk of bias was high in three studies, unclear in five studies and low in two studies. The diagnostic accuracy of malignant (vs. benign) masses was assessed in five studies (64% [179/281] malignant). The summary estimate of sensitivity was 95% (95% confidence interval [CI]: 77%-99%), and specificity was 63% (95% CI: 46%-77%). No study assessed aggressive (vs. indolent) masses. The diagnostic accuracy of ccRCC (vs. other subtypes) was evaluated in six studies (47% [455/971] ccRCC): the summary estimate of sensitivity was 85% (95% CI: 77%-90%) and specificity was 77% (95% CI: 73%-81%). Our study reveals deficits in the available evidence on MRI for diagnosis of renal mass histology. The number of studies was limited, at unclear/high risk of bias, with heterogeneous definitions of solid masses, imaging techniques, diagnostic criteria, and outcome measures. 3 TECHNICAL EFFICACY: Stage 2.

Xpert MTB/RIF Ultra versus Xpert MTB/RIF for diagnosis of tuberculous pleural effusion: A systematic review and comparative meta-analysis.

We compared diagnostic accuracy of pleural fluid Xpert MTB/RIF (Xpert) and Xpert MTB/RIF Ultra (Ultra) assays for diagnosing tuberculous pleural effusion (TPE), through systematic review and comparative meta-analysis. We searched PubMed and Embase databases for publications reporting diagnostic accuracy of Xpert or Ultra for TPE. We used bivariate random-effects modeling to summarize diagnostic accuracy information from individual studies using either mycobacterial culture or composite criteria as reference standard. We performed meta-regression through hierarchical summary receiver operating characteristic (HSROC) modeling to evaluate comparative performance of the two tests from studies reporting diagnostic accuracy of both in the same study population. We retrieved 1097 publications, and included 74 for review. Summary estimates for sensitivity and specificity for Xpert were 0.52 (95% CI 0.43-0.60, I2 82.1%) and 0.99 (95% CI 0.97-0.99, I2 85.1%), respectively, using culture-based reference standard; and 0.21 (95% CI 0.17-0.26, I2 81.5%) and 1.00 (95% CI 0.99-1.00, I2 37.6%), respectively, using composite reference standard. Summary estimates for sensitivity and specificity for Ultra were 0.68 (95% CI 0.55-0.79, I2 80.0%) and 0.97 (95% CI 0.97-0.99, I2 92.1%), respectively, using culture-based reference standard; and 0.47 (95% CI 0.40-0.55, I2 64.1%) and 0.98 (95% CI 0.95-0.99, I2 54.8%), respectively, using composite reference standard. HSROC meta-regression yielded relative diagnostic odds ratio of 1.28 (95% CI 0.65-2.50) and 1.80 (95% CI 0.41-7.84) respectively in favor of Ultra, using culture and composite criteria as reference standard. Ultra provides superior diagnostic accuracy over Xpert for diagnosing TPE, mainly because of its higher sensitivity.

Comparative diagnostic accuracy of immunoprecipitation versus immunoassay methods for detecting Aspergillus fumigatus-specific IgG in allergic bronchopulmonary aspergillosis: A systematic review and meta-analysis.

The diagnostic accuracy of immunoassays versus immunoprecipitation methods for detecting A.fumigatus-specific IgG in patients with allergic bronchopulmonary aspergillosis (ABPA) complicating asthma remains unclear. We performed a systematic review to identify studies describing both the methods in the same ABPA subjects. We assessed study quality using the QUADAS-2 tool. We derived the relative sensitivity and specificity using the HSROC meta-regression model. We calculated the number-needed-to-test using an immunoassay to detect one additional positive test in ABPA. Our search yielded 20 studies (796 ABPA and 929 controls). The studies had a high risk of bias. The summary estimates for sensitivity and specificity of immunoprecipitation methods were 68.6% (95% CI, 48.4-83.5) and 93.8% (95% CI, 83.6-97.8), respectively, while for immunoassays they were 85.2% (95% CI, 73.3-92.3) and 84.6% (95% CI, 76.0-90.5), respectively. The relative sensitivity and specificity of immunoassays compared to immunoprecipitation tests were 1.29 (95% CI, 1.1-1.6) and 0.91 (95% CI, 0.85-0.97), respectively. The automated immunoassays (1.77; 95% CI, 1.1-2.8) had better relative sensitivity than the manual (1.1; 95% CI, 1.02-1.18) assays compared to immunoprecipitation. The relative specificity of manual immunoassays (0.95; 95% CI, 0.91-0.99) was significantly lower, while that of automated (0.88; 95% CI, 0.77-1.0) assays was lower but not statistically different. One additional positive result was detected for every six (95% CI, 5-7) tests performed with immunoassay (versus immunoprecipitation). Compared to immunoprecipiation methods, automated immunoassays have higher sensitivity and similar specificity, manual immunoassays have higher sensitivity and lower specificity, while automated immunoassays have higher sensitivity and similar specificity for detecting A.fumigatus-IgG in patients with ABPA. [www.crd.york.ac.uk/prospero/display_record.php?RecordID=309864].

Point-of-care testing for tetanus immunity: a systematic review and meta-analysis

BackgroundThe current standard of care for tetanus prophylaxis management in patients with open wounds likely results in overtreatment and unnecessary costs. Point-of-care immunochromatographic tests, known as Tetanus Quick Sticks (TQS),...

Symptom- and chest-radiography screening for active pulmonary tuberculosis in HIV-negative adults and adults with unknown HIV status.

Symptom- and chest-radiography screening for active pulmonary tuberculosis in HIV-negative adults and adults with unknown HIV status.

Immunohistochemical markers to diagnose primary squamous cell carcinoma of the lung: a meta-analysis of diagnostic test accuracy.

Background:Inconsistent diagnostic test accuracies of immunohistological staining for squamous cell carcinoma (SQC) of the lung have been frequently reported. There have been few meta-analyses of the diagnostic accuracies of the immunohistochemical markers.Methods:A systematic review and meta-analysis were performed following standard guidelines for systematic reviews of diagnostic test accuracy. Immunohistochemical markers (p40, p63, CK5/6, and DSC3) were evaluated as index tests for SQC. The diagnostic odds ratio (DOR) was obtained by the DerSimonian–Laird variate model. Summary estimates of sensitivity and specificity were calculated using a bivariate model. The protocol registration ID is UMIN000041664.Results:The meta-analysis included 85 of the 1353 first-screened articles. The total number of patients was 17,893, which consisted 6151 SQC cases and 11,742 non-squamous non-small-cell lung cancer cases. The DOR was better for p40 (377, 95% confidence interval (CI) = 213–644, I2 = 0%) than for CK5/6 (120, 95% CI = 78–184, I2 = 2.5%), p63 (70, 95% CI = 55–88, I2 = 9.1%), and DSC3 (94, 95% CI = 35–250, I2 = 3.7%). Summary estimates of sensitivity and specificity were followings: p40 sensitivity 0.92 (95% CI = 0.89–0.95), specificity 0.94 (95% CI = 0.93–0.96); p63 sensitivity 0.92 (95% CI = 0.90–0.94), specificity 0.83 (95% CI = 0.80–0.86); CK5/6 sensitivity 0.90 (95% CI = 0.87–0.93), specificity 0.91 (95% CI = 0.89–0.93); DSC3 sensitivity 0.81 (95% CI = 0.73–0.88), and specificity 0.95 (95% CI = 0.85–0.98).Conclusion:P40 had the best DOR to diagnose SQC in non-small-cell lung carcinoma. Despite its lower sensitivity, DSC3 had the best specificity among the four markers and might be useful to rule-in the diagnosis of SQC.

Pleural fluid lysozyme as a diagnostic biomarker of pleural tuberculosis: A systematic review and meta-analysis.

Pleural fluid lysozyme (LP) and its ratio to serum lysozyme (LP/LS) have been proposed as potential biomarkers for diagnosing tuberculous pleural effusion (TPE). We assessed the diagnostic accuracy of LP and LP/LS for TPE and evaluated their ability to differentiate TPE from other effusions. We queried the PubMed and Embase databases for studies indexed until October 2021. We included studies that (a) provided information regarding the sensitivity and specificity of LP or LP/LS for the diagnosis of TPE, or (b) compared LP or LP/LS between TPE and malignant or parapneumonic effusions. We used hierarchical summary receiver operating characteristic plots to model summary sensitivity and specificity. Random effects modeling was employed to pool standardized mean differences (SMD) across descriptive studies comparing TPE and other effusions. We included 11 publications in our review, most of which were small and of poor quality. The summary estimates for sensitivity, specificity, and diagnostic odds ratio (DOR) were 0.94 (95% confidence interval [CI] 0.53-1.00), 0.89 (95% CI 0.63-0.97), and 129.88 (95% CI 6.26-2695), and 0.98 (95% CI 0.58-1.00), 0.91 (95% CI 0.84-0.96), and 708.47 (95% CI 11.42-43946), respectively, for LP and LP/LS. Mean LP and LP/LS in TPE were significantly higher than in malignant effusions (summary SMD 1.51 [95% CI 1.04-1.98] and 1.77 [95% CI 1.31-2.22], respectively), and parapneumonic effusions (summary SMD 0.86 [95% CI 0.51-1.22] and 1.15 [95% CI 0.64-1.66], respectively). There is low-quality evidence of good diagnostic accuracy for both LP and LP/LS in identifying TPE, the latter being marginally superior.

Magnetic resonance imaging (MRI) for diagnosis of acute appendicitis.

Appendicitis remains a difficult disease to diagnose, and imaging adjuncts are commonly employed. Magnetic resonance imaging (MRI) is an imaging test that can be used to diagnose appendicitis. It is not commonly regarded as a first-line imaging test for appendicitis, but the reported diagnostic accuracy in some studies is equivalent to computed tomography (CT) scans. As it does not expose patients to radiation, it is an attractive imaging modality, particularly in women and children. The primary objective was to determine the diagnostic accuracy of MRI for detecting appendicitis in all patients. Secondary objectives: To investigate the accuracy of MRI in subgroups of pregnant women, children, and adults. To investigate the potential influence of MRI scanning variables such as sequences, slice thickness, or field of view. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and Embase until February 2021. We searched the references of included studies and other systematic reviews to identify further studies. We did not exclude studies that were unpublished, published in another language, or retrospective. We included studies that compared the outcome of an MRI scan for suspected appendicitis with a reference standard of histology, intraoperative findings, or clinical follow-up. Three study team members independently filtered search results for eligible studies. We independently extracted study data and assessed study quality using the Quality Assessment of Studies of Diagnostic Accuracy - Revised (QUADAS-2) tool. We used the bivariate model to calculate pooled estimates of sensitivity and specificity. We identified 58 studies with sufficient data for meta-analysis including a total of 7462 participants (1980 with and 5482 without acute appendicitis). Estimates of sensitivity ranged from 0.18 to 1.0; estimates of specificity ranged from 0.4 to 1.0. Summary sensitivity was 0.95 (95% confidence interval (CI) 0.94 to 0.97); summary specificity was 0.96 (95% CI 0.95 to 0.97). Sensitivity and specificity remained high on subgroup analysis for pregnant women (sensitivity 0.96 (95% CI 0.88 to 0.99); specificity 0.97 (95% CI 0.95 to 0.98); 21 studies, 2282 women); children (sensitivity 0.96 (95% CI 0.95 to 0.97); specificity 0.96 (95% CI 0.92 to 0.98); 17 studies, 2794 children); and adults (sensitivity 0.96 (95% CI 0.93 to 0.97); specificity 0.93 (95% CI 0.80 to 0.98); 9 studies, 1088 participants), as well as different scanning techniques. In a hypothetical cohort of 1000 patients, there would be 12 false-positive results and 30 false-negative results. Methodological quality of the included studies was poor, and the risk of bias was high or unclear in 53% to 83% of the QUADAS-2 domains. MRI appears to be highly accurate in confirming and excluding acute appendicitis in adults, children, and pregnant women regardless of protocol. The methodological quality of the included studies was generally low due to incomplete and low standards of follow-up, so summary estimates of sensitivity and specificity may be biased. We could not assess the impact and direction of potential bias given the very low number of high-quality studies. Studies comparing MRI protocols were few, and although we found no influence of MRI protocol variables on the summary estimates of accuracy, our results do not rule out that some MRI protocols are more accurate than others.

Contrast-enhanced Mammography: A Systematic Review and Meta-Analysis of Diagnostic Performance.

Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ2 = 0.3). At meta-regression, CEM interpretation with both low-energy and recombined images had higher sensitivity (95% vs 94%, P < .001) and specificity (81% vs 71%, P = .03) compared with recombined images alone. At subgroup analysis, CEM showed a 95% pooled sensitivity (95% CI: 92, 97) and a 78% pooled specificity (95% CI: 66, 87) from nine studies in patients with dense breasts, while in 10 studies on mammography-detected suspicious findings, CEM had a 92% pooled sensitivity (95% CI: 89, 94) and an 84% pooled specificity (95% CI: 73, 91). Conclusion Contrast-enhanced mammography demonstrated high performance in breast cancer detection, especially with joint interpretation of low-energy and recombined images. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bahl in this issue.

Comparing drawing under instructions with image copying for mild cognitive impairment (MCI) or dementia screening: A meta‐analysis of 92 diagnostic studies

AbstractBackgroundDrawing is a major component of cognitive screening for dementia. It can be performed without language restriction. Drawing pictures under instructions and copying images are different screening approaches. The objective of this study was to compare the diagnostic performance between drawing under instructions and image copying for MCI and dementia screening.MethodA literature search was carried out in the OVID databases with keywords related to drawing for cognitive screening. Study quality and risk of bias were assessed by QUADAS‐2. The level of diagnostic accuracy across different drawing tests were pooled by bivariate analysis in a random effects model. Summary estimates of sensitivity and specificity with 95% CI and prediction region were presented in a hierarchical summary receiver operating characteristic (HSROC) curve. The area under the hierarchical summary receiver‐operating characteristic curve (AUC) was constructed to summarize the diagnostic performance.ResultNinety‐two studies with sample size of 22,085 were included. The pooled results for drawing under instructions showed a sensitivity of 79% (95% CI: 76 – 83%) and a specificity of 80% (95% CI: 77 – 83%) with AUC of 0.87 (95% CI: 0.83 – 0.89). The pooled results for image copying showed a sensitivity of 71% (95% CI: 62 – 79%) and a specificity of 83% (95% CI: 72 – 90%) with AUC of 0.83 (95% CI: 0.80 – 0.86) (Fig. 1). Subgroup analysis for the diagnostic accuracy for MCI and dementia showed that both drawing under instructions and image copying have better diagnostic performance for patients with dementia. The AUC of drawing under instructions and image copying for patients with dementia were 0.88 (95% CI: 0.85 – 0.91) and 0.85 (95% CI: 0.82 – 0.88) and the AUC for patients with MCI were 0.77 (0.73 – 0.80) and 0.73 (95% CI: 0.69 – 0.77), respectively. Most of the studies used clock‐drawing test as the screening test.ConclusionDrawing under instructions showed a similar diagnostic performance when compared with image copying for cognitive screening and the administration of image copying is relatively simpler. Self‐screening for dementia is feasible to be done at home in the near future.

Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis

BackgroundSignificant morbidity, mortality, and financial burden are associated with cardiac rhythm abnormalities. Conventional investigative tools are often unsuccessful in detecting cardiac arrhythmias because of their episodic nature. Smartwatches have gained popularity in recent years as a health tool for the detection of cardiac rhythms.ObjectiveThis study aims to systematically review and meta-analyze the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias.MethodsA systematic literature search of the Embase, MEDLINE, and Cochrane Library databases was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies reporting the use of a smartwatch for the detection of cardiac arrhythmia. Summary estimates of sensitivity, specificity, and area under the curve were attempted using a bivariate model for the diagnostic meta-analysis. Studies were examined for quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.ResultsA total of 18 studies examining atrial fibrillation detection, bradyarrhythmias and tachyarrhythmias, and premature contractions were analyzed, measuring diagnostic accuracy in 424,371 subjects in total. The signals analyzed by smartwatches were based on photoplethysmography. The overall sensitivity, specificity, and accuracy of smartwatches for detecting cardiac arrhythmias were 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97), and 97% (95% CI 0.96-0.99), respectively. The pooled positive predictive value and negative predictive value for detecting cardiac arrhythmias were 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively.ConclusionsThis review demonstrates the evolving field of digital disease detection. The current diagnostic accuracy of smartwatch technology for the detection of cardiac arrhythmias is high. Although the innovative drive of digital devices in health care will continue to gain momentum toward screening, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed.Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42020213237; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213237.