Diagnostic Test Accuracy Meta-analysis Research Articles

Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence.

There is an extensive literature on methods for meta-analysis of diagnostic test accuracy, but it mainly focuses on a single test. A multinomial generalised linear mixed model was recently proposed for the joint meta-analysis of studies comparing two tests on the same participants in a paired tests design with a gold standard. In this setting, we propose a novel model for joint meta-analysis of studies comparing two diagnostic tests which assumes independent multinomial distributions for the counts of each combination of test results in diseased and non-diseased patients, conditional on the latent vector of probabilities of each combination of test results in diseased and non-diseased patients. For the random effects distribution of the latent proportions, we employ a one-truncated D-vine copula that can provide tail dependence or asymmetry. The proposed model includes the multinomial generalised linear mixed model as a special case, accounts for the within-study dependence induced because the tests are applied to the same participants, allows for between-studies dependence, and can also operate on the original scale of the latent proportions. The latter enables the derivation of summary receiver operating characteristic curves. Our methodology is demonstrated with simulation studies and a meta-analysis of screening for Down's syndrome with two tests: shortened humerus and shortened femur.

Contrast-enhanced CT scan (CECT) for the detection of hollow viscus and mesenteric injuries in blunt trauma - an updated systematic review of the literature and meta-analysis of diagnostic test accuracy.

Despite improved awareness of blunt traumatic hollow viscus and mesenteric injuries (THVMI), the accuracy of contrast-enhanced CT (CECT) varies considerably among studies. This systematic review and meta-analysis of test accuracy aims to explore the diagnostic performance of CECT in detecting THVMI in blunt trauma. The study was conducted according to the Cochrane recommendations searching the PubMed, Scopus, and Cochrane Library datasets from 2000 to 8 September 2023 (PROSPERO ID: CRD42023473041). Surgical exploration, autopsy, and discharge from the hospital after monitoring were set as reference standard. To explore the diagnostic accuracy of CECT in detecting THVMI hierarchical models were developed. The risk of bias in individual studies was assessed with the QUADAS-2 tool. Sensitivity analysis was conducted to detect sources of heterogeneity. Twelve studies, for a total of 4537 patients, were deemed eligible. After identification of outliers and sensitivity analysis, the pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were 0.85 (95% CI: 0.69-0.93), 0.94 (95% CI: 0.8-0.98), 14.65 (95% CI: 4.22-50.85), 0.16 (95% CI: 0.07-0.34), 92.3 (95% CI: 29.75-286.34), respectively. The Area under the HSROC curve was 0.95 (95% CI: 0.92-0.96). Meta-regression analysis identified the year of publication as a covariate significantly associated with heterogeneity. A high risk of bias was detected in the "patient selection" domains. CECT has a fundamental role in identifying THVMI with high specificity but suboptimal sensitivity. Clinical criteria are still of paramount importance, especially in cases of ambiguous initial CECT images.

The serological diagnostic value of EBV-related IgA antibody panels for nasopharyngeal carcinoma: a diagnostic test accuracy meta-analysis

BackgroundNasopharyngeal carcinoma (NPC) is diagnosed relatively late and has a poor prognosis, requiring early detection to reduce the disease burden. This diagnostic test accuracy meta-analysis evaluated the serological diagnostic value of nine EBV-related IgA antibody panels (EBNA1-IgA, VCA-IgA, EA-IgA, Zta-IgA, EBNA1-IgA + VCA-IgA, VCA-IgA + EA-IgA, VCA-IgA + Rta-IgG, EBNA1-IgA + VCA-IgA + Zta-IgA and VCA-IgA + EA-IgA + Rta-IgG), aiming to identify suitable serological detection biomarkers for NPC screening.MethodsPubMed, Embase, China National Knowledge Infrastructure and Chinese BioMedical Literature Database were searched from January 1st, 2000 to September 30th, 2023, with keywords nasopharyngeal carcinoma, IgA, screening, early detection, early diagnosis, sensitivity and specificity. Articles on the diagnostic value of serum EBV-related IgA antibody panels for NPC were included. Study selection, data extraction, and quality assessment were performed independently by two researchers, and a third researcher was consulted in the case of disagreement. Bivariate models were used for statistical analysis. The quality of included studies was evaluated through Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2).ResultsA total of 70 articles were included, involving 11 863 NPC cases and 34 995 controls. Among the nine EBV-related IgA antibody panels, EBNA1-IgA + VCA-IgA [0.928 (0.898, 0.950)], VCA-IgA + Rta-IgG [0.925 (0.890, 0.949)], EBNA1-IgA + VCA-IgA + Zta-IgA [0.962 (0.909, 0.985)] and VCA-IgA + EA-IgA + Rta-IgG [0.945 (0.918, 0.964)] demonstrated higher pooled sensitivity (95%CI). In terms of diagnostic odds ratio (DOR) (95%CI), EBNA1-IgA + VCA-IgA [107.647 (61.173, 189.430)], VCA-IgA + Rta-IgG [105.988 (60.118, 186.857)] and EBNA1-IgA + VCA-IgA + Zta-IgA [344.450 (136.351, 870.153)] showed superior performance. Additionally, the SROC curves for EBNA1-IgA + VCA-IgA and VCA-IgA + Rta-IgG were more favorable. However, publication bias was detected for VCA-IgA (P = 0.005) and EBNA1-IgA + VCA-IgA (P = 0.042).ConclusionsIn general, parallel detection of serum EBNA1-IgA, VCA-IgA and Zta-IgA antibodies using ELISA demonstrates better pooled sensitivity and DOR among the studied panels. In the cases where fewer indicators are used, serum VCA-IgA and EBNA1-IgA/Rta-IgG antibody panel exhibits a comparable performance.Trial registrationThe International Prospective Register of Systematic Reviews registration number: CRD42023426984, registered on May 28, 2023.

Diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions in CT and MRI: a systematic review and meta-analysis of diagnostic test accuracy (DTA) studies.

To perform a systematic review and meta-analysis of the diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions using CT and MRI. A systematic literature search of databases was performed between January 1, 1980 and September 26, 2022. We included studies reporting the accuracy of CE thresholds on CT and MRI indeterminate renal lesions, with pathologic examination and follow-up as the reference standard. Studies meeting the inclusion criteria underwent quality assessment with the Cochrane recommendation for diagnostic accuracy study Quality Assessment 2. We excluded studies with high risk of bias. Summary estimates of diagnostic performance were obtained with the bivariate Bayesian model for CT and MRI. Effects of different thresholds and index test modalities were investigated through subgroup analysis. Eleven studies (1372 patients) using CT and six studies (218 patients) using MRI were included. Of the eleven studies, 15 parts from 9 studies were considered for the CT meta-analysis, and 6 parts from 3 studies for the MRI meta-analysis. Diagnostic performance meta-analysis on enhancement found a 96% summary sensitivity (95% CI 92, 98) and a 92% summary specificity (95% CI 85, 96) in 2056 renal lesions for CT; and 82% summary sensitivity (95% CI 65, 89) and an 89% summary specificity (95% CI 77, 95) in 634 lesions for MRI. CT and MRI have high accuracy to determine enhancement and classify renal lesions, and both modalities can be used with confidence for this purpose. There are still some controversies about the optimal thresholds. Future research should evaluate outcomes and decision-making pathways to determine whether basing clinical decisions on a specific threshold on CT and MRI would do more harm than good.

Reliability of predictive models based on the mesiodistal and buccolingual diameters of permanent canine teeth for sex estimation in forensic contexts: A systematic review and meta-analysis

This study aimed to assess the reliability of predictive models for sex estimation based on permanent canine size. A systematic literature review was performed by following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). Six electronic databases were searched as the primary source of information. As a secondary source of information, a manual search was performed to identify additional relevant studies not captured in the initial search. After assessing the methodological quality and risk of bias with the Joanna Briggs Institute Critical Appraisal Tools for Systematic Reviews, the data were subjected to statistical tests for a meta-analysis of diagnostic test accuracy and Higgin’s I2 statistic to evaluate the heterogeneity between the eligible studies. The systematic search resulted in 21 studies for qualitative synthesis, and 13 of them were selected for quantitative analysis. The analysis of 25 univariate predictive models showed an estimated sensitivity of 77.2 % and specificity of 67.1 %. Meta-regression analyses were performed for dental arch, the type of diameter and dental region outcomes for these univariate predictive models. Dental arch (p = 0.029) and the dental region of measurement (p = 0.001) were significant modifiers. The analysis of 25 multivariate predictive models showed an estimated sensitivity of 82.6 % and specificity of 70.1 %. There were significant methodological limitations and substantial heterogeneity among the included studies. Based on the results, there is insufficient high-quality scientific evidence to support the safe use of predictive models based on permanent canine measurements as the exclusive method for sex estimation in forensic settings.

Methods of diagnostic meta-analysis: comparing the generalized linear mixed model and the split component synthesis model

Purpose of review Diagnostic meta-analyses combine data from several diagnostic test accuracy (DTA) studies to provide an in-depth assessment of a specific diagnostic test's performance across diverse populations and settings. Additionally, knowledge on common methods of diagnostic meta-analyses is crucial for researchers to make informed decisions on best practice for reporting analyses and results. This article provides an overview of commonly used methods of diagnostic meta-analyses using real-life and simulation data. Recent findings Advances in methods of diagnostic meta-analyses in recent years have increased uncertainty among researchers in relation to the most suitable method to be used. Currently, the most popular approaches for diagnostic evidence synthesis include hierarchical summary operating characteristic (HSROC) and bivariate random effects models though other methods such as the split component synthesis method have been proposed. In addition, different software modules exist for DTA meta-analyses. Summary This article presents a thorough evaluation of current frequentist DTA meta-analysis methods implementing both simulated and real-world data. By understanding the recent methods of diagnostic meta-analyses and their limitations, clinicians may better be equipped in selecting the optimum approach to improve clinical judgement and consequently better patient outcomes.

Updates on the Diagnostic Use of Ultrasonography Augmented With Perfluorobutane Contrast in Hepatocellular Carcinoma: A Meta-Analysis.

To investigate the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) in the diagnosis of primary hepatocellular carcinoma (HCC), a thorough search was conducted for pertinent literature using PubMed, SCOPUS, Web of Science, Science Direct, and Wiley Library. This was a meta-analysis of diagnostic test accuracy. MetaDiSc 1.4 was used for all analyses and assessed statistical heterogeneity with the I2 index and the chi-square test. The random-effects model was applied where there was considerable heterogeneity. Using the eight elements of the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies, we assessed the quality of the included studies. Our results included nine studies with a total of 2598 patients, and 1607 (61.8%) were males.The pooled overall sensitivity of perfluorobutane with CEUS was 85.6% (95% CI 0.832, -0.878, and P=0.000) and specificity was 91.5% (95% CI 0.899, -0.930, and P=0.000) with significant inter heterogeneity between studies (I2=94.3% and 95.7%), respectively. The pooled positive likelihood ratio was 12.42 (4.59 to 33.61, P=0.000). Our analysis revealed a symmetric summary receiver operating characteristic (SROC) curve and seven of the included studies are near the top left corner of the graph, indicating that this test has a high diagnostic value. The results showed that CEUS augmented with perfluorobutane contrast had good diagnostic accuracy (sensitivity and specificity) for primary HCC. Further real-world data studies are needed to confirm the good diagnosis accuracy of perfluorobutane CEUS in primary HCC.

MRI and SPECT/CT demonstrate, with low certainty of evidence, the highest diagnostic accuracy for aseptic knee arthroplasty loosening: A systematic comparative diagnostic test review and meta-analysis.

The purpose of this study was to evaluate and compare the diagnostic accuracy of modalities used to aid the diagnosis of aseptic knee arthroplasty loosening. A comparative diagnostic test accuracy systematic review and meta-analysis was conducted following the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, EMBASEand Cochrane databases were searched for original articles evaluating diagnostic modalities up to March 2024. Included studies compared the modality (index test) to the intraoperative finding as reference test. The QUADAS-C (Quality Assessment of Diagnostic Accuracy Studies-Comparative)tool was used to assess the quality of the included studies. The GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach was used to evaluate the certainty of evidence. Level of evidence was evaluated using the Oxford Levels of Evidence tool. The primary outcome wasthe summary of diagnostic accuracy metrics for each modality as demonstrated by a summary receiver-operating characteristic (SROC) curve. The search yielded 467 articles. Of these, 14 articles were included. These 14 articles evaluated a total of five different diagnostic modalities: bone scintigraphy (three studies, 146 cases), 18-fluorodeoxyglucose positron emission tomography(two studies, 50 cases), single-photon emission computed tomography combined with computed tomography (SPECT/CT) (seven studies, 371 cases), radionuclide arthrogram (three studies, 196 cases)and magnetic resonance imaging (MRI) (one study, 116 cases). Nine studies exhibited a high risk of bias in patient selection, and all studies showed a high risk of bias related to the reference test. The majority of the included studies were classified as Level III evidence, leading to an overall low level of certainty in the evidence. The most accurate tests, as demonstrated by the SROC analysis, were MRI and SPECT/CT, with sensitivities ranging from 0.00 to 1.00 and 0.33 to 1.00 and specificities between 0.31-1.00 and 0.00-1.00, respectively. This review and meta-analysis evaluated available diagnostic modalities to aid the diagnosis of knee arthroplasty loosening and based on a low certainty of evidence suggests that MRI and SPECT/CT are currently the most accurate modalities available to aid the diagnosis of aseptic loosening of knee arthroplasty components. Level III.

A systematic review and meta-analysis of diagnostic test accuracy of chest ultrasound in diagnosing pediatric pulmonary tuberculosis.

Despite medical advancement, pediatric pulmonary tuberculosis (PTB) still has high morbidity and mortality, due to challenging detection in clinical practice. Ultrasound has been touted as the next best diagnostic tool but currently, this claim is unfounded. Therefore, this study aims to systematically review the diagnostic parameters of chest ultrasound in diagnosing pediatric PTB. The literature search started and ended on December 23, 2023. We searched MEDLINE, Cochrane Library, Pubmed, Science Direct, and Google Scholar. Our research question could be formulated as "In pediatric patients who present with signs and symptoms of PTB such as fever, cough, and poor weight gain, how accurate is chest ultrasound in ruling in and ruling out pediatric PTB when the diagnosis is compared to culture, PCR or CXR?" This systematic review adhered to the PRISMA-DTA guidelines while the meta-analysis was conducted with STATA program using the "midas" and "metandi" commands. There are five studies included with 137 positive PTB children. The combined sensitivity is 84% (95% confidence interval [CI]: 76-89), specificity of 38% (95% CI: 24-54), and summary receiver operating curve yields an area under the curve of 0.83 (95% CI: 0.80-0.86). The I2 value is 24% (95% CI: 0-100) with a p-value of 0.13. The combined negative predictive value is 0.68 (95% CI: 0.58-0.79), and the positive predictive value is 0.57 (95% CI: 0.51-0.63). The positive likelihood ratio is 1 with a 6% increase from the baseline while the negative likelihood ratio is 0.43 with a 12% decrease from the baseline. Chest ultrasound is sensitive but currently could neither exclude nor confirm pediatric PTB.

Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis

BackgroundThe prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis.MethodsA systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis’s evidence.ResultsThe analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58–0.74) and 0.74 (95% CI 0.67–0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99–3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37–0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80–8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI’s sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group.ConclusionOur study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.

Diagnostic performance of different imaging modalities for splenic malignancies: A comparative meta-analysis

Background and objectivesThe spleen hosts both benign and malignant lesions. Despite multiple imaging modalities, the distinction between these lesions poses a diagnostic challenge, marked by varying diagnostic accuracy levels across methods. In this study, we aimed to evaluate and compare the diagnostic performance of various imaging techniques for detecting malignant splenic lesions. MethodsFollowing PRISMA guidelines, we searched PubMed, Scopus, and Web of Sciences databases for studies evaluating imaging techniques in detecting malignant splenic lesions. Data extraction included diagnostic accuracy metrics, and methodological quality was assessed using QUADAS-2. Diagnostic Test Accuracy meta-analyses were conducted using R (version: 4.2.1). Subgroup analyses and meta-regression were performed to compare different modalities and clinical settings. ResultsOur study included 28 studies (pooled sample size: 2358), primarily using retrospective designs with histopathology as the reference standard. PET scan demonstrated the highest diagnostic accuracy (AUC: 92 %), demonstrating a sensitivity of 93 % (95 % CI: 80.4 % - 97.7 %) and a specificity of 82.8 % (95 % CI: 71.1 % - 90.4 %). Contrast-enhanced ultrasound (CEUS), Contrast-enhanced CT scan, and contrast-enhanced MRI also showed impressive performance with AUCs of 91.4 %, 90.9 %, and 85.3 %, respectively. Differences among these modalities were not statistically significant, but they outperformed non-contrast-enhanced methods. PET and CEUS exhibited higher specificity for lymphoma cases compared to studies including other malignancies. Conclusion and clinical implicationsOverall, PET emerges as the best modality for splenic malignancies, and CEUS and CE-MRI show promise as potential alternatives, notably due to their reduced radiation exposure. Further research is essential for precise malignancy differentiation.

Atrial Fibrillation Screening During Routine Automated Office, Home, and Ambulatory Blood Pressure Measurement: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis.

Atrial fibrillation (AF) is often asymptomatic and undiagnosed. As AF and hypertension often coexist, opportunistic AF detection during routine automated blood pressure (BP) measurement appears to be an attractive screening method. A systematic literature search was conducted to identify studies assessing the diagnostic test accuracy of office, home, or 24-hour ambulatory BP measuring devices with AF detection algorithms versus reference electrocardiography. Analyses were performed per participant (AF status based on several BP readings; most office/home devices) or per reading (AF status based on individual readings; all ambulatory devices). A meta-analysis stratified by device type (office/home/ambulatory) was conducted to calculate pooled measures of diagnostic accuracy. Sensitivity/meta-regression analyses were also performed. Among 3096 records initially retrieved, 23 diagnostic test accuracy studies were included. Data derived from 11 093 individuals (weighted age 69 years, males 56%, hypertensives 79%, diabetics 24%, and AF prevalence 17%) indicated a pooled sensitivity 0.97 (95% CI, 0.92-0.99), specificity 0.93 (95% CI, 0.90-0.95), and accuracy 0.93 (95% CI, 0.89-0.95), with generally consistent results using office, home, or ambulatory BP devices (slightly lower specificity with the latter). The positive and negative predictive values were 0.70 (95% CI, 0.60-0.80) and 0.99 (95% CI, 0.98-1.00), respectively. Sensitivity analyses indicated lower specificity in studies implementing reading versus participant analyses. Most studies presented a low risk of bias and minor applicability concerns. There is considerable and consistent evidence suggesting high diagnostic accuracy of AF detection algorithms implemented in automated BP monitors during routine BP measurements in and out of the office. AF diagnosis requires verification (electrocardiography) before treatment is administered.

Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aimed to systematically evaluate the quality of these studies and assess the diagnostic accuracy of existing models. Twelve databases (Europe PMC, Embase, etc.) and two registers were searched for published and unpublished studies using ML algorithms on medical images. Two reviewers extracted the characteristics of studies and assessed the methodological quality using the QUADAS-2 tool independently. A total of 28 studies (29 reports) were included: one was at unclear risk of bias and the others were at high risk. Thus the certainty of evidence was quite low. These studies used many types of algorithms including 8 machine learning models (logistic regression, support vector machine, random forest, etc.) and 15 deep learning models (Resnet152, Yolo v5, Inception V3, etc.). The diagnostic accuracy of a few models was relatively satisfactory. The pooled sensitivity and specificity were 0.745 (0.660-0.814) and 0.770 (0.700-0.828) in random forest, 0.765 (0.686-0.829) and 0.766 (0.688-0.830) in XGBoost, and 0.781 (0.704-0.843) and 0.781 (0.704-0.843) in LightGBM. Most studies had high risks of bias in Patient Selection and Index Test. Some algorithms are relatively satisfactory and might be promising in intelligent diagnosis. Overall, more high-quality studies and more types of algorithms should be conducted in the future. We evaluated the diagnostic accuracy of the existing models and provided clinicians with much advice about the selection of algorithms. This study stated the promising orientation of future research, and we believe it will promote the intelligent diagnosis of TMDs.

Accuracy of Intraoperative Neuromonitoring in the Diagnosis of Intraoperative Neurological Decline in the Setting of Spinal Surgery-A Systematic Review and Meta-Analysis.

Systematic review and meta-analysis. In an effort to prevent intraoperative neurological injury during spine surgery, the use of intraoperative neurophysiological monitoring (IONM) has increased significantly in recent years. Using IONM, spinal cord function can be evaluated intraoperatively by recording signals from specific nerve roots, motor tracts, and sensory tracts. We performed a systematic review and meta-analysis of diagnostic test accuracy (DTA) studies to evaluate the efficacy of IONM among patients undergoing spine surgery for any indication. The current systematic review and meta-analysis was performed using the Preferred Reporting Items for a Systematic Review and Meta-analysis statement for Diagnostic Test Accuracy Studies (PRISMA-DTA) and was registered on PROSPERO. A comprehensive search was performed using MEDLINE, EMBASE and SCOPUS for all studies assessing the diagnostic accuracy of neuromonitoring, including somatosensory evoked potential (SSEP), motor evoked potential (MEP) and electromyography (EMG), either on their own or in combination (multimodal). Studies were included if they reported raw numbers for True Positives (TP), False Negatives (FN), False Positives (FP) and True Negative (TN) either in a 2 × 2 contingency table or in text, and if they used postoperative neurologic exam as a reference standard. Pooled sensitivity and specificity were calculated to evaluate the overall efficacy of each modality type using a bivariate model adapted by Reitsma et al, for all spine surgeries and for individual disease groups and regions of spine. The risk of bias (ROB) of included studies was assessed using the quality assessment tool for diagnostic accuracy studies (QUADAS-2). A total of 163 studies were included; 52 of these studies with 16,310 patients reported data for SSEP, 68 studies with 71,144 patients reported data for MEP, 16 studies with 7888 patients reported data for EMG and 69 studies with 17,968 patients reported data for multimodal monitoring. The overall sensitivity, specificity, DOR and AUC for SSEP were 71.4% (95% CI 54.8-83.7), 97.1% (95% CI 95.3-98.3), 41.9 (95% CI 24.1-73.1) and .899, respectively; for MEP, these were 90.2% (95% CI 86.2-93.1), 96% (95% CI 94.3-97.2), 103.25 (95% CI 69.98-152.34) and .927; for EMG, these were 48.3% (95% CI 31.4-65.6), 92.9% (95% CI 84.4-96.9), 11.2 (95% CI 4.84-25.97) and .773; for multimodal, these were found to be 83.5% (95% CI 81-85.7), 93.8% (95% CI 90.6-95.9), 60 (95% CI 35.6-101.3) and .895, respectively. Using the QUADAS-2 ROB analysis, of the 52 studies reporting on SSEP, 13 (25%) were high-risk, 10 (19.2%) had some concerns and 29 (55.8%) were low-risk; for MEP, 8 (11.7%) were high-risk, 21 had some concerns and 39 (57.3%) were low-risk; for EMG, 4 (25%) were high-risk, 3 (18.75%) had some concerns and 9 (56.25%) were low-risk; for multimodal, 14 (20.3%) were high-risk, 13 (18.8%) had some concerns and 42 (60.7%) were low-risk. These results indicate that all neuromonitoring modalities have diagnostic utility in successfully detecting impending or incident intraoperative neurologic injuries among patients undergoing spine surgery for any condition, although it is clear that the accuracy of each modality differs.PROSPERO Registration Number: CRD42023384158.

A Clinical Practice Guideline for Prevention, Diagnosis and Management of Intraoperative Spinal Cord Injury: Recommendations for Use of Intraoperative Neuromonitoring and for the Use of Preoperative and Intraoperative Protocols for Patients Undergoing Spine Surgery.

Development of a clinical practice guideline following the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) process. The objectives of this study were to develop guidelines that outline the utility of intraoperative neuromonitoring (IONM) to detect intraoperative spinal cord injury (ISCI) among patients undergoing spine surgery, to define a subset of patients undergoing spine surgery at higher risk for ISCI and to develop protocols to prevent, diagnose, and manage ISCI. All systematic reviews were performed according to PRISMA standards and registered on PROSPERO. A multidisciplinary, international Guidelines Development Group (GDG) reviewed and discussed the evidence using GRADE protocols. Consensus was defined by 80% agreement among GDG members. A systematic review and diagnostic test accuracy (DTA) meta-analysis was performed to synthesize pooled evidence on the diagnostic accuracy of IONM to detect ISCI among patients undergoing spinal surgery. The IONM modalities evaluated included somatosensory evoked potentials (SSEPs), motor evoked potentials (MEPs), electromyography (EMG), and multimodal neuromonitoring. Utilizing this knowledge and their clinical experience, the multidisciplinary GDG created recommendations for the use of IONM to identify ISCI in patients undergoing spine surgery. The evidence related to existing care pathways to manage ISCI was summarized and based on this a novel AO Spine-PRAXIS care pathway was created. Our recommendations are as follows: (1) We recommend that intraoperative neurophysiological monitoring be employed for high risk patients undergoing spine surgery, and (2) We suggest that patients at "high risk" for ISCI during spine surgery be proactively identified, that after identification of such patients, multi-disciplinary team discussions be undertaken to manage patients, and that an intraoperative protocol including the use of IONM be implemented. A care pathway for the prevention, diagnosis, and management of ISCI has been developed by the GDG. We anticipate that these guidelines will promote the use of IONM to detect and manage ISCI, and promote the use of preoperative and intraoperative checklists by surgeons and other team members for high risk patients undergoing spine surgery. We welcome teams to implement and evaluate the care pathway created by our GDG.

Heterogeneity in Systematic Reviews of Medical Imaging Diagnostic Test Accuracy Studies

Systematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings. To assess how heterogeneity has been examined in medical imaging DTA studies. The PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022. A total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02). In this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.

Systematic review and meta-analysis of diagnostic test accuracy of ST-segment elevation for acute coronary occlusion

ObjectiveTo evaluate the diagnostic sensitivity and specificity of ST-segment elevation on a 12‑lead ECG in detecting ACO across any coronary artery, challenging the current STEMI-NSTEMI paradigm. MethodsStudies from MEDLINE and Scopus (2012−2023) comparing ECG findings with coronary angiograms were systematically reviewed and analyzed following PRISMA-DTA guidelines. QUADAS-2 assessed the risk of bias. Study selectionStudies included focused on AMI patients and provided data enabling the construction of contingency tables for sensitivity and specificity calculation, excluding those with non-ACS conditions, outdated STEMI criteria, or a specific focus on bundle branch blocks or other complex diagnoses. Data were extracted systematically and pooled test accuracy estimates were computed using MetaDTA software, employing bivariate analyses for within- and between-study variation. The primary outcomes measured were the sensitivity and specificity of ST-segment elevation in detecting ACO. ResultsThree studies with 23,704 participants were included. The pooled sensitivity of ST-segment elevation for detecting ACO was 43.6% (95% CI: 34.7%–52.9%), indicating that over half of ACO cases may not exhibit ST-segment elevation. The specificity was 96.5% (95% CI: 91.2%–98.7%). Additional analysis using the OMI-NOMI strategy showed improved sensitivity (78.1%, 95% CI: 62.7%–88.3%) while maintaining similar specificity (94.4%, 95% CI: 88.6%–97.3%). ConclusionThe findings reveal a significant diagnostic gap in the current STEMI-NSTEMI paradigm, with over half of ACO cases potentially lacking ST-segment elevation. The OMI-NOMI strategy could offer an improved diagnostic approach. The high heterogeneity and limited number of studies necessitate cautious interpretation and further research in diverse settings.

Urea breath test for Helicobacter pylori infection in adult dyspeptic patients: A meta-analysis of diagnostic test accuracy.

Helicobacter pylori (H. pylori) infection has been well-established as a significant risk factor for several gastrointestinal disorders. The urea breath test (UBT) has emerged as a leading non-invasive method for detecting H. pylori. Despite numerous studies confirming its substantial accuracy, the reliability of UBT results is often compromised by inherent limitations. These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H. pylori infection. To determine and compare the diagnostic accuracy of 13C-UBT and 14C-UBT for H. pylori infection in adult patients with dyspepsia. We conducted an independent search of the PubMed/MEDLINE, EMBASE, and Cochrane Central databases until April 2022. Our search included diagnostic accuracy studies that evaluated at least one of the index tests (13C-UBT or 14C-UBT) against a reference standard. We used the QUADAS-2 tool to assess the methodological quality of the studies. We utilized the bivariate random-effects model to calculate sensitivity, specificity, positive and negative test likelihood ratios (LR+ and LR-), as well as the diagnostic odds ratio (DOR), and their 95% confidence intervals. We conducted subgroup analyses based on urea dosing, time after urea administration, and assessment technique. To investigate a possible threshold effect, we conducted Spearman correlation analysis, and we generated summary receiver operating characteristic (SROC) curves to assess heterogeneity. Finally, we visually inspected a funnel plot and used Egger's test to evaluate publication bias. The titles and abstracts of 4621 studies were screened; 79 articles were retrieved and selected for full-text reading. Finally, 60 studies were included in the diagnostic test accuracy meta-analysis. Our analysis demonstrates superior diagnostic accuracy of 13C-UBT over 14C-UBT, indicated by higher sensitivity (96.60% vs 96.15%), specificity (96.93% vs 89.84%), likelihood ratios (LR+ 22.00 vs 10.10; LR- 0.05 vs 0.06), and area under the curve (AUC; 0.979 vs 0.968). Notably, 13C-UBT's DOR (586.47) significantly outperforms 14C-UBT (DOR 226.50), making it the preferred diagnostic tool for dyspeptic individuals with H. pylori infection. Correlation analysis revealed no threshold effect (13C-UBT: r = 0.48; 14C-UBT: r = -0.01), and SROC curves showed consistent accuracy. Both 13C-UBT and 14C-UBT showed high AUC values (13C-UBT 0.979; 14C-UBT 0.968) near 1.00, reinforcing their excellent accuracy and endorsing both as reliable diagnostic tools in clinical practice. In summary, our study has demonstrated that 13C-UBT has been found to outperform the 14C-UBT, making it the preferred diagnostic approach. Additionally, our results emphasize the significance of carefully considering urea dosage, assessment timing, and measurement techniques for both tests to enhance diagnostic precision. Nevertheless, it is crucial for researchers and clinicians to evaluate the strengths and limitations of our findings before implementing them in practice.

Risk of Endometrial Cancer in Asymptomatic Postmenopausal Women in Relation to Ultrasonographic Endometrial Thickness: Systematic Review and Diagnostic Test Accuracy Meta-analysis

(Abstracted from Am J Obstet Gynecol 2023;228:22–35.e2) Endometrial carcinoma (EC) can be suspected in cases of postmenopausal bleeding (PMB) with a thickened endometrium on transvaginal ultrasonography (TVS) examination. Typical guidelines recommend further investigation of PMB when the endometrial lining is greater than 4–5 mm, indicating an elevated risk of EC.

An empirical comparison of statistical methods for multiple cut-off diagnostic test accuracy meta-analysis of the Edinburgh postnatal depression scale (EPDS) depression screening tool using published results vs individual participant data

BackgroundSelective reporting of results from only well-performing cut-offs leads to biased estimates of accuracy in primary studies of questionnaire-based screening tools and in meta-analyses that synthesize results. Individual participant data meta-analysis (IPDMA) of sensitivity and specificity at each cut-off via bivariate random-effects models (BREMs) can overcome this problem. However, IPDMA is laborious and depends on the ability to successfully obtain primary datasets, and BREMs ignore the correlation between cut-offs within primary studies.MethodsWe compared the performance of three recent multiple cut-off models developed by Steinhauser et al., Jones et al., and Hoyer and Kuss, that account for missing cut-offs when meta-analyzing diagnostic accuracy studies with multiple cut-offs, to BREMs fitted at each cut-off. We used data from 22 studies of the accuracy of the Edinburgh Postnatal Depression Scale (EPDS; 4475 participants, 758 major depression cases). We fitted each of the three multiple cut-off models and BREMs to a dataset with results from only published cut-offs from each study (published data) and an IPD dataset with results for all cut-offs (full IPD data). We estimated pooled sensitivity and specificity with 95% confidence intervals (CIs) for each cut-off and the area under the curve.ResultsCompared to the BREMs fitted to the full IPD data, the Steinhauser et al., Jones et al., and Hoyer and Kuss models fitted to the published data produced similar receiver operating characteristic curves; though, the Hoyer and Kuss model had lower area under the curve, mainly due to estimating slightly lower sensitivity at lower cut-offs. When fitting the three multiple cut-off models to the full IPD data, a similar pattern of results was observed. Importantly, all models had similar 95% CIs for sensitivity and specificity, and the CI width increased with cut-off levels for sensitivity and decreased with an increasing cut-off for specificity, even the BREMs which treat each cut-off separately.ConclusionsMultiple cut-off models appear to be the favorable methods when only published data are available. While collecting IPD is expensive and time consuming, IPD can facilitate subgroup analyses that cannot be conducted with published data only.