Diagnostic test accuracy: application and practice using R software

Diagnostic and prognostic value of heparin-binding protein in sepsis: A systematic review and meta-analysis

BACKGROUND

Sepsis remains a leading cause of death worldwide. In this context, heparin-binding protein (HBP) has emerged as a possible biomarker, drawing significant attention for its diagnostic and prognostic usefulness in septic patients. Despite this advancement, the literature yields conflicting results. This study is intended to critically evaluate the diagnostic and prognostic value of HBP in critically ill septic patients.

METHODS

We searched multiple databases, including PubMed, SCOPUS, Web of Science, and EBSCO, to identify relevant studies on April 27, 2023. We included studies investigating sepsis or its severe outcomes that reported HBP levels and the required data to create 2 × 2 tables. We used R version 4.2.2 and R Studio to analyze the pooled diagnostic accuracy outcomes. The diagmeta package was utilized to calculate the optimum cutoff value.

RESULTS

In our meta-analysis, we incorporated 28 studies including 5508 patients. The analysis revealed that HBP has a sensitivity of 0.71 (95% CI: 0.60; 0.79) and a specificity of 0.68 (95% CI: 0.51; 0.81) in diagnosing sepsis, respectively. HBP demonstrated moderate prognostic accuracy for mortality at a cutoff value of 161.415 ng/mL, with a sensitivity and specificity of 72%, and for severe sepsis outcomes at a cutoff value of 58.907 ng/mL, with a sensitivity and specificity of 71%.

CONCLUSION

Our findings indicate a relatively moderate diagnostic and prognostic accuracy of HBP for sepsis. Future studies are required to verify the accuracy of HBP as a biomarker for sepsis.

The conundrum of differentiating Cushing's syndrome from non-neoplastic hypercortisolism: a systematic review and meta-analysis

CONTEXT

Once hypercortisolemia is confirmed, differential diagnosis between Cushing's syndrome (CS) due to neoplastic endogenous hypercortisolism and non-neoplastic hypercortisolism (NNH, pseudo-Cushing's syndrome) is crucial. Due to worldwide corticotropin-releasing hormone (CRH) unavailability, accuracy of alternative tests to dexamethasone (Dex)-CRH, is clearly needed.

OBJECTIVE

Assess the diagnostic accuracy of Dex-CRH test, desmopressin stimulation test, midnight serum cortisol (MSC), and late-night salivary cortisol (LNSC) levels to distinguish CS from NNH.

METHODS

Articles through March 2022 were identified from Scopus, Web of Science, MEDLINE, EMBASE, and PubMed. All steps through the systematic review were performed independently and in duplicate and strictly adhered to the updated PRISMA-DTA checklist.

DATA SYNTHESIS

A total of 24 articles (1900 patients) were included. Dex-CRH had a pooled sensitivity and specificity of 91% (95%CI 87-94%; I2 0%) and 82% (73-88%; I2 50%), desmopressin test 86% (81-90%; I2 28%) and 90% (84-94%; I2 15%), MSC 91% (85-94%; I2 66%) and 81% (70-89%; I2 71%), and LNSC 80% (67-89%; I2 57%) and 90% (84-93%; I2 21%), respectively. Summary receiver operating characteristics areas under the curve were Dex-CRH 0.949, desmopressin test 0.936, MSC 0.942, and LNSC 0.950 without visual or statistical significance. The overall risk of studies bias was moderate.

CONCLUSION

Dex-CRH, the desmopressin stimulation test, and MSC have similar diagnostic accuracy, with Dex-CRH and MSC having slightly higher sensitivity, and the desmopressin test being more specific. LNSC was the least accurate, probably due to high heterogeneity, intrinsic variability, different assays, and lack of consistent reported cutoffs. When facing this challenging differential diagnosis, the results presented here should increase clinicians' confidence when deciding which test to perform.

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

BACKGROUND

The 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.

METHODS

A 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.

RESULTS

The 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.

CONCLUSION

Our 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.

Artificial intelligence in diagnosing upper limb musculoskeletal disorders: a systematic review and meta-analysis of diagnostic tests

Purpose

The integration of artificial intelligence (AI) in radiology has revolutionized diagnostics, optimizing precision and decision-making. Specifically in musculoskeletal imaging, AI tools can improve accuracy for upper extremity pathologies. This study aimed to assess the diagnostic performance of AI models in detecting musculoskeletal pathologies of the upper extremity using different imaging modalities.

Methods

A meta-analysis was conducted, involving searches on MEDLINE/PubMed, SCOPUS, Cochrane Library, Lilacs, and SciELO. The quality of the studies was assessed using the QUADAS-2 tool. Diagnostic accuracy measures including sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR, NLR), area under the curve (AUC), and summary receiver operating characteristic were pooled using a random-effects model. Heterogeneity and subgroup analyses were also included. All statistical analyses and plots were performed using the R software package.

Results

Thirteen models from ten articles were analyzed. The sensitivity and specificity of the AI models to detect musculoskeletal conditions in the upper extremity were 0.926 (95% CI: 0.900; 0.945) and 0.908 (95% CI: 0.810; 0.958). The PLR, NLR, lnDOR, and the AUC estimates were found to be 19.18 (95% CI: 8.90; 29.34), 0.11 (95% CI: 0.18; 0.46), 4.62 (95% CI: 4.02; 5.22) with a (P < 0.001), and 95%, respectively.

Conclusion

The AI models exhibited strong univariate and bivariate performance in detecting both positive and negative cases within the analyzed dataset of musculoskeletal pathologies in the upper extremity.

Comparative Study of Different Imaging Modalities for Diagnosis of Bone Metastases of Prostate Cancer: A Bayesian Network Meta-analysis

PURPOSE

This study aimed to compare the diagnostic performances of 8 different imaging modalities for preoperative detection of bone metastases in prostate cancer patients by performing a network meta-analysis using direct comparison studies with 2 or more imaging techniques.

PATIENTS AND METHODS

We searched PubMed, Embase, and Cochrane Library for studies evaluating the performances of 8 different imaging modalities for the preoperative detection of bone metastases in prostate cancer patients. The network meta-analysis was performed in patient-based analysis. The consistency was evaluated by examining the agreement between direct and indirect treatment effects, and the surface under the cumulative ranking curve (SUCRA) values were obtained to calculate the probability of each imaging modality being the most effective diagnostic method.

RESULTS

A total of 999 patients from 13 direct comparison studies using 8 different imaging modalities for preoperative detection or follow-up of bone metastases in prostate cancer patients were included. For the detection of bone metastases of prostate cancer, 68 Ga-PSMA-11 PET/CT showed the highest SUCRA values of sensitivity, positive predictive value, accuracy, and diagnostic odds ratio. In addition, 18 F-NaF PET/CT and SPECT/CT showed high SUCRA values.

CONCLUSIONS

68 Ga-PSMA-11 PET/CT showed the highest SUCRA values. Other imaging modalities showed complementary diagnostic roles for preoperative detection of bone metastases in patients with prostate cancer, except bone scintigraphy and MRI.

The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis

OBJECTIVES

To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions.

MATERIALS AND METHODS

A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated.

RESULTS

A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585).

CONCLUSIONS

UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions.

CLINICAL RELEVANCE STATEMENT

UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients.

KEY POINTS

• Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.

Clinical Presentation, Risk Factors, and Comparison of Laboratory Diagnostics for Seasonal Influenza Virus Among Cambodians From 2007 to 2020

Background

Despite its global significance, challenges associated with understanding the epidemiology and accurately detecting, measuring, and characterizing the true burden of seasonal influenza remain in many resource-poor settings.

Methods

A prospective observational study was conducted in Cambodia at 28 health facilities between 2007 and 2020 utilizing passive surveillance data of patients presenting with acute undifferentiated febrile illness (AUFI) to describe the prevalence of influenza A and B and characterize associated risk factors and symptoms using a questionnaire. A comparison of rapid influenza diagnostic tests (RIDTs) and real-time reverse transcription polymerase chain reaction (rRT-PCR) results was also conducted.

Results

Of 30 586 total participants, 5634 (18.4%) tested positive for either influenza A or B, with 3557 (11.6%) positive for influenza A and 2288 (7.5%) positive for influenza B during the study. Influenza A and B were strongly associated with the rainy season (odds ratio [OR], 2.30; P < .001) and being from an urban area (OR, 1.45; P < .001). Analysis of individual symptoms identified cough (OR, 2.8; P < .001), chills (OR, 1.4; P < .001), and sore throat (OR, 1.4; P < .001) as having the strongest positive associations with influenza among patients with AUFI. Analysis comparing RIDTs and rRT-PCR calculated the overall sensitivity of rapid tests to be 0.492 (95% CI, 0.479-0.505) and specificity to be 0.993 (95% CI, 0.992-0.994) for both influenza type A and B.

Conclusions

Findings from this 14-year study include describing the epidemiology of seasonal influenza over a prolonged time period and identifying key risk factors and clinical symptoms associated with infection; we also demonstrate the poor sensitivity of RIDTs in Cambodia.

Diagnostic performance of angiography-derived fractional flow reserve and CT-derived fractional flow reserve: A systematic review and Bayesian network meta-analysis

OBJECTIVE

Accumulating evidence has demonstrated that fractional flow reserves (FFRs) derived from invasive coronary angiograms (CA-FFRs) and coronary computed tomography angiography-derived FFRs (CT-FFRs) are promising alternatives to wire-based FFRs. However, it remains unclear which method has better diagnostic performance. This systematic review and meta-analysis aimed to compare the diagnostic performances of the two approaches.

METHODS

The Cochrane Library, PubMed, Embase, Medline (Ovid), the Chinese China National Knowledge Infrastructure Database (CNKI), VIP, and WanFang Data databases were searched for relevant studies that included comparisons between CA-FFR and CT-FFR, from their respective database inceptions until January 1, 2023. Studies where both noninvasive FFR (including CA-FFR and CT-FFR) and invasive FFR (as a reference standard) were performed for the diagnosis of ischemic coronary artery disease and were designed as prospective, paired diagnostic studies, were pulled. The diagnostic test accuracy method and Bayesian hierarchical summary receiver operating characteristic (ROC) model for network meta-analysis (NMA) of diagnostic tests (HSROC-NMADT) were both used to perform a meta-analysis on the data.

RESULTS

Twenty-six studies were included in this NMA. The results from both the diagnostic test accuracy and HSROC-NMADT methods revealed that the diagnostic accuracy of CA-FFR was higher than that of CT-FFR, in terms of sensitivity (Se; 0.86 vs. 0.84), specificity (Sp; 0.90 vs. 0.78), positive predictive value (PPV; 0.83 vs. 0.70), and negative predictive value (NPV; 0.91 vs. 0.89) for the detection of myocardial ischemia. A cumulative ranking curve analysis indicated that CA-FFR had a higher diagnostic accuracy than CT-FFR in the context of this study, with a higher area under the ROC curve (AUC; 0.94 vs. 0.87).

CONCLUSIONS

Although both of these two commonly used virtual FFR methods showed high levels of diagnostic accuracy, we demonstrated that CA-FFR had a better Se, Sp, PPV, NPV, and AUC than CT-FFR. However, this study provided only indirect comparisions; therefore, larger studies are warranted to directly compare the diagnostic performances of these two approaches.

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

STUDY DESIGN

Systematic review and meta-analysis.

OBJECTIVES

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.

METHODS

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).

RESULTS

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.

CONCLUSIONS

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.

The Efficacy and Safety of Metastasis-directed Therapy in Patients with Prostate Cancer: A Systematic Review and Meta-analysis of Prospective Studies

CONTEXT

Despite the lack of level 1 evidence, metastasis-directed therapy (MDT) is used widely in the management of metastatic prostate cancer (mPCa) patients. Data are continuously emerging from well-designed prospective studies.

OBJECTIVE

To summarise and report the evidence on oncological and safety outcomes of MDT in the management of mPCa patients.

EVIDENCE ACQUISITION

We searched the PubMed, Scopus, and Web of Science databases for prospective studies assessing progression-free survival (PFS), local control (LC), androgen deprivation therapy (ADT)-free survival (ADT-FS), overall survival (OS), and/or adverse events (AEs) in mPCa patients treated with MDT. A meta-analysis was performed for 1- and 2-yr PFS, LC, ADT-FS, OS, and rate of AEs. Meta-regression and sensitivity analysis were performed to account for heterogeneity and identify moderators.

EVIDENCE SYNTHESIS

We identified 22 prospective studies (n = 1137), including two randomised controlled trials (n = 116). Two studies were excluded from the meta-analysis (n = 120). The estimated 2-yr PFS was 46% (95% confidence interval [CI]: 36-56%) or 42% (95% CI: 33-52%) after excluding studies using biochemical or ADT-related endpoints. The estimated 2-yr LC, ADT-FS, and OS were 97% (95% CI: 94-98%), 55% (95% CI: 44-65%), and 97% (95% CI: 95-98%), respectively. Rates of treatment-related grade 2 and ≥3 AEs were 2.4% (95% CI: 0.2-7%) and 0.3% (95% CI: 0-1%), respectively.

CONCLUSIONS

MDT is a promising treatment strategy associated with favourable PFS, excellent LC, and a low toxicity profile that allows oligorecurrent hormone-sensitive patients to avoid or defer ADT-related toxicity. Integration of MDT with other therapies offers a promising research direction, in particular, in conjunction with systemic treatments and as a component of definitive care for oligometastatic PCa. However, in the absence of randomised trials, using MDT for treatment intensification remains an experimental approach, and the impact on OS is uncertain.

PATIENT SUMMARY

Direct treatment of metastases is a promising option for selected prostate cancer patients. It can delay hormone therapy and is being investigated as a way of intensifying treatment at the expense of manageable toxicity.

The diagnostic utility of heparin-binding protein among patients with bacterial infections: a systematic review and meta-analysis

BACKGROUND

Bacterial infections are considered a leading cause of hospitalization and death globally. There is still a need for a rapid and feasible biomarker for bacterial infections. Heparin-binding protein (HBP) was shown to be related to bacterial infections. The objective of the study is to investigate the diagnostic accuracy of HBP in bacterial infections.

METHODS

Articles were screened in PubMed, SCOPUS, Web of Science, and Cochrane to recognize eligible studies. We included studies investigating the diagnostic accuracy of HBP and reported the necessary data to construct 2 × 2 tables. A univariate analysis was conducted to determine the pooled sensitivity and specificity, and a bivariate diagnostic random-effects model was used to calculate the optimal cut-off point.

RESULTS

The analysis comprised sixteen studies in total. Plasma HBP showed a sensitivity of 0.90 (95% CI: [0.79, 0.96]) and a specificity of 0.87 (95% CI: [0.66, 0.96]) in diagnosing bacterial infections using blood samples. Pooling data from seven studies revealed that HBP in cerebrospinal fluid (CSF) has sensitivity and specificity of 96% (95% CI: [0.85, 0.99]), and 95% (95% CI: [0.89, 0.97]), respectively, for the diagnosis of bacterial meningitis. In urinary tract infections (UTI), urine-HBP was revealed to have a high diagnostic value in discriminating bacterial from non-bacterial UTI infection at a cut-off value of 32.868 ng/ml with sensitivity and specificity of 87%.

CONCLUSION

HBP has shown a high diagnostic accuracy of bacterial infections, including UTI and meningitis. Further studies are needed to determine its prognostic value and whether it could guide antibiotic therapy.

Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis

(1) Background: This meta-analysis assessed the diagnostic accuracy of deep learning model-based osteoporosis prediction using plain X-ray images. (2) Methods: We searched PubMed, Web of Science, SCOPUS, and Google Scholar from no set beginning date to 28 February 2023, for eligible studies that applied deep learning methods for diagnosing osteoporosis using X-ray images. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. The area under the receiver operating characteristic curve (AUROC) was used to quantify the predictive performance. Subgroup, meta-regression, and sensitivity analyses were performed to identify the potential sources of study heterogeneity. (3) Results: Six studies were included; the pooled AUROC, sensitivity, and specificity were 0.88 (95% confidence interval [CI] 0.85-0.91), 0.81 (95% CI 0.78-0.84), and 0.87 (95% CI 0.81-0.92), respectively, indicating good performance. Moderate heterogeneity was observed. Mega-regression and subgroup analyses were not performed due to the limited number of studies included. (4) Conclusion: Deep learning methods effectively extract bone density information from plain radiographs, highlighting their potential for opportunistic screening. Nevertheless, additional prospective multicenter studies involving diverse patient populations are required to confirm the applicability of this novel technique.

Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data

BACKGROUND

Breath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported.

OBJECTIVE

The objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm.

METHODS

We conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard.

RESULTS

We enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84-0.91), the summary specificity was 1.00 (95% CI 0.85-1.00), the AUC was 0.96 (95% CI 0.94-0.98), the pAUC was 0.92 (95% CI 0.89-0.96), and the DOR was 207.62 (95% CI 24.62-924.64).

CONCLUSION

Electronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.

Comparable performance of antigen-detecting rapid test by healthcare worker-collected and self-collected swabs for SARS-CoV-2 diagnostic: A systematic review and meta-analysis

Usage of self-screening tests has become increasingly relevant in public health perspective for early detection of SARS-CoV-2 infection in the transitioning era of the COVID-19 pandemic into an endemic. This study was designed to compare the diagnostic accuracy of self-conducted and health professional-conducted SARS-CoV-2 rapid antigen tests (Ag-RDTs) and whether the sample was taken from anterior nasal or nasal mid-turbinate. Eligible comparative Ag-RDTs accuracy studies were retrieved from electronic databases systematically, in accordance with PRISMA. Selected studies were assessed for risk of bias using QUADAS-2 and QUADAS-C. In total, we selected five out of 1952 studies retrieved using the keywords. The overall sensitivity for the self-collected nasal swab method and healthcare worker-collected nasopharyngeal swab method was 79% (95% CI 68-87; I2  = 62%) and 83% (95% CI 75-89; I2  = 32%), respectively, which was not statistically different (p = 0.499). Nasal mid-turbinate swabs have a significantly higher sensitivity compared to anterior nasal swabs (p < 0.01). Both sampling methods represent high and comparable specificity values of 98% (95% CI 97-99; I2  = 0%) and 99% (95% CI 98-99; I2  = 0%). Positive predictive value (range 90%-99%) and negative predictive value (range 87%-98%) were equivalent for both methods. Our findings indicated the accuracy of self-collected Ag-RDT on nasal swabs was comparable to those performed by healthcare worker-collected on nasopharyngeal swabs. Self-collected Ag-RDT could be considered as a transmission prevention method in the transition of COVID-19 pandemic.

Diagnostic performance of CL Detect rapid-immunochromatographic test for cutaneous leishmaniasis: a systematic review and meta-analysis

BACKGROUND

Sensitive, robust, and fast point-of-care tests are needed for cutaneous leishmaniasis (CL) diagnosis. The recently developed CL Detect rapid test (InBios) for detecting Leishmania peroxidoxin antigen has been evaluated in several studies. However, diagnostic performances were controversial. Therefore, this systematic review and meta-analysis aimed to determine the pooled sensitivity and specificity of CL Detect for CL diagnosis.

METHODS

PubMed, Scopus, EMBASE, ScienceDirect, and Google Scholar were sources of articles. We included studies reporting the diagnostic accuracy of CL Detect and CL-suspected patients in the English language. The methodological qualities of the included studies were appraised using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2). Meta-analysis was conducted using Stata 14.2 and R software.

RESULTS

A total of 9 articles were included. The study sample size ranged from 11 to 274. The sensitivities of the individual studies ranged from 23 to 100%, and the specificities ranged from 78 to 100%. Pooled sensitivity and specificity were 68% (95% CI, 41-86%) and 94% (95% CI, 87-97%), respectively. AUC displayed 0.899. Pooled sensitivity was lower (47%, 95% CI, 34-61%) when PCR was used as a reference than microscopy (83%, 95% CI, 39-97%). Pooled sensitivity was lower (48%, 95% CI, 30-67%) for all lesion durations compared to ≤ 4 months (89%, 95% CI, 43-99%).

CONCLUSIONS

CL Detect has poor sensitivity and does not meet the minimal sensitivity of 95% of target product profiles designed for CL point-of-care tests. Currently, the CL Detect test looks unsuitable for CL diagnosis, despite its high specificity. Findings are limited by the low number of studies available. Further large-scale studies are recommended.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022323497.

Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study

BACKGROUND

This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans.

METHODS

Until May 2023, systematic searches were conducted in ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE for studies that evaluated the diagnostic precision of ML model-assisted ICH detection. Patients with and without ICH as the target condition who were receiving CT-Scan were eligible for the research, which used ML algorithms based on radiologists' reports as the gold reference standard. For meta-analysis, pooled sensitivities, specificities, and a summary receiver operating characteristics curve (SROC) were used.

RESULTS

At last, after screening the title, abstract, and full paper, twenty-six retrospective and three prospective, and two retrospective/prospective studies were included. The overall (Diagnostic Test Accuracy) DTA of retrospective studies with a pooled sensitivity was 0.917 (95% CI 0.88-0.943, I2 = 99%). The pooled specificity was 0.945 (95% CI 0.918-0.964, I2 = 100%). The pooled diagnostic odds ratio (DOR) was 219.47 (95% CI 104.78-459.66, I2 = 100%). These results were significant for the specificity of the different network architecture models (p-value = 0.0289). However, the results for sensitivity (p-value = 0.6417) and DOR (p-value = 0.2187) were not significant. The ResNet algorithm has higher pooled specificity than other algorithms with 0.935 (95% CI 0.854-0.973, I2 = 93%).

CONCLUSION

This meta-analysis on DTA of ML algorithms for detecting ICH by assessing non-contrast CT-Scans shows the ML has an acceptable performance in diagnosing ICH. Using ResNet in ICH detection remains promising prediction was improved via training in an Architecture Learning Network (ALN).

Diagnostic accuracy of whole-body magnetic resonance imaging versus positron emission tomography-computed tomography for the staging of pediatric lymphoma: a systematic review and meta-analysis

BACKGROUND

Whole-body magnetic resonance imaging (MRI) has been investigated by multiple authors as a radiation-free alternative to positron emission tomography computed tomography (PET-CT) in children with lymphoma.

OBJECTIVE

To evaluate the sensitivity, specificity, and diagnostic odds ratio of whole-body MRI compared to PET-CT for the staging of pediatric lymphoma.

METHODS

The databases PubMed, Embase, and Scopus were searched for studies that reported the accuracy of whole-body MRI compared to PET-CT for lymphoma staging in children. Data was collected from included studies to formulate 2 × 2 contingency tables, including the number of true positive, true negative, false positive, and false negative. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated. Summary receiver operating characteristic curves were drawn and the area under the curve (AUC) calculated. In addition, the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) tool was used to assess the risk of bias and applicability concerns.

RESULTS

A total of seven studies were included in the final analysis. Of these, six studies used unenhanced whole-body MRI. The pooled sensitivity of whole-body MRI-based staging was 95.8%, while the pooled specificity was 21.8%. The DOR for whole-body MRI was 1.19. For extranodal staging, the pooled sensitivity was 88.9%, specificity was 97.4%, and DOR was 25.29. The partial AUC for overall staging was 0.63, whereas that for extranodal staging stood at 0.88. Based on the QUADAS 2 tool, all seven studies were at risk of bias (six at high risk, one at unclear risk).

CONCLUSION

Whole-body MRI has high sensitivity for staging of pediatric lymphoma and may be a useful alternative to PET-CT.

The utility of long non-coding RNAs in chronic obstructive pulmonary disease: a comprehensive analysis

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is one of the main causes of morbidity and mortality in the world. However, there are some patients who are not diagnosed early and correctly through routine methods because of inconspicuous or serious symptoms. This study aims to assess the diagnostic role of long non-coding RNA (lncRNA) in COPD.

METHODS

We searched literature from electronic databases, after excluding non-COPD literature, the bibliometric analysis was performed, and VOSviewer software was used to represent the data analyzed. Literature evaluating the diagnostic test accuracy of lncRNA for COPD was eligible, and the QUADAS-2 checklist was used to evaluate the quality. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (sROC) were used to analyze the overall diagnostic performance. Subgroup and meta-regression analyses were performed to explore the heterogeneity, and a funnel plot was assessed for publication bias. Also, lncRNAs related to COPD were identified and explored for their potential biological function.

RESULTS

An increased annual growth rate of literature on this subject from 2016 focused on COPD, humans, RNA, and lncRNA. The meta-analysis enrolled 17 literature indicated that the SEN, SPE, and DOR differentiating COPD patients from normal controls (NCs) were 0.86 (95% CI [0.80, 0.90]), 0.78 (95% CI [0.67, 0.86]), and 21.59 (95% CI [11.39, 40.91]), respectively. Meanwhile, lncRNAs had the ability to distinguish acute exacerbations of COPD (AECOPD) patients from COPD; the SEN, SPE, and DOR were 0.75 (95% CI [0.62, 0.85]), 0.81 (95% CI [0.71, 0.89]), and 13.02 (95% CI [7.76, 21.85]), respectively. The area under the sROC were calculated to be greater than 0.8 at least. Subgroup and meta-regression analysis showed that the types of specimens and dysregulated lncRNAs might affect the diagnostic accuracy. The funnel plot showed there was a certain publication bias. 41 lncRNAs related to COPD were identified and mainly located in the nucleus and cytoplasm, associated with proliferation, invasion, and prognosis. These lncRNA-binding proteins were involved in the spliceosome, Rap1 signaling pathway, MAPK signaling pathway, and so on.

CONCLUSION

LncRNA suggests potential diagnostic biomarkers and therapeutic targets for COPD patients.

Diagnostic accuracy of biomarkers to detect acute mesenteric ischaemia in adult patients: a systematic review and meta-analysis

BACKGROUND

Acute mesenteric ischaemia (AMI) is a disease with different pathophysiological mechanisms, leading to a life-threatening condition that is difficult to diagnose based solely on clinical signs. Despite widely acknowledged need for biomarkers in diagnosis of AMI, a broad systematic review on all studied biomarkers in different types of AMI is currently lacking. The aim of this study was to estimate the diagnostic accuracy of all potential biomarkers of AMI studied in humans.

METHODS

A systematic literature search in PubMed, The Cochrane Library, Web of Science and Scopus was conducted in December 2022. Studies assessing potential biomarkers of AMI in (at least 10) adult patients and reporting their diagnostic accuracy were included. Meta-analyses of biomarkers' sensitivity, specificity, and positive and negative likelihood ratios were conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study quality was assessed with the QUADAS-2 tool.

RESULTS

Seventy-five studies including a total of 9914 patients assessed 18 different biomarkers in serum/plasma and one in urine (each reported in at least two studies), which were included in meta-analyses. None of the biomarkers reached a conclusive level for accurate prediction. The best predictive value overall (all studies with any type and stage of AMI pooled) was observed for Ischaemia-modified albumin (2 studies, sensitivity 94.7 and specificity 90.5), interleukin-6 (n = 4, 96.3 and 82.6), procalcitonin (n = 6, 80.1 and 86.7), and intestinal fatty acid-binding protein (I-FABP) measured in serum (n = 16, 73.9 and 90.5) or in urine (n = 4, 87.9 and 78.9). In assessment of transmural mesenteric ischaemia, urinary I-FABP (n = 2, 92.3 and 85.2) and D-dimer (n = 3, 87.6 and 83.6) showed moderate predictive value. Overall risk of bias was high, mainly because of selected study populations and unclear timings of the biomarker measurements after onset of symptoms. Combinations of biomarkers were rarely studied, not allowing meta-analyses.

CONCLUSIONS

None of the studied biomarkers had sufficient sensitivity and specificity to diagnose AMI, although some biomarkers showed moderate predictive accuracy. Future studies should focus on timing of measurements of biomarkers, distinguishing between early stage and transmural necrosis, and between different types of AMI. Additionally, studies on combinations of biomarkers are warranted. PROSPERO registration: CRD42022379341.

Machine learning algorithms for diagnosis of hip bone osteoporosis: a systematic review and meta-analysis study

BACKGROUND

Osteoporosis is a significant health problem in the skeletal system, associated with bone tissue changes and its strength. Machine Learning (ML), on the other hand, has been accompanied by improvements in recent years and has been in the spotlight. This study is designed to investigate the Diagnostic Test Accuracy (DTA) of ML to detect osteoporosis through the hip dual-energy X-ray absorptiometry (DXA) images.

METHODS

The ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched until June 2023 for studies that tested the diagnostic precision of ML model-assisted for predicting an osteoporosis diagnosis.

RESULTS

The pooled sensitivity of univariate analysis of seven studies was 0.844 (95% CI 0.791 to 0.885, I² = 94% for 7 studies). The pooled specificity of univariate analysis was 0.781 (95% CI 0.732 to 0.824, I² = 98% for 7 studies). The pooled diagnostic odds ratio (DOR) was 18.91 (95% CI 14.22 to 25.14, I² = 93% for 7 studies). The pooled mean positive likelihood ratio (LR⁺) and the negative likelihood ratio (LR^-) were 3.7 and 0.22, respectively. Also, the summary receiver operating characteristics (sROC) of the bivariate model has an AUC of 0.878.

CONCLUSION

Osteoporosis can be diagnosed by ML with acceptable accuracy, and hip fracture prediction was improved via training in an Architecture Learning Network (ALN).

Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis

BACKGROUND

IntraUterine Growth Restriction (IUGR) is a global public health concern and has major implications for neonatal health. The early diagnosis of this condition is crucial for obtaining positive outcomes for the newborn. In recent years Artificial intelligence (AI) and machine learning (ML) techniques are being used to identify risk factors and provide early prediction of IUGR. We performed a systematic review (SR) and meta-analysis (MA) aimed to evaluate the use and performance of AI/ML models in detecting fetuses at risk of IUGR.

METHODS

We conducted a systematic review according to the PRISMA checklist. We searched for studies in all the principal medical databases (MEDLINE, EMBASE, CINAHL, Scopus, Web of Science, and Cochrane). To assess the quality of the studies we used the JBI and CASP tools. We performed a meta-analysis of the diagnostic test accuracy, along with the calculation of the pooled principal measures.

RESULTS

We included 20 studies reporting the use of AI/ML models for the prediction of IUGR. Out of these, 10 studies were used for the quantitative meta-analysis. The most common input variable to predict IUGR was the fetal heart rate variability (n = 8, 40%), followed by the biochemical or biological markers (n = 5, 25%), DNA profiling data (n = 2, 10%), Doppler indices (n = 3, 15%), MRI data (n = 1, 5%), and physiological, clinical, or socioeconomic data (n = 1, 5%). Overall, we found that AI/ML techniques could be effective in predicting and identifying fetuses at risk for IUGR during pregnancy with the following pooled overall diagnostic performance: sensitivity = 0.84 (95% CI 0.80-0.88), specificity = 0.87 (95% CI 0.83-0.90), positive predictive value = 0.78 (95% CI 0.68-0.86), negative predictive value = 0.91 (95% CI 0.86-0.94) and diagnostic odds ratio = 30.97 (95% CI 19.34-49.59). In detail, the RF-SVM (Random Forest-Support Vector Machine) model (with 97% accuracy) showed the best results in predicting IUGR from FHR parameters derived from CTG.

CONCLUSIONS

our findings showed that AI/ML could be part of a more accurate and cost-effective screening method for IUGR and be of help in optimizing pregnancy outcomes. However, before the introduction into clinical daily practice, an appropriate algorithmic improvement and refinement is needed, and the importance of quality assessment and uniform diagnostic criteria should be further emphasized.

A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19

In this paper, we present a systematic review and meta-analysis that aims to evaluate the reliability of coronavirus disease diagnostic tests in 2019 (COVID-19). This article seeks to describe the scientific discoveries made because of diagnostic tests conducted in recent years during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Between 2020 and 2021, searches for published papers on the COVID-19 diagnostic were made in the PubMed database. Ninety-nine scientific articles that satisfied the requirements were analyzed and included in the meta-analysis, and the specificity and sensitivity of the diagnostic accuracy were assessed. When compared to serological tests such as the enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (CLIA), lateral flow immunoassay (LFIA), and chemiluminescent microparticle immunoassay (CMIA), molecular tests such as reverse transcription polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) performed better in terms of sensitivity and specificity. Additionally, the area under the curve restricted to the false-positive rates (AUC_FPR) of 0.984 obtained by the antiviral neutralization bioassay (ANB) diagnostic test revealed significant potential for the identification of COVID-19. It has been established that the various diagnostic tests have been effectively adapted for the detection of SARS-CoV-2; nevertheless, their performance still must be enhanced to contain potential COVID-19 outbreaks, which will also help contain potential infectious agent outbreaks in the future.

Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: a systematic review and meta-analysis

BACKGROUND

Point-of-care (POC) lung ultrasound (LUS) is widely used in the emergency setting and there is an established evidence base across a range of respiratory diseases, including previous viral epidemics. The necessity for rapid testing combined with the limitations of other diagnostic tests has led to the proposal of various potential roles for LUS during the COVID-19 pandemic. This systematic review and meta-analysis focused specifically on the diagnostic accuracy of LUS in adult patients presenting with suspected COVID-19 infection.

METHODS

Traditional and grey-literature searches were performed on 1 June 2021. Two authors independently carried out the searches, selected studies and completed the Quality Assessment Tool for Diagnostic Test Accuracy Studies (QUADAS-2). Meta-analysis was carried out using established open-source packages in R. We report overall sensitivity, specificity, positive and negative predictive values, and the hierarchical summary receiver operating characteristic curve for LUS. Heterogeneity was determined using the I² statistic.

RESULTS

Twenty studies were included, published between October 2020 and April 2021, providing data from a total of 4314 patients. The prevalence and admission rates were generally high across all studies. Overall, LUS was found to be 87.2% sensitive (95% CI 83.6 to 90.2) and 69.5% specific (95% CI 62.2 to 72.5) and demonstrated overall positive and negative likelihood ratios of 3.0 (95% CI 2.3 to 4.1) and 0.16 (95% CI 0.12 to 0.22), respectively. Separate analyses for each reference standard revealed similar sensitivities and specificities for LUS. Heterogeneity was found to be high across the studies. Overall, the quality of studies was low with a high risk of selection bias due to convenience sampling. There were also applicability concerns because all studies were undertaken during a period of high prevalence.

CONCLUSION

During a period of high prevalence, LUS had a sensitivity of 87% for the diagnosis of COVID-19 infection. However, more research is required to confirm these results in more generalisable populations, including those less likely to be admitted to hospital.

PROSPERO REGISTRATION NUMBER

CRD42021250464.

Influence of seasonal and operator variations on diagnostic accuracy of lateral flow devices during the COVID-19 pandemic: a systematic review and meta-analysis

BACKGROUND

Lateral flow tests (LFT) are point-of-care rapid antigen tests that allow isolation and control of disease outbreaks through convenient, practical testing. However, studies have shown significant variation in their diagnostic accuracy. We conducted a systematic review of the diagnostic accuracy of LFTs for the detection of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) to identify potential factors affecting their performance.

METHODS

A systematic search of online databases was carried out to identify studies assessing the sensitivity and specificity of LFTs compared with polymerase chain reaction (PCR) tests. Data were extracted and used to calculate pooled sensitivity and specificity. Meta-regression analysis was conducted to identify covariates influencing diagnostic accuracy.

RESULTS

In total, 76 articles with 108,820 test results were identified for analysis. Pooled sensitivity and specificity were 72% (95% confidence interval (CI): 0.68-0.76) and 100% (95% CI: 0.99-1.00), respectively. Staff operation of the LFT showed a statistically significant increase in sensitivity (p=0.04) and specificity (p=0.001) compared with self-operation by the test subjects. The use of LFTs in symptomatic patient subgroups also resulted in higher test sensitivity.

CONCLUSION

LFTs display good sensitivity and extremely good specificity for SARS-CoV-2 antigen detection; they become more sensitive in patients with symptoms and when performed by trained professionals.

CA125 for the Diagnosis of Advanced Urothelial Carcinoma of the Bladder: A Systematic Review and Meta-Analysis

BACKGROUND

Urothelial carcinoma of the bladder (UCB) is the second most common genitourinary cancer. This study aims to assess the diagnostic accuracy of CA125 in advanced UCB.

METHODS

We searched prevalent studies in PubMed, the Cochrane Library, Scopus, Embase, the Web of Science China National Knowledge Infrastructure database, and Wanfang data before October 2022. Pooled sensitivity, specificity, and summary receiver operating characteristics were used to assess the diagnostic value of CA125.

RESULTS

One thousand six hundred forty-one patients from 14 studies were analyzed. UCB stage T3-4N1 was defined as advanced UCB in ten studies; T2-4 was used in three studies; and N1M1 in one study. Patients' age was between 21 to 92, and 21% to 48.6% of patients were female. The pooled sensitivity was 0.695 (95% confidence interval (CI): 0.426-0.875). The pooled specificity was 0.846 (95% CI: 0.713-0.924). The diagnostic odds ratio was 8.138 (95% CI: 4.559-14.526). The AUC was 0.797.

CONCLUSION

CA125 may provide significant diagnostic accuracy in identifying muscle-invasive, lymph node-involved, and distant metastatic tumors in patients with urothelial carcinoma of the bladder. Limited studies have been conducted on the prognostic role of CA125. More studies are needed for a meta-analysis on the prognostic role of CA125 in UCB.

Clinical value of alarm features for colorectal cancer: a meta-analysis

BACKGROUND

Colorectal cancer (CRC) is a common neoplasm in Western countries. Prioritizing access to colonoscopy appears of critical relevance. Alarm features are considered to increase the likelihood of CRC. Our aim was to assess the diagnostic performance of alarm features for CRC diagnosis.

METHODS

We performed a systematic review and meta-analysis of studies reporting the diagnostic accuracy of alarm features (rectal bleeding, anemia, change in bowel habit, and weight loss) for CRC, published up to September 2021. Colonoscopy was required as the reference diagnostic test. Diagnostic accuracy measures were pooled by a bivariate mixed-effects regression model. The number needed to scope (NNS; i. e. the number of patients who need to undergo colonoscopy to diagnose one CRC) according to each alarm feature was calculated.

RESULTS

31 studies with 45 100 patients (mean age 31-88 years; men 36 %-63 %) were included. The prevalence of CRC ranged from 0.2 % to 22 %. Sensitivity was suboptimal, ranging from 12.4 % for weight loss to 49 % for rectal bleeding, whereas specificity ranged from 69.8 % for rectal bleeding to 91.9 % for weight loss. Taken individually, rectal bleeding and anemia would be the only practical alarm features mandating colonoscopy (NNS 5.3 and 6.7, respectively).

CONCLUSIONS

When considered independently, alarm features have variable accuracy for CRC, given the high heterogeneity of study populations reflected by wide variability in CRC prevalence. Rectal bleeding and anemia are the most practical to select patients for colonoscopy. Integration of alarm features in a comprehensive evaluation of patients should be considered.

Identifying the culprit artery via 12-lead electrocardiogram in inferior wall ST-segment elevation myocardial infarction: A meta-analysis

BACKGROUND

Inferior wall ST-segment elevation myocardial infarction (STEMI) is mostly caused by acute occlusion of right coronary artery (RCA) and left circumflex artery (LCX). Several methods and algorithms using 12-lead ECG were developed to localize the lesion in inferior wall STEMI. However, the diagnostic properties of these methods remain under-recognized.

AIMS

The aim of this meta-analysis is to compare the diagnostic properties among the methods of identifying culprit artery in inferior wall STEMI using 12-lead ECG.

METHODS

We performed a meta-analysis to calculate the pooled sensitive, specificity, area under the curve (AUC) and diagnostic odds ratio (DOR) of each method.

RESULTS

Thirty-three studies with 4414 participants were included in the analysis. Methods using double leads had better diagnostic properties, especially ST-segment elevation (STE) in III > II [with pooled sensitivity 0.89 (0.84-0.93), specificity 0.68 (0.57-0.79), DOR 17 (9-32), AUC 0.88 (0.85-0.91)], ST-segment depression (STD) in aVL > I [with pooled sensitivity 0.82 (0.72-0.90), specificity 0.69 (0.48-0.86), DOR 11 (4-29), AUC 0.85 (0.81-0.88)], and STD V3/STE III ≤1.2 [with pooled sensitivity 0.88 (0.78-0.95), specificity 0.59 (0.42-0.75), DOR 12 (5-27), AUC 0.82 (0.78-0.85)]. Diagnostic algorithms, including Jim score[pooled sensitivity 0.70 (0.55-0.85), specificity 0.88 (0.75-0.96)], Fiol's algorithm [pooled sensitivity 0.54 (0.44-0.62), specificity 0.92 (0.88-0.96)] and Tierala's algorithm [pooled sensitivity 0.60 (0.49-0.71), specificity 0.91 (0.86-0.96)], were not superior to these simple methods.

CONCLUSIONS

Our meta-analysis indicated that diagnostic methods using double leads had better properties. STE in III > II together with STD in aVL > I may be the most ideal method, for its accuracy and convenience.

Performance of screening tools for cervical neoplasia among women in low- and middle-income countries: A systematic review and meta-analysis

OBJECTIVE

To evaluate the performance of visual inspection with acetic acid (VIA) testing, visual inspection with Lugol's iodine (VILI), primary HPV testing, and conventional Pap smear in detecting CIN2+ among non-pregnant women aged 30-65 in LMICs between 1990 and 2020.

DESIGN

Systematic review and meta-analysis.

SETTING AND PARTICIPANTS

Low- and middle-income countries, non-pregnant women aged 30-65.

METHODS

CENTRAL (Cochrane Library), CINAHL, Embase, Global Health, PubMed, and Web of Science databases were systematically searched to identify studies evaluating the performance of cervical cancer screening methods in LMICs. A diagnostic test accuracy meta-analysis was conducted to evaluate the performance of 4 screening methods in detecting CIN2+ relative to biopsy or cytology reference standards. Pooled statistics for sensitivity, specificity, diagnostic odds ratios, and summary receiver operating characteristic curves were determined for each method. Subgroup analyses were performed to examine whether there was variation in performance based on different reference standards for defining CIN2+, specifically: colposcopy-directed biopsy, biopsy alone, colposcopy alone, or liquid-based cytology.

RESULTS

Eighteen studies were identified through systematic review. Twelve studies were included in meta-analysis; 11 were cross-sectional and 1 was a randomized controlled clinical trial. The remaining six of the eighteen studies were inclided in a narrative syntehsis. Pooled estimates for sensitivity for VIA, VILI, primary HPV testing, and conventional Pap smear were 72.3%, 64.5%, 79.5%, and 60.2%, respectively; pooled estimates for specificity were 74.5%, 68.5%, 72.6%, and 97.4%, respectively; the diagnostic odds ratios were 7.31, 3.73, 10.42, 69.48, respectively; and the area under the summary receiver operating characteristic curves were 0.766, 0.647, 0.959, and 0.818, respectively. Performance of the screening method varied based on the reference standard used; pooled estimates using either colposcopy-directed biopsy or biopsy alone as the reference standard generally reported lower estimates; pooled estimates using either colposcopy alone or liquid-based cytology as references reported higher estimates.

CONCLUSIONS AND IMPLICATIONS

This meta-analysis found primary HPV testing to be the highest performing cervical cancer screening method in accurately identifying or excluding CIN2+. Further evaluation of performance at different CIN thresholds is warranted.

The Diagnostic Power of Circulating miR-1246 in Screening Cancer: An Updated Meta-analysis

Background

MicroRNA-1246 (miR-1246), an oncomiR that regulates the expression of multiple cancer-related genes, has been attracted and studied as a promising indicator of various tumors. However, diverse conclusions on diagnostic accuracy have been shown due to the small sample size and limited studies included. This meta-analysis is aimed at systematically assessing the performance of extracellular circulating miR-1246 in screening common cancers.

Methods

We searched the PubMed/MEDLINE, Web of Science, Cochrane Library, and Google Scholar databases for relevant studies until November 28, 2022. Then, the summary receiver operating characteristic (SROC) curves were drawn and calculated area under the curve (AUC), diagnostic odds ratio (DOR), sensitivity, and specificity values of circulating miR-1246 in the cancer surveillance.

Results

After selection and quality assessment, 29 eligible studies with 5914 samples (3232 cases and 2682 controls) enrolled in the final analysis. The pooled AUC, DOR, sensitivity, and specificity of circulating miR-1246 in screening cancers were 0.885 (95% confidence interval (CI): 0.827-0.892), 27.7 (95% CI: 17.1-45.0), 84.2% (95% CI: 79.4-88.1), and 85.3% (95% CI: 80.5-89.2), respectively. Among cancer types, superior performance was noted for breast cancer (AUC = 0.950, DOR = 98.5) compared to colorectal cancer (AUC = 0.905, DOR = 47.6), esophageal squamous cell carcinoma (AUC = 0.757, DOR = 8.0), hepatocellular carcinoma (AUC = 0.872, DOR = 18.6), pancreatic cancer (AUC = 0.767, DOR = 12.3), and others (AUC = 0.887, DOR = 27.5, P = 0.007). No significant publication bias in DOR was observed in the meta-analysis (funnel plot asymmetry test with P = 0.652; skewness value = 0.672, P = 0.071).

Conclusion

Extracellular circulating miR-1246 may serve as a reliable biomarker with good sensitivity and specificity in screening cancers, especially breast cancer.

Virotyping and genetic antimicrobial susceptibility testing of porcine ETEC/STEC strains and associated plasmid types

Introduction

Enterotoxigenic Escherichia coli (ETEC) infections are the most common cause of secretory diarrhea in suckling and post-weaning piglets. For the latter, Shiga toxin-producing Escherichia coli (STEC) also cause edema disease. This pathogen leads to significant economic losses. ETEC/STEC strains can be distinguished from general E. coli by the presence of different host colonization factors (e.g., F4 and F18 fimbriae) and various toxins (e.g., LT, Stx2e, STa, STb, EAST-1). Increased resistance against a wide variety of antimicrobial drugs, such as paromomycin, trimethoprim, and tetracyclines, has been observed. Nowadays, diagnosing an ETEC/STEC infection requires culture-dependent antimicrobial susceptibility testing (AST) and multiplex PCRs, which are costly and time-consuming.

Methods

Here, nanopore sequencing was used on 94 field isolates to assess the predictive power, using the meta R package to determine sensitivity and specificity and associated credibility intervals of genotypes associated with virulence and AMR.

Results

Genetic markers associated with resistance for amoxicillin (plasmid-encoded TEM genes), cephalosporins (ampC promoter mutations), colistin (mcr genes), aminoglycosides (aac(3) and aph(3) genes), florfenicol (floR), tetracyclines (tet genes), and trimethoprim-sulfa (dfrA genes) could explain most acquired resistance phenotypes. Most of the genes were plasmid-encoded, of which some collocated on a multi-resistance plasmid (12 genes against 4 antimicrobial classes). For fluoroquinolones, AMR was addressed by point mutations within the ParC and GyrA proteins and the qnrS1 gene. In addition, long-read data allowed to study the genetic landscape of virulence- and AMR-carrying plasmids, highlighting a complex interplay of multi-replicon plasmids with varying host ranges.

Conclusion

Our results showed promising sensitivity and specificity for the detection of all common virulence factors and most resistance genotypes. The use of the identified genetic hallmarks will contribute to the simultaneous identification, pathotyping, and genetic AST within a single diagnostic test. This will revolutionize future quicker and more cost-efficient (meta)genomics-driven diagnostics in veterinary medicine and contribute to epidemiological studies, monitoring, tailored vaccination, and management.

Assessment of the accuracy of 11 different diagnostic tests for the detection of Schistosomiasis mansoni in individuals from a Brazilian area of low endemicity using latent class analysis

Background

Schistosomiasis is a parasitic disease associated with poverty. It is estimated that 7.1 million people are infected with Schistosoma mansoni in Latin America, with 95% of them living in Brazil. Accurate diagnosis and timely treatment are important measures to control and eliminate schistosomiasis, but diagnostic improvements are needed to detect infections, especially in areas of low endemicity.

Methodology

This research aimed to evaluate the performance of 11 diagnostic tests using latent class analysis (LCA). A cross-sectional survey was undertaken in a low endemicity area of the municipality of Malacacheta, Minas Gerais, Brazil. Feces, urine, and blood samples were collected from 400 residents older than 6 years of age, who had not been treated with praziquantel in the 12 months previous to the collection of their samples. The collected samples were examined using parasitological (Helm Test® kit Kato-Katz), nucleic acid amplification tests -NAATs (PCR, qPCR and LAMP on urine; PCR-ELISA, qPCR and LAMP on stool), and immunological (POC-CCA, the commercial anti-Schistosoma mansoni IgG ELISA kit from Euroimmun, and two in-house ELISA assays using either the recombinant antigen PPE or the synthetic peptide Smp150390.1) tests.

Results

The positivity rate of the 11 tests evaluated ranged from 5% (qPCR on urine) to 40.8% (commercial ELISA kit). The estimated prevalence of schistosomiasis was 12% (95% CI: 9-15%) according to the LCA. Among all tests assessed, the commercial ELISA kit had the highest estimated sensitivity (100%), while the Kato-Katz had the highest estimated specificity (99%). Based on the accuracy measures observed, we proposed three 2-step diagnostic approaches for the active search of infected people in endemic settings. The approaches proposed consist of combinations of commercial ELISA kit and NAATs tests performed on stool. All the approaches had higher sensitivity and specificity than the mean values observed for the 11 tests (70.4 and 89.5%, respectively).

Conclusion

We showed that it is possible to achieve high specificity and sensitivity rates with lower costs by combining serological and NAATs tests, which would assist in the decision-making process for appropriate allocation of public funding aiming to achieve the WHO target of eliminating schistosomiasis as a public health problem by 2030.

Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis

BACKGROUND

Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response.

METHODS

A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy.

RESULTS

Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis.

CONCLUSION

A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.

Accuracy of Diagnostic Tests for the Detection of Chagas Disease: A Systematic Review and Meta-Analysis

The present systematic review and meta-analysis about the accuracy of diagnostic tests aim to describe the findings of literature over the last thirty years for the diagnosis of Chagas disease (CD). This work aimed to determine the accuracy of diagnostic techniques for CD in the disease's acute and chronic phases. The PubMed database was searched for studies published between 1990 and 2021 on CD diagnostics. Fifty-six published studies that met the criteria were analyzed and included in the meta-analysis, evaluating diagnostic accuracy through sensitivity and specificity. For Enzyme-Linked Immunosorbent Assay (ELISA), Fluorescent Antibody Technique (IFAT), Hemagglutination Test (HmT), Polymerase Chain Reaction (PCR), and Real-Time Polymerase Chain Reaction (qPCR) diagnosis methods, the sensitivity had a median of 99.0%, 78.0%, 75.0%, 76.0%, and 94.0%, respectively; while specificity presented a median of 99.0%, 99.0%, 99.0%, 98.0%, and 98.0%, respectively. This meta-analysis showed that ELISA and qPCR techniques had a higher performance compared to other methods of diagnosing CD in the chronic and acute phases, respectively. It was concluded utilizing the Area Under the Curve restricted to the false positive rates (AUCFPR), that the ELISA diagnostic test presents the highest performance in diagnosing acute and chronic CD, compared to serological and molecular tests. Future studies focusing on new CD diagnostics approaches should be targeted.

Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis

Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72-0.92), 85% (95% CI, 0.75-0.91), and 24.17 (95% CI: 7.85-74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results.

Growth Differentiation Factor-15 as a candidate biomarker in gynecologic malignancies: A meta-analysis

Growth Differentiation Factor-15 (GDF-15), though emerged as a novel marker in gynecological cancers, is yet to be recognized in clinical diagnostics. Eligible studies were sorted from multiple online databases, namely PubMed, Cochrane, ClinicalTrials.gov, Google Scholar, Web of Science, Embase, Scopus, LILACS, Opengrey. From six studies, histopathologically diagnosed cases without prior treatment, and with diagnostic accuracy data for GDF-15 in gynecological cancers, were included. Our meta-analysis shows that GDF-15 has pooled diagnostic odds ratio of 12.74 at 80.5% sensitivity and 74.1% specificity, and an AUC of 0.84. Hence, GDF-15 is a potential marker to differentiate gynecological malignancy from non-malignant tumors.

Meta-analysis of diagnostic test accuracy studies with multiple thresholds for data integration

OBJECTIVES

The objective of this study is to introduce methods to use all of the information without omission when individual studies provide multiple effect sizes according to multiple cut-off values (thresholds) during diagnostic test accuracy (DTA) for data integration. For diagnostic test meta-analysis, a general performance method for synthesizing data according to one cut value in one study and a performance method for synthesizing data according to two or more cut values in one study were compared and analyzed.

METHODS

As sample data for meta-analysis of DTA studies, 13 DTA studies on prostate cancer (34 effect sizes including total cut-offs) were collected. The summary statistics were calculated and the summary line was analyzed using the "meta", "mada", and "diagmeta" packagesof the R software.

RESULTS

The summary statistics of the random effect model univariate analysis of the "meta" package with a single cut-off corresponding to the highest Youden index in a single study and those of the bivariate analysis of the "mada" package were highly similar. However, in the bivariate analysis of the "diagmeta" package including all cut-off values, the sensitivity decreased and the specificity increased as the amount of data increased.

CONCLUSIONS

Considering the heterogeneity of the summary receiver op erating characteristic curve and the use of all given cut-offs, the use of the bivariate analysis model of the "diagmeta" package is recommended. This study focused on practical methods of DTA rather than theoretical concepts for use by researchers whose fields of study are non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.

Structured data vs. unstructured data in machine learning prediction models for suicidal behaviors: A systematic review and meta-analysis

Suicide remains a leading cause of preventable death worldwide, despite advances in research and decreases in mental health stigma through government health campaigns. Machine learning (ML), a type of artificial intelligence (AI), is the use of algorithms to simulate and imitate human cognition. Given the lack of improvement in clinician-based suicide prediction over time, advancements in technology have allowed for novel approaches to predicting suicide risk. This systematic review and meta-analysis aimed to synthesize current research regarding data sources in ML prediction of suicide risk, incorporating and comparing outcomes between structured data (human interpretable such as psychometric instruments) and unstructured data (only machine interpretable such as electronic health records). Online databases and gray literature were searched for studies relating to ML and suicide risk prediction. There were 31 eligible studies. The outcome for all studies combined was AUC = 0.860, structured data showed AUC = 0.873, and unstructured data was calculated at AUC = 0.866. There was substantial heterogeneity between the studies, the sources of which were unable to be defined. The studies showed good accuracy levels in the prediction of suicide risk behavior overall. Structured data and unstructured data also showed similar outcome accuracy according to meta-analysis, despite different volumes and types of input data.

Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis

BACKGROUND

Machine-learning approaches have enabled promising results in efforts to simplify the diagnosis of pediatric obstructive sleep apnea (OSA). A comprehensive review and analysis of such studies increase the confidence level of practitioners and healthcare providers in the implementation of these methodologies in clinical practice.

OBJECTIVE

To assess the reliability of machine-learning-based methods to detect pediatric OSA.

DATA SOURCES

Two researchers conducted an electronic search on the Web of Science and Scopus using term, and studies were reviewed along with their bibliographic references.

ELIGIBILITY CRITERIA

Articles or reviews (Year 2000 onwards) that applied machine learning to detect pediatric OSA; reported data included information enabling derivation of true positive, false negative, true negative, and false positive cases; polysomnography served as diagnostic standard.

APPRAISAL AND SYNTHESIS METHODS

Pooled sensitivities and specificities were computed for three apnea-hypopnea index (AHI) thresholds: 1 event/hour (e/h), 5 e/h, and 10 e/h. Random-effect models were assumed. Summary receiver-operating characteristics (SROC) analyses were also conducted. Heterogeneity (I ² ) was evaluated, and publication bias was corrected (trim and fill).

RESULTS

Nineteen studies were finally retained, involving 4767 different pediatric sleep studies. Machine learning improved diagnostic performance as OSA severity criteria increased reaching optimal values for AHI = 10 e/h (0.652 sensitivity; 0.931 specificity; and 0.940 area under the SROC curve). Publication bias correction had minor effect on summary statistics, but high heterogeneity was observed among the studies.

Prospective study of Na[18F]F PET/CT for cancer staging in morbidly obese patients compared with [99mTc]Tc-MDP whole-body planar, SPECT and SPECT/CT

PURPOSE

This prospective study aims to assess the diagnostic test characteristics of Na[¹⁸F]F PET/CT for the skeletal staging of cancer in morbidly obese patients compared with ^99mTc-methylene diphosphonate (MDP), whole-body planar (WBS), SPECT, and SPECT/CT acquisitions.

MATERIAL AND METHODS

One hundred seventeen obese patients (BMI 46.5 ± 6.1 kg/m² and mean age, 59.0 years; range 32-89 years) with BMI > 40 kg/m² were prospectively enrolled and underwent [^99mTc]Tc-MDP WBS, SPECT, SPECT/CT, and Na[¹⁸F]F PET/CT within two weeks for the osseous staging of a malignancy. Images were assessed qualitatively using a 3-point scale. Patient and lesion-based diagnostic test characteristics were estimated using an optimistic and pessimistic dichotomization method.

RESULTS

Bone metastases were confirmed in 44 patients. Patient-based optimistic diagnostic test characteristics were (sensitivity, specificity, overall accuracy): Na[¹⁸F]F PET/CT (95.5%, 95.9%, 95.7%), [^99mTc]Tc-MDP WBS (52.3%, 71.2%, 64.1%), SPECT (61.4%, 80.8%, 73.5%) and SPECT/CT (65.9%, 91.8%, 82.1%). Lesion-based optimistic diagnostic test characteristics were: Na[¹⁸F]F PET/CT (97.7%, 97.9%, 97.7%), [^99mTc]Tc-MDP WBS (39%, 67%, 48.9%), SPECT (52.9%, 93.6%, 67.3%) and SPECT/CT (65.9%, 91.8%, 82.1%). There was no significant difference in the specificity of Na[¹⁸F]F and SPECT/CT. All other pairwise comparisons were significant (p<.001). ROC curve analysis showed a high overall accuracy of Na[¹⁸F]F with significantly higher AUCs for Na[¹⁸F]F PET/CT compared to [^99mTc]Tc-MDP WBS, SPECT, and SPECT/CT on both patient and lesion-based analysis (p<.001). Moreover, Na[¹⁸F]F PET/CT changed patient management in 38% of patients.

CONCLUSIONS

Na[¹⁸F]F PET/CT may be the preferred imaging modality for skeletal staging in morbidly obese patients. The technique provides excellent diagnostic test characteristics superior to [^99mTc]Tc-MDP bone scan (including SPECT/CT), impacts patient management, has an acceptable radiation exposure profile, and is well-tolerated. Further cost-effectiveness evaluations are warranted.

Association of No Evidence of Disease Activity With No Long-term Disability Progression in Multiple Sclerosis: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

We conducted a systematic review and meta-analysis to evaluate the relationship between no evidence of disease activity (NEDA) and no long-term disability progression on low- and high-efficacy therapy in relapsing-remitting multiple sclerosis (RRMS).

METHODS

MEDLINE, Embase, and the Cochrane Database were searched from January 1, 2006, to January 26, 2021. We selected studies that evaluated NEDA-3 (no relapse, new MRI lesion, or confirmed disability progression) at 1 or 2 years and had a minimum of 4 years of follow-up for determination of disability progression. Data were extracted by 2 independent reviewers and were meta-analyzed with a random-effects model. Primary outcome of no disability progression was defined as no confirmed progression on the Expanded Disability Status Scale during follow-up. We assessed the odds ratio (OR) for no disability progression with NEDA vs evidence of disease activity (EDA). Positive predictive value (PPV) of NEDA for no disability progression was summarized for studies with prevalence of no progression >80% vs ≤80% separately.

RESULTS

We included 29 studies in our qualitative synthesis, of which 27 (16 low efficacy, 11 high efficacy) were included in the meta-analysis (N = 10,935 participants). Median follow-up was 5.6 years (interquartile range 4.3-8.0 years). The pooled ORs for no progression with NEDA-3 vs EDA were 2.32 (95% CI 1.58-3.42; I 2 = 73%) for low-efficacy therapy and 3.19 (95% CI 1.86-5.47; I 2 = 86%) for high-efficacy therapy. Among studies with prevalence of no progression at follow-up >80%, the pooled PPV for low efficacy therapy was 91% (95% CI 89%-93%) and for high-efficacy therapy was 92% (95% CI 88%-94%). Among studies with prevalence of no progression ≤80%, the pooled PPV for low-efficacy therapy was 81% (95% CI 75%-86%) and for high-efficacy therapy was 86% (95% CI 80%-90%).

DISCUSSION

NEDA-3 is associated with no long-term disability progression in RRMS on both low- and high-efficacy therapies. Further studies of early composite outcome measures incorporating easily measurable biomarkers and longer follow-up may help to improve the prognostic value of NEDA-3 in RRMS.

TRIAL REGISTRATION INFORMATION

International Prospective Register of Systematic Reviews Identifier: CRD42020189316.

Diagnostic Accuracy of Machine Learning Models on Mammography in Breast Cancer Classification: A Meta-Analysis

In this meta-analysis, we aimed to estimate the diagnostic accuracy of machine learning models on digital mammograms and tomosynthesis in breast cancer classification and to assess the factors affecting its diagnostic accuracy. We searched for related studies in Web of Science, Scopus, PubMed, Google Scholar and Embase. The studies were screened in two stages to exclude the unrelated studies and duplicates. Finally, 36 studies containing 68 machine learning models were included in this meta-analysis. The area under the curve (AUC), hierarchical summary receiver operating characteristics (HSROC) curve, pooled sensitivity and pooled specificity were estimated using a bivariate Reitsma model. Overall AUC, pooled sensitivity and pooled specificity were 0.90 (95% CI: 0.85–0.90), 0.83 (95% CI: 0.78–0.87) and 0.84 (95% CI: 0.81–0.87), respectively. Additionally, the three significant covariates identified in this study were country (p = 0.003), source (p = 0.002) and classifier (p = 0.016). The type of data covariate was not statistically significant (p = 0.121). Additionally, Deeks’ linear regression test indicated that there exists a publication bias in the included studies (p = 0.002). Thus, the results should be interpreted with caution.

Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis

(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791–0.914) and 0.879 (95% CrI, 0.784–0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960–0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.

Clinical Validity of 16α-[18F]Fluoro-17β-Estradiol Positron Emission Tomography/Computed Tomography to Assess Estrogen Receptor Status in Newly Diagnosed Metastatic Breast Cancer

PURPOSE

Determining the estrogen receptor (ER) status is essential in metastatic breast cancer (MBC) management. Whole-body ER imaging with 16α-[¹⁸F]fluoro-17β-estradiol positron emission tomography ([¹⁸F]FES-PET) is increasingly used for this purpose. To establish the clinical validity of the [¹⁸F]FES-PET, we studied the diagnostic accuracy of qualitative and quantitative [¹⁸F]FES-PET assessment to predict ER expression by immunohistochemistry in a metastasis.

METHODS

In a prospective multicenter trial, 200 patients with newly diagnosed MBC underwent extensive workup including molecular imaging. For this subanalysis, ER expression in the biopsied metastasis was related to qualitative whole-body [¹⁸F]FES-PET evaluation and quantitative [¹⁸F]FES uptake in the corresponding metastasis. A review and meta-analysis regarding [¹⁸F]FES-PET diagnostic performance were performed.

RESULTS

Whole-body [¹⁸F]FES-PET assessment predicted ER expression in the biopsied metastasis with good accuracy: a sensitivity of 95% (95% CI, 89 to 97), a specificity of 80% (66 to 89), a positive predictive value (PPV) of 93% (87 to 96), and a negative predictive value (NPV) of 85% (72 to 92) in 181 of 200 evaluable patients. Quantitative [¹⁸F]FES uptake predicted ER immunohistochemistry in the corresponding metastasis with a sensitivity/specificity of 91%/69% and a PPV/NPV of 90%/71% in 156 of 200 evaluable patients. For bone metastases, PPV/NPV was 92%/81%. Meta-analysis with addition of our data has increased diagnostic performance and narrowed the 95% CIs compared with previous studies with a sensitivity/specificity of both 86% (81 to 90 and 73 to 93, respectively).

CONCLUSION

In this largest prospective series so far, we established the clinical validity of [¹⁸F]FES-PET to determine tumor ER status in MBC. In view of the high diagnostic accuracy of qualitatively assessed whole-body [¹⁸F]FES-PET, this noninvasive imaging modality can be considered a valid alternative to a biopsy of a metastasis to determine ER status in newly MBC (ClinicalTrials.gov identifier: NCT01957332).

Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach

BACKGROUND

Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers.

METHODS

Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were estimated using the bivariate model.

RESULTS

The pooled sensitivity specificity, LR+ and LR- and AUC at 95% confidence interval are 86.7% (80.3-91.2), 87.0% (79.9-91.8), 6.28 (4.40-8.96), 0.17 (0.12-0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6-95.7), 71.3% (47.5-87.2), 2.71 (1.39-5.29), 0.20 (0.04-1.05), and 0.831 are the pooled sensitivity specificity, LR+ and LR- and AUC for the five studies in the CBBCT arm, respectively.

CONCLUSIONS

Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application.

Prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome: a systematic review and meta-analysis

OBJECTIVE

To review, inventory and compare available diagnostic tools and investigate which tool has the best performance for prehospital risk assessment in patients suspected of non-ST-segment elevation acute coronary syndrome (NSTE-ACS).

METHODS

Systematic review and meta-analysis. Medline and Embase were searched up till 1 April 2021. Prospective studies with patients, suspected of NSTE-ACS, presenting in the primary care setting or by emergency medical services (EMS) were included. The most important exclusion criteria were studies including only patients with ST-elevation myocardial infarction and studies before 1995, the pretroponin era. The primary end point was the final hospital discharge diagnosis of NSTE-ACS or major adverse cardiac events (MACE) within 6 weeks. Risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies Criteria.

MAIN OUTCOME AND MEASURES

Sensitivity, specificity and likelihood ratio of findings for risk stratification in patients suspected of NSTE-ACS.

RESULTS

In total, 15 prospective studies were included; these studies reflected in total 26 083 patients. No specific variables related to symptoms, physical examination or risk factors were useful in risk stratification for NSTE-ACS diagnosis. The most useful electrocardiographic finding was ST-segment depression (LR+3.85 (95% CI 2.58 to 5.76)). Point-of-care troponin was found to be a strong predictor for NSTE-ACS in primary care (LR+14.16 (95% CI 4.28 to 46.90) and EMS setting (LR+6.16 (95% CI 5.02 to 7.57)). Combined risk scores were the best for risk assessment in an NSTE-ACS. From the combined risk scores that can be used immediately in a prehospital setting, the PreHEART score, a validated combined risk score for prehospital use, derived from the HEART score (History, ECG, Age, Risk factors, Troponin), was most useful for risk stratification in patients with NSTE-ACS (LR+8.19 (95% CI 5.47 to 12.26)) and for identifying patients without ACS (LR-0.05 (95% CI 0.02 to 0.15)).

DISCUSSION

Important study limitations were verification bias and heterogeneity between studies. In the prehospital setting, several diagnostic tools have been reported which could improve risk stratification, triage and early treatment in patients suspected for NSTE-ACS. On-site assessment of troponin and combined risk scores derived from the HEART score are strong predictors. These results support further studies to investigate the impact of these new tools on logistics and clinical outcome.

FUNDING

This study is funded by ZonMw, the Dutch Organisation for Health Research and Development.

TRIAL REGISTRATION NUMBER

This meta-analysis was published for registration in PROSPERO prior to starting (CRD York, CRD42021254122).

Assessing the Knowledge of the Osteopathic Profession in New York City’s Eastern European Communities

Background

According to the decennial Osteopathic Survey of Healthcare in America, the osteopathic profession has been steadily gaining recognition in the United States, particularly among the White/Caucasian demographic. This, however, does not take into account immigrant European communities that, while racially classified as White/Caucasian, may be unexposed to osteopathic physicians (DOs) in their home country and may be reticent to osteopathic manipulative medicine. Data on non-English-speaking communities are limited and can mask the need for further outreach. This study aimed to identify literature in osteopathic outreach to minority communities and assess osteopathic awareness in New York City’s Eastern European communities. Secondary objectives include characterization of potential barriers in hindering access to osteopathic medicine, and, by extension, other minority groups.

Methodology

An anonymous survey prepared in Russian and English was used to gather demographics, education level, healthcare habits, and knowledge of the osteopathic profession. To provide a clinical scenario, a health habit question regarding low back pain (LBP) was provided to participants. Participants over the age of 18 were randomly selected from high density Eastern European areas at two separate time points. Statistical analysis was performed using R to evaluate independence between questions using chi-square tests.

Results

A total of 150 surveys met the inclusion criteria, with 71 males and 79 females, an age range of 18-92, and a median age of 62. On comparing demographics, education level, and healthcare habits, only English proficiency showed statistical significance (p = 0.039) in determining recognition of the osteopathic profession. Overall, 60% (n = 94) stated that they have heard of osteopathic medicine and knew what a DO physician does. However, only 35% (n = 53) would see a DO for LBP, with 50% (n = 77) seeing a physical therapist.

Conclusions

Compared to research examining osteopathic awareness in ethnic minority communities, the Russian community in New York appears to have greater recognition of the osteopathic profession. This, however, does not translate into a clinical scenario as more participants were more likely to see a physical therapist. While this difference can be attributed to numerous factors, it stands without doubt that greater osteopathic outreach and data collection needs to be performed in minority communities.

Diagnostic performance and prognostic impact of coronary angiography-based Index of Microcirculatory Resistance assessment: A systematic review and meta-analysis

BACKGROUND

The Index of Microcirculatory Resistance (IMR), measured with a pressure-thermistor tipped coronary guidewire has been established as a gold standard for coronary microvascular assessment. Angiography-based IMR (angio-IMR) is a novel method to derive IMR without intracoronary instrumentation or the need for adenosine.

METHODS

PubMed and Embase databases were systemically searched in November 2021 for studies that measured angio-IMR. The primary outcomes were pooled sensitivity and specificity as well as the area under the curve (AUC) of the summary receiver operating characteristic curve using IMR as a reference standard.

RESULTS

A total of 129 records were initially identified and 8 studies were included in the final analysis. Overall, 1653 lesions were included in this study, of which 733 were in patients presenting with ST-segment elevation myocardial infarction. Angio-IMR yielded high diagnostic performance predicting wire-based IMR with pooled sensitivity = 0.81 (95% confidence interval: 0.76, 0.85), specificity = 0.80 (0.72, 0.86), and AUC = 0.86 (0.82, 0.88), which was similar irrespective of patient presentation. When the clinical outcome was compared between high versus low angio-IMR in patients presenting with myocardial infarction, high angio-IMR predicted an increased risk of major adverse cardiac events (MACE).

CONCLUSION

Our study found that coronary angio-IMR has relatively high diagnostic performance as well as prognostic values predicting MACE, supporting its use in clinical practice.

The diagnostic accuracy of clinical tests for anterior cruciate ligament tears are comparable but the Lachman test has been previously overestimated: a systematic review and meta-analysis

PURPOSE

The diagnostic accuracy of clinical tests for anterior cruciate ligament injury has been reported in previous systematic reviews. Numerous studies in these reviews include subjects with additional knee ligament injury, which could affect the sensitivity of the tests. Meta-analyses have also been performed using methods that do not account for the non-independence of sensitivity and specificity, potentially overestimating diagnostic accuracy. The aim of this study was to report the diagnostic accuracy of clinical tests for anterior cruciate ligament tears (partial and complete) without concomitant knee ligament injury.

METHODS

A systematic review with meta-analysis was performed according to the PRISMA guidelines. Meta-analyses included studies reporting the specificity and/or sensitivity of tests with or without concomitant meniscal injury. Where possible, pooled diagnostic estimates were calculated with bivariate random-effects modelling to determine the most accurate effect sizes. Diagnostic accuracy values are presented for the anterior drawer, Lachman, Lever sign and pivot shift tests overall and in acute or post-acute presentations.

RESULTS

Pooled estimates using a bivariate model for overall sensitivity and specificity respectively were as follows: anterior drawer test 83% [95% CI, 77-88] and 85% [95% CI, 64-95]; Lachman test 81% [95% CI, 73-87] and 85% [95% CI, 73-92]; pivot shift test 55% [95% CI, 47-62] and 94% [95% CI, 88-97]; Lever sign test 83% [95% CI, 68-92] and 91% [95% CI, 83-95]. For specific presentations, the sensitivity and specificity of the Lachman test, respectively, were: complete tears 68% [95% CI, 54-79] and 79% [95% CI, 51-93]; post-acute injuries 70% [95% CI, 57-80] and 77% [95% CI, 53-91].

CONCLUSIONS

The pivot shift and Lever sign were the best tests overall for ruling in or ruling out an anterior cruciate ligament tear, respectively. The diagnostic accuracy of the Lachman test, particularly in post-acute presentations and for complete tears, is lower than previously reported. Further research is required to establish more accurate estimates for the Lachman test in acute presentations and partial ligament tears using bivariate analysis.

LEVEL OF EVIDENCE

III.

Immunofluorescence Targeting PBP2a Protein: A New Potential Methicillin Resistance Screening Test

The indiscriminate use of first-line drugs contributed to the spread of resistant bacteria, a major concern for both human and veterinary medicine. Methicillin resistance is acquired through the mecA gene, which encodes for the PBP2a protein and lends the resistance to β-lactams. Verifying the correspondence between gene harboring and protein expression and accelerating methicillin resistance diagnosis is critical to improve the management of antimicrobial administration and to reduce the spread of drug resistances. We tested the applicability of immunofluorescence targeting PBP2a protein to identify a new potential methicillin resistance screening test, ancillary to conventional culture methods. We collected 26 clinical Staphylococcus pseudintermedius (SP) isolates: 25 from canine pyoderma and 1 from dermatitis in a dog owner. SP is one of the most important etiological agents in canine pyoderma and can harbor the mecA gene. We performed PCR for mecA gene detection, broth microdilution (BMD) for phenotypic methicillin resistance, and immunofluorescence targeting PBP2a protein. Compared to the PCR as the gold standard, immunofluorescence showed an apparent prevalence of 34.6% vs. a true prevalence of 53.8%, with 100% specificity, 64.3% sensitivity, and 80.8% diagnostic accuracy. PBP2a expression showed isolate-dependent variability: in some isolates, most of the bacterial cells showed an intense and clearly membranous pattern, while in others only a few of them could be detected. Performing the assay in duplicate improved the diagnostic accuracy. Since the mecA gene is shared among the members of the Staphylococcus genus, the test can be applied to identify methicillin resistance independently from the staphylococcal species, both in human and animal samples. Being a rapid and easy method and providing the unique possibility to study the expression of PBP2a by directly visualizing the morphology, it could represent a new interesting tool for both research and diagnostics. To accelerate methicillin resistance diagnosis, it would be worth further testing of its performance on cytological samples.

Diagnostic accuracy of magnetic resonance imaging targeted biopsy techniques compared to transrectal ultrasound guided biopsy of the prostate: a systematic review and meta-analysis

Background

Multiparametric MRI localizes cancer in the prostate, allowing for MRI guided biopsy (MRI-GB) 43 alongside transrectal ultrasound-guided systematic biopsy (TRUS-GB). Three MRI-GB approaches exist; visual estimation (COG-TB); fusion software-assisted (FUS-TB) and MRI ‘in-bore’ biopsy (IB-TB). It is unknown whether any of these are superior.

We conducted a systematic review and meta-analysis to address three questions. First, whether MRI-GB is superior to TRUS-GB at detecting clinically significant PCa (csPCa). Second, whether MRI-GB is superior to TRUS-GB at avoiding detection of insignificant PCa. Third, whether any MRI-GB strategy is superior at detecting csPCa.

Methods

A systematic literature review from 2015 to 2019 was performed in accordance with the START recommendations. Studies reporting PCa detection rates, employing MRI-GB and TRUS-GB were included and evaluated using the QUADAS-2 checklist. 1553 studies were found, of which 43 were included in the meta-analysis.

Results

For csPCa, MRI-GB was superior in detection to TRUS-GB (0.83 vs. 0.63 [p = 0.02]). MRI-GB was superior in detection to TRUS-GB at avoiding detection of insignificant PCa. No MRI-GB technique was superior at detecting csPCa (IB-TB 0.87; COG TB 0.81; FUS-TB 0.81, [p = 0.55]). There was significant heterogeneity observed between the included studies.

Conclusions

In patients with suspected PCa on MRI, MRI-GB offers superior rates of csPCa detection and reduces detection of insignificant PCa compared to TRUS-GB. No individual MRI-GB technique was found to be better in csPCa detection. Prospective adequately powered randomized controlled trials are required.