Diagnostic accuracy of tests for tuberculous pericarditis: A network meta-analysis.

Tuberculous pericarditis (TBP) is a relatively uncommon but potentially fatal extrapulmonary manifestation of tuberculosis. Despite its severity, there is no universally accepted gold standard diagnostic test for TBP currently. The objective of this study is to compare the diagnostic accuracy of the most commonly used tests in terms of specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV), and provide a summary of their diagnostic accuracies. A comprehensive literature review was performed using Scopus, MEDLINE, and Cochrane central register of controlled trials, encompassing studies published from start to April 2022. Studies that compared Interferon Gamma Release Assay (IGRA), Xpert MTB/RIF, Adenosine Deaminase levels (ADA), and Smear Microscopy (SM) were included in the analysis. Bayesian random-effects model was used for statistical analysis and mean and standard deviation (SD) with 95% confidence intervals were calculated using the absolute risk (AR) and odds ratio (OR). Rank probability and heterogeneity were determined using risk difference and Cochran Q test, respectively. Sensitivity and specificity were evaluated using true negative, true positive, false positive, and false negative rates. Area under the receiver operating characteristic (AUROC) was calculated for mean and standard error. A total of seven studies comprising 16 arms and 618 patients were included in the analysis. IGRA exhibited the highest mean (SD) sensitivity of 0.934 (0.049), with a high rank probability of 87.5% for being the best diagnostic test, and the AUROC was found to be 94.8 (0.36). On the other hand, SM demonstrated the highest mean (SD) specificity of 0.999 (0.011), with a rank probability of 99.5%, but a leave-one-out analysis excluding SM studies revealed that Xpert MTB/RIF ranked highest for specificity, with a mean (SD) of 0.962 (0.064). The diagnostic tests compared in our study exhibited similar high NPV, while ADA was found to have the lowest PPV among the evaluated methods. Further research, including comparative studies, should be conducted using a standardized cutoff value for both ADA levels and IGRA to mitigate the risk of threshold effect and minimize bias and heterogeneity in data analysis.

Diagnostic accuracy of smartphone-based artificial intelligence systems for detecting diabetic retinopathy: A systematic review and meta-analysis.

AIMS: Diabetic retinopathy (DR) is a major cause of blindness globally, early detection is critical to prevent vision loss. Traditional screening that, rely on human experts are, however, costly, and time-consuming. The purpose of this systematic review is to assess the diagnostic accuracy of smartphone-based artificial intelligence(AI) systems for DR detection. METHODS: Literature review was conducted on MEDLINE, Embase, Scopus, CINAHL Plus, and Cochrane from inception to December 2022. We included diagnostic test accuracy studies evaluating the use of smartphone-based AI algorithms for DR screening in patients with diabetes, with expert human grader as the reference standard. Random-effects model was used to pool sensitivity and specificity. Any DR(ADR) and referable DR(RDR) were analyzed separately. RESULTS: Out of 968 identified articles, six diagnostic test accuracy studies met our inclusion criteria, comprising 3,931 patients. Four of these studies used the Medios AI algorithm. The pooled sensitivity and specificity for diagnosis of ADR were 88 % and 91.5 % respectively and for diagnosis of RDR were 98.2 % and 81.2 % respectively. The overall risk of bias across the studies was low. CONCLUSIONS: Smartphone-based AI algorithms show high diagnostic accuracy for detecting DR. However, more high-quality comparative studies are needed to evaluate the effectiveness in real-world clinical settings.

Comparative analysis of pinning techniques for supracondylar humerus fractures in paediatrics: A systematic review and meta-analysis of randomized controlled trials.

Purpose: Supracondylar humeral fractures (SCHFs) rank among the frequently observed fractures in children. Nonetheless, there exists a dearth of consensus regarding the optimal surgical approach. This meta-analysis aims to thoroughly evaluate and compare two distinct pinning techniques (cross pinning versus lateral pinning) for SCHFs, using data from Randomized controlled trials (RCTs). Methods: Literature review was done using PubMed, CINAHL, Scopus, and The Cochrane Library for RCTs comparing the two pinning methods and providing information on at least one of the following: Loss of Baumann's angle, loss of carrying angle, elbow function assessed based on Flynn criteria, pin tract infection, and iatrogenic ulnar nerve injury. Random effect model was used to calculate standardized mean difference or Odds Ratio (OR) for the outcomes. Review Manager 5.4.1. was used to perform quality assessment and statistical analysis. Results: A total of 22 RCTs were included. 20 studies reported data for iatrogenic ulnar nerve injury, the OR was calculated to be 3.76 (95% CI 1.75-8.06), showing a significantly lower risk of surgical ulnar nerve injury with the lateral technique. However, no significant difference was found between the pinning techniques in regard to the other outcomes. Conclusion: In comparison to lateral pinning, the utilization of cross pinning technique exposes the patient to a heightened susceptibility of iatrogenic nerve injury. Therefore, it is recommended that surgeons prioritize the implementation of the lateral pinning technique whenever feasible, as it offers greater protection against iatrogenic ulnar nerve injury. For the other intraoperative and postoperative outcomes, both surgical techniques yield comparable results.