scholarly journals Optimal Screening Methods to Detect Cardiac Disorders in Athletes: An Evidence-Based Review

2017 ◽  
Vol 52 (12) ◽  
pp. 1168-1170 ◽  
Author(s):  
Zachary K. Winkelmann ◽  
Ashley K. Crossway
Keyword(s):  
False Positive ◽  
Best Practice ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Screening Method ◽  
Heart Association ◽  
Screening Methods ◽  
Likelihood Ratios ◽  
Positive Rate ◽  
Cardiac Disorders

Reference/Citation:  Harmon KG, Zigman M, Drezner JA. The effectiveness of screening history, physical exam, and ECG to detect potentially lethal cardiac disorders in athletes: a systematic review/meta-analysis. J Electrocardiol. 2015;48(3):329–338. Clinical Question:  Which screening method should be considered best practice to detect potentially lethal cardiac disorders during the preparticipation physical examination (PE) of athletes? Data Sources:  The authors completed a comprehensive literature search of MEDLINE, CINAHL, Cochrane Library, Embase, Physiotherapy Evidence Database (PEDro), and SPORTDiscus from January 1996 to November 2014. The following key words were used individually and in combination: ECG, athlete, screening, pre-participation, history, and physical. A manual review of reference lists and key journals was performed to identify additional studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed for this review. Study Selection:  Studies selected for this analysis involved (1) outcomes of cardiovascular screening in athletes using the history, PE, and electrocardiogram (ECG); (2) history questions and PE based on the American Heart Association recommendations and guidelines; and (3) ECGs interpreted following modern standards. The exclusion criteria were (1) articles not in English, (2) conference abstracts, and (3) clinical commentary articles. Study quality was assessed on a 7-point scale for risk of bias; a score of 7 indicated the highest quality. Articles with potential bias were excluded. Data Extraction:  Data included number and sex of participants, number of true- and false-positives and negatives, type of ECG criteria used, number of cardiac abnormalities, and specific cardiac conditions. The sensitivity, specificity, false-positive rate, and positive predictive value of each screening tool were calculated and summarized using a bivariate random-effects meta-analysis model. Main Results:  Fifteen articles reporting on 47 137 athletes were fully reviewed. The overall quality of the 15 articles ranged from 5 to 7 on the 7-item assessment scale (ie, participant selection criteria, representative sample, prospective data with at least 1 positive finding, modern ECG criteria used for screening, cardiovascular screening history and PE per American Heart Association guidelines, individual test outcomes reported, and abnormal screening findings evaluated by appropriate diagnostic testing). The athletes (66% males and 34% females) were ethnically and racially diverse, were from several countries, and ranged in age from 5 to 39 years. The sensitivity and specificity of the screening methods were, respectively, ECG, 94% and 93%; history, 20% and 94%; and PE, 9% and 97%. The overall false-positive rate for ECG (6%) was less than that for history (8%) or PE (10%). The positive likelihood ratios of each screening method were 14.8 for ECG, 3.22 for history, and 2.93 for PE. The negative likelihood ratios were 0.055 for ECG, 0.85 for history, and 0.93 for PE. A total of 160 potentially lethal cardiovascular conditions were detected, for a rate of 0.3%, or 1 in 294 patients. The most common conditions were Wolff-Parkinson-White syndrome (n = 67, 42%), long QT syndrome (n = 18, 11%), hypertrophic cardiomyopathy (n = 18, 11%), dilated cardiomyopathy (n = 11, 7%), coronary artery disease or myocardial ischemia (n = 9, 6%), and arrhythmogenic right ventricular cardiomyopathy (n = 4, 3%). Conclusions:  The most effective strategy to screen athletes for cardiovascular disease was ECG. This test was 5 times more sensitive than history and 10 times more sensitive than PE, and it had a higher positive likelihood ratio, lower negative likelihood ratio, and lower false-positive rate than history or PE. The 12-lead ECG interpreted using modern criteria should be considered the best practice in screening athletes for cardiovascular disease, and the use of history and PE alone as screening tools should be reevaluated.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals Utilizing two-tiered screening for early detection of autism spectrum disorder

Autism ◽  
2017 ◽  
Vol 22 (7) ◽  
pp. 881-890 ◽  
Author(s):  
Meena Khowaja ◽  
Diana L Robins ◽  
Lauren B Adamson
Keyword(s):  
Early Detection ◽  
Young Children ◽  
False Positive ◽  
Screening Tool ◽  
False Positive Rate ◽  
Autism Spectrum ◽  
Screening Methods ◽  
Positive Rate ◽  
Level 1 ◽  
Level 2

Despite advances in autism screening practices, challenges persist, including barriers to implementing universal screening in primary care and difficulty accessing services. The high false positive rate of Level 1 screening methods presents especially daunting difficulties because it increases the need for comprehensive autism evaluations. This study explored whether two-tiered screening—combining Level 1 (Modified Checklist for Autism in Toddlers, Revised with Follow-Up) and Level 2 (Screening Tool for Autism in Toddlers and Young Children) measures—improves the early detection of autism. This study examined a sample of 109 toddlers who screened positive on Level 1 screening and completed a Level 2 screening measure prior to a diagnostic evaluation. Results indicated that two-tiered screening reduced the false positive rate using published Screening Tool for Autism in Toddlers and Young Children cutoffs compared to Level 1 screening alone, although at a cost to sensitivity. However, alternative Screening Tool for Autism in Toddlers and Young Children scoring in the two-tiered screening improved both positive predictive value and sensitivity. Exploratory analyses were conducted, including comparison of autism symptoms and clinical profiles across screening subsamples. Recommendations regarding clinical implications of two-tiered screening and future areas of research are presented.

scholarly journals Estimating the statistical performance of different approaches to meta-analysis of data from animal studies in identifying the impact of aspects of study design

2018 ◽  
Author(s):  
Qianying Wang ◽  
Jing Liao ◽  
Kaitlyn Hair ◽  
Alexandra Bannach-Brown ◽  
Zsanett Bahor ◽  
...  
Keyword(s):  
Effect Size ◽  
False Positive ◽  
Latent Variable ◽  
Statistical Power ◽  
Animal Studies ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Mean Difference ◽  
Positive Rate ◽  
Meta Regression

AbstractBackgroundMeta-analysis is increasingly used to summarise the findings identified in systematic reviews of animal studies modelling human disease. Such reviews typically identify a large number of individually small studies, testing efficacy under a variety of conditions. This leads to substantial heterogeneity, and identifying potential sources of this heterogeneity is an important function of such analyses. However, the statistical performance of different approaches (normalised compared with standardised mean difference estimates of effect size; stratified meta-analysis compared with meta-regression) is not known.MethodsUsing data from 3116 experiments in focal cerebral ischaemia to construct a linear model predicting observed improvement in outcome contingent on 25 independent variables. We used stochastic simulation to attribute these variables to simulated studies according to their prevalence. To ascertain the ability to detect an effect of a given variable we introduced in addition this “variable of interest” of given prevalence and effect. To establish any impact of a latent variable on the apparent influence of the variable of interest we also introduced a “latent confounding variable” with given prevalence and effect, and allowed the prevalence of the variable of interest to be different in the presence and absence of the latent variable.ResultsGenerally, the normalised mean difference (NMD) approach had higher statistical power than the standardised mean difference (SMD) approach. Even when the effect size and the number of studies contributing to the meta-analysis was small, there was good statistical power to detect the overall effect, with a low false positive rate. For detecting an effect of the variable of interest, stratified meta-analysis was associated with a substantial false positive rate with NMD estimates of effect size, while using an SMD estimate of effect size had very low statistical power. Univariate and multivariable meta-regression performed substantially better, with low false positive rate for both NMD and SMD approaches; power was higher for NMD than for SMD. The presence or absence of a latent confounding variables only introduced an apparent effect of the variable of interest when there was substantial asymmetry in the prevalence of the variable of interest in the presence or absence of the confounding variable.ConclusionsIn meta-analysis of data from animal studies, NMD estimates of effect size should be used in preference to SMD estimates, and meta-regression should, where possible, be chosen over stratified meta-analysis. The power to detect the influence of the variable of interest depends on the effect of the variable of interest and its prevalence, but unless effects are very large adequate power is only achieved once at least 100 experiments are included in the meta-analysis.

Asymptomatic Bacteriuria in Adolescent Girls: II. Screening Methods

PEDIATRICS ◽  
1979 ◽  
Vol 64 (4) ◽  
pp. 438-441
Author(s):  
S. Jean Emans ◽  
Estherann Grace ◽  
Robert P. Masland
Keyword(s):  
Adolescent Girls ◽  
False Positive ◽  
Prior Experience ◽  
False Positive Rate ◽  
Asymptomatic Bacteriuria ◽  
Screening Methods ◽  
Home Test ◽  
Positive Rate ◽  
History Of ◽  
Reagent Strips

Of 500 asymptomatic adolescent girls who were screened for bacteriuria by three methods—dipslide (Uricult), dipstrip (Microstix-3 reagent strips), and home nitrite test (Microstix-Nitrite reagent strips)—eight cases (1.6%) were detected: 6/8 by dipslide and dipstrip; 5/8 by nitrite testing. The false-positive-rate (> 104 colonies/ml) of the dipslide test was 6.4%, and the dipstrip test, 2.8%. A history of vaginal discharge was not associated with "contaminated" specimens. False-positive nitrite tests were reported by 0.6% of the patients who returned the postcards. Overall, 70.4% of the patients returned the postcards for the home nitrite test. The patients were divided by method of payment (Medicaid vs non-Medicaid) in order to provide an approximation of socioeconomic status; non-Medicaid patients were significantly more likely to return postcards than Medicaid patients (75.8% vs 63.7%). Of the group reporting previous urinary tract infection, 79% of both Medicaid and non-Medicaid patients returned postcards, suggesting that a prior experience with the diagnosis increased compliance with a home test.

scholarly journals Brain metastasis detection using machine learning: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Se Jin Cho ◽  
Leonard Sunwoo ◽  
Sung Hyun Baik ◽  
Yun Jung Bae ◽  
Byung Se Choi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Metastasis ◽  
False Positive ◽  
Data Augmentation ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Relevant Literature ◽  
Inverse Variance ◽  
Positive Rate

Abstract Background Accurate detection of brain metastasis (BM) is important for cancer patients. We aimed to systematically review the performance and quality of machine-learning-based BM detection on MRI in the relevant literature. Methods A systematic literature search was performed for relevant studies reported before April 27, 2020. We assessed the quality of the studies using modified tailored questionnaires of the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Pooled detectability was calculated using an inverse-variance weighting model. Results A total of 12 studies were included, which showed a clear transition from classical machine learning (cML) to deep learning (DL) after 2018. The studies on DL used a larger sample size than those on cML. The cML and DL groups also differed in the composition of the dataset, and technical details such as data augmentation. The pooled proportions of detectability of BM were 88.7% (95% CI, 84–93%) and 90.1% (95% CI, 84–95%) in the cML and DL groups, respectively. The false-positive rate per person was lower in the DL group than the cML group (10 vs 135, P < 0.001). In the patient selection domain of QUADAS-2, three studies (25%) were designated as high risk due to non-consecutive enrollment and arbitrary exclusion of nodules. Conclusion A comparable detectability of BM with a low false-positive rate per person was found in the DL group compared with the cML group. Improvements are required in terms of quality and study design.

scholarly journals The copy quantities of TRECs as a biomarker for screening SCID in newborns：a meta-analysis

2021 ◽  
Author(s):  
Bihan Li ◽  
Zhiyong Sun ◽  
Ying Liu ◽  
Jinxia Song ◽  
Lijuan Wang ◽  
...  
Keyword(s):  
False Positive ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Severe Combined Immunodeficiency ◽  
Positive Likelihood Ratio ◽  
Current Evidence ◽  
Cochrane Library ◽  
Control Group ◽  
China National Knowledge Infrastructure ◽  
Positive Rate

Abstract Purpose Severe combined immunodeficiency (SCID) threatens the newborns' living qualities. The aim of our study is to evaluate the the value of detecting the copy quantities of T-cell receptor excision circles (TRECs) in screening for the newborns' SCID. Methods We searched eligible studies in PubMed, Web of science, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI) and chose the Endnote software to filter the whole studies. Meta-analysis was conducted with meta-disc 1.4 and STATA 12.0 software. We used sensitivity and false positive rate (FPR) to evaluate this detecting method; subgroup analysis to explore the sources of heterogeneity. The literature quality was assessed by the quality assessment of diagnostic accuracy studies (QUADAS-Ⅱ). Results Fifteen studies were enrolled containing 3,570 cases in the decreased TREC copy quantities group and 12,186,899 cases in control group. All the included studies are of high quality. The heterogeneity in Diagnostic Odds Ratio (DOR) is 77.9%. The summarized estimates revealed that the pooled sensitivity is 100% (95% confidence interval (CI): 99–100%), the false positive rate is 0.00 (95% CI: 0.00–0.00) and Positive Predict Value (PPV) is 0.14 (95% CI: 0.08-0.19). The current evidence shows detecting the copy quantities of TRECs has the screening value with a high sensitivity and positive likelihood ratio (LR+) for newborns' SCID without published bias (p>0.05). Our result suggests 90 and 40 copies/ul of TRECs as the primary and secondary cut-off value. Conclusion Detecting the individual TREC contents could be used as the premise to diagnosis the newborns' SCID.

scholarly journals Isolated Echogenic Cardiac Focus: Assessing Association with Trisomy 21 by Combining Results from a Prenatal Center with a Bayesian Meta-Analysis

2019 ◽  
Vol 05 (03) ◽  
pp. E98-E106
Author(s):  
Elisabeth Wrede ◽  
Alexander Johannes Knippel ◽  
Pablo Emilio Verde ◽  
Ruediger Hammer ◽  
Peter Kozlowski
Keyword(s):  
Trisomy 21 ◽  
Meta Analysis ◽  
False Positive Rate ◽  
A Priori ◽  
Low Risk ◽  
Trisomy 13 ◽  
Chromosomal Anomalies ◽  
Second Trimester ◽  
Likelihood Ratios ◽  
Positive Rate

Abstract Objective To investigate the clinical relevance of an isolated echogenic cardiac focus (iECF) as a marker for trisomy 21 using a large second-trimester collective including a low-risk subgroup. Materials and Methods We retrospectively evaluated 1 25 211 pregnancies from 2000–2016 and analyzed all iECF cases with regard to chromosomal anomalies. It consisted of an early second-trimester collective from 14+0−17+6 weeks (n=34 791) and a second-trimester anomaly scan collective from 18+0–21+6 weeks. Two a priori risk subgroups (high and low risk) of the latter were built based on maternal age and previous screening test results using a cut-off of 1:300. Likelihood ratios (LR) of iECF for the detection of trisomy 21, trisomy 13, trisomy 18 and structural chromosomal anomalies were estimated. Results In total, 1 04 001 patients were included. An iECF was found in 4416 of 1 02 847 euploid fetuses (4.29%) and in 64 of 557 cases with trisomy 21 (11.49%) giving a positive LR of 2.68 (CI: 2.12–3.2). The sensitivity was 11.5% at a false-positive rate of 4.29% (CI:4.17–4.42) with p≤0.01%. In the high-and low-risk subgroups, the prevalence of iECF was comparable: 5.08% vs. 5.05%. The frequency of trisomy 21 was 0.39%, 98/24 979 vs 0.16%, 69/44 103. LR+was 3.86 (2.43–5.14) and 2.59 (1.05–4). For both subgroups the association of iECF with trisomy 21 was statistically significant. The prevalence of structural chromosomal anomalies in the second-trimester anomaly scan collective was 0.08% (52/68 967), of which 2 showed an iECF. Conclusion The detection of an iECF at the time of 14+0–21+6 weeks significantly increases the risk for trisomy 21 in the high-risk and in the low-risk subgroups and does not statistically change the risks for trisomy 13/18 or structural abnormalitie.

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