scholarly journals Potential application of Rapid Antigen Diagnostic Tests for the detection of infectious individuals attending mass gatherings: a simulation study

2022 ◽  
Author(s):  
Conor G McAloon ◽  
Darren Dahly ◽  
Cathal Walsh ◽  
Patrick Wall ◽  
Breda Smyth ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Diagnostic Tests ◽  
Potential Application ◽  
Baseline Risk ◽  
Expected Number ◽  
Predictive Values ◽  
Age Cohorts ◽  
Incidence Data ◽  
Mass Gatherings ◽  
Age Cohort

Rapid Antigen Diagnostic Tests (RADTs) for the detection of SARS-CoV-2 offer advantages in that they are cheaper and faster than currently used PCR tests but have reduced sensitivity and specificity. One potential application of RADTs is to facilitate gatherings of individuals, through testing of attendees at the point of, or immediately prior to entry at a venue. Understanding the baseline risk in the tested population is of particular importance when evaluating the utility of applying diagnostic tests for screening purposes. We used incidence data to estimate the prevalence of infectious individuals in the community at a particular time point and simulated mass gatherings by sampling from a series of age cohorts. Nine different illustrative scenarios were simulated, small (n=100), medium (n=1000) and large (n=10,000) gatherings each with 3 possible age constructs: mostly younger, mostly older or a gathering with equal numbers from each age cohort. For each scenario, we estimated the prevalence of infectious attendees, then simulated the likely number of positive and negative test results, the proportion of cases detected and the corresponding positive and negative predictive values, and the cost per case identified. Our findings suggest that for each detected individual on a given day, there are likely to be 13.8 additional infectious individuals also present in the community. Prevalence of infectious individuals at events was highest with mostly younger attendees (1.00%), followed by homogenous age gatherings (0.55%) and lowest with mostly older events (0.26%). For small events (100 attendees) the expected number of infectious attendees was less than 1 across all age constructs of attendees. For large events (10,000 attendees) the expected number of infectious attendees ranged from 26 (95% confidence intervals 12 to 45) for mostly older events, to almost 100 (95% confidence intervals 46 to 174) infectious attendees for mostly younger attendees. Given rapid changes in SARS-CoV-2 incidence over time, we developed an RShiny app to allow users to run updated simulations for specific events.

scholarly journals Compbdt: an R program to compare two binary diagnostic tests subject to a paired design

2020 ◽  
Author(s):  
Jose Antonio Roldán-Nofuentes
Keyword(s):  
Confidence Intervals ◽  
Diagnostic Tests ◽  
Null Hypothesis ◽  
Type Ii ◽  
Type Ii Error ◽  
Hypothesis Tests ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
R Program ◽  
Paired Design

Abstract Background: The comparison of the effectiveness of two binary diagnostic tests is an important topic in Clinical Medicine. The most frequent type of sample design to compare two binary diagnostic tests is the paired design. This design consists of applying the two binary diagnostic tests to all of the individuals in a random sample, where the disease status of each individual is known through the application of a gold standard . This article presents an R program to compare parameters of two binary tests subject to a paired design. Results: The “compbdt” program estimates the sensitivity and the specificity, the likelihood ratios and the predictive values of each diagnostic test applying the confidence intervals with the best asymptotic performance. The program compares the sensitivities and specificities of the two diagnostic tests simultaneously, as well as the likelihood ratios and the predictive values, applying the global hypothesis tests with the best performance in terms of Type I error and power. When the global hypothesis test is significant, the causes of the significance are investigated solving the individual hypothesis tests and applying the multiple comparison method of Holm. The most optimal confidence intervals are also calculated for the difference or ratio between the respective parameters. Based on the data observed in the sample, the program also estimates the probability of making a Type II error if the null hypothesis is not rejected, or estimates the power if the if the alternative hypothesis is accepted. The “compbdt” program provides all the necessary results so that the researcher can easily interpret them. The estimation of the probability of making a Type II error allows the researcher to decide about the reliability of the null hypothesis when this hypothesis is not rejected. The “compbdt” program has been applied to a real example on the diagnosis of coronary artery disease. Conclusions: The “compbdt” program is one which is easy to use and allows the researcher to compare the most important parameters of two binary tests subject to a paired design. The “compbdt” program is available as supplementary material.

scholarly journals Confidence Intervals and Sample Size to Compare the Predictive Values of Two Diagnostic Tests

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1462
Author(s):  
José Antonio Roldán-Nofuentes ◽  
Saad Bouh Regad
Keyword(s):  
Sample Size ◽  
Confidence Intervals ◽  
Diagnostic Test ◽  
Diagnostic Tests ◽  
Medical Test ◽  
Predictive Values ◽  
General Rules ◽  
Clinical Accuracy ◽  
The Difference ◽  
Paired Design

A binary diagnostic test is a medical test that is applied to an individual in order to determine the presence or the absence of a certain disease and whose result can be positive or negative. A positive result indicates the presence of the disease, and a negative result indicates the absence. Positive and negative predictive values represent the accuracy of a binary diagnostic test when it is applied to a cohort of individuals, and they are measures of the clinical accuracy of the binary diagnostic test. In this manuscript, we study the comparison of the positive (negative) predictive values of two binary diagnostic tests subject to a paired design through confidence intervals. We have studied confidence intervals for the difference and for the ratio of the two positive (negative) predictive values. Simulation experiments have been carried out to study the asymptotic behavior of the confidence intervals, giving some general rules for application. We also study a method to calculate the sample size to compare the parameters using confidence intervals. We have written a program in R to solve the problems studied in this manuscript. The results have been applied to the diagnosis of colorectal cancer.

scholarly journals Compbdt: an R program to compare two binary diagnostic tests subject to a paired design

2020 ◽  
Author(s):  
Jose Antonio Roldán-Nofuentes
Keyword(s):  
Confidence Intervals ◽  
Diagnostic Tests ◽  
Null Hypothesis ◽  
Type Ii ◽  
Type Ii Error ◽  
Hypothesis Tests ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
R Program ◽  
Paired Design

Abstract Background: The comparison of the effectiveness of two binary diagnostic tests is an important topic in Clinical Medicine. The most frequent type of sample design to compare two binary diagnostic tests is the paired design. This design consists of applying the two binary diagnostic tests to all of the individuals in a random sample, where the disease status of each individual is known through the application of a gold standard . This article presents an R program to compare parameters of two binary tests subject to a paired design. Results: The “compbdt” program estimates the sensitivity and the specificity, the likelihood ratios and the predictive values of each diagnostic test applying the confidence intervals with the best asymptotic performance. The program compares the sensitivities and specificities of the two diagnostic tests simultaneously, as well as the likelihood ratios and the predictive values, applying the global hypothesis tests with the best performance in terms of Type I error and power. When the global hypothesis test is significant, the causes of the significance are investigated solving the individual hypothesis tests and applying the multiple comparison method of Holm. The most optimal confidence intervals are also calculated for the difference or ratio between the respective parameters. Based on the data observed in the sample, the program also estimates the probability of making a Type II error if the null hypothesis is not rejected, or estimates the power if the if the alternative hypothesis is accepted. The “compbdt” program provides all the necessary results so that the researcher can easily interpret them. The estimation of the probability of making a Type II error allows the researcher to decide about the reliability of the null hypothesis when this hypothesis is not rejected. The “compbdt” program has been applied to a real example on the diagnosis of coronary artery disease. Conclusions: The “compbdt” program is one which is easy to use and allows the researcher to compare the most important parameters of two binary tests subject to a paired design. The “compbdt” program is available as supplementary material.

scholarly journals Age Cohort Differences and Depressive Symptoms Among Community-Dwelling Older Americans

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 61-61
Author(s):  
Ethan Siu Leung Cheung ◽  
Ada Mui
Keyword(s):  
Depressive Symptoms ◽  
Short Form ◽  
Cognitive Status ◽  
Community Dwelling ◽  
Independent Effect ◽  
Depression Symptoms ◽  
Older Americans ◽  
Age Cohorts ◽  
Cohort Differences ◽  
Age Cohort

Abstract This study uses Wave 3 National Social Life, Health and Aging Project to examine the correlation between age cohorts [60s (n=1204); 70s (n=1176); 80 and older (n= 724)], cognitive status, and depression symptoms. In the total sample, 53.90% were females, 76.15% Whites, 15.29% Blacks, and 8.56% Asians. Compared to the 60s and 70s cohorts, 80+ cohort was cognitively more impaired [Mean (SD) of MoCA Short Form were 10.7(2.9), 10.0(3.2), and 8.1(3.6)]. There were no age cohorts’ differences in depressive symptoms experienced (Mean of CESD Short Form = 21.03; SD = 4.06). In order to identify predictors of depression, multiple hierarchical regressions were performed. The 60s sample was the reference group to compare with 70s and 80s cohorts. Results showed that age cohort variables had a significant independent effect as well as a joint effect with cognitive status in explaining depression scores. For each age cohort group, parallel regression analyses were conducted and all models were significant. Findings suggest that ADL impairment was the only common predictor for depressive symptoms for the three cohort groups, and the association was the strongest for the 60s cohort (b = .31). Other unique predictors for 60s cohort were lower-income, more IADLs impairment, higher stress and cognitive impairment. For the 70s cohort, unique predictors of depressive symptoms were female gender, unmarried, and less socialization. For the 80 and above group, correlates of depression are female, White, and high stress level. Findings highlight the necessity of age-sensitive programs on depression support for community-dwelling older Americans.

Confidence intervals for predictive values with an emphasis to case–control studies

2007 ◽  
Vol 26 (10) ◽  
pp. 2170-2183 ◽  
Author(s):  
Nathaniel D. Mercaldo ◽  
Kit F. Lau ◽  
Xiao H. Zhou
Keyword(s):  
Confidence Intervals ◽  
Case Control ◽  
Case Control Studies ◽  
Predictive Values

scholarly journals Sensory Consumer and Descriptive Analysis of Steaks from Beef Animals Selected from Tough and Tender Animal Genotypes: Genetic Meat Quality Traits Can Be Detected by Consumers

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1911
Author(s):  
Maurice G. O’Sullivan ◽  
Ciara M. O’Neill ◽  
Stephen Conroy ◽  
Michelle J. Judge ◽  
Emily C. Crofton ◽  
...  
Keyword(s):  
Descriptive Analysis ◽  
Meat Tenderness ◽  
Genetic Merit ◽  
Age Cohorts ◽  
Overall Acceptability ◽  
Consumer Study ◽  
Age Cohort ◽  
Affective Analysis ◽  
Consumer Age ◽  
Sensory Acuity

The objective of the present study was to determine if animals who were genetically divergent in the predicted tenderness of their meat actually produced more tender meat, as well as what the implications were for other organoleptic properties of the meat. The parental average genetic merit for meat tenderness was used to locate 20 “Tough genotype” heifers and 17 “Tender genotype” heifers; M. longissimus thoracis steaks from all heifers were subjected to sensory affective analysis (140 consumers) and sensory profiling using two trained sensory panels. All sample steaks were treated identically regarding pre- and post-mortem handling, storage, cooking and presentation (i.e., randomised, blind coded). For the affective consumer study, eight steaks were sectioned from the same location of the striploin muscles from each of the heifers. In total, 108 steaks from the Tender genotype and 118 from the Tough genotype were tested in the consumer study to determine the preference or liking of these steaks for appearance, aroma, flavour, tenderness, juiciness and overall acceptability. The consumer study found that the Tender genotype scored higher (p < 0.0001) for liking of tenderness, juiciness, flavour and overall acceptability compared to the Tough genotype. Similar results were generally found for the separate consumer age cohorts (18–64 years) with lower sensory acuity in the 65+ age cohort. For the descriptive analysis, the Tender genotype scored numerically more tender, juicy and flavoursome, although the differences were only significant for one of the panels. The critical outcome from this study is that parental average genetic merit can be used to pre-select groups of animals for tenderness, which, in turn, can be detected by consumers.

Research Methods, Statistics, Patient Safety, and Quality Improvement

2020 ◽  
pp. 521-530
Author(s):  
Carlos Lerner
Keyword(s):  
Patient Safety ◽  
Quality Improvement ◽  
Adverse Events ◽  
Research Methods ◽  
Confidence Intervals ◽  
Medical Errors ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Analysis Of Variation ◽  
Answer Format

The chapter on research methods, statistics, patient safety, and quality improvement (QI) uses a question-and-answer format to make concepts in these areas relevant and accessible to general pediatricians. Research topics covered include study design and study types, validity, sources of bias, types of errors, sensitivity and specificity, positive and negative predictive values, likelihood ratios, incidence and prevalence, p values and confidence intervals. The patient safety questions focus on medical errors and adverse events, including their categorization, detection, prevention, and disclosure. Finally, the QI questions address key QI principles and methods, including tools to understand systems (e.g. fishbone diagrams and Pareto charts), analysis of variation, and the Langley Model for Improvement.

scholarly journals Risk factors, diagnosis and non-surgical treatment for meniscal tears: evidence and recommendations: a statement paper commissioned by the Danish Society of Sports Physical Therapy (DSSF)

2018 ◽  
Vol 52 (9) ◽  
pp. 557-565 ◽  
Author(s):  
Jonas Bloch Thorlund ◽  
Carsten Bogh Juhl ◽  
Lina Holm Ingelsrud ◽  
Søren Thorgaard Skou
Keyword(s):  
Risk Factors ◽  
Diagnostic Tests ◽  
Young Patients ◽  
Evaluation Framework ◽  
Diagnostic Tools ◽  
Meniscal Tears ◽  
Predictive Values ◽  
And Function ◽  
Surgical Treatments ◽  
Quality Evidence

This statement aimed at summarising and appraising the available evidence for risk factors, diagnostic tools and non-surgical treatments for patients with meniscal tears. We systematically searched electronic databases using a pragmatic search strategy approach. Included studies were synthesised quantitatively or qualitatively, as appropriate. Strength of evidence was determined according to the Grading of Recommendations Assessment Development and Evaluation framework. Low-quality evidence suggested that overweight (degenerative tears, k=3), male sex (k=4), contact and pivoting sports (k=2), and frequent occupational kneeling/squatting (k=3) were risk factors for meniscal tears. There was low to moderate quality evidence for low to high positive and negative predictive values, depending on the underlying prevalence of meniscal tears for four common diagnostic tests (k=15, n=2474). Seven trials investigated exercise versus surgery (k=2) or the effect of surgery in addition to exercise (k=5) for degenerative meniscal tears. There was moderate level of evidence for exercise improving self-reported pain (Effect Size (ES)−0.51, 95% CI −1.16 to 0.13) and function (ES −0.06, 95% CI −0.23 to 0.11) to the same extent as surgery, and improving muscle strength to a greater extent than surgery (ES −0.45, 95% CI −0.62 to −0.29). High-quality evidence showed no clinically relevant effect of surgery in addition to exercise on pain (ES 0.18, 95% 0.05 to 0.32) and function (ES, 0.13 95% CI −0.03 to 0.28) for patients with degenerative meniscal tears. No randomised trials comparing non-surgical treatments with surgery in patients younger than 40 years of age or patients with traumatic meniscal tears were identified. Diagnosis of meniscal tears is challenging as all clinical diagnostic tests have high risk of misclassification. Exercise therapy should be recommended as the treatment of choice for middle-aged and older patients with degenerative meniscal lesions. Evidence on the best treatment for young patients and patients with traumatic meniscal tears is lacking.

Sign in / Sign up

Export Citation Format

Share Document