scholarly journals Corrigendum to: Suboptimal Biological Sampling as a Probable Cause of False-Negative COVID-19 Diagnostic Test Results

Author(s):  
Natalie N Kinloch ◽  
Gordon Ritchie ◽  
Chanson J Brumme ◽  
Winnie Dong ◽  
Weiyan Dong ◽  
...  
2020 ◽  
Vol 222 (6) ◽  
pp. 899-902 ◽  
Author(s):  
Natalie N Kinloch ◽  
Gordon Ritchie ◽  
Chanson J Brumme ◽  
Winnie Dong ◽  
Weiyan Dong ◽  
...  

Abstract False-negative severe acute respiratory syndrome coronavirus 2 test results can negatively impact the clinical and public health response to coronavirus disease 2019 (COVID-19). We used droplet digital polymerase chain reaction (ddPCR) to demonstrate that human DNA levels, a stable molecular marker of sampling quality, were significantly lower in samples from 40 confirmed or suspected COVID-19 cases that yielded negative diagnostic test results (ie, suspected false-negative test results) compared with a representative pool of 87 specimens submitted for COVID-19 testing. Our results support suboptimal biological sampling as a contributor to false-negative COVID-19 test results and underscore the importance of proper training and technique in the collection of nasopharyngeal specimens.


Author(s):  
Natalie N. Kinloch ◽  
Gordon Ritchie ◽  
Chanson J. Brumme ◽  
Winnie Dong ◽  
Weiyan Dong ◽  
...  

AbstractImproper nasopharyngeal swab collection could contribute to false-negative COVID-19 results. In support of this, specimens from confirmed or suspected COVID-19 cases that tested negative or indeterminate (i.e. suspected false-negatives) contained less human DNA (a stable molecular marker of sampling quality) compared to a representative pool of specimens submitted for testing.


2013 ◽  
Vol 57 (4) ◽  
pp. 494-500 ◽  
Author(s):  
Venkata C. K. Sunkesula ◽  
Sirisha Kundrapu ◽  
Christine Muganda ◽  
Ajay K. Sethi ◽  
Curtis J. Donskey

BJGP Open ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. bjgpopen20X101007 ◽  
Author(s):  
Christian von Wagner ◽  
Wouter Verstraete ◽  
Yasemin Hirst ◽  
Brian D Nicholson ◽  
Sandro T Stoffel ◽  
...  

BackgroundThere has been interest in using the non-invasive, home-based quantitative faecal immunochemical test (FIT) to rule out colorectal cancer (CRC) in high-risk symptomatic patients.AimTo elicit public preferences for FIT versus colonoscopy (CC) and its delivery in primary care.Design & settingA cross-sectional online survey in England.MethodA total of 1057 adults (without CRC symptoms and diagnosis) aged 40–59 years were invited from an English online survey panel. Responders were asked to imagine they had been experiencing CRC symptoms that would qualify them for a diagnostic test. Participants were presented with choices between CC and FIT in ascending order of number of CRCs missed by FIT (from 1–10%). It was measured at what number of missed CRCs responders preferred CC over FIT.ResultsWhile 150 participants did not want either of the tests when both missed 1% CRCs, the majority (n = 741, 70.0%) preferred FIT to CC at that level of accuracy. However, this preference reduced to 427 (40.4%) when FIT missed one additional cancer. Women were more likely to tolerate missing CRC when using FIT. Having lower numeracy and perceiving a higher level of risk meant participants were less likely to tolerate a false negative test. Most of those who chose FIT preferred to return it by mail (62.2%), to be informed about normal test results by letter (42.1%), and about abnormal test results face to face (32.5%).ConclusionWhile the majority of participants preferred FIT over CC when both tests had the same sensitivity, tolerance for missed CRCs was low.


2019 ◽  
Vol 1 (1) ◽  
pp. 24-33
Author(s):  
Anna Shalihah ◽  
Diah Mulhayatiah ◽  
Fathiah Alatas

This research aims to identify misconceptions that occur in Newton's law and its application based on diagnostic test results of students of class X SMAN 6 Tangerang Selatan and show sub concepts that experienced the highest misconceptions and low. The research was conducted in October 2015 - January 2016. The research method used is descriptive-quantitative. This study was conducted in two stages: stage manufacture of instruments held in SMAN 6 and 4 Tangerang Selatan and the implementation phase of the research conducted at SMAN 6 Tangerang Selatan. The instrument used is a three-tier diagnostic test. Results obtained 20 questions about the making of a valid with validity 0.64 and reliability 0.78. Results of the discussion showed misconception that occurred at 32.50% with a false positive at 20.97% and false negative amounting to 11.67% and misconceptions highest in subconcepts legal principles III Newton with a percentage of 56.92% and the lowest in the subconcepts variety of force with a percentage of 24.08%.


2020 ◽  
Author(s):  
Stephen Salerno ◽  
Zhangchen Zhao ◽  
Swaraaj Prabhu Sankar ◽  
Maxwell Salvatore ◽  
Tian Gu ◽  
...  

Importance The diagnostic tests for COVID-19 have a high false negative rate, but not everyone with an initial negative result is re-tested. Michigan Medicine, being one of the primary regional centers accepting COVID-19 cases, provided an ideal setting for studying COVID-19 repeated testing patterns during the first wave of the pandemic. Objective To identify the characteristics of patients who underwent repeated testing for COVID-19 and determine if repeated testing was associated with patient characteristics and with downstream outcomes among positive cases. Design This cross-sectional study described the pattern of testing for COVID-19 at Michigan Medicine. The main hypothesis under consideration is whether patient characteristics differed between those tested once and those who underwent multiple tests. We then restrict our attention to those that had at least one positive test and study repeated testing patterns in patients with severe COVID-19 related outcomes (testing positive, hospitalization and ICU care). Setting Demographic and clinical characteristics, test results, and health outcomes for 15,920 patients presenting to Michigan Medicine between March 10 and June 4, 2020 for a diagnostic test for COVID-19 were collected from their electronic medical records on June 24, 2020. Data on the number and types of tests administered to a given patient, as well as the sequences of patient-specific test results were derived from records of patient laboratory results. Participants Anyone tested between March 10 and June 4, 2020 at Michigan Medicine with a diagnostic test for COVID-19 in their Electronic Health Records were included in our analysis. Exposures Comparison of repeated testing across patient demographics, clinical characteristics, and patient outcomes Main Outcomes and Measures Whether patients underwent repeated diagnostic testing for SARS CoV-2 in Michigan Medicine Results Between March 10th and June 4th, 19,540 tests were ordered for 15,920 patients, with most patients only tested once (13596, 85.4%) and never testing positive (14753, 92.7%). There were 5 patients who got tested 10 or more times and there were substantial variations in test results within a patient. After fully adjusting for patient and neighborhood socioeconomic status (NSES) and demographic characteristics, patients with circulatory diseases (OR: 1.42; 95% CI: (1.18, 1.72)), any cancer (OR: 1.14; 95% CI: (1.01, 1.29)), Type 2 diabetes (OR: 1.22; 95% CI: (1.06, 1.39)), kidney diseases (OR: 1.95; 95% CI: (1.71, 2.23)), and liver diseases (OR: 1.30; 95% CI: (1.11, 1.50)) were found to have higher odds of undergoing repeated testing when compared to those without. Additionally, as compared to non-Hispanic whites, non-Hispanic blacks were found to have higher odds (OR: 1.21; 95% CI: (1.03, 1.43)) of receiving additional testing. Females were found to have lower odds (OR: 0.86; 95% CI: (0.76, 0.96)) of receiving additional testing than males. Neighborhood poverty level also affected whether to receive additional testing. For 1% increase in proportion of population with annual income below the federal poverty level, the odds ratio of receiving repeated testing is 1.01 (OR: 1.01; 95% CI: (1.00, 1.01)). Focusing on only those 1167 patients with at least one positive result in their full testing history, patient age in years (OR: 1.01; 95% CI: (1.00, 1.03)), prior history of kidney diseases (OR: 2.15; 95% CI: (1.36, 3.41)) remained significantly different between patients who underwent repeated testing and those who did not. After adjusting for both patient demographic factors and NSES, hospitalization (OR: 7.44; 95% CI: (4.92, 11.41)) and ICU-level care (OR: 6.97; 95% CI: (4.48, 10.98)) were significantly associated with repeated testing. Of these 1167 patients, 306 got repeated testing and 1118 tests were done on these 306 patients, of which 810 (72.5%) were done during inpatient stays, substantiating that most repeated tests for test positive patients were done during hospitalization or ICU care. Additionally, using repeated testing data we estimate the "real world" false negative rate of the RT-PCR diagnostic test was 23.8% (95% CI: (19.5%, 28.5%)). Conclusions and Relevance This study sought to quantify the pattern of repeated testing for COVID-19 at Michigan Medicine. While most patients were tested once and received a negative result, a meaningful subset of patients (2324, 14.6% of the population who got tested) underwent multiple rounds of testing (5,944 tests were done in total on these 2324 patients, with an average of 2.6 tests per person), with 10 or more tests for five patients. Both hospitalizations and ICU care differed significantly between patients who underwent repeated testing versus those only tested once as expected. These results shed light on testing patterns and have important implications for understanding the variation of repeated testing results within and between patients.


2000 ◽  
Vol 83 (6) ◽  
pp. 1429-1434
Author(s):  
Robert J Blodgett ◽  
Anthony D Hitchins

Abstract A typical qualitative microbiological method performance (collaborative) study gathers a data set of responses about a test for the presence or absence of a target microbe. We developed 2 models that estimate false-positive and false-negative rates. One model assumes a constant probability that the tests will indicate the target microbe is present for any positive concentration in the test portion. The other model assumes that this probability follows a logistic curve. Test results from several method performance studies illustrate these estimates.


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