scholarly journals Audit of the first > 7500 noninvasive prenatal aneuploidy tests in a Swiss genetics center

2021 ◽  
Author(s):  
Anahita Bajka ◽  
Michael Bajka ◽  
Fabian Chablais ◽  
Tilo Burkhardt
Keyword(s):  
Pregnancy Outcome ◽  
False Positive Rate ◽  
Prenatal Testing ◽  
Accurate Method ◽  
Test Results ◽  
Data Set ◽  
Single Nucleotide ◽  
Noninvasive Prenatal Testing ◽  
Positive Rate

Abstract Objectives Noninvasive prenatal testing (NIPT) is actually the most accurate method of screening for fetal chromosomal aberration (FCA). We used pregnancy outcome record to evaluate a complete data set of single nucleotide polymorphism-based test results performed by a Swiss genetics center. Materials and methods The Panorama® test assesses the risk of fetal trisomies (21, 18 and 13), gonosomal aneuploidy (GAN), triploidy or vanishing twins (VTT) and five different microdeletions (MD). We evaluated all 7549 test results meeting legal and quality requirements taken in women with nondonor singleton pregnancies between April 2013 and September 2016 classifying them as high or low risk. Follow-up ended after 9 months, data collection 7 months later. Results The Panorama® test provided conclusive results in 96.1% of cases, detecting 153 FCA: T21 n = 76, T18 n = 19, T13 n = 15, GAN n = 19, VTT n = 13 and MD n = 11 (overall prevalence 2.0%). Pregnancy outcome record was available for 68.6% of conclusive laboratory results, including 2.0% high-risk cases. In this cohort the Panorama® test exhibited 99.90% sensitivity for each trisomy; specificity was 99.90% for T21, 99.98% for T18 and 99.94% for T13. False positive rate was 0.10% for T21, 0.02% for T18 and 0.06% for T13. Conclusion SNP-based testing by a Swiss genetics center confirms the expected accuracy of NIPT in FCA detection.

Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao
Keyword(s):  
Acute Appendicitis ◽  
False Positive ◽  
False Positive Rate ◽  
Accurate Method ◽  
Clinical Findings ◽  
Pathological Findings ◽  
Lower Quadrant ◽  
Predictive Values ◽  
Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

scholarly journals Follow-Up SARS-CoV-2 PCR Testing Outcomes From a Large Reference Lab in the US

2021 ◽  
Vol 9 ◽  
Author(s):  
Adam Sullivan ◽  
David Alfego ◽  
Brian Poirier ◽  
Jonathan Williams ◽  
Dorothy Adcock ◽  
...  
Keyword(s):  
United States ◽  
Cohort Study ◽  
False Positive ◽  
False Positive Rate ◽  
The United States ◽  
Positive Test ◽  
Test Results ◽  
Rt Pcr ◽  
Positive Rate

By analyzing COVID-19 sequential COVID-19 test results of patients across the United States, we herein attempt to quantify some of the observations we've made around long-term infection (and false-positive rates), as well as provide observations on the uncertainty of sampling variability and other dynamics of COVID-19 infection in the United States. Retrospective cohort study of a registry of RT-PCR testing results for all patients tested at any of the reference labs operated by Labcorp® including both positive, negative, and inconclusive results, from March 1, 2020 to January 28, 2021, including patients from all 50 states and outlying US territories. The study included 22 million patients with RT-PCR qualitative test results for SARS-CoV-2, of which 3.9 million had more than one test at Labcorp. We observed a minuscule <0.1% basal positive rate for follow up tests >115 days, which could account for false positives, long-haulers, and/or reinfection but is indistinguishable in the data. In observing repeat-testing, for patients who have a second test after a first RT-PCR, 30% across the cohort tested negative on the second test. For patients who test positive first and subsequently negative within 96 h (40% of positive test results), 18% of tests will subsequently test positive within another 96-h span. For those who first test negative and then positive within 96 h (2.3% of negative tests), 56% will test negative after a third and subsequent 96-h period. The sudden changes in RT-PCR test results for SARS-CoV-2 from this large cohort study suggest that negative test results during active infection or exposure can change rapidly within just days or hours. We also demonstrate that there does not appear to be a basal false positive rate among patients who test positive >115 days after their first RT-PCR positive test while failing to observe any evidence of widespread reinfection.

scholarly journals Role of Invasive Urodynamic Studies in Establishing Cauda Equina Syndrome and Postoperative Recovery

2020 ◽  
pp. 219256822097964
Author(s):  
Abhinandan Reddy Mallepally ◽  
Bibhudendu Mohapatra ◽  
Kalidutta Das
Keyword(s):  
Clinical Symptoms ◽  
False Positive Rate ◽  
Cauda Equina ◽  
Postoperative Recovery ◽  
Normal Bladder ◽  
Acontractile Detrusor ◽  
Positive Rate ◽  
Acute Radiculopathy ◽  
Operative Recovery

Study design: Retrospective with prospective follow-up. Objective: Confirming the diagnosis of CES based purely on symptoms and signs is unreliable and usually associated with high false positive rate. A missed diagnosis can permanently disable the patient. Present study aims to determine the relationship between clinical symptoms/ signs (bladder dysfunction) with UDS, subsequently aid in surgical decision making and assessing post-operative recovery. Methods: A prospective follow-up of patients with disc herniation and bladder symptoms from January 2018 to July 2020 was done. All patients underwent UDS and grouped into acontractile, hypocontractile and normal bladder. Data regarding PAS, VAC, GTP, timing to surgery and onset of radiculopathy and recovery with correlation to UDS was done preoperatively and post operatively. Results: 107 patients were studied (M-63/F-44). Patients with PAS present still had acontractile (61%) or hypocontractile (39%) detrusor and with VAC present, 57% had acontractile and 43% hypocontractile detrusors. 10 patients with both PAS and VAC present had acontractile detrusor. 82% patients with acute radiculopathy (<2 days) improved when operated <24 hrs while only 47% showed improvement with chronic radiculopathy. The detrusor function recovered in 66.1% when operated <12 hours, 40% in <12-24 hours of presentation. Conclusion: Adjuvant information from UDS in combination with clinicoradiological findings help in accurate diagnosis even in patients with no objective motor and sensory deficits. Quantitative findings on UDS are consistent with postoperative recovery of patient’s urination power, representing improvement and can be used as a prognostic factor.

Investigating the clinical usefulness of definitions of progression with 10-2 visual field

2021 ◽  
pp. bjophthalmol-2020-318188
Author(s):  
Shotaro Asano ◽  
Hiroshi Murata ◽  
Yuri Fujino ◽  
Takehiro Yamashita ◽  
Atsuya Miki ◽  
...  
Keyword(s):  
Visual Field ◽  
False Positive ◽  
False Positive Rate ◽  
Clinical Validity ◽  
Data Set ◽  
Humphrey Field Analyzer ◽  
Positive Rate ◽  
Using Data ◽  
Sensitivity Specificity ◽  
Higher Sensitivity

Background/AimTo investigate the clinical validity of the Guided Progression Analysis definition (GPAD) and cluster-based definition (CBD) with the Humphrey Field Analyzer 10-2 test in diagnosing glaucomatous visual field (VF) progression, and to introduce a novel definition with optimised specificity by combining the ‘any-location’ and ‘cluster-based’ approaches (hybrid definition).Methods64 400 stable glaucomatous VFs were simulated from 664 pairs of 10-2 tests (10 sets × 10 VF series × 664 eyes; data set 1). Using these simulated VFs, the specificity to detect progression and the effects of changing the parameters (number of test locations or consecutive VF tests, and percentile cut-off values) were investigated. The hybrid definition was designed as the combination where the specificity was closest to 95.0%. Subsequently, another 5000 actual glaucomatous 10-2 tests from 500 eyes (10 VFs each) were collected (data set 2), and their accuracy (sensitivity, specificity and false positive rate) and the time needed to detect VF progression were evaluated.ResultsThe specificity values calculated using data set 1 with GPAD and CBD were 99.6% and 99.8%. Using data set 2, the hybrid definition had a higher sensitivity than GPAD and CBD, without detriment to the specificity or false positive rate. The hybrid definition also detected progression significantly earlier than GPAD and CBD (at 3.1 years vs 4.2 years and 4.1 years, respectively).ConclusionsGPAD and CBD had specificities of 99.6% and 99.8%, respectively. A novel hybrid definition (with a specificity of 95.5%) had higher sensitivity and enabled earlier detection of progression.

scholarly journals Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates

2014 ◽  
Author(s):  
Andreas Tuerk ◽  
Gregor Wiktorin ◽  
Serhat Güler
Keyword(s):  
Probability Distributions ◽  
False Positive Rate ◽  
Synthetic Data ◽  
True Positive Rate ◽  
Rna Seq ◽  
Microarray Quality Control ◽  
Data Set ◽  
Rna Transcripts ◽  
Positive Rate ◽  
Fragment Distribution

Quantification of RNA transcripts with RNA-Seq is inaccurate due to positional fragment bias, which is not represented appropriately by current statistical models of RNA-Seq data. This article introduces the Mix2(rd. "mixquare") model, which uses a mixture of probability distributions to model the transcript specific positional fragment bias. The parameters of the Mix2model can be efficiently trained with the Expectation Maximization (EM) algorithm resulting in simultaneous estimates of the transcript abundances and transcript specific positional biases. Experiments are conducted on synthetic data and the Universal Human Reference (UHR) and Brain (HBR) sample from the Microarray quality control (MAQC) data set. Comparing the correlation between qPCR and FPKM values to state-of-the-art methods Cufflinks and PennSeq we obtain an increase in R2value from 0.44 to 0.6 and from 0.34 to 0.54. In the detection of differential expression between UHR and HBR the true positive rate increases from 0.44 to 0.71 at a false positive rate of 0.1. Finally, the Mix2model is used to investigate biases present in the MAQC data. This reveals 5 dominant biases which deviate from the common assumption of a uniform fragment distribution. The Mix2software is available at http://www.lexogen.com/fileadmin/uploads/bioinfo/mix2model.tgz.

A Novel Approach for Computer-Aided Diagnosis for Distinction Between Benign and Malignant of Lung Nodules Based on Machine Learning Techniques

2018 ◽  
pp. 281-290
Author(s):  
Shashidhara Bola
Keyword(s):  
False Positive Rate ◽  
Lung Nodule ◽  
Machine Learning Techniques ◽  
Lung Nodules ◽  
Data Set ◽  
Novel Approach ◽  
Learning Techniques ◽  
Nodule Shape ◽  
Positive Rate ◽  
Aided Diagnosis

A new method is proposed to classify the lung nodules as benign and malignant. The method is based on analysis of lung nodule shape, contour, and texture for better classification. The data set consists of 39 lung nodules of 39 patients which contain 19 benign and 20 malignant nodules. Lung regions are segmented based on morphological operators and lung nodules are detected based on shape and area features. The proposed algorithm was tested on LIDC (lung image database consortium) datasets and the results were found to be satisfactory. The performance of the method for distinction between benign and malignant was evaluated by the use of receiver operating characteristic (ROC) analysis. The method achieved area under the ROC curve was 0.903 which reduces the false positive rate.

scholarly journals Cloud Detection of SuperView-1 Remote Sensing Images Based on Genetic Reinforcement Learning

2020 ◽  
Vol 12 (19) ◽  
pp. 3190
Author(s):  
Xiaolong Li ◽  
Hong Zheng ◽  
Chuanzhao Han ◽  
Haibo Wang ◽  
Kaihan Dong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Reinforcement Learning ◽  
False Positive Rate ◽  
Optical Remote Sensing ◽  
Cloud Detection ◽  
Remote Sensing Images ◽  
Threshold Method ◽  
Data Set ◽  
Action Strategy ◽  
Positive Rate

Cloud pixels have massively reduced the utilization of optical remote sensing images, highlighting the importance of cloud detection. According to the current remote sensing literature, methods such as the threshold method, statistical method and deep learning (DL) have been applied in cloud detection tasks. As some cloud areas are translucent, areas blurred by these clouds still retain some ground feature information, which blurs the spectral or spatial characteristics of these areas, leading to difficulty in accurate detection of cloud areas by existing methods. To solve the problem, this study presents a cloud detection method based on genetic reinforcement learning. Firstly, the factors that directly affect the classification of pixels in remote sensing images are analyzed, and the concept of pixel environmental state (PES) is proposed. Then, PES information and the algorithm’s marking action are integrated into the “PES-action” data set. Subsequently, the rule of “reward–penalty” is introduced and the “PES-action” strategy with the highest cumulative return is learned by a genetic algorithm (GA). Clouds can be detected accurately through the learned “PES-action” strategy. By virtue of the strong adaptability of reinforcement learning (RL) to the environment and the global optimization ability of the GA, cloud regions are detected accurately. In the experiment, multi-spectral remote sensing images of SuperView-1 were collected to build the data set, which was finally accurately detected. The overall accuracy (OA) of the proposed method on the test set reached 97.15%, and satisfactory cloud masks were obtained. Compared with the best DL method disclosed and the random forest (RF) method, the proposed method is superior in precision, recall, false positive rate (FPR) and OA for the detection of clouds. This study aims to improve the detection of cloud regions, providing a reference for researchers interested in cloud detection of remote sensing images.

An approach to optimize delta checks in test panels – The effect of the number of rules included

2020 ◽  
Vol 57 (3) ◽  
pp. 215-222 ◽  
Author(s):  
Rui Zhen Tan ◽  
Corey Markus ◽  
Tze Ping Loh
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Original Data ◽  
Random Permutation ◽  
Full Blood Count ◽  
Hypothesis Tests ◽  
Data Set ◽  
Laboratory Results ◽  
Positive Rate ◽  
Common Laboratory

Objectives The interpretation of delta check rules in a panel of tests should be different to that at the single analyte level, as the number of hypothesis tests conducted (i.e. the number of delta check rules) is greater and needs to be taken into account. Methods De-identified paediatric laboratory results were extracted, and the first two serial results for each patient were used for analysis. Analytes were grouped into four common laboratory test panels consisting of renal, liver, bone and full blood count panels. The sensitivities and specificities of delta check limits as discrete panel tests were assessed by random permutation of the original data-set to simulate a wrong blood in tube situation. Results Generally, as the number of analytes included in a panel increases, the delta check rules deteriorate considerably due to the increased number of false positives, i.e. increased number hypothesis tests performed. To reduce high false-positive rates, patient results may be rejected from autovalidation only if the number of analytes failing the delta check limits exceeds a certain threshold of the total number of analytes in the panel (N). Our study found that the use of the ([Formula: see text] rule) for panel results had a specificity >90% and sensitivity ranging from 25% to 45% across the four common laboratory panels. However, this did not achieve performance close to some analytes when considered in isolation. Conclusions The simple [Formula: see text] rule reduces the false-positive rate and minimizes unnecessary, resource-intensive investigations for potentially erroneous results.

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