Validating the efficacy of the binomial pointwise linear regression method to detect glaucoma progression with multicentral database

2019 ◽  
Vol 104 (4) ◽  
pp. 569-574
Author(s):  
Shotaro Asano ◽  
Hiroshi Murata ◽  
Masato Matsuura ◽  
Yuri Fujino ◽  
Atsuya Miki ◽  
...  
Keyword(s):  
Visual Field ◽  
Linear Regression ◽  
Trend Analysis ◽  
Predictive Value ◽  
False Positive Rate ◽  
Linear Regression Method ◽  
Trend Analyses ◽  
Total Deviation ◽  
Positive Rate ◽  
Test Points

Background/aimWe previously reported the benefit of applying binomial pointwise linear regression (PLR: binomial PLR) to detect 10–2 glaucomatous visual field (VF) progression. The purpose of the current study was to validate the usefulness of the binomial PLR to detect glaucomatous VF progression in the central 24°.MethodsSeries of 15 VFs (Humphrey Field Analyzer 24–2 SITA-standard) from 341 eyes of 233 patients, obtained over 7.9±2.1 years (mean±SD), were investigated. PLR was performed by regressing the total deviation of all test points. VF progression was determined from the VF test points analyses using the binomial test (one side, p<0.025). The time needed to detect VF progression was compared across the binomial PLR, permutation analysis of PLR (PoPLR) and mean total deviation (mTD) trend analysis.ResultsThe binomial PLR was comparable with PoPLR and mTD trend analyses in the positive predictive value (0.18–0.87), the negative predictive value (0.89–0.95) and the false positive rate (0.057–0.35) to evaluate glaucomatous VF progression. The time to classify progression with binomial PLR (5.8±2.8 years) was significantly shorter than those with mTD trend analysis (6.7±2.8 years) and PoPLR (6.6±2.7 years).ConclusionsThe binomial PLR method, which detected glaucomatous VF progression in the central 24° significantly earlier than PoPLR and mTD trend analyses, shows promise for improving our ability to detect visual field progression for clinical management of glaucoma and in clinical trials of new glaucoma therapies.

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 Identification of newborns at risk for autism using electronic medical records and machine learning

2019 ◽  
Author(s):  
Rayees Rahman ◽  
Arad Kodesh ◽  
Stephen Z Levine ◽  
Sven Sandin ◽  
Abraham Reichenberg ◽  
...  
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Positive Predictive Value ◽  
Electronic Medical Records ◽  
Predictive Value ◽  
False Positive ◽  
Medical Records ◽  
False Positive Rate ◽  
Autism Spectrum ◽  
Positive Rate

AbstractImportanceCurrent approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, where most ASD patients are not identified until after the age of 4. This is despite substantial evidence suggesting that early diagnosis and intervention improves developmental course and outcome.ObjectiveDevelop a machine learning (ML) method predicting the diagnosis of ASD in offspring in a general population sample, using parental electronic medical records (EMR) available before childbirthDesignPrognostic study of EMR data within a single Israeli health maintenance organization, for the parents of 1,397 ASD children (ICD-9/10), and 94,741 non-ASD children born between January 1st, 1997 through December 31st, 2008. The complete EMR record of the parents was used to develop various ML models to predict the risk of having a child with ASD.Main outcomes and measuresRoutinely available parental sociodemographic information, medical histories and prescribed medications data until offspring’s birth were used to generate features to train various machine learning algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross validation, by computing C statistics, sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value, PPV).ResultsAll ML models tested had similar performance, achieving an average C statistics of 0.70, sensitivity of 28.63%, specificity of 98.62%, accuracy of 96.05%, false positive rate of 1.37%, and positive predictive value of 45.85% for predicting ASD in this dataset.Conclusion and relevanceML algorithms combined with EMR capture early life ASD risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.Key pointsQuestionCan autism risk in children be predicted using the pre-birth electronic medical record (EMR) of the parents?FindingsIn this population-based study that included 1,397 children with autism spectrum disorder (ASD) and 94,741 non-ASD children, we developed a machine learning classifier for predicting the likelihood of childhood diagnosis of ASD with an average C statistic of 0.70, sensitivity of 28.63%, specificity of 98.62%, accuracy of 96.05%, false positive rate of 1.37%, and positive predictive value of 45.85%.MeaningThe results presented serve as a proof-of-principle of the potential utility of EMR for the identification of a large proportion of future children at a high-risk of ASD.

Venous Flow Coupler in Head and Neck Free Flap Reconstruction

2020 ◽  
pp. 019459982095309
Author(s):  
Scott H. Troob ◽  
Quinn Self ◽  
Deniz Gerecci ◽  
Macgregor Hodgson ◽  
Javier González-Castro ◽  
...  
Keyword(s):  
Free Flap ◽  
Predictive Value ◽  
False Positive ◽  
False Positive Rate ◽  
Case Series ◽  
Arterial Flow ◽  
Retrospective Case ◽  
Venous Flow ◽  
Retrospective Case Series ◽  
Positive Rate

Objective To describe the utility of venous flow couplers in monitoring free tissue flaps in the immediate postoperative setting. Study Design Retrospective case series. Setting Otolaryngology department at a single tertiary care institution. Methods A retrospective case series of free flap reconstructions in which venous flow couplers were employed to supplement flap monitoring. All free flap cases performed over the past 4 years were reviewed. Inclusion criteria were venous flow coupler and arterial flow Doppler monitored for 5 days postoperatively. Results From July 2014 through May 2018, the venous flow coupler was used with the arterial flow Doppler and clinical monitoring in 228 cases. Eleven cases did not meet criteria for inclusion; thus, 217 cases were analyzed. Twenty cases (9.2%) returned to the operating room with concern for flap compromise, and 16 were salvaged. The combination of venous flow coupler and arterial flow Doppler identified 19 of these flaps. Venous flow couplers identified 5 compromised flaps before there was an arterial signal change, and all were salvaged. Additionally, there was a 24.1% false-positive rate when 2 venous flow couplers were used in parallel. For the venous flow coupler, the positive predictive value was 64.3% and the negative predictive value, 98.9%. The false-positive rate in the series was 5.1%. The sensitivity was 90% and the specificity, 94.9%. Conclusion The venous flow coupler is able to detect venous thrombosis in the absence of arterial thrombosis and may contribute to improved flap salvage rates.

Protein Expression Signatures Determined by Reverse Phase Proteins Arrays (RPPA) Accurately Predict FLT3-ITD Mutation Status in AML.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2398-2398
Author(s):  
Steven M. Kornblau ◽  
YiHua Qiu ◽  
Wenjing Chen ◽  
Srdan Verstovsek ◽  
Kevin R. Coombes ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Protein Expression ◽  
Mutation Analysis ◽  
Predictive Value ◽  
False Positive ◽  
False Positive Rate ◽  
Myelogenous Leukemia ◽  
Reverse Phase ◽  
Mutation Status ◽  
Positive Rate

Abstract We have used Reverse Phase Protein Arrays (RPPA) to perform proteomic profiling in Acute Myelogenous Leukemia (AML) focusing on cell cycle, apoptosis and signal transduction pathway proteins (ASH 2006, abstract #107). Protein expression signatures were derived from this dataset of 436 AML patients, analyzed for 30 total and 22 phopho- proteins. The predictive ability of these RPPA derived protein expression signatures has not been prospectively tested to determine if they are valid. This dataset presented an opportunity to validate this as there was a population of patients with known FLT3-ITD and D835 mutation status (n=297) and another population where the status was unknown (n=139), among which 55 had sufficient sample available for mutation analysis. Prior to performing the mutation analysis a predictive model was built using linear regression with part of the data utilized for training and the reminder for validation. The model was designed to predict for the presence of mutation, either ITD or D835, although there are differences int eh signature of each. The total population had 85 cases with FLT3-ITD and 15 with the D835 mutation. The optimal model that was developed, using 30%, 50% and 70% of the samples for training and the remainder for validation, had a median validation accuracy of 68%, 70% and 72% respectively. Prospective predictions of FLT3-ITD or D835 mutation status were then made for all samples lacking FLT3-ITD or D835 mutation data. Mutation analysis was then performed using PCR amplification followed by 2-D gel electrophoresis (FLT3-ITD) to evaluate for PCR product size, or sequencing (D835) on 55 samples. This revealed 9 cases with FLT3-ITD, 3 with a D835 mutation, 1 with both and 43 without mutation. Among these 55 cases the model correctly predicted that 8 of the 12 mutant cases would be mutant including 8 of 10 with a FLT3-ITD, but 0 of 2 with only the D835 mutation. Among the 43 wildtype cases 36 were accurately predicted to be wildtype, while 7 were incorrectly predicted to have the mutation mutant. This yields an overall accuracy (OA) of 80%, Sensitivity =66%, Specificity=90%, Positive Predictive Value (PPV) of 53%, False positive rate of (FPR) of 16%. Since most patients with FLT3-ITD have Diploid cytogenetics we also looked at the predictive accuracy of the protein expression signature in that population. Among 23 patients with Diploid cytogenetics the overall accuracy was OA) of 83%, Sensitivity =75%, Specificity=87%, Positive Predictive Value (PPV) of 75%, False positive rate of (FPR) of 13%. Since FLT3-ITD and D835 carry different prognostic impact, and had different protein expression signatures, greater accuracy might be achieved if separate models were developed for each mutation individually. The model demonstrated that RPPA derived protein expression signatures can accurately be used to predict mutation status providing the first prospective validation of protein expression signatures in AML.

scholarly journals Early Radiologic Diagnosis of Pulmonary Infection in Febrile Neutropenic Patients: A Comparison of Serial Chest Radiography and Single CT Chest

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Wanaporn Burivong ◽  
Thanatorn Sricharoen ◽  
Apichart Thachang ◽  
Sunsiree Soodchuen ◽  
Panitpong Maroongroge ◽  
...  
Keyword(s):  
Febrile Neutropenia ◽  
Positive Predictive Value ◽  
Absolute Neutrophil Count ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
False Positive Rate ◽  
Radiologic Diagnosis ◽  
Chest Film ◽  
Positive Rate ◽  
Sensitivity Specificity

Objective. The purpose of this study is to compare the early radiologic diagnosis of pulmonary infection between serial chest radiography (chest film) and single chest computed tomography (CT chest) in the first seven days of febrile neutropenia. Methods. This study included 78 patients with hematologic malignancies who developed 107 episodes of febrile neutropenia from January 2012 to October 2017 and had a chest film performed within the first seven days. Demographic and radiographic data were retrospectively reviewed. Three radiologists independently and blindly evaluated chest films and CT chests. The sensitivity, specificity, and correlation of chest film with absolute neutrophil count were carried out. Results. A total of 222 chest films were performed during this period and found thirty-nine episodes (36.4%) of radiographic active pulmonary infection. The diagnosis of clinical positive for pulmonary infection is 44.8% (48/107). Sensitivity, specificity, positive predictive value, and negative predictive value of serial chest film in the early radiologic diagnosis of pulmonary infection are 50%, 74%, 61%, and 64%, respectively. The false-positive rate was 14%, and the false-negative rate was 22%. For single CT chest examinations, twenty-six studies were assessed, and 42.3% was indicative of radiographic active pulmonary infection. Sensitivity, specificity, positive predictive value, and negative predictive value of CT chest in the early radiologic diagnosis of pulmonary infection are 91%, 40%, 53%, and 86%, respectively. The false-positive rate was 60%. The absolute neutrophil count was not useful for predicting radiographic active pulmonary infection. Conclusion. Serial chest film for early radiologic diagnosis of pulmonary infection within the first seven days of febrile neutropenia has lower sensitivity with higher specificity as compared to a single CT chest. Conversely, CT chest may not only have a higher sensitivity in determining early pulmonary infection but also has a higher rate of false-positives.

scholarly journals Early Post-operative CT-Angiography Imaging After EC-IC Bypass Surgery in Moyamoya Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Helene Hurth ◽  
Till-Karsten Hauser ◽  
Patrick Haas ◽  
Sophie Wang ◽  
Annerose Mengel ◽  
...  
Keyword(s):  
Predictive Value ◽  
Bypass Surgery ◽  
False Positive Rate ◽  
Computed Tomographic Angiography ◽  
Clinical Value ◽  
Computed Tomographic ◽  
Bypass Patency ◽  
Imaging Results ◽  
Positive Rate ◽  
Tomographic Angiography

Objective: To evaluate the clinical value of early post-operative computed tomographic angiography (CTA) after direct extracranial-intracranial (EC-IC) bypass surgery in moyamoya patients.Methods: A retrospective analysis of all adult moyamoya patients treated at our center from 2013 to 2019 with a direct EC-IC bypass was performed. Early post-operative CTA (within 24 h after surgery) was compared with conventional digital subtraction angiography (DSA) 6–12 months after surgery. If available, magnetic resonance time-of-flight angiography (MR-TOF) was evaluated 3 months and 6–12 months post-operatively as well. Imaging results were analyzed and compared with CTA, MR-TOF and DSA, whereat DSA was used as the final and definite modality to decide on bypass patency.Results: A total of 103 direct EC-IC bypasses in 63 moyamoya patients were analyzed. All inclusion criteria were met in 32 patients (53 direct bypasses). In 84.9% the bypass appeared definitively, in 5.7% uncertainly and in 9.4% not patent according to early post-operative CTA. MR-TOF suggested definitive bypass patency in 86.8% 3 months after surgery and in 93.5% 6–12 months after surgery. DSA 6–12 months post-operatively showed a patency in 98.1% of all bypasses. The positive predictive value (to correctly detect an occluded bypass) on post-operative CTA was 12.5%, the negative predictive value (to correctly detect a patent bypass) was 100% with a sensitivity of 100% and a specificity of 86.5%.Conclusion: Early post-operative CTA has a high predictive value to confirm the patency of a bypass. On the other hand, a high false positive rate of (according to CTA) occluded bypasses after direct EC-IC bypass surgery can be seen. This must be considered critically when initiating possible therapeutic measures.

scholarly journals A Smart Context-Aware Hazard Attention System to Help People with Peripheral Vision Loss

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1630 ◽  
Author(s):  
Ola Younis ◽  
Waleed Al-Nuaimy ◽  
Fiona Rowe ◽  
Mohammad Alomari
Keyword(s):  
Visual Field ◽  
Vision Loss ◽  
Peripheral Vision ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Visual Field Defects ◽  
Context Aware ◽  
Motion Model ◽  
Positive Rate

Peripheral vision loss results in the inability to detect objects in the peripheral visual field which affects the ability to evaluate and avoid potential hazards. A different number of assistive navigation systems have been developed to help people with vision impairments using wearable and portable devices. Most of these systems are designed to search for obstacles and provide safe navigation paths for visually impaired people without any prioritisation of the degree of danger for each hazard. This paper presents a new context-aware hybrid (indoor/outdoor) hazard classification assistive technology to help people with peripheral vision loss in their navigation using computer-enabled smart glasses equipped with a wide-angle camera. Our proposed system augments users’ existing healthy vision with suitable, meaningful and smart notifications to attract the user’s attention to possible obstructions or hazards in their peripheral field of view. A deep learning object detector is implemented to recognise static and moving objects in real time. After detecting the objects, a Kalman Filter multi-object tracker is used to track these objects over time to determine the motion model. For each tracked object, its motion model represents its way of moving around the user. Motion features are extracted while the object is still in the user’s field of vision. These features are then used to quantify the danger using five predefined hazard classes using a neural network-based classifier. The classification performance is tested on both publicly available and private datasets and the system shows promising results with up to 90% True Positive Rate (TPR) associated with as low as 7% False Positive Rate (FPR), 13% False Negative Rate (FNR) and an average testing Mean Square Error (MSE) of 8.8%. The provided hazard type is then translated into a smart notification to increase the user’s cognitive perception using the healthy vision within the visual field. A participant study was conducted with a group of patients with different visual field defects to explore their feedback about the proposed system and the notification generation stage. The real-world outdoor evaluation of human subjects is planned to be performed in our near future work.

Is D2 surgery necessary for clinical T1 gastric cancer with nodal swelling?

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 288-288
Author(s):  
Takeyuki Wada ◽  
Takaki Yoshikawa ◽  
Ayako Kamiya ◽  
Keichi Date ◽  
Tsutomu Hayashi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
False Positive ◽  
False Positive Rate ◽  
False Positivity ◽  
Positive Rate ◽  
D2 Surgery ◽  
Sensitivity Specificity

288 Background: D2 surgery is required for clinical T1 gastric cancer with nodal swelling, however, D2 has a higher risk for morbidity than D1/D1+. Moreover, previous study demonstrated that the false positive rate for nodal diagnosis in clinical T1 was very high. To select optimal surgery with high probability, we explored risk factors for false positivity in clinical T1 disease. Methods: Patients who underwent radical gastrectomy for clinical T1 gastric cancer between April 2015 and June 2019 were enrolled. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for nodal diagnosis were retrospectively investigated. The risk factors for false positivity were also analyzed by the following factors; age, sex, histological type, tumor size, tumor depth, location, tumor type, presence of ulcer, and timing of CT that is (1) the patients who underwent primary endoscopic mucosal dissection (ESD) but resulted in non-curative resection, then received CT to proceed to surgery (delayed CT group) or (2) the other patients who had received CT before primary surgery or before non-curative ESD (primary CT group). Results: A total of 679 patients were examined in the present study. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 83.5% (567/679), 14.3% (13/91), 94.2% (554/588), 27.7% (13/47), and 87.7% (554/632), respectively. The false positive rate was 72.3% (34/47). In univariate analysis, differentiated tumor ( p= 0.012) and delayed CT (p < 0.001) were associated with the false positivity. Multivariate analysis revealed that delayed CT (OR, 4.534; p < 0.001) was a sole significant risk factor for false positivity. False positive rate was 100% (13/13) in the delayed CT group and 61.8% (21/34) in the primary CT group ( p= 0.009). Conclusions: False positive rate was high in clinical T1 disease, especially when the patients received delayed CT after non-curative ESD. D2 surgery would be unnecessary even though nodal swelling was detected in CT after non-curative ESD.

scholarly journals A device for surveillance of vascular access sites for bleeding: results from a clinical evaluation trial

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Chang Yin Chionh ◽  
◽  
Desilyn Yuqing Soh ◽  
Chee How Tan ◽  
Jien-Yi Khaw ◽  
...  
Keyword(s):  
Vascular Access ◽  
Predictive Value ◽  
False Positive Rate ◽  
False Alarms ◽  
Detection Failure ◽  
Reflected Light ◽  
Positive Rate ◽  
Life Threatening ◽  
Bleeding Episodes ◽  
Evaluation Trial

Abstract Post-procedural wound haemorrhage is a potentially life-threatening complication. For haemodialysis patients, bleeding is often encountered after vascular access procedures and fatal episodes have been reported. Visual monitoring for bleeding is manpower intensive and bleeding episodes may still be missed between inspections. A device, Blood WArning Technology with Continuous Haemoglobin sensor (BWATCH), was developed to detect bleeding from wounds. This a prospective, observational clinical trial on patients who have had a dialysis catheter inserted or removed. The battery-powered, disc-shaped device (43 mm diameter, 12 mm height) was placed over the dressing for at least six hours. The device detects reflected light with characteristics specific for haemoglobin and an alarm would be triggered if bleeding occurs. There were 250 participants (177 post-insertion, 73 post-removal) and 36 episodes of bleeding occurred. The device alarm was triggered in all instances but there were also 9 false alarms. Specificity was 95.8%, false positive rate was 4.2% and positive predictive value was 80.0%. Sensitivity and negative predictive value were 100% but detection failure may still occur due to improper application or device maintenance. The use of technological aids for monitoring improves patient safety and may reduce demand on manpower.

scholarly journals Multi-Platform Comparison of SARS-CoV-2 Serology Assays for the Detection of COVID-19

2020 ◽  
Vol 5 (6) ◽  
pp. 1324-1336 ◽  
Author(s):  
Raymond T Suhandynata ◽  
Melissa A Hoffman ◽  
Michael J Kelner ◽  
Ronald W McLawhon ◽  
Sharon L Reed ◽  
...  
Keyword(s):  
Predictive Value ◽  
False Positive Rate ◽  
Disease Prevalence ◽  
Percentage Agreement ◽  
Chain Reaction ◽  
Acute Infections ◽  
Positive Rate ◽  
Platform Comparison ◽  
Polymerase Chain ◽  
Time Frames

Abstract Background COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel beta-coronavirus that is responsible for the 2019 coronavirus pandemic. Acute infections should be diagnosed by polymerase chain reaction (PCR) based tests, but serology tests can demonstrate previous exposure to the virus. Methods We compared the performance of the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays using 179 negative participants to determine negative percentage agreement (NPA) and in 60 SARS-CoV-2 PCR-confirmed positive patients to determine positive percentage agreement (PPA) at 3 different time frames following a positive SARS-CoV-2 PCR result. Results At ≥15 days, the PPA (95% CI) was 100 (86.3–100)% for the Diazyme IgM/IgG panel, 96.0 (79.7–99.9)% for the Roche total Ig assay, and 100 (86.3–100)% for the Abbott IgG assay. The NPA (95% CI) was 98.3 (95.2–99.7)% for the Diazyme IgM/IgG panel, 99.4 (96.9–100)% for the Roche total Ig assay, and 98.9 (96.0–99.9)% for the Abbott IgG assay. When the Roche total Ig assay was combined with either the Diazyme IgM/IgG panel or the Abbott IgG assay, the positive predictive value was 100% while the negative predictive value remained greater than 99%. Conclusions Our data demonstrates that the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays have similar clinical performances. We demonstrated a low false-positive rate across all 3 platforms and observed that false positives observed on the Roche platform are unique compared to those observed on the Diazyme or Abbott assays. Using multiple platforms in tandem increases the PPVs, which is important when screening populations with low disease prevalence.

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