scholarly journals Has the Pandemic Triggered a ‘Paperdemic’? Towards an Assessment of Diagnostic Indicators for COVID-19

2021 ◽  
Author(s):  
AISDL
Keyword(s):  
Predictive Value ◽  
Diagnostic Testing ◽  
Supporting Evidence ◽  
The Novel ◽  
Scientific Publications ◽  
Widespread Belief ◽  
Novel Method ◽  
Consistency Problem ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

This paper is a preliminary step towards the assessment of an alarming widespread belief that victims of the novel coronavirus SARS-CoV-2 include the quality and accuracy of scientific publications about it. Our initial results suggest that this belief cannot be readily ignored, denied, dismissed or refuted, since some genuine supporting evidence can be forwarded for it. This evidence includes an obvious increase in retractions of papers published about the COVID-19 pandemic plus an extra-ordinary phenomenon of inconsistency that we report herein. In fact, we provide a novel method for validating any purported set of the four most prominent indicators of diagnostic testing (Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value), by observing that these indicators constitute three rather than four independent quantities. This observation has virtually been unheard of in the open medical literature, and hence researchers have not taken it into consideration. We define two functions, which serve as consistency criteria, since each of them checks consistency for any set of four numerical values (naturally belonging to the interval [0.0,1.0]) claimed to be the four basic diagnostic indicators. Most of the data we came across in various international journals met our criteria for consistency, but in a few cases, there were obvious unexplained blunders. We explored the same consistency problem for some diagnostic data published in 2020 concerning the ongoing COVID-19 pandemic and observed that the afore-mentioned unexplained blunders tended to be on the rise. A systematic extensive statistical assessment of this resumed tendency is warranted.

scholarly journals Has the Pandemic Triggered a ‘Paperdemic’? Towards an Assessment of Diagnostic Indicators for COVID-19

2021 ◽  
pp. 28-49
Author(s):  
Ali Muhammad Ali Rushdi ◽  
Hamzah Abdul Majid Serag
Keyword(s):  
Predictive Value ◽  
Diagnostic Testing ◽  
Supporting Evidence ◽  
The Novel ◽  
Scientific Publications ◽  
Widespread Belief ◽  
Novel Method ◽  
Consistency Problem ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

This paper is a preliminary step towards the assessment of an alarming widespread belief that victims of the novel coronavirus SARS-CoV-2 include the quality and accuracy of scientific publications about it. Our initial results suggest that this belief cannot be readily ignored, denied, dismissed or refuted, since some genuine supporting evidence can be forwarded for it. This evidence includes an obvious increase in retractions of papers published about the COVID-19 pandemic plus an extra-ordinary phenomenon of inconsistency that we report herein. In fact, we provide a novel method for validating any purported set of the four most prominent indicators of diagnostic testing (Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value), by observing that these indicators constitute three rather than four independent quantities. This observation has virtually been unheard of in the open medical literature, and hence researchers have not taken it into consideration. We define two functions, which serve as consistency criteria, since each of them checks consistency for any set of four numerical values (naturally belonging to the interval [0.0,1.0]) claimed to be the four basic diagnostic indicators. Most of the data we came across in various international journals met our criteria for consistency, but in a few cases, there were obvious unexplained blunders. We explored the same consistency problem for some diagnostic data published in 2020 concerning the ongoing COVID-19 pandemic and observed that the afore-mentioned unexplained blunders tended to be on the rise. A systematic extensive statistical assessment of this presumed tendency is warranted.

scholarly journals The Four Prominent Indicators of Diagnostic Testing: Consistency among their Values Reported in Saudi Medical Journals

2022 ◽  
Author(s):  
Hamzah Abdul Majid Serag ◽  
Ali Muhammad Ali Rushdi
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Medical Literature ◽  
Diagnostic Testing ◽  
Research Field ◽  
Medical Journals ◽  
General Issue ◽  
Novel Method ◽  
Sensitivity Specificity

We provide a novel method for validating any purported set of the four most prominent indicators of diagnostic testing (Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value), by observing that these indicators constitute three rather than four independent quantities. This observation has virtually been unheard of in the open medical literature. We defined two functions, which serve as consistency criteria, since each of them checks consistency for any set of four numerical values claimed to be the four basic diagnostic indicators. Most of the data we came across in various Saudi medical journals met our criteria for consistency, but in a few cases, there were obvious unexplained blunders. We relate our present findings to the more general issue of detection and ramifications of flawed, fabricated or wrong data. We observe that the research field handling the detection of flawed data is still in its infancy, and hope that this field will reach maturity very soon.

scholarly journals 458. Molecular SARS-CoV-2 Testing During the COVID-19 Outbreak: Experiences of a Hospital in Southeast Michigan, USA

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S296-S297
Author(s):  
Trini A Mathew ◽  
Jonathan Hopkins ◽  
Diane Kamerer ◽  
Shagufta N Ali ◽  
Daniel Ortiz ◽  
...  
Keyword(s):  
Clinical Features ◽  
Diagnostic Testing ◽  
Beaumont Hospital ◽  
High Capacity ◽  
Turnaround Time ◽  
Molecular Diagnostic ◽  
The Novel ◽  
Repeat Testing ◽  
Asymptomatic Patients ◽  
Novel Coronavirus

Abstract Background The novel Coronavirus SARS CoV-2 (COVID-19) outbreak was complicated by the lack of diagnostic testing kits. In early March 2020, leadership at Beaumont Hospital, Royal Oak Michigan (Beaumont) identified the need to develop high capacity testing modalities with appropriate sensitivity and specificity and rapid turnaround time. We describe the molecular diagnostic testing experience since initial rollout on March 16, 2020 at Beaumont, and results of repeat testing during the peak of the COVID-19 pandemic in MI. Methods Beaumont is an 1100 bed hospital in Southeast MI. In March, testing was initially performed with the EUA Luminex NxTAG CoV Extended Panel until March 28, 2020 when testing was converted to the EUA Cepheid Xpert Xpress SARS-CoV-2 for quicker turnaround times. Each assay was validated with a combination of patient samples and contrived specimens. Results During the initial week of testing there was > 20 % specimen positivity. As the prevalence grew the positivity rate reached 68% by the end of March (Figure 1). Many state and hospital initiatives were implemented during the outbreak, including social distancing and screening of asymptomatic patients to increase case-finding and prevent transmission. We also adopted a process for clinical review of symptomatic patients who initially tested negative for SARS-CoV-2 by a group of infectious disease physicians (Figure 2). This process was expanded to include other trained clinicians who were redeployed from other departments in the hospital. Repeat testing was performed to allow consideration of discontinuation of isolation precautions. During the surge of community cases from March 16 to April 30, 2020, we identified patients with negative PCR tests who subsequently had repeat testing based on clinical evaluation, with 7.1% (39/551) returning positive for SARS- CoV2. Of the patients who expired due to COVID-19 during this period, 4.3% (9/206) initially tested negative before ultimately testing positive. Figure 1 BH RO testing Epicurve Figure 2: Screening tool for repeat COVID19 testing and precautions Conclusion Many state and hospital initiatives helped us flatten the curve for COVID-19. Our hospital testing experience indicate that repeat testing may be warranted for those patients with clinical features suggestive of COVID-19. We will further analyze these cases and clinical features that prompted repeat testing. Disclosures All Authors: No reported disclosures

scholarly journals Prehospital identification of Covid-19: an observational study

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Douglas Spangler ◽  
Hans Blomberg ◽  
David Smekal
Keyword(s):  
Predictive Value ◽  
Prehospital Care ◽  
The Novel ◽  
Test Results ◽  
Care Providers ◽  
Care Systems ◽  
Primary Hospital ◽  
Novel Coronavirus ◽  
Rule Out ◽  
Descriptive Statistical Analysis

Abstract Background The novel coronavirus disease 2019 (Covid-19) pandemic has affected prehospital care systems across the world, but the prehospital presentation of affected patients and the extent to which prehospital care providers are able to identify them is not well characterized. In this study, we describe the presentation of Covid-19 patients in a Swedish prehospital care system, and asses the predictive value of Covid-19 suspicion as documented by dispatch and ambulance nurses. Methods Data for all patients with dispatch, ambulance, and hospital records between January 1–August 31, 2020 were extracted. A descriptive statistical analysis of patients with and without hospital-confirmed Covid-19 was performed. In a subset of records beginning from April 14, we assessed the sensitivity and specificity of documented Covid-19 suspicion in dispatch and ambulance patient care records. Results A total of 11,894 prehospital records were included, of which 481 had a primary hospital diagnosis code related to-, or positive test results for Covid-19. Covid-19-positive patients had considerably worse outcomes than patients with negative test results, with 30-day mortality rates of 24% vs 11%, but lower levels of prehospital acuity (e.g. emergent transport rates of 14% vs 22%). About half (46%) of Covid-19-positive patients presented to dispatchers with primary complaints typically associated with Covid-19. Six thousand seven hundred seventy-six records were included in the assessment of predictive value. Sensitivity was 76% (95% CI 71–80) and 82% (78–86) for dispatch and ambulance suspicion respectively, while specificities were 86% (85–87) and 78% (77–79). Conclusions While prehospital suspicion was strongly indicative of hospital-confirmed Covid-19, based on the sensitivity identified in this study, prehospital suspicion should not be relied upon as a single factor to rule out the need for isolation precautions. The data provided may be used to develop improved guidelines for identifying Covid-19 patients in the prehospital setting.

scholarly journals Pooling of coronavirus tests under unknown prevalence

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Pikovski ◽  
K. Bentele
Keyword(s):  
Diagnostic Testing ◽  
False Positives ◽  
Pool Size ◽  
The Novel ◽  
Average Model ◽  
Pooled Testing ◽  
Testing Protocol ◽  
Test Errors ◽  
Novel Coronavirus ◽  
Dilution Effects

Abstract Diagnostic testing for the novel coronavirus is an important tool to fight the coronavirus disease (Covid-19) pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are ‘pooled’ (i.e. grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. The results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.

scholarly journals A blueprint for academic laboratories to produce SARS-CoV-2 quantitative RT-PCR test kits

2020 ◽  
Vol 295 (46) ◽  
pp. 15438-15453 ◽  
Author(s):  
Samantha J. Mascuch ◽  
Sara Fakhretaha-Aval ◽  
Jessica C. Bowman ◽  
Minh Thu H. Ma ◽  
Gwendell Thomas ◽  
...  
Keyword(s):  
Support Group ◽  
Diagnostic Testing ◽  
The Novel ◽  
Rt Pcr ◽  
Research Teams ◽  
Environmental Testing ◽  
Resource Limited ◽  
Test Kit ◽  
Institute Of Technology ◽  
Novel Coronavirus

Widespread testing for the presence of the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in individuals remains vital for controlling the COVID-19 pandemic prior to the advent of an effective treatment. Challenges in testing can be traced to an initial shortage of supplies, expertise, and/or instrumentation necessary to detect the virus by quantitative RT-PCR (RT-qPCR), the most robust, sensitive, and specific assay currently available. Here we show that academic biochemistry and molecular biology laboratories equipped with appropriate expertise and infrastructure can replicate commercially available SARS-CoV-2 RT-qPCR test kits and backfill pipeline shortages. The Georgia Tech COVID-19 Test Kit Support Group, composed of faculty, staff, and trainees across the biotechnology quad at Georgia Institute of Technology, synthesized multiplexed primers and probes and formulated a master mix composed of enzymes and proteins produced in-house. Our in-house kit compares favorably with a commercial product used for diagnostic testing. We also developed an environmental testing protocol to readily monitor surfaces for the presence of SARS-CoV-2. Our blueprint should be readily reproducible by research teams at other institutions, and our protocols may be modified and adapted to enable SARS-CoV-2 detection in more resource-limited settings.

scholarly journals Diagnostic value of mean platelet volume in neonatal sepsis

2019 ◽  
Vol 59 (6) ◽  
pp. 289-93
Author(s):  
Kristopher May Pamudji ◽  
I Made Kardana
Keyword(s):  
Neonatal Sepsis ◽  
Predictive Value ◽  
Mean Platelet Volume ◽  
Severe Disease ◽  
Diagnostic Testing ◽  
Clinical Signs ◽  
Diagnostic Value ◽  
Platelet Volume ◽  
Good Potential ◽  
Sensitivity Specificity

Background Neonatal sepsis is a severe disease with potentially serious impacts if not treated early. However, the symptoms and clinical signs are not specific. Several studies have been conducted to find early infection markers for detection of neonatal sepsis, but without satisfactory results. Mean platelet volume (MPV) is a new marker of infection that has good potential for diagnosing neonatal sepsis. Objective To assess the diagnostic value of MPV in early detection of neonatal sepsis. Methods This retrospective study with diagnostic testing was done with data collected from medical records of neonates with neonatal sepsis who were admitted to the Neonatology Department in Sanglah Hospital, Denpasar from December 2018 to March 2019. Mean platelet volume cut-off point was determined using a receiver-operating characteristic (ROC) curve. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MPV in neonatal sepsis were determined using a 2x2 table. Results Of 82 subjects, 55 subjects were male (67%). Positive blood culture results were found in 25 subjects (30%). Mean platelet volume with a cut-off point of 7.44 fL had 80% sensitivity, 84.2% specificity, 69% PPV, and 90.6% NPV. Conclusion Mean platelet volume with a cut-off point of 7.44 fL can be used to diagnose neonatal sepsis with a sensitivity of 80% and specificity of 84.2%.

scholarly journals Diagnostic accuracy of the Novel 29 MHz micro-ultrasound “ExactVuTM” for the detection of clinically significant prostate cancer: A prospective single institutional study. A step forward in the diagnosis of prostate cancer

2021 ◽  
Vol 93 (2) ◽  
pp. 132-138
Author(s):  
Francesco Chessa ◽  
Riccardo Schiavina ◽  
Amelio Ercolino ◽  
Caterina Gaudiano ◽  
Davide Giusti ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Predictive Value ◽  
Transrectal Ultrasound ◽  
Peripheral Zone ◽  
Risk Identification ◽  
The Novel ◽  
Fusion Biopsy ◽  
Ultrasound System ◽  
Clinically Significant ◽  
Sensitivity Specificity

Introduction and Objective: ExactVuTM is a real-time micro-ultrasound system which provides, according to the Prostate Risk Identification Using Micro-Ultrasound protocol (PRI-MUS), a 300% higher resolution compared to conventional transrectal ultrasound. To evaluate the performance of ExactVuTM in the detection of Clinically significant Prostate Cancer (CsPCa). Materials and methods: Patients with Prostate Cancer diagnosed at fusion biopsy were imaged with ExactVuTM. CsPCa was defined as any Gleason Score ≥ 3+4. ExactVuTM examination was considered as positive when PRI-MUS score was ≥ 3. PRI-MUS scoring system was considered as correct when the fusion biopsy was positive for CsPCa. A transrectal fusion biopsy- proven CsPCa was considered as a gold standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operator characteristic (ROC) curve (AUC) were calculated. Results: 57 patients out of 68 (84%) had a csPCa. PRI-MUS score was correctly assessed in 68% of cases. Regarding the detection of CsPCa, ExactVuTM ’s sensitivity, specificity, PPV, and NPV was 68%, 73%, 93%, and 31%, respectively and the AUC was 0.7 (95% CI 0.5-0-8). For detecting CsPCa in the transition/ anterior zone the sensitivity, specificity, PPV, and NPV was 45%, 66%, 83% and 25% respectively ant the AUC was 0.5 (95% CI 0.2-0.9). Accounting only the CsPCa located in the peripheral zone, sensitivity, specificity, PPV, and NPV raised up to 74%, 75%, 94%, 33%, respectively with AUC 0.75 (95% CI 0.5-0-9). Conclusions: ExactVuTM provides high resolution of the prostatic peripheral zone and could represent a step forward in the detection of CsPCa as a triage tool. Further studies are needed to confirm these promising results.

scholarly journals Prehospital Identification of Covid-19: An Observational Study

2020 ◽  
Author(s):  
Douglas Nils Spangler ◽  
Hans Blomberg ◽  
David Smekal
Keyword(s):  
Predictive Value ◽  
Prehospital Care ◽  
The Novel ◽  
Test Results ◽  
Care Providers ◽  
Care Systems ◽  
Primary Hospital ◽  
Novel Coronavirus ◽  
Rule Out ◽  
Descriptive Statistical Analysis

Abstract Background The novel coronavirus disease 2019 (Covid-19) pandemic has affected prehospital care systems across the world, but the prehospital presentation of affected patients and the extent to which prehospital care providers are able to identify them is not well characterized. In this study, we describe the presentation of Covid-19 patients in a Swedish prehospital care system, and asses the predictive value of Covid-19 suspicion as documented by dispatch and ambulance nurses.Methods Data for all patients with dispatch, ambulance, and hospital records between January 1 - August 31, 2020 were extracted. A descriptive statistical analysis of patients with and without hospital-confirmed Covid-19 was performed. In a subset of records beginning from April 14, we assessed the sensitivity and specificity of documented Covid-19 suspicion in dispatch and ambulance patient care records.Results A total of 11 894 prehospital records were included, of which 481 had a primary hospital diagnosis code related to-, or positive test results for Covid-19. Covid-19-positive patients had considerably worse outcomes than patients with negative test results, with 30-day mortality rates of 24% vs 11%, but lower levels of prehospital acuity (e.g. emergent transport rates of 14% vs 22%). About half (46%) of Covid-19-positive patients presented to dispatchers with primary complaints typically associated with Covid-19. 6 776 of records were included in the assessment of predictive value. Sensitivity was 76% (95% CI 71 - 80) and 82% (78 - 86) for dispatch and ambulance suspicion respectively, while specificities were 86% (85 - 87) and 78% (77 - 79).Conclusions While prehospital suspicion was strongly indicative of hospital-confirmed Covid-19, based on the sensitivity identified in this study, prehospital suspicion should not be relied upon as a single factor to rule out the need for isolation precautions. The data provided may be used to develop improved guidelines for identifying Covid-19 patients in the prehospital setting.

scholarly journals Multiobjective Genetic Algorithm and Convolutional Neural Network Based COVID-19 Identification in Chest X-Ray Images

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Prashant Kumar Shukla ◽  
Jasminder Kaur Sandhu ◽  
Anamika Ahirwar ◽  
Deepika Ghai ◽  
Priti Maheshwary ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Diagnostic Testing ◽  
The Novel ◽  
Screening Process ◽  
X Ray ◽  
Multiobjective Genetic Algorithm ◽  
Global Pandemic ◽  
Chest X Ray ◽  
Novel Coronavirus ◽  
Fold Cross Validation

COVID-19 is a new disease, caused by the novel coronavirus SARS-CoV-2, that was firstly delineated in humans in 2019.Coronaviruses cause a range of illness in patients varying from common cold to advanced respiratory syndromes such as Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV). The SARS-CoV-2 outbreak has resulted in a global pandemic, and its transmission is increasing at a rapid rate. Diagnostic testing and approaches provide a valuable tool for doctors and support them with the screening process. Automatic COVID-19 identification in chest X-ray images can be useful to test for COVID-19 infection at a good speed. Therefore, in this paper, a framework is designed by using Convolutional Neural Networks (CNN) to diagnose COVID-19 patients using chest X-ray images. A pretrained GoogLeNet is utilized for implementing the transfer learning (i.e., by replacing some sets of final network CNN layers). 20-fold cross-validation is considered to overcome the overfitting quandary. Finally, the multiobjective genetic algorithm is considered to tune the hyperparameters of the proposed COVID-19 identification in chest X-ray images. Extensive experiments show that the proposed COVID-19 identification model obtains remarkably better results and may be utilized for real-time testing of patients.

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