scholarly journals An Online Calculator to Better Understand the Impact of False-Negative COVID-19 Polymerase Chain Reaction Test Results in the Context of Anesthesia Providers (Preprint)

2020 ◽  
Author(s):  
Sean Runnels ◽  
John Frederick Pearson ◽  
Jon Dean Samuels ◽  
Rohan Kirit Panchamia
Keyword(s):  
False Negative ◽  
Polymerase Chain Reaction Test ◽  
Test Results ◽  
Anesthesia Providers ◽  
Reaction Test ◽  
Online Calculator ◽  
Polymerase Chain ◽  
Exposure Problem ◽  
Chain Reaction Test ◽  
The Impact

UNSTRUCTURED What does the COVID-19 false-negative exposure problem mean in the context of a local anesthesia practice? We present a customizable online calculator designed to quantify and better understand individual and aggregate provider exposure risk.

scholarly journals An Online Calculator to Better Understand the Impact of False-Negative COVID-19 Polymerase Chain Reaction Test Results in the Context of Anesthesia Providers

10.2196/26316 ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. e26316
Author(s):  
Sean Runnels ◽  
John Frederick Pearson ◽  
Jon Dean Samuels ◽  
Rohan Kirit Panchamia
Keyword(s):  
False Negative ◽  
Polymerase Chain Reaction Test ◽  
Test Results ◽  
Anesthesia Providers ◽  
Reaction Test ◽  
Online Calculator ◽  
Polymerase Chain ◽  
Exposure Problem ◽  
Chain Reaction Test ◽  
The Impact

What does the COVID-19 false-negative exposure problem mean in the context of a local anesthesia practice? We present a customizable online calculator designed to quantify and better understand individual and aggregate provider exposure risk.

scholarly journals AI-Empowered Computational Examination of Chest Imaging for COVID-19 Treatment: A Review

2021 ◽  
Vol 4 ◽  
Author(s):  
Hanqiu Deng ◽  
Xingyu Li
Keyword(s):  
False Negative ◽  
Screening Tools ◽  
Polymerase Chain Reaction Test ◽  
Test Results ◽  
First Case ◽  
Lung Scan ◽  
Screening Efficiency ◽  
Polymerase Chain ◽  
Chain Reaction Test ◽  
Full Swing

Since the first case of coronavirus disease 2019 (COVID-19) was discovered in December 2019, COVID-19 swiftly spread over the world. By the end of March 2021, more than 136 million patients have been infected. Since the second and third waves of the COVID-19 outbreak are in full swing, investigating effective and timely solutions for patients’ check-ups and treatment is important. Although the SARS-CoV-2 virus-specific reverse transcription polymerase chain reaction test is recommended for the diagnosis of COVID-19, the test results are prone to be false negative in the early course of COVID-19 infection. To enhance the screening efficiency and accessibility, chest images captured via X-ray or computed tomography (CT) provide valuable information when evaluating patients with suspected COVID-19 infection. With advanced artificial intelligence (AI) techniques, AI-driven models training with lung scans emerge as quick diagnostic and screening tools for detecting COVID-19 infection in patients. In this article, we provide a comprehensive review of state-of-the-art AI-empowered methods for computational examination of COVID-19 patients with lung scans. In this regard, we searched for papers and preprints on bioRxiv, medRxiv, and arXiv published for the period from January 1, 2020, to March 31, 2021, using the keywords of COVID, lung scans, and AI. After the quality screening, 96 studies are included in this review. The reviewed studies were grouped into three categories based on their target application scenarios: automatic detection of coronavirus disease, infection segmentation, and severity assessment and prognosis prediction. The latest AI solutions to process and analyze chest images for COVID-19 treatment and their advantages and limitations are presented. In addition to reviewing the rapidly developing techniques, we also summarize publicly accessible lung scan image sets. The article ends with discussions of the challenges in current research and potential directions in designing effective computational solutions to fight against the COVID-19 pandemic in the future.

scholarly journals Evaluation of the Criteria Adopted to Identify Suspected Cases of COVID-19 in the Emergency Department Service of a Referral Palliative Oncology Care Unit

2020 ◽  
Vol 38 (2) ◽  
pp. 199-203
Author(s):  
Simone Garruth dos Santos Machado Sampaio ◽  
Andréa Marins Dias ◽  
Renata de Freitas ◽  
Alessandra Zanei Borsatto ◽  
Elisa Maffioletti Furtunato Leocádio Esteves ◽  
...  
Keyword(s):  
Emergency Department ◽  
False Negative ◽  
Polymerase Chain Reaction Test ◽  
Clinical Criteria ◽  
Palliative Oncology ◽  
Reaction Test ◽  
Oncology Care ◽  
Great Relevance ◽  
Polymerase Chain ◽  
Chain Reaction Test

Context: Due to the need for isolation of inpatients with suspected COVID-19, accuracy in identifying these cases in Emergency Department (ED) has great relevance, especially in Palliative Oncology Care Unit (PCU). Objective: To evaluate the efficiency of clinical criteria adopted to identify suspected cases of COVID-19 by the ED in PCU. Methods: All patients admitted to PCU between April and June 2020 from ED were included. The clinical criteria adopted to identify suspected COVID-19 cases were: being in contact with a suspected or confirmed case less than 14 days ago and / or presenting fever with no defined focus and / or respiratory symptoms not explained by oncological disease and / or suggestive image in radiological examination (if necessary). All suspected cases were submitted to deep nasal and throat swab for SARS COV-2 investigation by Reverse Transcription Polymerase Chain Reaction Test, adopted as gold standard. Inpatients hospitalized by ED, without suspicion, and then diagnosed with COVID-19 within 10 days of hospitalization were considered as false-negative cases. Results: During the period, 327 patients were admitted from ED. Of these, 69 (21%) were considered suspects, of whom 34 (49%) tested positive for COVID-19. The sensitivity of the clinical criterion to identify suspected cases was 87%, specificity was 88%, positive predictive value was 49%, negative was 98% and accuracy was 88%. Conclusion: The clinical criteria adopted to identify suspected cases of COVID-19 at ED proved to be efficient, with low risk of spreading in-hospital infection, avoiding unnecessary isolation of patients.

scholarly journals High Prevalence of Sars-Cov-2 Infection In Patients Undergoing Cataract Surgery

2021 ◽  
Author(s):  
ŞERİFE GÜLHAN KONUK ◽  
RAŞİT KILIÇ ◽  
FATİH KAYA ◽  
ALPER GÜNEŞ
Keyword(s):  
Cataract Surgery ◽  
Healthcare Professionals ◽  
Adverse Outcomes ◽  
Polymerase Chain Reaction Test ◽  
Test Results ◽  
High Prevalence ◽  
Reaction Test ◽  
Study Population ◽  
Polymerase Chain ◽  
Chain Reaction Test

Abstract PurposeThe coronavirus disease 2019 (COVID-19) prevalence has rapidly been increased worldwide in the last a few months. Asymptomatic COVID-19 cases scheduled for elective surgeries can be a risk factor for the healthcare professionals. The aim of this study was to estimate the prevalence of SARS-CoV-2 infection in patients undergoing cataract surgery.MethodsPatients scheduled for cataract surgery in months of November and December 2020 were included in the study. COVID 19 PCR (polymerase chain reaction) test was taken routinely from all patients within 48 hours before the operation date. ResultIn this study, 151 patients who planned cataract surgery were included. The average age of the patients was 64,6±12,6 years. The study population consisted of 94 (%62,3)men and 57 (%37,7) women. According to COVID 19 PCR test results, there were 16 (%10.6) positive cases. All cases were asymptomatic.ConclusionsAsymptomatic covid patients continue to be contagious. We need to be careful when taking elective cases to minimize the risk of adverse outcomes after surgery and transmission of viruses to medical staff and other patients.

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