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Showing papers on "Mass screening published in 2021"


Book
23 Apr 2021
TL;DR: Studies from past decades related to such translational research as the use of hydroxyurea in treatment, as well as the therapeutic promise of red-cell ion-channel blockers, and antiadhesion and anti-inflammatory therapy are highlighted.
Abstract: Sickle-cell disease is one of the most common severe monogenic disorders in the world. Haemoglobin polymerisation, leading to erythrocyte rigidity and vaso-occlusion, is central to the pathophysiology of this disease, although the importance of chronic anaemia, haemolysis, and vasculopathy has been established. Clinical management is basic and few treatments have a robust evidence base. One of the main problems of sickle-cell disease in children is the development of cerebrovascular disease and cognitive impairment, and the role of blood transfusion and hydroxycarbamide for prevention of these complications is starting to be understood. Recurrent episodes of vaso-occlusion and inflammation result in progressive damage to most organs, including the brain, kidneys, lungs, bones, and cardiovascular system, which becomes apparent with increasing age. Most people with sickle-cell disease live in Africa, where little is known about this disease; however, we do know that the disorder follows a more severe clinical course in Africa than for the rest of the world and that infectious diseases have a role in causing this increased severity of sickle-cell disease. More work is needed to develop effective treatments that specifically target pathophysiological changes and clinical complications of sickle-cell disease.

966 citations


Journal ArticleDOI
TL;DR: It is demonstrated that effective screening depends largely on frequency of testing and speed of reporting and is only marginally improved by high test sensitivity, and should prioritize accessibility, frequency, and sample-to-answer time.
Abstract: The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with presymptomatic, symptomatic, and asymptomatic infections, the reopening of societies and the control of virus spread will be facilitated by robust population screening, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are too low to detect, followed by exponential viral growth, leading to peak viral load and infectiousness and ending with declining titers and clearance. Given the pattern of viral load kinetics, we model the effectiveness of repeated population screening considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective screening depends largely on frequency of testing and speed of reporting and is only marginally improved by high test sensitivity. We therefore conclude that screening should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.

891 citations


Journal ArticleDOI
TL;DR: The authors in this paper found that at least one third of SARS-CoV-2 infections are asymptomatic, which is the highest quality evidence from nationwide, representative serosurveys of England (n = 365  104) and Spain (n = 61Â075).
Abstract: BACKGROUND: Asymptomatic infection seems to be a notable feature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), but the prevalence is uncertain. PURPOSE: To estimate the proportion of persons infected with SARS-CoV-2 who never develop symptoms. DATA SOURCES: Searches of Google News, Google Scholar, medRxiv, and PubMed using the keywords antibodies, asymptomatic, coronavirus, COVID-19, PCR, seroprevalence, and SARS-CoV-2. STUDY SELECTION: Observational, descriptive studies and reports of mass screening for SARS-CoV-2 that were either cross-sectional or longitudinal in design; were published through 17 November 2020; and involved SARS-CoV-2 nucleic acid or antibody testing of a target population, regardless of current symptomatic status, over a defined period. DATA EXTRACTION: The authors collaboratively extracted data on the study design, type of testing performed, number of participants, criteria for determining symptomatic status, testing results, and setting. DATA SYNTHESIS: Sixty-one eligible studies and reports were identified, of which 43 used polymerase chain reaction (PCR) testing of nasopharyngeal swabs to detect current SARS-CoV-2 infection and 18 used antibody testing to detect current or prior infection. In the 14 studies with longitudinal data that reported information on the evolution of symptomatic status, nearly three quarters of persons who tested positive but had no symptoms at the time of testing remained asymptomatic. The highest-quality evidence comes from nationwide, representative serosurveys of England (n = 365 104) and Spain (n = 61 075), which suggest that at least one third of SARS-CoV-2 infections are asymptomatic. LIMITATION: For PCR-based studies, data are limited to distinguish presymptomatic from asymptomatic infection. Heterogeneity precluded formal quantitative syntheses. CONCLUSION: Available data suggest that at least one third of SARS-CoV-2 infections are asymptomatic. Longitudinal studies suggest that nearly three quarters of persons who receive a positive PCR test result but have no symptoms at the time of testing will remain asymptomatic. Control strategies for COVID-19 should be altered, taking into account the prevalence and transmission risk of asymptomatic SARS-CoV-2 infection. PRIMARY FUNDING SOURCE: National Institutes of Health.

367 citations


Journal ArticleDOI
TL;DR: A smartphone app that combines smartwatch and activity tracker data together with self-reported symptoms allows continuous monitoring of SARS-CoV-2 infection and finds that a combination of symptom and sensor data resulted in an area under the curve (AUC) of 0.80, which is significantly better than a model 1 that considers symptoms alone.
Abstract: Traditional screening for COVID-19 typically includes survey questions about symptoms and travel history, as well as temperature measurements. Here, we explore whether personal sensor data collected over time may help identify subtle changes indicating an infection, such as in patients with COVID-19. We have developed a smartphone app that collects smartwatch and activity tracker data, as well as self-reported symptoms and diagnostic testing results, from individuals in the United States, and have assessed whether symptom and sensor data can differentiate COVID-19 positive versus negative cases in symptomatic individuals. We enrolled 30,529 participants between 25 March and 7 June 2020, of whom 3,811 reported symptoms. Of these symptomatic individuals, 54 reported testing positive and 279 negative for COVID-19. We found that a combination of symptom and sensor data resulted in an area under the curve (AUC) of 0.80 (interquartile range (IQR): 0.73-0.86) for discriminating between symptomatic individuals who were positive or negative for COVID-19, a performance that is significantly better (P < 0.01) than a model1 that considers symptoms alone (AUC = 0.71; IQR: 0.63-0.79). Such continuous, passively captured data may be complementary to virus testing, which is generally a one-off or infrequent sampling assay.

282 citations


Journal ArticleDOI
TL;DR: This overview examines genetic changes, potential and established predictive and prognostic markers and end results of surgery, radiotherapy and systemic therapy for early, locally advanced and metastatic disease stages in Egyptian women.
Abstract: Carcinoma of the breast is the most prevalent cancer among Egyptian women and constitutes 29% of National Cancer Institute cases. Median age at diagnosis is one decade younger than in countries of Europe and North America and most patients are premenopausal. Tumours are relatively advanced at presentation. The majority of tumours are invasive duct subtype and the profile of hormone receptors is positive for estrogen receptors and/or progesterone receptors in less than half of cases. This overview examines genetic changes, potential and established predictive and prognostic markers and end results of surgery, radiotherapy and systemic therapy for early, locally advanced and metastatic disease stages. Disease presentations common to the region and early detection strategies are presented.

148 citations


Journal ArticleDOI
12 Jan 2021-JAMA
TL;DR: Open-angle and narrow-angle forms of glaucoma are reviewed in this article, including a description of the pathophysiology, risk factors, screening, disease monitoring, and treatment options.
Abstract: Importance Glaucoma is the most common cause of irreversible blindness worldwide. Many patients with glaucoma are asymptomatic early in the disease course. Primary care clinicians should know which patients to refer to an eye care professional for a complete eye examination to check for signs of glaucoma and to determine what systemic conditions or medications can increase a patient’s risk of glaucoma. Open-angle and narrow-angle forms of glaucoma are reviewed, including a description of the pathophysiology, risk factors, screening, disease monitoring, and treatment options. Observations Glaucoma is a chronic progressive optic neuropathy, characterized by damage to the optic nerve and retinal nerve fiber layer, that can lead to permanent loss of peripheral or central vision. Intraocular pressure is the only known modifiable risk factor. Other important risk factors include older age, nonwhite race, and a family history of glaucoma. Several systemic medical conditions and medications including corticosteroids, anticholinergics, certain antidepressants, and topiramate may predispose patients to glaucoma. There are 2 broad categories of glaucoma, open-angle and angle-closure glaucoma. Diagnostic testing to assess for glaucoma and to monitor for disease progression includes measurement of intraocular pressure, perimetry, and optical coherence tomography. Treatment of glaucoma involves lowering intraocular pressure. This can be achieved with various classes of glaucoma medications as well as laser and incisional surgical procedures. Conclusions and Relevance Vision loss from glaucoma can be minimized by recognizing systemic conditions and medications that increase a patient’s risk of glaucoma and referring high-risk patients for a complete ophthalmologic examination. Clinicians should ensure that patients remain adherent with taking glaucoma medications and should monitor for adverse events from medical or surgical interventions used to treat glaucoma.

148 citations


Journal ArticleDOI
TL;DR: Self-collected saliva is a valuable specimen to detect SARS-CoV-2 in mass screening of asymptomatic persons because of its high sensitivity and specificity.
Abstract: Background Coronavirus disease 2019 (COVID-19) has rapidly evolved to become a global pandemic, largely owing to the transmission of its causative virus through asymptomatic carriers. Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of polymerase chain reaction testing. In addition, although self-collected saliva samples have significant logistical advantages in mass screening, their utility as an alternative specimen in asymptomatic persons is yet to be determined. Methods We conducted a mass screening study to compare the utility of nucleic acid amplification, such as reverse-transcription polymerase chain reaction testing, using nasopharyngeal swab (NPS) and saliva samples from each individual in 2 cohorts of asymptomatic persons: the contact-tracing cohort and the airport quarantine cohort. Results In this mass screening study including 1924 individuals, the sensitivities of nucleic acid amplification testing with NPS and saliva specimens were 86% (90% credible interval, 77%-93%) and 92% (83%-97%), respectively, with specificities >99.9%. The true concordance probability between the NPS and saliva tests was estimated at 0.998 (90% credible interval, .996-.999) given the recent airport prevalence of 0.3%. In individuals testing positive, viral load was highly correlated between NPS and saliva specimens. Conclusion Both NPS and saliva specimens had high sensitivity and specificity. Self-collected saliva specimens are valuable for detecting SARS-CoV-2 in mass screening of asymptomatic persons.

139 citations


Journal ArticleDOI
TL;DR: This combinatorial approach may include rhizosphere engineering by addition of drought-tolerant bacteria, nanoparticles, liquid nano clay, nutrients, organic matter, along with plant-modification with next-generation genome editing tool (e.g., CRISPR/Cas9) for quickly addressing emerging challenges in agriculture.

120 citations


Journal ArticleDOI
TL;DR: In this paper, the authors proposed universal screening for gestational diabetes mellitus, which is associated with an increased risk of adverse maternal and perinatal outcomes, although universal screening is not recommended.
Abstract: Background Gestational diabetes mellitus is common and is associated with an increased risk of adverse maternal and perinatal outcomes. Although experts recommend universal screening for g...

117 citations


Journal ArticleDOI
TL;DR: An audit of the impact of the COVID-19 pandemic-related delay in the diagnosis of major cancers at a Pathology Unit of a Secondary Care Hospital Network in Italy found that cancer diagnoses fell in 2020 by 39% compared with the average number recorded in 2018 and 2019.
Abstract: Aims We performed an audit to evaluate the impact of the COVID-19 pandemic-related delay in the diagnosis of major cancers at a Pathology Unit of a Secondary Care Hospital Network in Italy. Methods A comparison was made among the number of first cellular pathological diagnoses of malignancy made from the 11th to the 20th week of the years 2018–2020. Results Cancer diagnoses fell in 2020 by 39% compared with the average number recorded in 2018 and 2019. Prostate cancer (75%) bladder cancer (66%) and colorectal cancer (CRC; 62%) had the greatest decrease. CRC was identified as carrying a potentially important diagnostic delay. Conclusions For CRC corrective procedures (continuing mass screening tests; patient triage by family physicians; diagnostic procedures alternative to colonoscopy; predictive evaluation on biopsy samples) were advised. Our simple audit model is widely applicable to avoid pandemic-related delay in clinical diagnosis of cancer.

107 citations


Journal ArticleDOI
TL;DR: A light-weight Convolutional Neural Network (CNN)-tailored shallow architecture that can automatically detect COVID-19 positive cases using chest X-rays, with no false positive, and the current results were better than other deep learning models and state-of-the-art works.
Abstract: Among radiological imaging data, Chest X-rays (CXRs) are of great use in observing COVID-19 manifestations. For mass screening, using CXRs, a computationally efficient AI-driven tool is the must to detect COVID-19-positive cases from non-COVID ones. For this purpose, we proposed a light-weight Convolutional Neural Network (CNN)-tailored shallow architecture that can automatically detect COVID-19-positive cases using CXRs, with no false negatives. The shallow CNN-tailored architecture was designed with fewer parameters as compared to other deep learning models. The shallow CNN-tailored architecture was validated using 321 COVID-19-positive CXRs. In addition to COVID-19-positive cases, another set of non-COVID-19 5856 cases (publicly available, source: Kaggle) was taken into account, consisting of normal, viral, and bacterial pneumonia cases. In our experimental tests, to avoid possible bias, 5-fold cross-validation was followed, and both balanced and imbalanced datasets were used. The proposed model achieved the highest possible accuracy of 99.69%, sensitivity of 1.0, where AUC was 0.9995. Furthermore, the reported false positive rate was only 0.0015 for 5856 COVID-19-negative cases. Our results stated that the proposed CNN could possibly be used for mass screening. Using the exact same set of CXR collection, the current results were better than other deep learning models and major state-of-the-art works.

Journal ArticleDOI
TL;DR: The data highlight the need to reorganize efforts against high-impact diseases such as CRC, considering possible future waves of SARS-CoV-2 or other pandemics, and also mortality if lasting beyond 12 months.

Journal ArticleDOI
TL;DR: In this paper, the authors discuss the epidemiology, management and outcomes of the most common aortic diseases, namely, acute and chronic aneurysms and acute aortric syndromes.
Abstract: The aorta is the 'greatest artery', through which oxygenated blood is delivered from the left ventricle to end organs with each cardiac cycle (200 million litres of blood transported in an average lifetime). The aorta can be affected by a wide spectrum of acute factors (such as cocaine use, weight lifting and trauma) and chronic acquired and/or genetic conditions (such as systemic arterial hypertension and phaeochromocytoma), which variously lead to increased aortic wall stress. The medial layer of the aorta can also be subject to abnormalities (such as Marfan syndrome, bicuspid aortic valve, inflammatory vasculitis, atherosclerosis and infections). Despite important advances in diagnostic and therapeutic interventions, data derived from registries and population-based studies highlight that the burden of aortic diseases remains high. Therefore, specific resources need to be allocated to design and implement preventive strategies (healthy lifestyles, modifications to cardiovascular risk factors, and educational and screening programmes) at individual and community levels. In this Review, we discuss the epidemiology, management and outcomes of the most common aortic diseases, namely, aortic aneurysms and acute aortic syndromes.

Journal ArticleDOI
01 Feb 2021
TL;DR: Two early-detection models for COVID-19 were developed and validated, screening for the disease among patients attending the emergency department and the subset being admitted to hospital, using routinely collected health-care data (laboratory tests, blood gas measurements, and vital signs).
Abstract: Summary Background The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, viral-specific PCR testing has limited sensitivity and results can take up to 72 h for operational reasons. We aimed to develop and validate two early-detection models for COVID-19, screening for the disease among patients attending the emergency department and the subset being admitted to hospital, using routinely collected health-care data (laboratory tests, blood gas measurements, and vital signs). These data are typically available within the first hour of presentation to hospitals in high-income and middle-income countries, within the existing laboratory infrastructure. Methods We trained linear and non-linear machine learning classifiers to distinguish patients with COVID-19 from pre-pandemic controls, using electronic health record data for patients presenting to the emergency department and admitted across a group of four teaching hospitals in Oxfordshire, UK (Oxford University Hospitals). Data extracted included presentation blood tests, blood gas testing, vital signs, and results of PCR testing for respiratory viruses. Adult patients (>18 years) presenting to hospital before Dec 1, 2019 (before the first COVID-19 outbreak), were included in the COVID-19-negative cohort; those presenting to hospital between Dec 1, 2019, and April 19, 2020, with PCR-confirmed severe acute respiratory syndrome coronavirus 2 infection were included in the COVID-19-positive cohort. Patients who were subsequently admitted to hospital were included in their respective COVID-19-negative or COVID-19-positive admissions cohorts. Models were calibrated to sensitivities of 70%, 80%, and 90% during training, and performance was initially assessed on a held-out test set generated by an 80:20 split stratified by patients with COVID-19 and balanced equally with pre-pandemic controls. To simulate real-world performance at different stages of an epidemic, we generated test sets with varying prevalences of COVID-19 and assessed predictive values for our models. We prospectively validated our 80% sensitivity models for all patients presenting or admitted to the Oxford University Hospitals between April 20 and May 6, 2020, comparing model predictions with PCR test results. Findings We assessed 155 689 adult patients presenting to hospital between Dec 1, 2017, and April 19, 2020. 114 957 patients were included in the COVID-negative cohort and 437 in the COVID-positive cohort, for a full study population of 115 394 patients, with 72 310 admitted to hospital. With a sensitive configuration of 80%, our emergency department (ED) model achieved 77·4% sensitivity and 95·7% specificity (area under the receiver operating characteristic curve [AUROC] 0·939) for COVID-19 among all patients attending hospital, and the admissions model achieved 77·4% sensitivity and 94·8% specificity (AUROC 0·940) for the subset of patients admitted to hospital. Both models achieved high negative predictive values (NPV; >98·5%) across a range of prevalences (≤5%). We prospectively validated our models for all patients presenting and admitted to Oxford University Hospitals in a 2-week test period. The ED model (3326 patients) achieved 92·3% accuracy (NPV 97·6%, AUROC 0·881), and the admissions model (1715 patients) achieved 92·5% accuracy (97·7%, 0·871) in comparison with PCR results. Sensitivity analyses to account for uncertainty in negative PCR results improved apparent accuracy (ED model 95·1%, admissions model 94·1%) and NPV (ED model 99·0%, admissions model 98·5%). Interpretation Our models performed effectively as a screening test for COVID-19, excluding the illness with high-confidence by use of clinical data routinely available within 1 h of presentation to hospital. Our approach is rapidly scalable, fitting within the existing laboratory testing infrastructure and standard of care of hospitals in high-income and middle-income countries. Funding Wellcome Trust, University of Oxford, Engineering and Physical Sciences Research Council, National Institute for Health Research Oxford Biomedical Research Centre.

Journal ArticleDOI
TL;DR: In this article, the authors examined COVID-19's impact on NBCCEDP screening services during January-June 2020 and found that the total number of screened women in the United States dropped by 87% and 84% during April 2020 compared with the previous 5-year averages for that month.

Journal ArticleDOI
TL;DR: In this paper, the authors designed a randomized controlled open-label trial to assess the effectiveness of a comprehensive preventive intervention for a mass-gathering indoor event (a live concert) based on systematic same-day screening of attendees with antigen-detecting rapid diagnostic tests (Ag-RDTs), use of facial masks, and adequate air ventilation.
Abstract: Summary Background The banning of mass-gathering indoor events to prevent SARS-CoV-2 spread has had an important effect on local economies Despite growing evidence on the suitability of antigen-detecting rapid diagnostic tests (Ag-RDT) for mass screening at the event entry, this strategy has not been assessed under controlled conditions We aimed to assess the effectiveness of a prevention strategy during a live indoor concert Methods We designed a randomised controlled open-label trial to assess the effectiveness of a comprehensive preventive intervention for a mass-gathering indoor event (a live concert) based on systematic same-day screening of attendees with Ag-RDTs, use of facial masks, and adequate air ventilation The event took place in the Sala Apolo, Barcelona, Spain Adults aged 18–59 years with a negative result in an Ag-RDT from a nasopharyngeal swab collected immediately before entering the event were randomised 1:1 (block randomisation stratified by age and gender) to either attend the indoor event for 5 hours or go home Nasopharyngeal specimens used for Ag-RDT screening were analysed by real-time reverse-transcriptase PCR (RT-PCR) and cell culture (Vero E6 cells) 8 days after the event, a nasopharyngeal swab was collected and analysed by Ag-RDT, RT-PCR, and a transcription-mediated amplification test (TMA) The primary outcome was the difference in incidence of RT-PCR-confirmed SARS-CoV-2 infection at 8 days between the control and the intervention groups, assessed in all participants who were randomly assigned, attended the event, and had a valid result for the SARS-CoV-2 test done at follow-up The trial is registered at ClinicalTrialsgov, NCT04668625 Findings Participant enrollment took place during the morning of the day of the concert, Dec 12, 2020 Of the 1140 people who responded to the call and were deemed eligible, 1047 were randomly assigned to either enter the music event (experimental group) or continue with normal life (control group) Of the 523 randomly assigned to the experimental group, 465 were included in the analysis of the primary outcome (51 did not enter the event and eight did not take part in the follow-up assessment), and of the 524 randomly assigned to the control group, 495 were included in the final analysis (29 did not take part in the follow-up) At baseline, 15 (3%) of 495 individuals in the control group and 13 (3%) of 465 in the experimental group tested positive on TMA despite a negative Ag-RDT result The RT-PCR test was positive in one case in each group and cell viral culture was negative in all cases 8 days after the event, two ( Interpretation Our study provides preliminary evidence on the safety of indoor mass-gathering events during a COVID-19 outbreak under a comprehensive preventive intervention The data could help restart cultural activities halted during COVID-19, which might have important sociocultural and economic implications Funding Primavera Sound Group and the #YoMeCorono Initiative Translation For the Spanish translation of the abstract see Supplementary Materials section

Journal ArticleDOI
TL;DR: Oral cancer is a major public health problem and there is an increasing trend for oral cancer to affect young men and women as mentioned in this paper, and many patients present with late-stage disease, contributing to high mortality.
Abstract: Oral cancer is a major public health problem, and there is an increasing trend for oral cancer to affect young men and women. Public awareness is poor, and many patients present with late-stage disease, contributing to high mortality. Oral cancer is often preceded by a clinical premalignant phase accessible to visual inspection, and thus there are opportunities for earlier detection and to reduce morbidity and mortality. Screening asymptomatic individuals by systematic visual oral examinations to detect the disease has been shown to be feasible. A positive screen includes both oral cancer and oral potentially malignant disorders. We review key screening studies undertaken, including 1 randomized clinical trial. Screening of high-risk groups is cost-effective. Strengths and weaknesses of oral cancer screening studies are presented to help guide new research in primary care settings and invigorated by the prospect of using emerging new technologies that may help to improve discriminatory accuracy of case detection. Most national organizations, including the US Preventive Services Task Force, have so far not recommended population-based screening due a lack of sufficient evidence that screening leads to a reduction in oral cancer mortality. Where health care resources are high, opportunistic screening in dental practices is recommended, although the paucity of research in primary care is alarming. The results of surveys suggest that dentists do perform oral cancer screenings, but there is only weak evidence that screening in dental practices leads to downstaging of disease. Where health care resources are low, the feasibility of using primary health care workers for oral cancer screening has been tested, and measures indicate good outcomes. Most studies reported in the literature are based on 1 round of screening, whereas screening should be a continuous process. This review identifies a huge potential for new research directions on screening for oral cancer.

Journal ArticleDOI
TL;DR: In this article, a random effects model was applied to analyze pooled data on the prevalence of asymptomatic cases among all COVID-19 patients and also by age and gender.
Abstract: Asymptomatic cases of SARS-CoV-2 can be unknown carriers magnifying the transmission of COVID-19. This study appraised the frequency of asymptomatic individuals and estimated occurrence by age group and gender by reviewing the existing published data on asymptomatic people with COVID-19. Three electronic databases, PubMed, Embase, and Web of Science (WoS), were used to search the literature following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The study population for this review included asymptomatic individuals infected with SARS-CoV-2 reported in original articles published up to 30 April 2020. A random effects model was applied to analyze pooled data on the prevalence of asymptomatic cases among all COVID-19 patients and also by age and gender. From the meta-analysis of 16 studies, comprising 2,788 SARS-CoV-2 infected patients, the pooled prevalence according to the random effect size of asymptomatic cases was 48.2% (95% CI, 30-67%). Of the asymptomatic cases, 55.5% (95% CI, 43.6-66.8%) were female and 49.6% (95% CI, 20.5-79.1%) were children. Children and females were more likely to present as asymptomatic COVID-19 cases and could act as unknown carriers of SARS-CoV-2. Symptom-based screening might fail to identify all SARS-CoV-2 infections escalating the threat of global spread and impeding containment. Therefore, a mass surveillance system to track asymptomatic cases is critical, with special attention to females and children.

Journal ArticleDOI
01 May 2021-Gut
TL;DR: A serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer, is developed and validated and is cost- effective for mass screening relative to current practice (incremental cost-effectiveness ratio=US$44 531/quality of-life year).
Abstract: Objective An unmet need exists for a non-invasive biomarker assay to aid gastric cancer diagnosis. We aimed to develop a serum microRNA (miRNA) panel for identifying patients with all stages of gastric cancer from a high-risk population. Design We conducted a three-phase, multicentre study comprising 5248 subjects from Singapore and Korea. Biomarker discovery and verification phases were done through comprehensive serum miRNA profiling and multivariant analysis of 578 miRNA candidates in retrospective cohorts of 682 subjects. A clinical assay was developed and validated in a prospective cohort of 4566 symptomatic subjects who underwent endoscopy. Assay performance was confirmed with histological diagnosis and compared with Helicobacter pylori (HP) serology, serum pepsinogens (PGs), ‘ABC’ method, carcinoembryonic antigen (CEA) and cancer antigen 19–9 (CA19-9). Cost-effectiveness was analysed using a Markov decision model. Results We developed a clinical assay for detection of gastric cancer based on a 12-miRNA biomarker panel. The 12-miRNA panel had area under the curve (AUC)=0.93 (95% CI 0.90 to 0.95) and AUC=0.92 (95% CI 0.88 to 0.96) in the discovery and verification cohorts, respectively. In the prospective study, overall sensitivity was 87.0% (95% CI 79.4% to 92.5%) at specificity of 68.4% (95% CI 67.0% to 69.8%). AUC was 0.848 (95% CI 0.81 to 0.88), higher than HP serology (0.635), PG 1/2 ratio (0.641), PG index (0.576), ABC method (0.647), CEA (0.576) and CA19-9 (0.595). The number needed to screen is 489 annually. It is cost-effective for mass screening relative to current practice (incremental cost-effectiveness ratio=US$44 531/quality-of-life year). Conclusion We developed and validated a serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer. Trial registration number This study is registered with ClinicalTrials.gov (Registration number: NCT04329299).


Journal ArticleDOI
TL;DR: The evaluated AI system can correctly identify a proportion of a screening population as cancer-free and also reduce false positives, indicating that AI has the potential to improve mammography screening efficiency.
Abstract: To evaluate the potential of artificial intelligence (AI) to identify normal mammograms in a screening population. In this retrospective study, 9581 double-read mammography screening exams including 68 screen-detected cancers and 187 false positives, a subcohort of the prospective population-based Malmo Breast Tomosynthesis Screening Trial, were analysed with a deep learning–based AI system. The AI system categorises mammograms with a cancer risk score increasing from 1 to 10. The effect on cancer detection and false positives of excluding mammograms below different AI risk thresholds from reading by radiologists was investigated. A panel of three breast radiologists assessed the radiographic appearance, type, and visibility of screen-detected cancers assigned low-risk scores (≤ 5). The reduction of normal exams, cancers, and false positives for the different thresholds was presented with 95% confidence intervals (CI). If mammograms scored 1 and 2 were excluded from screen-reading, 1829 (19.1%; 95% CI 18.3–19.9) exams could be removed, including 10 (5.3%; 95% CI 2.1–8.6) false positives but no cancers. In total, 5082 (53.0%; 95% CI 52.0–54.0) exams, including 7 (10.3%; 95% CI 3.1–17.5) cancers and 52 (27.8%; 95% CI 21.4–34.2) false positives, had low-risk scores. All, except one, of the seven screen-detected cancers with low-risk scores were judged to be clearly visible. The evaluated AI system can correctly identify a proportion of a screening population as cancer-free and also reduce false positives. Thus, AI has the potential to improve mammography screening efficiency. • Retrospective study showed that AI can identify a proportion of mammograms as normal in a screening population. • Excluding normal exams from screening using AI can reduce false positives.

Journal ArticleDOI
27 Feb 2021
TL;DR: In this article, a rRT-PCR-based screening for SARS-CoV-2 was performed by pooling of samples, and the results were analyzed alongside contact tracing data.
Abstract: Background To accompany the lifting of COVID-19 lockdown measures, Luxembourg implemented a mass screening (MS) programme. The first phase coincided with an early summer epidemic wave in 2020. Methods rRT-PCR-based screening for SARS-CoV-2 was performed by pooling of samples. The infrastructure allowed the testing of the entire resident and cross-border worker populations. The strategy relied on social connectivity within different activity sectors. Invitation frequencies were tactically increased in sectors and regions with higher prevalence. The results were analysed alongside contact tracing data. Findings The voluntary programme covered 49% of the resident and 22% of the cross-border worker populations. It identified 850 index cases with an additional 249 cases from contact tracing. Over-representation was observed in the services, hospitality and construction sectors alongside regional differences. Asymptomatic cases had a significant but lower secondary attack rate when compared to symptomatic individuals. Based on simulations using an agent-based SEIR model, the total number of expected cases would have been 42·9% (90% CI [-0·3, 96·7]) higher without MS. Mandatory participation would have resulted in a further difference of 39·7% [19·6, 59·2]. Interpretation Strategic and tactical MS allows the suppression of epidemic dynamics. Asymptomatic carriers represent a significant risk for transmission. Containment of future outbreaks will depend on early testing in sectors and regions. Higher participation rates must be assured through targeted incentivisation and recurrent invitation. Funding This project was funded by the Luxembourg Ministries of Higher Education and Research, and Health.


Journal ArticleDOI
TL;DR: Novel diagnostic assays, population-based studies, and bioinformatic techniques could be used to better estimate the contribution of individuals with subclinical tuberculosis to overall transmission, to help understand whether finding and treating people with sub clinical tuberculosis is essential or extraneous as part of a comprehensive strategy to end the epidemic.
Abstract: Subclinical tuberculosis includes disease forms that are detectable by radiographic or microbiological assays but do not cause recognizable symptoms. Population-based prevalence surveys demonstrate that the majority of individuals with culture-positive tuberculosis and corresponding radiographic abnormalities lack recognizable symptoms. Subclinical tuberculosis is often conceptualized as an early stage that generally progresses to recognizable active tuberculosis disease within months. However, many individuals with subclinical tuberculosis likely never develop recognizable symptoms, and consequently are never identified as having tuberculosis. A growing body of evidence indicates that, in high-burden settings, people with tuberculosis spend more time in a subclinical state than they spend with recognizable symptoms, and that people with subclinical tuberculosis may be infectious. As such, the subclinical period may represent a long window of potential Mycobacterium tuberculosis transmission. To appropriately prioritize interventions, there is a need to quantify the amount of transmission that occurs during the subclinical period, including the contribution of those who never develop clinically symptomatic disease. If individuals with subclinical tuberculosis are responsible for a large fraction of M. tuberculosis transmission, then ambitious reductions in tuberculosis incidence cannot be achieved without greater focus on early detection and treatment of subclinical tuberculosis. Novel diagnostic assays, population-based studies, and bioinformatic techniques could be used to better estimate the contribution of individuals with subclinical tuberculosis to overall transmission. This knowledge can help us understand whether finding and treating people with subclinical tuberculosis is essential or extraneous as part of a comprehensive strategy to end the epidemic.

Journal ArticleDOI
TL;DR: In this article, the authors compared the performance of seven automated artificial intelligence-based diabetic retinopathy (DR) screening algorithms against human graders when analyzing real-world retinal imaging data.
Abstract: OBJECTIVE With rising global prevalence of diabetic retinopathy (DR), automated DR screening is needed for primary care settings. Two automated artificial intelligence (AI)–based DR screening algorithms have U.S. Food and Drug Administration (FDA) approval. Several others are under consideration while in clinical use in other countries, but their real-world performance has not been evaluated systematically. We compared the performance of seven automated AI-based DR screening algorithms (including one FDA-approved algorithm) against human graders when analyzing real-world retinal imaging data. RESEARCH DESIGN AND METHODS This was a multicenter, noninterventional device validation study evaluating a total of 311,604 retinal images from 23,724 veterans who presented for teleretinal DR screening at the Veterans Affairs (VA) Puget Sound Health Care System (HCS) or Atlanta VA HCS from 2006 to 2018. Five companies provided seven algorithms, including one with FDA approval, that independently analyzed all scans, regardless of image quality. The sensitivity/specificity of each algorithm when classifying images as referable DR or not were compared with original VA teleretinal grades and a regraded arbitrated data set. Value per encounter was estimated. RESULTS Although high negative predictive values (82.72–93.69%) were observed, sensitivities varied widely (50.98–85.90%). Most algorithms performed no better than humans against the arbitrated data set, but two achieved higher sensitivities, and one yielded comparable sensitivity (80.47%, P = 0.441) and specificity (81.28%, P = 0.195). Notably, one had lower sensitivity (74.42%) for proliferative DR (P = 9.77 × 10−4) than the VA teleretinal graders. Value per encounter varied at $15.14–$18.06 for ophthalmologists and $7.74–$9.24 for optometrists. CONCLUSIONS The DR screening algorithms showed significant performance differences. These results argue for rigorous testing of all such algorithms on real-world data before clinical implementation.

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TL;DR: In this paper, a combination of maternal factors with measurements of mean arterial pressure, serum placental growth factor, and serum soluble leucocyte protein (SLP) was used for screening for term preeclampsia.
Abstract: Background: Effective screening for term preeclampsia is provided by a combination of maternal factors with measurements of mean arterial pressure, serum placental growth factor, and serum soluble ...

Journal ArticleDOI
12 Oct 2021-JAMA
TL;DR: In this article, the authors describe research on screening and interventions for social risk factors to inform US Preventive Services Task Force considerations of the implications for its portfolio of recommendations, and present a technical brief identifying 106 social risk intervention studies (n = 5.5 million) that addressed at least one of seven social risk domains: housing instability, food insecurity, transportation difficulties, utility needs, interpersonal safety, education, and financial strain.
Abstract: Importance Evidence-based guidance is limited on how clinicians should screen for social risk factors and which interventions related to these risk factors improve health outcomes. Objective To describe research on screening and interventions for social risk factors to inform US Preventive Services Task Force considerations of the implications for its portfolio of recommendations. Data Sources Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Ovid MEDLINE, Sociological Abstracts, and Social Services Abstracts (through 2018); Social Interventions Research and Evaluation Network evidence library (January 2019 through May 2021); surveillance through May 21, 2021; interviews with 17 key informants. Study Selection Individual-level and health care system–level interventions with a link to the health care system that addressed at least 1 of 7 social risk domains: housing instability, food insecurity, transportation difficulties, utility needs, interpersonal safety, education, and financial strain. Data Extraction and Synthesis One investigator abstracted data from studies and a second investigator evaluated data abstractions for completeness and accuracy; key informant interviews were recorded, transcribed, summarized, and integrated with evidence from the literature; narrative synthesis with supporting tables and figures. Main Outcomes and Measures Validity of multidomain social risk screening tools; all outcomes reported for social risk–related interventions; challenges or unintended consequences of screening and interventions. Results Many multidomain social risk screening tools have been developed, but they vary widely in their assessment of social risk and few have been validated. This technical brief identified 106 social risk intervention studies (N = 5 978 596). Of the interventions studied, 73 (69%; n = 127 598) addressed multiple social risk domains. The most frequently addressed domains were food insecurity (67/106 studies [63%], n = 141 797), financial strain (52/106 studies [49%], n = 111 962), and housing instability (63/106 studies [59%], n = 5 881 222). Food insecurity, housing instability, and transportation difficulties were identified by key informants as the most important social risk factors to identify in health care. Thirty-eight studies (36%, n = 5 850 669) used an observational design with no comparator, and 19 studies (18%, n = 15 205) were randomized clinical trials. Health care utilization measures were the most commonly reported outcomes in the 68 studies with a comparator (38 studies [56%], n = 111 102). The literature and key informants described many perceived or potential challenges to implementation of social risk screening and interventions in health care. Conclusions and Relevance Many interventions to address food insecurity, financial strain, and housing instability have been studied, but more randomized clinical trials that report health outcomes from social risk screening and intervention are needed to guide widespread implementation in health care.

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TL;DR: In this article, the authors present data on the performance of lateral flow devices (LFDs) to test almost 8,000 students at the University of Birmingham between December 2 and December 9, 2020.
Abstract: Lateral flow devices (LFDs) are quickly being implemented for use in large-scale population surveillance programs for SARS-CoV-2 infection in the United Kingdom. These programs have been piloted in city-wide screening in the city of Liverpool and are now being rolled out to support care home visits and the return home of University students for the Christmas break. Here, we present data on the performance of LFDs to test almost 8,000 students at the University of Birmingham between December 2 and December 9, 2020. The performance is validated against almost 800 samples using PCR performed in the University Pillar 2 testing lab and theoretically validated on thousands of Pillar 2 PCR testing results performed on low-prevalence care home testing samples. Our data show that LFDs do not detect infections presenting with PCR Ct values over 29 to 30 as determined using the Thermo Fisher TaqPath asssay. This may be of particular importance in detecting individuals that are either at the early, or late stages of infection, and reinforces the need for frequent, recurrent testing.

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TL;DR: In this article, the authors established an international consensus algorithm of clinical, biochemical and imaging screening at diagnosis and during surveillance for both adults and children, and the Delphi method was used to reach a consensus on 41 statements.
Abstract: Approximately 20% of patients diagnosed with a phaeochromocytoma or paraganglioma carry a germline mutation in one of the succinate dehydrogenase (SDHx) genes (SDHA, SDHB, SDHC and SDHD), which encode the four subunits of the SDH enzyme. When a pathogenic SDHx mutation is identified in an affected patient, genetic counselling is proposed for first-degree relatives. Optimal initial evaluation and follow-up of people who are asymptomatic but might carry SDHx mutations have not yet been agreed. Thus, we established an international consensus algorithm of clinical, biochemical and imaging screening at diagnosis and during surveillance for both adults and children. An international panel of 29 experts from 12 countries was assembled, and the Delphi method was used to reach a consensus on 41 statements. This Consensus Statement covers a range of topics, including age of first genetic testing, appropriate biochemical and imaging tests for initial tumour screening and follow-up, screening for rare SDHx-related tumours and management of elderly people who have an SDHx mutation. This Consensus Statement focuses on the management of asymptomatic SDHx mutation carriers and provides clinicians with much-needed guidance. The standardization of practice will enable prospective studies in the near future.

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TL;DR: In this paper, a review summarizes the recent advances in the development of miniaturized PCR systems with an emphasis on COVID-19 detection, highlighting the potential of CRISPR/Cas technology for point-of-care diagnostics.