Search

This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus disease (COVID-19). The novelty of this work is in the introduction of optimized InceptionResNetV2 for COVID-19 (CO-IRv2) method. A part of the CO-IRv2 scheme is derived from the concepts of InceptionNet and ResNet with hyperparameter tuning, while the remaining part is a new architecture consisting of a global average pooling layer, batch normalization, dense layers, and dropout layers. The proposed CO-IRv2 is applied to a new dataset of 2481 computed tomography (CT) images formed by collecting two independent datasets. Data resizing and normalization are performed, and the evaluation is run up to 25 epochs. Various performance metrics, including precision, recall, accuracy, F1-score, area under the receiver operating characteristics (AUC) curve are used as performance metrics. The effectiveness of three optimizers known as Adam, Nadam and RMSProp are evaluated in classifying suspected COVID-19 patients and normal people. Results show that for CO-IRv2 and for CT images, the obtained accuracies of Adam, Nadam and RMSProp optimizers are 94.97%, 96.18% and 96.18%, respectively. Furthermore, it is shown here that for the case of CT images, CO-IRv2 with Nadam optimizer has better performance than existing DL algorithms in the diagnosis of COVID-19 patients. Finally, CO-IRv2 is applied to an X-ray dataset of 1662 images resulting in a classification accuracy of 99.40%. [ABSTRACT FROM AUTHOR]

This paper analyses COVID-19 patients' dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching an absorbing state of recovery or death. Demographic characteristics, epidemiological factors such as the time of infection and previous vaccinations, clinical history, complications during the course of the disease and drug therapy for hospitalised patients are considered as candidate predictors. Regarding risk factors associated with mortality and severity, consistent results with many other studies have been found, such as older age, being male, and chronic diseases. Specifically, the hospitalisation (death) rate for those over 69 is 27.2% (19.8%) versus 5.3% (0.7%) for those under 70, and for males is 14.5%(7%) versus 8.3%(4.6%)for females. Among patients with chronic diseases the highest rates of hospitalisation are 26.1% for diabetes and 26.3% for kidney disease, while the highest death rate is 21.9% for cerebrovascular disease. Moreover, specific predictors for different transitions are given, and estimates of the probability of recovery and death for each patient are provided by the model. Some interesting results obtained are that for patients infected at the end of the period the hazard of transition from hospitalisation to ICU is significatively lower (p < 0.001) and the hazard of transition from hospitalisation to recovery is higher (p < 0.001). For patients previously vaccinated against pneumococcus the hazard of transition to recovery is higher (p < 0.001). Finally, internal validation and calibration of the model are also performed. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is the leading cause of cancer-related mortality worldwide. Demographic differential has been linked with the treatment outcome and survival in recent literature, mostly from the developed world. Considering diversity in population characteristics across income strata, it's worth assessing the link in low- and middle-income population as well. Current study aimed to assess the association of demographic characteristics with lung cancer survival in Bangladeshi lung cancer patients. Methods & results: All newly diagnosed primary lung cancer cases attending the national institute of cancer research & Hospital (NICRH), a tertiary cancer care center in Dhaka, Bangladesh between 2018 and 2019 were considered for the study. Demographic information and clinical data were obtained from the patients' medical records by a trained physician. Survival estimate was generated using the Kaplan-Meier method and compared across demographic and clinicopathological categories using the log-rank test. Hazard ratio and 95% CI for treatment options are generated fitting multivariable Cox proportional hazard regression. Among 1868 patients, 84.6% were males and 15.4% were females, average (± standard deviation) age at diagnosis was 59.6±10.9 years, only 10.8% had not consumed tobacco of any form. Around two-thirds of the patient had Eastern Cooperative Oncology Group (ECOG) performance score ≥2, 29.5% had at least one comorbidity and 19.4% had metastasis at the time of presentation. Higher survival was associated with institutional education (HR 0.9; 95% CI 0.77, 0.99), and receipt of combined radiotherapy and chemotherapy (HR 0.56; 95% CI 0.46, 0.65; p <0.001). In contrast, lower survival was associated with older age between 60–69 years (HR 1.3; 95% CI 1.3, 1.5;), age ≥ 70 years (HR 1.4; 95% CI 1.1, 1.7), having any comorbidity (HR 1.1; 95% CI 1.0, 1.3), with ECOG score ≥ 3 (HR 1.41; 95% CI 1.01, 1.96) and receipt of radiotherapy treatments only (HR 1.6; 95% CI 1.3, 1.9). Conclusion: Older age, presence of one or more comorbidity, poorer performance status, and treatment with only RT appeared as a significant predictor of poorer prognosis of lung cancer in Bangladeshi patients. In contrast, having institutional education and treatment with combined Radiotherapy and Chemotherapy appeared as a predictor of a better prognosis. The finding of this study could serve as a basis for future studies inquiring into novel approaches for certain subgroups of patients believed to be challenged in limited resources. [ABSTRACT FROM AUTHOR]

Background: Patients with hepatocellular carcinoma (HCC) represent a vulnerable population potentially negatively affected by COVID-19-associated reallocation of healthcare resources. Here, we report the impact of COVID-19 on the management of HCC patients in a large tertiary care hospital. Methods: We retrospectively analyzed clinical data of HCC patients who presented at the Vienna General Hospital, between 01/DEC/2019 and 30/JUN/2020. We compared patient care before (period 1) and after (period 2) implementation of COVID-19-associated healthcare restrictions on 16/MAR/2020. Results: Of 126 patients, majority was male (n = 104, 83%) with a mean age of 66±11 years. Half of patients (n = 57, 45%) had impaired liver function (Child-Pugh stage B/C) and 91 (72%) had intermediate-advanced stage HCC (BCLC B-D). New treatment, was initiated in 68 (54%) patients. Number of new HCC diagnoses did not differ between the two periods (n = 14 vs. 14). While personal visits were reduced, an increase in teleconsultation was observed (period 2). Number of patients with visit delays (n = 31 (30%) vs. n = 10 (10%); p = 0.001) and imaging delays (n = 25 (25%) vs. n = 7 (7%); p = 0.001) was higher in period 2. Accordingly, a reduced number of patients was discussed in interdisciplinary tumor boards (lowest number in April (n = 24), compared to a median number of 57 patients during period 1). Median number of elective/non-elective admissions was not different between the periods. One patient contracted COVID-19 with lethal outcome. Conclusions: Changes in patient care included reduced personal contacts but increased telephone visits, and delays in diagnostic procedures. The effects on long-term outcome need to be determined. [ABSTRACT FROM AUTHOR]

The use of saliva for the diagnosis of SARS-CoV-2 has shown to be a good alternative to nasopharyngeal swabs (NPS), since it permits self-collection, avoids the exposure of healthy persons to infected patients, reduces waiting times, eliminates the need of personal protective equipment and is non-invasive. Yet current saliva testing is still expensive due to the need of specialized tubes containing buffers to stabilize the RNA of SARS-CoV-2 and inactivate the virus. These tubes are expensive and not always accessible in sufficient quantities. We now developed an alternative saliva testing method, using TRIzol for extraction, viral inactivation, and storage of SARS-CoV-2 RNA, combined with RT-qPCR, which was comparable in its performance to NPS. Paired saliva samples and NPS were taken from 15 asymptomatic healthcare workers and one patient with SARS-CoV-2. Further 13 patients with SARS-CoV-2 were only saliva-tested. All the tests were performed according to CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel. Saliva (4 mL) was taken in sterile 50 mL tubes, 1.5 mL TRIzol were added and mixed. Our results show that 5 μL of saliva RNA extracted with TRIzol allow for an adequate detection of the virus in patients positive for SARS-CoV-2 and was equally sensitive to NPS in TRIzol. We conclude that saliva testing using TRIzol is a recommendable method for diagnosis of SARS-CoV-2 since it has several advantages over currently used saliva tests: it can be done with normal sterile tubes, does not need cold-chain handling, is stable at room temperature, is non-invasive and less costly, making it more accessible for low-income countries. Cheaper saliva testing using TRIzol is especially relevant for low-income countries to optimize diagnosis and help define quarantine durations for families, healthcare workers, schools, and other public workplaces, thus decreasing infections and mortality caused by SARS-CoV-2. [ABSTRACT FROM AUTHOR]

As countries are lifting restrictions and resuming international travels, the rising risk of COVID-19 importation remains concerning, given that the SARS-CoV-2 virus could be transmitted unintentionally through the global transportation network. To explore and assess the effective strategies for curtailing the epidemic risk from international importation nationwide, we evaluated "the joint prevention and control" mechanism, which made up of 19 containment policies, on how it impacted the change of medical observation and detection time from border arrival to laboratory confirmation of COVID-19 in its burst in China. Based on 1,314 epidemiological-survey cases from February 29 to May 25, 2020, we found that the synchronized approach of implementing multi-dimensional interventional policies, such as a centralized quarantine and nucleic acid testing (NAT), flight service adjustment and border closure, effectively facilitate early identification of infected case. Specifically, the implementation of the international flight service reduction was found to be associated with a reduction of the mean intervals of diagnosis from arrival to lab-confirmation by 0.44 days maximally, and the border closure was associated with a reduction of the diagnosis interval of imported cases by 0.69 days, from arrival to laboratory confirmation. The study suggests that a timely and synchronized implementation of multi-dimensional policies is compelling in preventing domestic spreading from importation. [ABSTRACT FROM AUTHOR]

Few studies have focused on clinical courses or viral loads in young asymptomatic or mild patients with COVID-19 infection. We sought to better understand the clinical course and association between viral load and prevalence of pneumonia in young COVID-19 patients with asymptomatic or mild disease severity. In this retrospective study, 106 COVID-19 young patients with asymptomatic or mild disease severity were analyzed for clinical characteristics, clinical course, prevalence of radiologically proven pneumonia and viral load. The cut-off value of viral load for presence of pneumonia was also investigated. The mean age was 28.0±9.3 years. Eleven patients (10.4%) experienced viral remission within one week of diagnosis, but one (0.9%) transferred to the hospital due to aggravation of pneumonia. Patients with pneumonia had significantly higher viral load than those without, and the cut-off value of the Ct value for presence of pneumonia were 31.38. The patients with pneumonia had significantly slower recovery times than those without. Diarrhea was significantly more common in patients with pneumonia than patients without pneumonia. In conclusion, most young asymptomatic and mildly symptomatic patients showed stable clinical course. There were significant differences in viral load and recovery times between patients with and without pneumonia. [ABSTRACT FROM AUTHOR]

During the first wave of the global COVID-19 pandemic the clinical utility and indications for SARS-CoV-2 serological testing were not clearly defined. The urgency to deploy serological assays required rapid evaluation of their performance characteristics. We undertook an internal validation of a CE marked lateral flow immunoassay (LFIA) (SureScreen Diagnostics) using serum from SARS-CoV-2 RNA positive individuals and pre-pandemic samples. This was followed by the delivery of a same-day named patient SARS-CoV-2 serology service using LFIA on vetted referrals at central London teaching hospital with clinical interpretation of result provided to the direct care team. Assay performance, source and nature of referrals, feasibility and clinical utility of the service, particularly benefit in clinical decision-making, were recorded. Sensitivity and specificity of LFIA were 96.1% and 99.3% respectively. 113 tests were performed on 108 participants during three-week pilot. 44% participants (n = 48) had detectable antibodies. Three main indications were identified for serological testing; new acute presentations potentially triggered by recent COVID-19 e.g. pulmonary embolism (n = 5), potential missed diagnoses in context of a recent COVID-19 compatible illness (n = 40), and making infection control or immunosuppression management decisions in persistently SARS-CoV-2 RNA PCR positive individuals (n = 6). We demonstrate acceptable performance characteristics, feasibility and clinical utility of using a LFIA that detects anti-spike antibodies to deliver SARS-CoV-2 serology service in adults and children. Greatest benefit was seen where there is reasonable pre-test probability and results can be linked with clinical advice or intervention. Experience from this pilot can help inform practicalities and benefits of rapidly implementing new tests such as LFIAs into clinical service as the pandemic evolves. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic forced healthcare services organization to adjust to mutating healthcare needs. Not exhaustive data are available on the consequences of this on non-COVID-19 patients. The aim of this study was to assess the impact of the pandemic on non-COVID-19 patients living in a one-million inhabitants' area in Northern Italy (Bologna Metropolitan Area-BMA), analyzing time trends of Emergency Department (ED) visits, hospitalizations and mortality. We conducted a retrospective observational study using data extracted from BMA healthcare informative systems. Weekly trends of ED visits, hospitalizations, in- and out-of-hospital, all-cause and cause-specific mortality between December 1st, 2019 to May 31st, 2020, were compared with those of the same period of the previous year. Non-COVID-19 ED visits and hospitalizations showed a stable trend until the first Italian case of COVID-19 has been recorded, on February 19th, 2020, when they dropped simultaneously. The reduction of ED visits was observed in all age groups and across all severity and diagnosis groups. In the lockdown period a significant increase was found in overall out-of-hospital mortality (43.2%) and cause-specific out-of-hospital mortality related to neoplasms (76.7%), endocrine, nutritional and metabolic (79.5%) as well as cardiovascular (32.7%) diseases. The pandemic caused a sudden drop of ED visits and hospitalizations of non-COVID-19 patients during the lockdown period, and a concurrent increase in out-of-hospital mortality mainly driven by deaths for neoplasms, cardiovascular and endocrine diseases. As recurrencies of the COVID-19 pandemic are underway, the scenario described in this study might be useful to understand both the population reaction and the healthcare system response at the early phases of the pandemic in terms of reduced demand of care and systems capability in intercepting it. [ABSTRACT FROM AUTHOR]

The alarming spread of the pandemic coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus requires several measures to reduce the risk of contagion. Every successful strategy in controlling the SARS-CoV-2 infection depends on timely diagnosis, which should include testing of asymptomatic carriers. Consequently, increasing the throughput for clinical laboratories for the purposes of conducting large-scale diagnostic testing is urgently needed. Here we support the hypothesis that standard diagnostic protocol for SARS-CoV-2 virus could be conveniently applied to pooled samples obtained from different subjects. We suggest that a two-step sequential pooling procedure could identify positive subjects, ensuring at the same time significant benefits of cost and time. The simulation data presented herein were used to assess the efficiency, in terms of number of required tests, both for random assignment of the subjects to the pools and for situations in which epidemiological and clinical data are used to create "informed" pools. Different scenarios were simulated to measure the effect of different pool sizes and different values for virus frequency. Our results allow for a customization of the pooling strategy according to the specific characteristics of the cohort being tested. [ABSTRACT FROM AUTHOR]