Hypothesis testing using R

Competencies in statistical data processing are becoming increasingly important for modern scientists. The apparent advantages of open-source software for statistical analysis are its accessibility and adaptability. The programming language and the corresponding software R, available as a minimalistic console interface or a complete development environment RStudio/Posit, have the widest possibilities among free solutions. We present a practical guide for comparing two groups using the software R. This study compares the effective doses of standard computed tomography with low-dose computed tomography for COVID-19 patients. The practical guide summarizes theoretical approaches to medical data processing and recommendations for correctly formulating research tasks and selecting optimal statistical analysis methods. The main goal of the practical guide is to introduce the reader to the Posit interface and the basic functionality of the R language by using a practical example of treating a real medical problem. The presented material can be useful as an introduction to statistical analysis using the programming language R

Low-dose computed tomography in COVID-19: systematic review

BACKGROUND: The increased number of computed tomography scans during the COVID-19 pandemic has emphasized the task of decreasing radiation exposure of patients, since it is known to be associated with an elevated risk of cancer development. The ALARA (as low as reasonably achievable) principle, proposed by the International Commission on Radiation Protection, should be adhered to in the operation of radiation diagnostics departments, even during the pandemic. AIM: To systematize data on the appropriateness and effectiveness of low-dose computed tomography in the diagnosis of lung lesions in COVID-19. MATERIALS AND METHODS: Relevant national and foreign literature in scientific libraries PubMed and eLIBRARY, using English and Russian queries low-dose computed tomography and COVID-19, published between 2020 and 2022 were analyzed. Publications were evaluated after assessing the relevance to the review topic by title and abstract analysis. The references were further analyzed to identify articles omitted during the search that may meet the inclusion criteria. RESULTS: Published studies summarized the current data on the imaging of COVID-19 lung lesions and the use of computed tomography scans and identified possible options for reducing the effective dose. CONCLUSION: We present techniques to reduce radiation exposure during chest computed tomography and preserve high-quality diagnostic images potentially sufficient for reliable detection of COVID-19 signs. Reducing radiation dose is a valid approach to obtain relevant diagnostic information, preserving opportunities for the introduction of advanced computational analysis technologies in clinical practice

Случайные находки при скрининге рака легкого методом низкодозной компьютерной томографии

In Moscow in 2017, the project named Moscow Screening for Lung Cancer was started using low-dose computed tomography (LDCT) for selective screening for lung malignant tumors in the out-patient facilities and polyclinics.The main goal of the project: to improve early detection of lung cancer and reduce mortality caused by this disease in the long term.The objective of the study: to assess the importance of incidental findings during selective screening for lung cancer by LDCT in Moscow.Subjects and Methods. The retrospective study included 254 randomly selected LDCT, which were performed as a part of the screening program. During the repeated examination of images and protocols, all abnormalities were taken into account (but for foci in the lungs evaluated as per LungRADS-2014).Results. When analyzing the dissemination and character of incidental findings, detected by LDCT screening, it was found out that such findings had high clinical and/or predictive value in the majority of cases. The following disorders were detected the most often (% of those with incidental finding): coronary artery calcium - 49.3%; thickening of bronchial walls - 34.9%; bronchiectasis - 34.9%; emphysema - 21.6%.During primary interpretation of LDCT results, less attention was paid to description of abnormalities but for foci evaluated as per Lung RADS-2014. Further research and organization are needed to provide detection and reasonable routing for those with incidental findings.Conclusions. Incidental findings occur in 87.1% of cases during selective screening for lung cancer by LDCT. The majority of incidental findings are located in the cardio-vascular (75.4%) and respiratory (68.3%) systems, and they possess clinical and predictive value.В 2017 г. в г. Москве начат проект «Московский скрининг рака легкого» путем применения низкодозной компьютерной томографии (НДКТ), направленный на проведение селективного скрининга злокачественных новообразований (ЗНО) легкого в амбулаторно-поликлиническом звене.Основная задача проекта: повысить выявляемость рака легкого на ранних стадиях и в перспективе снизить смертность от этого заболевания.Цель исследования: оценить значимость случайных находок, выявляемых в процессе селективного скрининга рака легкого методом НДКТ в г. Москве.Материал и методы. В ретроспективное исследование включены случайно отобранные 254 НДКТ, выполненные в рамках программы скрининга. При повторном просмотре изображений и протоколов учитывали все патологические находки (кроме очагов в легких, оцененных по классификации «LungRADS-2014»).Результаты. При анализе распространенности и характера случайных находок, выявляемых при НДКТ-скрининге, установлено, что в большинстве случаев такие находки имеют высокую клиническую и/или прогностическую значимость. Наиболее часто выявляются (% от числа лиц со случайными находками): кальциноз коронарных артерий ‒ 49,3%; утолщение стенок бронхов ‒ 34,9%; бронхоэктазы ‒ 34,9%; эмфизема ‒ 21,6%.При первичных интерпретациях результатов НДКТ недостаточное внимание уделяется описанию патологических изменений, кроме классифицируемых по «Lung RADS-2014» очагов. Требуется дальнейшая научно-методическая работа по организации выявления и обоснованной маршрутизации лиц со случайными находками.Выводы. Случайные находки встречаются в 87,1% случаев при проведении селективного скрининга рака легкого методом НДКТ. Наиболее часто случайные находки локализуются в сердечно-сосудистой (75,4%) и дыхательной (68,3%) системах, при этом они носят клинически и прогностически значимый характер

Cosmic ray oriented performance studies for the JEM-EUSO first level trigger

JEM-EUSO is a space mission designed to investigate Ultra-High Energy Cosmic Rays and Neutrinos (E > 5 ⋅ 1019 eV) from the International Space Station (ISS). Looking down from above its wide angle telescope is able to observe their air showers and collect such data from a very wide area. Highly specific trigger algorithms are needed to drastically reduce the data load in the presence of both atmospheric and human activity related background light, yet retain the rare cosmic ray events recorded in the telescope. We report the performance in offline testing of the first level trigger algorithm on data from JEM-EUSO prototypes and laboratory measurements observing different light sources: data taken during a high altitude balloon flight over Canada, laser pulses observed from the ground traversing the real atmosphere, and model landscapes reproducing realistic aspect ratios and light conditions as would be seen from the ISS itself. The first level trigger logic successfully kept the trigger rate within the permissible bounds when challenged with artificially produced as well as naturally encountered night sky background fluctuations and while retaining events with general air-shower characteristics

Incidental findings during lung cancer screening by low-dose computed tomography

In Moscow in 2017, the project named Moscow Screening for Lung Cancer was started using low-dose computed tomography (LDCT) for selective screening for lung malignant tumors in the out-patient facilities and polyclinics.The main goal of the project: to improve early detection of lung cancer and reduce mortality caused by this disease in the long term.The objective of the study: to assess the importance of incidental findings during selective screening for lung cancer by LDCT in Moscow.Subjects and Methods. The retrospective study included 254 randomly selected LDCT, which were performed as a part of the screening program. During the repeated examination of images and protocols, all abnormalities were taken into account (but for foci in the lungs evaluated as per LungRADS-2014).Results. When analyzing the dissemination and character of incidental findings, detected by LDCT screening, it was found out that such findings had high clinical and/or predictive value in the majority of cases. The following disorders were detected the most often (% of those with incidental finding): coronary artery calcium - 49.3%; thickening of bronchial walls - 34.9%; bronchiectasis - 34.9%; emphysema - 21.6%.During primary interpretation of LDCT results, less attention was paid to description of abnormalities but for foci evaluated as per Lung RADS-2014. Further research and organization are needed to provide detection and reasonable routing for those with incidental findings.Conclusions. Incidental findings occur in 87.1% of cases during selective screening for lung cancer by LDCT. The majority of incidental findings are located in the cardio-vascular (75.4%) and respiratory (68.3%) systems, and they possess clinical and predictive value

Influenza Epidemiology And Influenza Vaccine Effectiveness During The 2016-2017 Season In The Global Influenza Hospital Surveillance Network (Gihsn)

BackgroundThe Global Influenza Hospital Surveillance Network (GIHSN) aims to determine the burden of severe influenza disease and Influenza Vaccine Effectiveness (IVE). This is a prospective, active surveillance and hospital-based epidemiological study to collect epidemiological data in the GIHSN. In the 2016-2017 influenza season, 15 sites in 14 countries participated in the GIHSN, although the analyses could not be performed in 2 sites. A common core protocol was used in order to make results comparable. Here we present the results of the GIHSN 2016-2017 influenza season.MethodsA RT-PCR test was performed to all patients that accomplished the requirements detailed on a common core protocol. Patients admitted were included in the study after signing the informed consent, if they were residents, not institutionalised, not discharged in the previous 30days from other hospitalisation with symptoms onset within the 7days prior to admission. Patients 5years old or more must also complied the Influenza-Like Illness definition. A test negative-design was implemented to perform IVE analysis. IVE was estimated using a logistic regression model, with the formula IVE=(1-aOR)x100, where aOR is the adjusted Odds Ratio comparing cases and controls.ResultsAmong 21,967 screened patients, 10,140 (46.16%) were included, as they accomplished the inclusion criteria, and tested, and therefore 11,827 (53.84%) patients were excluded. Around 60% of all patients included with laboratory results were recruited at 3 sites. The predominant strain was A(H3N2), detected in 63.6% of the cases (1840 patients), followed by B/Victoria, in 21.3% of the cases (618 patients). There were 2895 influenza positive patients (28.6% of the included patients). A(H1N1)pdm09 strain was mainly found in Mexico. IVE could only be performed in 6 sites separately. Overall IVE was 27.24 (95% CI 15.62-37.27. Vaccination seemed to confer better protection against influenza B and in people 2-4years, or 85years old or older. The aOR for hospitalized and testing positive for influenza was 3.02 (95% CI 1.59-5.76) comparing pregnant with non-pregnant women.ConclusionsVaccination prevented around 1 in 4 hospitalisations with influenza. Sparse numbers didn't allow estimating IVE in all sites separately. Pregnancy was found a risk factor for influenza, having 3 times more risk of being admitted with influenza for pregnant women.Wo