Федеральное государственное бюджетное учреждение «Научно-исследовательский институт пульмонологии» Федерального медико-биологического агентства: 115682, Россия, Москва, Ореховый бульвар, 28 2 Государственное бюджетное учреждение здравоохранения города Москвы «Московский клинический научно-практический центр имени А.С.Логинова» Департамента здравоохранения города Москвы: 111123, Россия, Москва, шоссе Энтузиастов, 86 3 Федеральное государственное бюджетное научное учреждение «Научно-исследовательский институт морфологии человека»: 117418, Россия, Москва, ул. Цюрупы, 3 4 Федеральное государственное автономное образовательное учреждение высшего образования «Российский национальный исследовательский медицинский университет имени Н.И.Пирогова» Министерства здравоохранения Российской Федерации: 117997, Россия, Москва, ул. Островитянова, 1 5 Государственное бюджетное учреждение здравоохранения города Москвы «Городская клиническая больница № 1 имени Н.И.Пирогова Департамента здравоохранения города Москвы»: 117049, Россия, Москва, Ленинский просп., 8 6 Федеральное государственное бюджетное образовательное учреждение высшего образования «Московский государственный медико-стоматологический университет имени А.И.Евдокимова» Министерства здравоохранения Российской Федерации: 127473, Россия, Москва, ул. Делегатская, 20, стр. 1 7 Федеральное государственное бюджетное учреждение «Национальный медицинский исследовательский центр хирургии имени А.В.Вишневского» Министерства здравоохранения Российской Федерации: 117997, Россия, Москва, ул. Б. Серпуховская, 27 8 Государственное бюджетное учреждение здравоохранения города Москвы «Городская клиническая больница имени И.В.Давыдовского Департамента здравоохранения города Москвы»: 109240, Россия, Москва, Яузская ул., 11 9 Государственное бюджетное учреждение здравоохранения «Городская больница № 52» Департамента здравоохранения Москвы: 123182, Россия, Москва, ул. Пехотная, 3 10 Государственное бюджетное учреждение здравоохранения города Москвы «Инфекционная клиническая больница №2 Департамента здравоохранения города Москвы»: 105275, Россия, Москва, 8-я улица Соколиной горы, 15 11 Клиническая больница № 1 Акционерного общества Группы компаний «МЕДСИ»: 143442, Россия, Московская область, городской округ Красногорск, пос. Отрадное, вл. 2, стр. 1 Резюме Целью статьи явилось изучение особенностей морфологических изменений в легких у умерших от COVID-19 в Москве за период 20.03.20-06.06.20. Материалы и методы. Проанализирован аутопсийный материал легких умерших от коронавирусной инфекции COVID-19 больных (n = 123: 54 женщины, 69 мужчин; средний возраст-71 (30-94) год; продолжительность заболевания-14 (3-65) суток), подтвержденной методом полимеразной цепной реакции. Проанализированы медицинские карты всех стационарных больных и все протоколы вскрытий. По данным всех наблюдений оценены макро-и микроскопические изменения в легких. Результаты. Патоморфологические изменения в легких соответствовали различным фазам диффузного альвеолярного повреждения (ДАП). Экссудативная фаза ДАП выявлена у 54 (43,...

Background: Until recently, Russia did not utilize noninvasive fractional flow reserve (FFR) assessment. We developed an automated algorithm for noninvasive assessment of FFR based on a one-dimensional (1D) mathematical modeling. Objective: The research aims to evaluate the diagnostic accuracy of this algorithm. Methods: The study enrolled 80 patients: 16 of them underwent 64-slice computed tomography – included retrospectively, 64 – prospectively, with a 640-slice CT scan. Specialists processed CT images and evaluated noninvasive FFR. Ischemia was confirmed if FFR < 0.80 and disproved if FFR ≥ 0.80. The prospective group of patients was hospitalized for invasive FFR assessment as a reference standard. If ischemic, patients underwent stent implantation. In the retrospective group, patients already had invasive FFR values. Statistical analysis was performed using GraphPad Prism 8. We compared two methods using a Bland–Altman plot and per-vessel ROC curve analysis. Considering the abnormality of distribution by the Kolmogorov-Smirnov test, we have used Spearman’s rank correlation coefficient. Results: During data processing, three patients of the retrospective and 46 patients of the prospective group were excluded. The sensitivity of our method was 66.67% (95% CI: 46.71–82.03); the specificity was 78.95% (95% CI: 56.67–91.49), p = 0.0052, in the per-vessel analysis. In per-patient analysis, the sensitivity was 69.57% (95% CI: 49.13–84.40); the specificity was 87.50% (95% CI: 52.91–99.36), p = 0.0109. The area under the ROC curve in the per-vessel analysis was 77.52% (95% CI: 66.97–88.08), p < 0.0001. Conclusion: The obtained indices of sensitivity, specificity, PPV, and NPV are, in general, comparable to those in other studies. Moreover, the noninvasive values of FFR yielded a high correlation coefficient with the invasive values. However, the AUC was not high enough, 77.52 (95% CI: 66.97–88.08), p < 0.0001. The discrepancy is probably attributed to the initial data heterogeneity and low statistical power.

Objectives: to determine the diagnostic performance of non-invasive FFR derived from standard acquired coronary computed tomography angiography (CTA) datasets (FFRCT) for the diagnosis of myocardial ischemia in patients with suspected stable coronary artery disease (CAD).Methods.Prospective study included 16 patients ((m/f – 13/3 mean age 47.8 ± 2.3 years) with CAD and coronary stenosis 40–75% lumen reduction. Coronary CTA was performed prior to ICA with invasive FFR measurement. FFRCT was calculated and interpreted in a blinded fashion by an independent Core Laboratory (HeartFlow, USA). Results were compared to invasively measured FFR, with ischemia defined as FFRCT or FFR ≤ 0.80.Results. The area under the receiver operating characteristic curve (95% CI) for FFCT was 0.90. Per-vessel sensitivity and specificity to identify myocardial ischemia were 91% and 89% for FFRCT.Conclusion.FFRCT provides high diagnostic accuracy, and discrimination for the diagnosis of hemodynamically significant CAD with invasive FFR as the reference standard.

Hypersensitivity pneumonitis (HP) is an interstitial lung disease (ILD) resulting from an immune-mediated response in susceptible and sensitized individuals to a large variety of inhaled antigens. Chronic HP with a fibrotic phenotype is characterized by disease progression and a dismal prognosis. The aim of this study was to identify predictors of progression and mortality in patients with chronic HP in real clinical practice. Materials and methods: This retrospective, multicenter, observational study used data from a registry of 1355 patients with fibrosing ILDs. The study included 292 patients diagnosed with chronic HP based on the conclusion of a multidisciplinary discussion (MDD). Results: The patients were divided into groups with progressive (92 (30.3%) patients) and nonprogressive pulmonary fibrosis (200 (69.7%) patients). The most significant predictors of adverse outcomes were a DLco < 50% predicted, an SpO2 at the end of a six-minute walk test (6-MWT) < 85%, and a GAP score ≥ 4 points. Conclusion: Pulmonary fibrosis and a progressive fibrotic phenotype are common in patients with chronic HP. Early detection of the predictors of an adverse prognosis of chronic HP is necessary for the timely initiation of antifibrotic therapy.

Aim.To evaluate the diagnostic accuracy of a noninvasive method of fractional flow reserve (FFR) assessment based on a one-dimensional hemodynamic model build on data obtained from the coronary computed tomography angiography (CCTA).Material and methods.The study enrolled 57 patients: 16 of them underwent 64-slice computed tomography — included retrospectively, 34 — prospectively, with a 640-slice CT scan. Specialists from the Laboratory of Mathematical Modeling processed CT images and evaluated noninvasive FFR. Ischemia was confirmed if FFR <0,80 and disproved if FFR ≥0,80. After that the prospective group of patients was hospitalized for invasive FFR assessment as a reference standard; if ischemia was proved, patients underwent stent implantation. In the retrospective group, patients already had invasive FFR values estimated. Statistical analysis was performed using R programming language packages (cran-r.project.com). Continuous variables are presented as mean values ± standard deviations, order variables are presented as medians with interquartile ranges in parentheses. We used the D’Agostino-Pearson omnibus test for the assessment of normality of distribution; a Q-Q Plot was also constructed. We performed the Bland-Altman analysis and ROC-analysis for comparison of these two methods, and the Pearson’s chi-squared to assess the degree of correlation.Results.During data processing, 3 patients of the retrospective and 34 patients of the prospective group were excluded from the study. The sensitivity of our method was 90,91% (95% CI; 58,72-99,77), specificity — 86,67% (95% CI; 59,54-98,34), P<0,05, accuracy — 88,46 (95% CI; 69,85-97,55) — in per-vessel analysis. In perpatient analysis, the sensitivity was 91,67% (95% CI; 61,52-99,79), specificity — 80% (95% CI; 28,36-99,49), (P<0,05); accuracy 88,24 (95% CI; 63,56-98,54).Conclusion.Our method has quite a high accuracy and can be successfully used in clinical practice in order to enhance the diagnostic efficiency of the CCTA.