504 research outputs found

    Genus <i>Nicotiana</i> L.: a review of traits significant for ornamental crop production

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    Background. The collection of Nicotiana L. species (Solanaceae) maintained at the All-Russian Scientific Research Institute of Tobacco, Makhorka and Tobacco Products (VNIITTI) is a valuable genetic resource used in breeding and genetic research on interspecific hybridization, cytoplasmic male sterility, and as a genebank for resistance to major tobacco diseases. Many species have ornamental features and properties: bright color and unusual morphology of the corolla, aroma, peculiar plant shape and others, and are promising for use in landscaping and garden designing. To identify and evaluate such species the collection was for the first time screened for a set of morphological and ornamental characters.Materials and methods. Thirty-seven accessions of Nicotiana spp. were studied in the greenhouses and at the experimental breeding site of VNIITTI using breeding methods and agricultural practices developed at the Institute and generally accepted in crop production.Results and conclusion. Phenotypic assessment of 37 Nicotiana accessions resulted in identifying for the first time 14 traits of ornamental value and selecting 18 original species and 10 hybrids of N. alata Γ— N. Γ— sanderae environmentally adapted to the local conditions and promising for landscaping and garden designing: with bright flowers, prolonged flowering, and relative resistance to stressful weather conditions. The typicality and stability of their progeny was assessed, and their germplasm was maintained and preserved in vivo

    Π‘Π»ΡƒΡ‡Π°ΠΉ Π½ΠΎΠ²ΠΎΠΉ коронавирусной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ COVID-19 Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π°, находящСгося Π½Π° Π»Π΅Ρ‡Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½Ρ‹ΠΌ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·ΠΎΠΌ

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    Coronavirus infection (COVID-19) is an acute infectious disease caused by a new strain of the virus of the genus coronavirus SARS-CoV-2 with the aerosol-droplet and contact-household transmission mechanism; patogenetically local and systemic inflammatory process, hyperactive impulsive cascade, endotheliopathy, hypoxia, leading to the development of micro – and microthrombosis; it occurs from asymptomatic to clinically significant forms of intoxication, vascular lesions, lungs, heart, kidneys, and GI tract with risk of complications (ARF, ARDS, sepsis, shock, multiple organ dysfunction SYNDROME, pulmonary embolism). Currently, there are few data on the course of this disease in patients undergoing treatment with program hemodialysis, as well as methods of specific treatment of this group of patients. The article describes the case of the first patient in the Clinical Infectious Hospital named after S.P. Botkin with end-stage chronic kidney disease corrected by program hemodialysis, who had a COVID-19.ΠšΠΎΡ€ΠΎΠ½Π°Π²ΠΈΡ€ΡƒΡΠ½Π°Ρ инфСкция (COVID-19) – остроС ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠ΅ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠ΅, Π²Ρ‹Π·Ρ‹Π²Π°Π΅ΠΌΠΎΠ΅ Π½ΠΎΠ²Ρ‹ΠΌ ΡˆΡ‚Π°ΠΌΠΌΠΎΠΌ вируса ΠΈΠ· Ρ€ΠΎΠ΄Π° коронавирусов SARS-CoV-2 с Π°ΡΡ€ΠΎΠ·ΠΎΠ»ΡŒΠ½ΠΎ-ΠΊΠ°ΠΏΠ΅Π»ΡŒΠ½Ρ‹ΠΌ ΠΈ ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΎ-Π±Ρ‹Ρ‚ΠΎΠ²Ρ‹ΠΌ ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΠΎΠΌ ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ, патогСнСтичСски характСризуСтся Π»ΠΎΠΊΠ°Π»ΡŒΠ½Ρ‹ΠΌ ΠΈ систСмным ΠΈΠΌΠΌΡƒΠ½ΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ процСссом, Π³ΠΈΠΏΠ΅Ρ€Π°ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒΡŽ коагуляционного каскада, эндотСлиопатиСй, гипоксиСй, приводящим ΠΊ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΡŽ ΠΌΠΈΠΊΡ€ΠΎ- ΠΈ ΠΌΠ°ΠΊΡ€ΠΎΡ‚Ρ€ΠΎΠΌΠ±ΠΎΠ·ΠΎΠ², ΠΏΡ€ΠΎΡ‚Π΅ΠΊΠ°Π΅Ρ‚ ΠΎΡ‚ бСссимптомных Π΄ΠΎ клиничСски Π²Ρ‹Ρ€Π°ΠΆΠ΅Π½Π½Ρ‹Ρ… Ρ„ΠΎΡ€ΠΌ с интоксикациСй, ΠΏΠΎΡ€Π°ΠΆΠ΅Π½ΠΈΠ΅ΠΌ сосудов, Π»Π΅Π³ΠΊΠΈΡ…, сСрдца, ΠΏΠΎΡ‡Π΅ΠΊ, ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎ-ΠΊΠΈΡˆΠ΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ‚Ρ€Π°ΠΊΡ‚Π° с риском развития ослоТнСний (острая Π΄Ρ‹Ρ…Π°Ρ‚Π΅Π»ΡŒΠ½Π°Ρ Π½Π΅Π΄ΠΎΡΡ‚Π°Ρ‚ΠΎΡ‡Π½ΠΎΡΡ‚ΡŒ, острый рСспираторный дистрСсс-синдром, сСпсис, шок, синдром ΠΏΠΎΠ»ΠΈΠΎΡ€Π³Π°Π½Π½ΠΎΠΉ нСдостаточности, тромбоэмболия Π»Π΅Π³ΠΎΡ‡Π½ΠΎΠΉ Π°Ρ€Ρ‚Π΅Ρ€ΠΈΠΈ). Π’ настоящСС врСмя ΠΈΠΌΠ΅ΡŽΡ‚ΡΡ нСмногочислСнныС Π΄Π°Π½Π½Ρ‹Π΅ ΠΎ Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠΈ Π΄Π°Π½Π½ΠΎΠ³ΠΎ заболСвания Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², находящихся Π½Π° Π»Π΅Ρ‡Π΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½Ρ‹ΠΌ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·ΠΎΠΌ, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°Ρ… спСцифичСского лСчСния Π΄Π°Π½Π½ΠΎΠΉ Π³Ρ€ΡƒΠΏΠΏΡ‹ Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ…. Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ описан случай ΠΏΠ΅Ρ€Π²ΠΎΠ³ΠΎ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π° Π² ΠšΠ»ΠΈΠ½ΠΈΡ‡Π΅ΡΠΊΠΎΠΉ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½ΠΎΠΉ Π±ΠΎΠ»ΡŒΠ½ΠΈΡ†Π΅ ΠΈΠΌΠ΅Π½ΠΈ Π‘.П. Π‘ΠΎΡ‚ΠΊΠΈΠ½Π° с хроничСской болСзнью ΠΏΠΎΡ‡Π΅ΠΊ Ρ‚Π΅Ρ€ΠΌΠΈΠ½Π°Π»ΡŒΠ½ΠΎΠΉ стадии, ΠΊΠΎΡ€Ρ€ΠΈΠ³ΠΈΡ€ΡƒΠ΅ΠΌΠΎΠΉ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½Ρ‹ΠΌ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·ΠΎΠΌ, ΠΏΠ΅Ρ€Π΅Π½Π΅ΡΡˆΠ΅Π³ΠΎ COVID-19

    Three-Dimensional Simulations of a Starburst-Driven Galactic Wind

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    We have performed a series of three-dimensional simulations of a starburst-driven wind in an inhomogeneous interstellar medium. The introduction of an inhomogeneous disk leads to differences in the formation of a wind, most noticeably the absence of the ``blow-out'' effect seen in homogeneous models. A wind forms from a series of small bubbles that propagate into the tenuous gas between dense clouds in the disk. These bubbles merge and follow the path of least resistance out of the disk, before flowing freely into the halo. Filaments are formed from disk gas that is broken up and accelerated into the outflow. These filaments are distributed throughout a biconical structure within a more spherically distributed hot wind. The distribution of the inhomogeneous interstellar medium in the disk is important in determining the morphology of this wind, as well as the distribution of the filaments. While higher resolution simulations are required in order to ascertain the importance of mixing processes, we find that soft X-ray emission arises from gas that has been mass-loaded from clouds in the disk, as well as from bow shocks upstream of clouds, driven into the flow by the ram pressure of the wind, and the interaction between these shocks.Comment: 37 pages, 16 figures, mpg movie can be obtained at http://www.mso.anu.edu.au/~jcooper/movie/video16.mpg, accepted for publication in Ap

    Dark Matter Search Perspectives with GAMMA-400

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    GAMMA-400 is a future high-energy gamma-ray telescope, designed to measure the fluxes of gamma-rays and cosmic-ray electrons + positrons, which can be produced by annihilation or decay of dark matter particles, and to survey the celestial sphere in order to study point and extended sources of gamma-rays, measure energy spectra of Galactic and extragalactic diffuse gamma-ray emission, gamma-ray bursts, and gamma-ray emission from the Sun. GAMMA-400 covers the energy range from 100 MeV to ~3000 GeV. Its angular resolution is ~0.01 deg(Eg > 100 GeV), and the energy resolution ~1% (Eg > 10 GeV). GAMMA-400 is planned to be launched on the Russian space platform Navigator in 2019. The GAMMA-400 perspectives in the search for dark matter in various scenarios are presented in this paperComment: 4 pages, 4 figures, submitted to the Proceedings of the International Cosmic-Ray Conference 2013, Brazil, Rio de Janeir

    ΠšΠΈΠ½Π΅Ρ‚ΠΈΡ‡Π΅ΡΠΊΠΈΠ΅ характСристики процСсса растворСния PdCl2 Π² Π²ΠΎΠ΄Π½ΠΎ-Ρ…Π»ΠΎΡ€ΠΈΠ΄Π½Ρ‹Ρ… Π‘Π Π•Π”Π°Ρ…

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    The reaction of dissolution of solid PdCl2 in water-chloride media at room temperature was studied. It was established that the reaction proceeds via a mechanism of topochemical reaction. With the ionic strength fixed, the reaction rate constant is shown to depend on the chloride ion concentration with n = -2, thus confirming that this reaction goes through the formation of hydroxyl and aquachloride complexes of palladium. At low chlorides background Π‘ (NaCl) &lt; 0.3 M, and the topochemical nature of the reaction is mainly determined by hydroxide concentration in equilibrium with aquachloride complexes of palladium. The nature and rate of topochemical reaction is determined by concentration of NaCl. With decreasing the concentration of chloride ion from 1 M to 0.2 M reaction proceeds from kinetic to diffusion region.Π˜Π·ΡƒΡ‡Π΅Π½Π° рСакция растворСния Ρ‚Π²Π΅Ρ€Π΄ΠΎΠ³ΠΎ PdCl2 Π² Π²ΠΎΠ΄Π½ΠΎ-Ρ…Π»ΠΎΡ€ΠΈΠ΄Π½Ρ‹Ρ… срСдах ΠΏΡ€ΠΈ ΠΊΠΎΠΌΠ½Π°Ρ‚Π½ΠΎΠΉ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π΅. Показано, Ρ‡Ρ‚ΠΎ ΠΎΠ½Π° ΠΏΡ€ΠΎΡ‚Π΅ΠΊΠ°Π΅Ρ‚ ΠΏΠΎ ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΡƒ топохимичСской Ρ€Π΅Π°ΠΊΡ†ΠΈΠΈ

    Two novel approaches for photometric redshift estimation based on SDSS and 2MASS databases

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    We investigate two training-set methods: support vector machines (SVMs) and Kernel Regression (KR) for photometric redshift estimation with the data from the Sloan Digital Sky Survey Data Release 5 and Two Micron All Sky Survey databases. We probe the performances of SVMs and KR for different input patterns. Our experiments show that the more parameters considered, the accuracy doesn't always increase, and only when appropriate parameters chosen, the accuracy can improve. Moreover for different approaches, the best input pattern is different. With different parameters as input, the optimal bandwidth is dissimilar for KR. The rms errors of photometric redshifts based on SVM and KR methods are less than 0.03 and 0.02, respectively. Finally the strengths and weaknesses of the two approaches are summarized. Compared to other methods of estimating photometric redshifts, they show their superiorities, especially KR, in terms of accuracy.Comment: accepted for publication in ChJA

    The GAMMA-400 space observatory: status and perspectives

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    The present design of the new space observatory GAMMA-400 is presented in this paper. The instrument has been designed for the optimal detection of gamma rays in a broad energy range (from ~100 MeV up to 3 TeV), with excellent angular and energy resolution. The observatory will also allow precise and high statistic studies of the electron component in the cosmic rays up to the multi TeV region, as well as protons and nuclei spectra up to the knee region. The GAMMA-400 observatory will allow to address a broad range of science topics, like search for signatures of dark matter, studies of Galactic and extragalactic gamma-ray sources, Galactic and extragalactic diffuse emission, gamma-ray bursts and charged cosmic rays acceleration and diffusion mechanism up to the knee

    The Minimum Stellar Mass in Early Galaxies

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    The conditions for the fragmentation of the baryonic component during merging of dark matter halos in the early Universe are studied. We assume that the baryonic component undergoes a shock compression. The characteristic masses of protostellar molecular clouds and the minimum masses of protostars formed in these clouds decrease with increasing halo mass. This may indicate that the initial stellar mass function in more massive galaxies was shifted towards lower masses during the initial stages of their formation. This would result in an increase of the number of stars per unit halo mass, i.e., the efficiency of star formation.Comment: 18 pages, 7 figure

    A New Model for the Spiral Structure of the Galaxy. Superposition of 2+4-armed patterns

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    We investigate the possibility of describing the spiral pattern of the Milky Way in terms of a model of superposition 2- and 4-armed wave harmonics (the simplest description, besides pure modes). Two complementary methods are used: a study of stellar kinematics, and direct tracing of positions of spiral arms. In the first method, the parameters of the galactic rotation curve and the free parameters of the spiral density waves were obtained from Cepheid kinematics, under different assumptions. To turn visible the structure corresponding to these models, we computed the evolution of an ensemble of N-particles, simulating the ISM clouds, in the perturbed galactic gravitational field. In the second method, we present a new analysis of the longitude-velocity (l-v) diagram of the sample of galactic HII regions, converting positions of spiral arms in the galactic plane into locii of these arms in the l-v diagram. Both methods indicate that the ``self-sustained'' model, in which the 2-armed and 4-armed mode have different pitch angles (6 arcdeg and 12 arcdeg, respectively) is a good description of the disk structure. An important conclusion is that the Sun happens to be practically at the corotation circle. As an additional result of our study, we propose an independent test for localization of the corotation circle in a spiral galaxy: a gap in the radial distribution of interstellar gas has to be observed in the corotation region.Comment: 17 pages, 9 figures, Latex, uses aas2pp4.st

    Анализ влияния Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² риска Π½Π° краткосрочныС ΠΈ ΠΎΡ‚Π΄Π΅Π»Π΅Π½Π½Ρ‹Π΅ исходы ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с COVID-19 Π½Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎΠΌ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·Π΅

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    Patients receiving renal replacement therapy (RRT) in the form of maintenance hemodialysis (MHD) belong to a group of particularly high risk of infection and the course of COVID-19. The new coronavirus infection also has a great impact on long-term outcomes.Materials and methods: A retrospective observational study included 510 patients on MHD, hospitalized from April 1, 2020 to April 01, 2021. The outcome of hospitalization was chosen as the primary endpoint of the study: discharge or 28day mortality. Death within 6 months after discharge and the development of complications related to COVID-19 during this period were considered as secondary endpoints. Data collection was carried out by analyzing electronic and archival medical records. Quantitative variables: age, duration of hospitalization, days in the intensive care unit, laboratory blood parameters: the level of D-Dimer, Glucose, Interleukin-6, Procalcitonin, Lymphocytes and Platelets, CRP, CPK, CPK-MB, LDH, Fibrinogen, Ferritin. Qualitative indicators: gender, ventilator, ARDS, the presence of diabetes, the presence of obesity, the presence of complications: cardiovascular, gastrointestinal, septic, macrothrombotic, stage of pneumonia. To identify statistically significant predictors of the risk of an event, the odds ratio (OR) method was used.Results: average age 57.8Β±14 years, men – 59.5%, average bed day 17.6Β±10.6 days. In concomitant diseases, diabetes mellitus was indicated in 24% of patients, obesity was registered in 4.3% of patients. Hospital mortality (28-day) in the total cohort of follow-up was 16.05%, in total with out-ofhospital mortality of 22%. Mortality in intensive care reached 62.7%, on ventilator more than 86%, with ARDS 94.3%. No statistical significance was revealed by gender and the presence of diabetes mellitus (DM) in concomitant diseases. When comparing short-term outcomes, the age groups over 65 differed statistically. The following laboratory blood parameters showed a significant difference (P&lt;0.001): D-Dimer, Glucose, IL-6 lymphocytes, Leukocytes, Neutrophils, Platelets, LDH, Ferritin. The following odds ratios (OR) were obtained: ARDS (OR 143.78; 95% CI 33.4-616.2; p=0.0001), on ventilator (OR 57.96; 95% CI 23.1-144.5; p=0.0001), the presence of septic complications (OR 26.4; 95% CI 13.8-50; p=0.0001), the course of the disease is defined as severe (OR 25; 95% CI 12.9-48.2; p=0.0001), the course of the disease is defined as complicated (OR 11.6; 95% CI 6.8-19.7; p=0.0001), the presence of gastrointestinal complications (OR 6.5; 95% CI 2.28-18.4; p=0.0007), the presence of obesity (OR 2.57; 95% CI 1.0-6.5; p=0.039). Mortality of patients receiving two main treatment regimens T-1 and T-2 did not differ (15.8% vs 15.7%). Significant differences (p=0.0001) appeared when compared with the T-0 and T-4 schemes, in which mortality was recorded at 8.8% and 85.7%, respectively. When comparing long-term outcomes, the analysis did not reveal statistical significance by gender. The statistical difference was noted by age. Among laboratory indicators, the PCT level was higher in survivors with complications. A significant difference among all survivors and deceased (P&lt;0.001) was shown by: D-Dimer, blood glucose level, IL-6, CRP. The highest OR was calculated for the following indicators: the presence of gastrointestinal complications (OR 7.7; 95% CI 1.0-57.7; p=0.03), the initial LDH blood level of 622 units /l (OR 4.7; 95% CI 1.63-13.63; p=0.0086), the course of the disease defined as complicated (OR 4.05; 95% 1.97-8.33; p=0.003), the course of the disease is defined as severe (OR 2.4; 95% CI 1.17-5.0; p=0.03).Conclusions: gastrointestinal complications had the greatest impact on unfavorable short-term and long-term outcomes in patients on programmed hemodialysis. In relation to such laboratory markers as Ferritin, CRH, LDH, threshold values of a significant increase in the chances characteristic of dialysis patients were obtained. During the first year of the epidemic, therapy remained largely supportive and aimed at preventing complications, the main isolated treatment regimens showed no significant differences in the impact on the outcomes of COVID-19.ΠŸΠ°Ρ†ΠΈΠ΅Π½Ρ‚Ρ‹, ΠΏΠΎΠ»ΡƒΡ‡Π°ΡŽΡ‰ΠΈΠ΅ Π·Π°ΠΌΠ΅ΡΡ‚ΠΈΡ‚Π΅Π»ΡŒΠ½ΡƒΡŽ ΠΏΠΎΡ‡Π΅Ρ‡Π½ΡƒΡŽ Ρ‚Π΅Ρ€Π°ΠΏΠΈΡŽ Π² Π²ΠΈΠ΄Π΅ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·Π°, относятся ΠΊ Π³Ρ€ΡƒΠΏΠΏΠ΅ особо высокого риска инфицирования SARS-CoV-2 ΠΈ тяТСлого тСчСния COVID-19. Π‘ΠΎΠ»ΡŒΡˆΠΎΠ΅ влияниС новая коронавирусная инфСкция ΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅Ρ‚ ΠΈ Π½Π° ΠΎΡ‚Π΄Π°Π»Π΅Π½Π½Ρ‹Π΅ исходы Ρƒ Π΄Π°Π½Π½ΠΎΠΉ ΠΊΠ°Ρ‚Π΅Π³ΠΎΡ€ΠΈΠΈ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ².ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. Π’ рСтроспСктивноС обсСрвационноС исслСдованиС Π±Ρ‹Π»ΠΈ Π²ΠΊΠ»ΡŽΡ‡Π΅Π½Ρ‹ 510 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², ΠΏΠΎΠ»ΡƒΡ‡Π°ΡŽΡ‰ΠΈΡ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½Ρ‹ΠΉ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·, госпитализированных Π² ΠšΠ»ΠΈΠ½ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½ΡƒΡŽ Π±ΠΎΠ»ΡŒΠ½ΠΈΡ†Ρƒ ΠΈΠΌ. Π‘.П. Π‘ΠΎΡ‚ΠΊΠΈΠ½Π° с 1 апрСля 2020 Π³. ΠΏΠΎ 1 апрСля 2021 Π³. Π’ качСствС ΠΏΠ΅Ρ€Π²ΠΈΡ‡Π½ΠΎΠΉ ΠΊΠΎΠ½Π΅Ρ‡Π½ΠΎΠΉ Ρ‚ΠΎΡ‡ΠΊΠΈ исслСдования Π²Ρ‹Π±Ρ€Π°Π½ исход госпитализации: выписка/ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ΄ ΠΈΠ»ΠΈ 28-днСвная (Π²Π½ΡƒΡ‚Ρ€ΠΈΠ³ΠΎΡΠΏΠΈΡ‚Π°Π»ΡŒΠ½Π°Ρ) ΡΠΌΠ΅Ρ€Ρ‚ΡŒ. Π’ качСствС Π²Ρ‚ΠΎΡ€ΠΈΡ‡Π½Ρ‹Ρ… ΠΊΠΎΠ½Π΅Ρ‡Π½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ Ρ€Π°ΡΡΠΌΠ°Ρ‚Ρ€ΠΈΠ²Π°Π»ΠΈΡΡŒ ΡΠΌΠ΅Ρ€Ρ‚ΡŒ Π² Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ 6 мСсяцСв послС выписки ΠΈ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ ослоТнСний, связанных с COVID-19 Π² этот ΠΏΠ΅Ρ€ΠΈΠΎΠ΄. Π‘Π±ΠΎΡ€ Π΄Π°Π½Π½Ρ‹Ρ… осущСствлялся ΠΏΡƒΡ‚Π΅ΠΌ Π°Π½Π°Π»ΠΈΠ·Π° элСктронных ΠΈ Π°Ρ€Ρ…ΠΈΠ²Π½Ρ‹Ρ… историй Π±ΠΎΠ»Π΅Π·Π½ΠΈ. ΠšΠΎΠ»ΠΈΡ‡Π΅ΡΡ‚Π²Π΅Π½Π½Ρ‹Π΅ ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Π΅: возраст, количСство Π΄Π½Π΅ΠΉ госпитализации (ΠΊΠΎΠΉΠΊΠΎ-дСнь), Π΄Π½Π΅ΠΉ Π² ΠΎΡ‚Π΄Π΅Π»Π΅Π½ΠΈΠΈ интСнсивной Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ, Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€Π½Ρ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ ΠΊΡ€ΠΎΠ²ΠΈ: ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ Π”-Π΄ΠΈΠΌΠ΅Ρ€Π°, Π³Π»ΡŽΠΊΠΎΠ·Ρ‹, ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π°-6, ΠΏΡ€ΠΎΠΊΠ°Π»ΡŒΡ†ΠΈΡ‚ΠΎΠ½ΠΈΠ½Π°, Π»ΠΈΠΌΡ„ΠΎΡ†ΠΈΡ‚ΠΎΠ² ΠΈ Ρ‚Ρ€ΠΎΠΌΠ±ΠΎΡ†ΠΈΡ‚ΠΎΠ², Π¦Π Π‘, КЀК, КЀК-ΠœΠ’, Π›Π”Π“, Ρ„ΠΈΠ±Ρ€ΠΈΠ½ΠΎΠ³Π΅Π½Π°, Ρ„Π΅Ρ€Ρ€ΠΈΡ‚ΠΈΠ½Π°. ΠšΠ°Ρ‡Π΅ΡΡ‚Π²Π΅Π½Π½Ρ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ: ΠΏΠΎΠ», искусствСнная вСнтиляция Π»Π΅Π³ΠΊΠΈΡ…, острый рСспираторный дистрСсс-синдром, Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ сахарного Π΄ΠΈΠ°Π±Π΅Ρ‚Π°, Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ оТирСния, Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ ослоТнСний: сСрдСчно-сосудистых, со стороны ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎ-ΠΊΠΈΡˆΠ΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ‚Ρ€Π°ΠΊΡ‚Π°, сСптичСских, макротромботичСских, стадия ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ. Для ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ статистичСски Π·Π½Π°Ρ‡ΠΈΠΌΡ‹Ρ… ΠΏΡ€Π΅Π΄ΠΈΠΊΡ‚ΠΎΡ€ΠΎΠ² риска наступлСния события использовался ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΡ шансов.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹: срСдний возраст 57,8Β±14 Π»Π΅Ρ‚, ΠΌΡƒΠΆΡ‡ΠΈΠ½Ρ‹ – 59, 5%, срСдний ΠΊΠΎΠΉΠΊΠΎ-дСнь 17,6Β±10,6 Π΄Π½Π΅ΠΉ. Π’ ΡΠΎΠΏΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… заболСваниях сахарный Π΄ΠΈΠ°Π±Π΅Ρ‚ Π±Ρ‹Π» ΡƒΠΊΠ°Π·Π°Π½ Ρƒ 24% ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², ΠΎΠΆΠΈΡ€Π΅Π½ΠΈΠ΅ зарСгистрировано Ρƒ 4,3% ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ². Π“ΠΎΡΠΏΠΈΡ‚Π°Π»ΡŒΠ½Π°Ρ Π»Π΅Ρ‚Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ (28-днСвная) Π² ΠΎΠ±Ρ‰Π΅ΠΉ ΠΊΠΎΠ³ΠΎΡ€Ρ‚Π΅ наблюдСния составила 16,05%, Π² суммС с Π²Π½Π΅Π³ΠΎΡΠΏΠΈΡ‚Π°Π»ΡŒΠ½ΠΎΠΉ Π»Π΅Ρ‚Π°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒΡŽ 22%. Π‘ΠΌΠ΅Ρ€Ρ‚Π½ΠΎΡΡ‚ΡŒ Π² Ρ€Π΅Π°Π½ΠΈΠΌΠ°Ρ†ΠΈΠΈ достигла 62,7%, Π½Π° Π˜Π’Π› Π±ΠΎΠ»Π΅Π΅ 86%, с ΠžΠ Π”Π‘ 94,3%. НС выявлСно статистичСской значимости ΠΏΠΎ ΠΏΠΎΠ»Ρƒ ΠΈ Π½Π°Π»ΠΈΡ‡ΠΈΡŽ Π² ΡΠΎΠΏΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… заболСваниях сахарного Π΄ΠΈΠ°Π±Π΅Ρ‚Π°. ΠŸΡ€ΠΈ сравнСнии краткосрочных исходов статистичСски Ρ€Π°Π·Π»ΠΈΡ‡Π°Π»ΠΈΡΡŒ Π³Ρ€ΡƒΠΏΠΏΡ‹ ΠΏΠΎ возрасту ΡΡ‚Π°Ρ€ΡˆΠ΅ 65 Π»Π΅Ρ‚. Π—Π½Π°Ρ‡ΠΈΠΌΡƒΡŽ Ρ€Π°Π·Π½ΠΈΡ†Ρƒ (P&lt;0,001) ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅ Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€Π½Ρ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ ΠΊΡ€ΠΎΠ²ΠΈ: Π”-Π΄ΠΈΠΌΠ΅Ρ€, глюкоза, Π˜Π›-6, Π»ΠΈΠΌΡ„ΠΎΡ†ΠΈΡ‚Ρ‹, Π»Π΅ΠΉΠΊΠΎΡ†ΠΈΡ‚Ρ‹, Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»Ρ‹, Ρ‚Ρ€ΠΎΠΌΠ±ΠΎΡ†ΠΈΡ‚Ρ‹, Π›Π”Π“, Ρ„Π΅Ρ€Ρ€ΠΈΡ‚ΠΈΠ½. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΡ шансов: острый рСспираторный дистрСсс-синдром (ОШ 143,78; 95% Π”Π˜ 33,4–616,2; p=0,0001), Π½Π° искусствСнной вСнтиляции Π»Π΅Π³ΠΊΠΈΡ… (ОШ 57,96; 95% Π”Π˜ 23,1–144,5; p=0,0001), Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ сСптичСских ослоТнСний (ОШ 26,4; 95% Π”Π˜ 13,8– 50; p=0,0001), тяТСлоС Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ заболСвания (ОШ 25; 95% Π”Π˜ 12,9–48,2; p=0,0001), ослоТнённоС Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ заболСвания (ОШ 11,6; 95% Π”Π˜ 6,8–19,7; p=0,0001), Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ ослоТнСний со стороны ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎ-ΠΊΠΈΡˆΠ΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ‚Ρ€Π°ΠΊΡ‚Π° (ОШ 6,5; 95% Π”Π˜ 2,28–18,4; p=0,0007), Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ оТирСния (ОШ 2,57; 95% Π”Π˜ 1,0–6,5; p=0,039). Π‘ΠΌΠ΅Ρ€Ρ‚Π½ΠΎΡΡ‚ΡŒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², ΠΏΠΎΠ»ΡƒΡ‡Π°ΡŽΡ‰ΠΈΡ… Π΄Π²Π΅ основныС схСмы лСчСния Π’-1 ΠΈ Π’-2, Π½Π΅ Ρ€Π°Π·Π»ΠΈΡ‡Π°Π»Π°ΡΡŒ (15,8% vs 15,7%). Π—Π½Π°Ρ‡ΠΈΠΌΡ‹Π΅ различия (p=0,0001) появлялись ΠΏΡ€ΠΈ сравнСнии со схСмами Π’-0 ΠΈ Π’-4, ΠΏΡ€ΠΈ ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… зарСгистрирована ΡΠΌΠ΅Ρ€Ρ‚Π½ΠΎΡΡ‚ΡŒ 8,8% ΠΈ 85,7% соотвСтствСнно. ΠŸΡ€ΠΈ сравнСнии ΠΎΡ‚Π΄Π°Π»Π΅Π½Π½Ρ‹Ρ… исходов Π°Π½Π°Π»ΠΈΠ· Π½Π΅ выявил статистичСской Π·Π½Π°Ρ‡ΠΈΠΌΠΎΡΡ‚ΡŒ ΠΏΠΎ ΠΏΠΎΠ»Ρƒ. БтатистичСскоС Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠ΅ ΠΎΡ‚ΠΌΠ΅Ρ‡Π°Π»ΠΎΡΡŒ ΠΏΠΎ возрасту. Π‘Ρ€Π΅Π΄ΠΈ Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€Π½Ρ‹Ρ… ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ PCT Π±Ρ‹Π» Π²Ρ‹ΡˆΠ΅ Ρƒ Π²Ρ‹ΠΆΠΈΠ²ΡˆΠΈΡ… с ослоТнСниями. Π—Π½Π°Ρ‡ΠΈΠΌΡƒΡŽ Ρ€Π°Π·Π½ΠΈΡ†Ρƒ срСди всСх Π²Ρ‹ΠΆΠΈΠ²ΡˆΠΈΡ… ΠΈ ΡƒΠΌΠ΅Ρ€ΡˆΠΈΡ… (P&lt;0,001) ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ: Π”-Π΄ΠΈΠΌΠ΅Ρ€, ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ Π³Π»ΡŽΠΊΠΎΠ·Ρ‹ ΠΊΡ€ΠΎΠ²ΠΈ, Π˜Π›-6, Π‘Π Π‘. НаиболСС высокоС ОШ Π±Ρ‹Π»ΠΎ рассчитано для ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ: Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ Π–ΠšΠ’-ослоТнСний (ОШ 7,7; 95% Π”Π˜ 1,0-57,7; p=0,03), уровня исходного Π›Π”Π“ ΠΊΡ€ΠΎΠ²ΠΈ 622 Π•Π΄/Π» (ОШ 4,7; 95% Π”Π˜ 1,63–13,63; p=0,0086), ослоТнённоС Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ заболСвания (ОШ 4,05; 95% 1,97–8,33; p=0,003), тяТСлоС Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ заболСвания (ОШ 2,4; 95% Π”Π˜ 1,17–5,0; p=0,03).Π’Ρ‹Π²ΠΎΠ΄Ρ‹: наибольшСС влияниС Π½Π° нСблагоприятныС краткосрочныС ΠΈ ΠΎΡ‚Π΄Π°Π»Π΅Π½Π½Ρ‹Π΅ исходы Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с COVID-19 Π½Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½ΠΎΠΌ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ°Π»ΠΈΠ·Π΅ ΠΎΠΊΠ°Π·Π°Π»ΠΈ ослоТнСния со стороны Π–ΠšΠ’. Π’ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΈ Ρ‚Π°ΠΊΠΈΡ… Π»Π°Π±ΠΎΡ€Π°Ρ‚ΠΎΡ€Π½Ρ‹Ρ… ΠΌΠ°Ρ€ΠΊΠ΅Ρ€ΠΎΠ², ΠΊΠ°ΠΊ Ρ„Π΅Ρ€Ρ€ΠΈΡ‚ΠΈΠ½, Π‘Π Π‘, Π›Π”Π“, Π±Ρ‹Π»ΠΈ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ ΠΏΠΎΡ€ΠΎΠ³ΠΎΠ²Ρ‹Π΅ значСния Π·Π½Π°Ρ‡ΠΈΠΌΠΎΠ³ΠΎ увСличСния шансов, Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π½Ρ‹Π΅ ΠΈΠΌΠ΅Π½Π½ΠΎ для Π΄ΠΈΠ°Π»ΠΈΠ·Π½Ρ‹Ρ… ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ². Π—Π° ΠΏΠ΅Ρ€Π²Ρ‹ΠΉ Π³ΠΎΠ΄ эпидСмии тСрапия ΠΎΡΡ‚Π°Π²Π°Π»Π°ΡΡŒ Π² Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ стСпСни ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΈΠ²Π°ΡŽΡ‰Π΅ΠΉ ΠΈ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Π½ΠΎΠΉ Π½Π° ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΡƒ ослоТнСний, основныС Π²Ρ‹Π΄Π΅Π»Π΅Π½Π½Ρ‹Π΅ схСмы лСчСния Π½Π΅ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ сущСствСнных Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ ΠΏΠΎ влиянию Π½Π° исходы COVID-19
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