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As coronavirus disease 2019 (COVID-19) spreads across the world, the intensive care unit (ICU) community must prepare for the challenges associated with this pandemic. Providing an efficient care to the patients of the most severely affected category - intensive care unit (ICU) patients - has become one of the serious problems appearing in the COVID-19 pandemics. A typical patient's clinical portrait in ICU of COVID centers is very similar in different countries, however, the key to improve the treatment results for critically ill patients has not yet been found. Data on predictors of severe course in COVID-19 is limited. Knowledge of predictors of severe course of disease can lead to different selection of therapeutic strategy, determine the group of risk of patients for severe course of disease, and improve outcomes.
The clinical disease (COVID-19) results in critical illness in about 5% of patients. The aim of the study is to identify predictors of the severe pneumonia caused by the SARS-CoV-2 virus, and to describe the clinical features of patients admitted to an ICU of the COVID-center of the Federal Research Clinical Center of Federal Medical & Biological Agency on the first day and in dynamics till discharge from the ICU or death.
The demographic and clinical data will be collected. Laboratory data (hemoglobin, lymphocytes, neutrophil to lymphocyte ratio, D-dimer level, IL-6, procalcitonin, glucose level, high-sensitive troponin Т, vitamin D level, signs of the presence of a secondary bacterial infection, immunogram and Instrumental data (CT-scan, Electrocardiography, echocardiography, arterial and venous ultrasound investigation) will be analysed.
This study is singlecentral observational trial.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Clinical Features of Severe Patients With COVID-19 | Critical ill patients with COVID-19 admitted to the ICU. The demographic, clinical data, laboratory data, and Instrumental data will be analysed. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| The demographic, clinical, laboratory, and instrumental data | Diagnostic Test | Measurement of the demographic, clinical data, laboratory data, and instrumental data |
|
| Measure | Description | Time Frame |
|---|---|---|
| Mechanical ventilation duration | The amount of mechanical ventilation days | 30 days |
| Non-invasive Mechanical ventilation duration | The amount of Non-invasive mechanical ventilation days | 30 days |
| Mortality | The dead and survived patients ratio | 60 days |
| Measure | Description | Time Frame |
|---|---|---|
| Сomplete blood count | Сomplete blood count | Change from baseline on day 5 during ICU treatment |
| Biochemistry analysis | Biochemistry analysis |
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Inclusion Criteria:
Exclusion Criteria:
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All patients with COVID-19 requiring respiratory support
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| Name | Affiliation | Role |
|---|---|---|
| Tatiana V Klypa, Dr.Med.Sc. | Federal Research Clinical Center of Federal Medical & Biological Agency | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Federal Research Clinical Center of Federal Medical & Biological Agency | Moscow | 115682 | Russia |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32007143 | Background | Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J, Yu T, Zhang X, Zhang L. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020 Feb 15;395(10223):507-513. doi: 10.1016/S0140-6736(20)30211-7. Epub 2020 Jan 30. | |
| 32441789 |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| D004194 | Disease |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| Change from baseline on day 5 during ICU treatment |
| Сomplete blood count dynamics | Сomplete blood count | Change from baseline on day 15 during ICU treatment |
| Biochemistry analysis dynamics | Biochemistry analysis | Change from baseline on day 15 during ICU treatment |
| Computer tomography | Computer tomography of lungs | Change from baseline on day 5 during ICU treatment |
| High-sensitive troponin Т | High-sensitive troponin Т | Change from baseline on day 5 during ICU treatment |
| High-sensitive troponin Т dynamics | High-sensitive troponin Т | Change from baseline on day 15 during ICU treatment |
| Vitamin D level | Vitamin D level | Change from baseline on day 5 during ICU treatment |
| Vitamin D level dynamics | Vitamin D level | Change from baseline on day 15 during ICU treatment |
| Immunogram | Immunogram | Change from baseline on day 5 during ICU treatment |
| Immunogram dynamics | Immunogram | Change from baseline on day 15 during ICU treatment |
| Tian W, Jiang W, Yao J, Nicholson CJ, Li RH, Sigurslid HH, Wooster L, Rotter JI, Guo X, Malhotra R. Predictors of mortality in hospitalized COVID-19 patients: A systematic review and meta-analysis. J Med Virol. 2020 Oct;92(10):1875-1883. doi: 10.1002/jmv.26050. Epub 2020 Jul 11. |
| 32511655 | Background | Paranjpe I, Russak AJ, De Freitas JK, Lala A, Miotto R, Vaid A, Johnson KW, Danieletto M, Golden E, Meyer D, Singh M, Somani S, Manna S, Nangia U, Kapoor A, O'Hagan R, O'Reilly PF, Huckins LM, Glowe P, Kia A, Timsina P, Freeman RM, Levin MA, Jhang J, Firpo A, Kovatch P, Finkelstein J, Aberg JA, Bagiella E, Horowitz CR, Murphy B, Fayad ZA, Narula J, Nestler EJ, Fuster V, Cordon-Cardo C, Charney DS, Reich DL, Just AC, Bottinger EP, Charney AW, Glicksberg BS, Nadkarni GN. Clinical Characteristics of Hospitalized Covid-19 Patients in New York City. medRxiv [Preprint]. 2020 Apr 26:2020.04.19.20062117. doi: 10.1101/2020.04.19.20062117. |
| 33982128 | Derived | Bychinin MV, Klypa TV, Mandel IA, Andreichenko SA, Baklaushev VP, Yusubalieva GM, Kolyshkina NA, Troitsky AV. Low Circulating Vitamin D in Intensive Care Unit-Admitted COVID-19 Patients as a Predictor of Negative Outcomes. J Nutr. 2021 Aug 7;151(8):2199-2205. doi: 10.1093/jn/nxab107. |
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |