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Although the recent literature is building a remarkable background to answer the many unknowns related to SARS-CoV-2 infection, it is absolutely necessary to finalize every clinical effort to collect data that may be useful, in a short time, to improve our knowledge of SARS-CoV-2 infection. Numerous biomarkers have been evaluated in the recent literature as being altered in patients with severe forms of COVID-19. Particularly, in the critical care area, the research of early predictors of mortality is essential for high-flow management of patients requiring invasive assisted ventilation and requiring invasive and non-invasive assisted ventilation, hemodynamic support, sometimes extracorporeal support (Extracorporeal Membrane Oxygenation, ECMO). The coordinated study of different biomarkers, in particular, if combined with each other, possibly even to constitute a possible score, could guide the correct allocation of patients between hospital departments and the appropriate management in intensive care units. appropriate management in intensive care units, as well as providing an early prognostic indication. prognostic indication. The combination of these biomarkers with routine clinical and laboratory data may further provide valuable information about their use in acute care and as progressive acute and as progressive monitoring over time.
Regarding the data of interest on the clinical trend, the evaluation of the respiratory support modalities, from the administration of oxygen therapy (by nasal cannulae or Venturi mask, or by high flow system - High Flow Nasal Cannula, HFNC), to CPAP support or by non-invasive or invasive ventilation, appears of particular importance.
Therefore, the present study will be conducted in sub-intensive as well as intensive care units, in order to evaluate different types of patients, and their possible evolution over time.
The comparison between the populations belonging to different areas of intensity of care will be able to describe the different populations. Data analysis will allow an evaluation of possible risk factors and prognostic determinants of the severity of the disease and its infectious complications.
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| Measure | Description | Time Frame |
|---|---|---|
| ICU inpatient mortality | 24 months | |
| ICU inpatient length of stay | 24 months |
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of over-infections (bacterial, viral, fungal), particularly of bacteremia and pneumonias associated with mechanical ventilation; observed infections' microbiological characteristics. | 24 months |
| Measure | Description | Time Frame |
|---|---|---|
| Identification of prognostic factors (biomarkers, clinical scores, respiratory support modalities, others). | 24 months |
Inclusion Criteria:
Exclusion Criteria:
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Patients admitted to intensive care areas (intensive care unit/intensive care unit) and semi-intensive care areas dedicated to the care of COVID-19 patients.
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| Name | Affiliation | Role |
|---|---|---|
| Luca Brazzi, Professor | University of Torino | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| AOU Città della Salute e della Scienza di Torino | Torino | 10100 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39916726 | Derived | Montrucchio G, Balzani E, Sales G, Bolla C, Sarda C, Della Selva A, Perotto M, Pomero F, Ravera E, Rumbolo F, Callegari T, Fanelli V, Mengozzi G, Brazzi L. Critical and non-critical coronavirus disease 2019 patients: which is the most predictive biomarker for disease severity and outcome?: A multicentre prospective cohort study comparing mid-regional pro-adrenomedullin, inflammatory and immunological patterns. Eur J Anaesthesiol Intensive Care. 2023 Nov 21;2(6):e0039. doi: 10.1097/EA9.0000000000000039. eCollection 2023 Dec. |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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Results of the following assays will be retrieved for the different times of the study:
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |