Predictive Factors COVID-19 Patients

Overview

This is a monocentric retro-prospective observational study that will be conducted on all COVID19 positive patients hospitalized at the S. Gerardo Hospital in Monza.

Full Title of Study: “Predictive Clinical Response Factors in COVID-19 Patients”

Study Type

  • Study Type: Observational
  • Study Design
    • Time Perspective: Retrospective
  • Study Primary Completion Date: May 2021

Detailed Description

BACKGROUND: The Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) pandemic is severely testing the health systems of the most advanced countries. Clinicians are faced with a new pathology of an emerging virus. There is therefore an urgent need to collect real-time clinical data that informs about outcome predictive variables. Furthermore, there are currently no antiviral drugs approved for the treatment of SARS-CoV-2 infection, off-label therapies are being used with drugs already in use for other pathologies that have shown some efficacy in vitro, and some treatments obtained for compassionate use with other drugs that are being tested. It is more than ever necessary to collect clinical practice data both retrospectively on the work done so far, and in a longitudinal perspective, and analyze them quickly to optimize current treatments and define protocols for the future. Having a good clinical data base also offers the possibility of collaborating with numerous international networks on translational research, which aims to correlate clinical data with virological and immunological data, aimed at the rapid identification of possible specific viral virulence factors, or particular immune structures of the guests who once again define the final clinical outcome. STUDY DESIGN: All COVID19 positive patients admitted to San Gerardo Hospital will be enrolled in the study. After patient signs the informed consent, the following data will be collected: – birth data – sex – demographic data – comorbidity – blood chemistry data at the entrance A series of variables will then be collected relating to the treatment procedure, the therapies, the team's choice to maximize the care ceiling in the individual patient and the entire clinical study of the patient. STATISTICAL ANALISYS: Central tendency and dispersion measurements will be used for descriptive analysis of continuous variables while absolute and relative frequencies will be used to describe categorical variables.

Interventions

  • Other: Predictive factors for clinical response in patients with COVID-19.
    • Identify the risk factors for intra-hospital mortality in patients hospitalized in the COVID + hospital wards of the San Gerardo hospital and build a prognostic score through which it is possible to define a stratification that immediately guides the therapeutic choices and the intensity of care .

Arms, Groups and Cohorts

  • Covid19 infection related patients
    • Patients admitted to COVID wards of the S. Gerardo Hospital of Monza, including Intensive Care wards.

Clinical Trial Outcome Measures

Primary Measures

  • Identify risk factors for intra-hospital mortality.
    • Time Frame: Until patient discharge from the hospital (approximately 1 year)
    • Identify risk factors for intra-hospital mortality in patients admitted to the COVID + hospital wards of San Gerardo hospital.
  • Identify risk factors to build a prognostic score.
    • Time Frame: Until patient discharge from the hospital (approximately 1 year)
    • Identify the risk factors to build a prognostic score through which it is possible to define a stratification that immediately guides the therapeutic choices.
  • Identify risk factors to build a prognostic score.
    • Time Frame: Until patient discharge from the hospital (approximately 1 year)
    • Identify the risk factors to build a prognostic score through which it is possible to define a stratification that immediately directs towards the right intensity of care.

Secondary Measures

  • Predictive factors for the hospitalization duration.
    • Time Frame: Until patient discharge from the hospital (approximately 1 year)
    • Description of the predictive factors for the hospitalization duration.
  • Predictive factors for clinical status patients based on “Ordinal Scale for Clinical Improvement”
    • Time Frame: Until patient discharge from the hospital (approximately 1 year)
    • Description of the predictive factors for the clinical status of patients based on “Ordinal Scale for Clinical Improvement” defined by OMS (
  • Describe the anti-viral therapies used commonly in this emergency in terms of efficacy
    • Time Frame: Until patient discharge from the hospital (approximately 1 year).
    • Description of efficacy of the anti-viral therapies used today without particular restrictions, but on which solid clinical functioning tests are lacking.
  • Describe the anti-viral therapies used commonly used in this emergency in terms of safety
    • Time Frame: Until patient discharge from the hospital (approximately 1 year).
    • Description of safety of the anti-viral therapies used today without particular restrictions, but on which solid clinical functioning tests are lacking.
  • Monitor the clinical course of the disease in discharged patients.
    • Time Frame: 12 month after discharge
    • Description of the disease clinical course in patients 12 months after discharge (mortality, neurological, respiratory and cardiac outcomes).

Participating in This Clinical Trial

Inclusion Criteria

  • Patients 18 years old or above – Diagnosis of SARS-CoV-2 pneumonia Exclusion Criteria:

  • Explicit refusal to participate in the study

Gender Eligibility: All

Minimum Age: 18 Years

Maximum Age: N/A

Are Healthy Volunteers Accepted: No

Investigator Details

  • Lead Sponsor
    • University of Milano Bicocca
  • Provider of Information About this Clinical Study
    • Sponsor

References

Rosenbaum L. Facing Covid-19 in Italy – Ethics, Logistics, and Therapeutics on the Epidemic's Front Line. N Engl J Med. 2020 May 14;382(20):1873-1875. doi: 10.1056/NEJMp2005492. Epub 2020 Mar 18. No abstract available.

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.

Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585. Erratum In: JAMA. 2021 Mar 16;325(11):1113.

Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, Huang H, Zhang L, Zhou X, Du C, Zhang Y, Song J, Wang S, Chao Y, Yang Z, Xu J, Zhou X, Chen D, Xiong W, Xu L, Zhou F, Jiang J, Bai C, Zheng J, Song Y. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020 Jul 1;180(7):934-943. doi: 10.1001/jamainternmed.2020.0994. Erratum In: JAMA Intern Med. 2020 Jul 1;180(7):1031.

Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648. No abstract available.

Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28.

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