Validation of Prognostic Clinical Risk Scores in Predicting Outcome for Patients With COVID-19 at Initial Triage

NCT05582382 | Unknown

• 1 other identifier: CMHS_IntMed_DOH/CVDC/2020/1251
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

Background Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing Covid-19 pandemic continues to be a global health threat with a massive burden on health care systems resulting in more than six million deaths in 188 countries. Because of wide clinical spectrum of disease severity, having clinically applicable prognostic tools for early identification of patients at high risk of progression to severe / critical illness is essential to guide clinical decision making and resource allocation efforts. So far, clinical prognostic tools have focused on host factors, but more recent data indicated a significant association between SARS-CoV-2 variants and the development of complications such as long COVID. Objectives

1. 1.Validation of the ALA \& ALKA prediction tools for initial evaluation of patients diagnosed with COVID-19 infection.
2. 2.Comparison of performance of the ALA \& ALKA prediction tools with the currently clinical risk assessment scoring system used during initial evaluation of patients diagnosed with COVID-19 infection.
3. 3.Evaluation of the clinical risk assessment scoring based on number of comorbidities in prediction of COVID-19 related complications
4. 4.Assessment of the association between SARS-CoV-2 variants and the risk of COVID-19 severity
5. 5.Assessment of the impact of SARS-CoV-2 variants on the performance of ALA \& ALKA prediction tools

Conditions

COVID-19

Keywords

hospitalization; COVID-19; clinical risk score; morbidity; prediction

Outcome Measures

Primary Outcomes (1)

• Validation of the ALA & ALKA prediction tools

  Validation of the ALA \& ALKA prediction tools for initial evaluation of patients diagnosed with COVID-19 infection

  12 months

Secondary Outcomes (1)

• Comparison of performance of the ALA & ALKA prediction tools with current clinical risk tools

  12 months

Interventions

logistic regression of known prognostic markers of severity of COVID19 OTHER

An observational longitudinal follow up of all consecutive patients with positive SARS-CoV-2 testing on nasopharyngeal swabs per WHO definitions presenting to the emergency department . The risk assessment score at initial presentation will be calculated for each patient using clinical assessment scoring of ALA \& ALKA and compared with the currently proposed clinical risk assessment scoring system The utility of the risk score in triaging patients on their initial visits to emergency department (ED) will be validated against the following measured outcomes: 1. Hospital admission on the first encounter to ED 2. Admission to ICU for the duration of the COVID-19 hospitalization 3. In hospital and out of hospital mortality 4. Return to ED following initial discharge (within the current covid illness period, Maximum 30 days from the initial diagnosis)

Eligibility Criteria

• Age: 16 Years - 99 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The sample will include all consecutive symptomatic patients with confirmed COVID-19 infection presented to ED. A sample size of 2000 is required for the validation of the prognostic predictive tools. Sample Collection Process: Data will be abstracted from electronic medical records using a data collection tool. The data would include demographics, clinical manifestation, comorbidities, laboratory and radiological results, and final outcomes. The assessment risk score at initial presentation will be calculated using a free web-based online calculator.

You may qualify if:

• All consecutive patients with positive SARS-CoV-2 testing on nasopharyngeal swabs per WHO definitions presenting to the emergency department
• All patients admitted to the hospital for isolation purposes only

You may not qualify if:

• Inconclusive PCR results on initial or repeat results with 24 hours

Sponsors & Collaborators

• Dr Adnan Agha: lead
• Abu Dhabi Health Services Company: collaborator

Study Sites (1)

Internal Medicine, College of Medicine and Health Sciences

Al Ain City, Abu Dhabi Emirate, 15551, United Arab Emirates

RECRUITING

Related Publications (4)

• Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review. JAMA. 2020 Aug 25;324(8):782-793. doi: 10.1001/jama.2020.12839.

  PMID: 32648899 BACKGROUND

• Halalau A, Imam Z, Karabon P, Mankuzhy N, Shaheen A, Tu J, Carpenter C. External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients. Ann Med. 2021 Dec;53(1):78-86. doi: 10.1080/07853890.2020.1828616. Epub 2020 Oct 9.

  PMID: 32997542 BACKGROUND

• Dardenne N, Locquet M, Diep AN, Gilbert A, Delrez S, Beaudart C, Brabant C, Ghuysen A, Donneau AF, Bruyere O. Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study. BMC Infect Dis. 2022 May 14;22(1):464. doi: 10.1186/s12879-022-07420-4.

  PMID: 35568825 BACKGROUND

• Kurban LAS, AlDhaheri S, Elkkari A, Khashkhusha R, AlEissaee S, AlZaabi A, Ismail M, Bakoush O. Predicting Severe Disease and Critical Illness on Initial Diagnosis of COVID-19: Simple Triage Tools. Front Med (Lausanne). 2022 Feb 10;9:817549. doi: 10.3389/fmed.2022.817549. eCollection 2022.

  PMID: 35223916 BACKGROUND

MeSH Terms

Conditions

COVID-19

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases

Study Officials

• Adnan Agha

  United Arab Emirates University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Omran Bakoush

CONTACT

+971-3-7673333; Omran.Bakoush@uaeu.ac.ae

Adnan Agha

CONTACT

+971-3-7673333; adnanagha@uaeu.ac.ae

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Assistant Professor, Internal Medicine, College of Medicine and Health Sciences, United Arab Emirates University

Study Record Dates

• First Submitted: October 14, 2022
• First Posted: October 17, 2022
• Study Start: January 1, 2023
• Primary Completion: December 1, 2023
• Study Completion: January 1, 2024
• Last Updated: February 6, 2023

Record last verified: 2023-02

Locations

AE (1)