Prediction for Critical Outcomes of Patients With COVID-19

NCT ID: NCT05124587

Last Updated: 2021-11-18

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 600 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-09-01
• Study Completion Date: 2022-12-31

Brief Summary

The study aims to develop and externally validate a prediction model for the critical outcomes of COVID-19 patients using predictors which can be easily obtained in clinical practice, including patients' demographic characteristics, self-reported medical conditions, and oral health.

Detailed Description

Background The novel coronavirus disease 2019 (COVID-19) pandemic has presented an important and urgent threat to global health since its outbreak in December 2019. The COVID-19 does not only affect the respiratory tract, but also other organs in human body including lungs, liver, kidney, heart, vessels, and other organs (1). Respiratory failure and acute respiratory distress syndrome (ARDS) are the most common serious complications of COVID-19 infection (2). The crude mortality rates (CMRs) of COVID-19 varies in different locations, which ranges from 37.0/100,000 to 167.6/100,000 in several European countries up to 30th August 2020 (3). The in-hospital mortality of COVID-19 was reported to be 17.1% based on 33 studies from 13,398 patients (4), and it was 2.9 times higher than that of influenza based on the French national administrative database (5). It was reported that 26% of the COVID-19 patients admitted to ICU with severe status and 31% of the patients who admitted to ICU died based on 37 studies from 24,983 patients (6).

There are several risk factors on patients' demographic characteristics and underlying medical conditions which were shown be associated with the critical outcomes of COVID-19 (7). In addition, poor oral health, in particular periodontitis, was also shown to be associated with the critical outcomes of COVID-19 (8). Marouf et al. showed that COVID-19 patients with periodontitis had 8 times higher odds of death and 3.5 times higher odds of ICU admission than those without periodontitis based on a case-control study (9). This may be because periodontal disease could enhance cytokine release via altered microflora, expression of multiple viral receptors, bacterial superinfection, and aspiration of periodontal pathogens (10). The increased production of pro-inflammatory cytokine, which is referred to as cytokine storm, is the foremost cause of the adverse events of COVID-19 (10).

Because of the high contagiousness, high ICU admission rate, and high mortality of COVID-19, it has led to tremendous increases in the demand for hospital beds and shortage of medical equipment. Therefore, there is an urgent need for a pragmatic risk stratification tool that allows the early identification of the COVID-19 patients who are likely to be at highest risk of ICU admission and death (11). This can help clinicians and policymakers make the decisions on the management and optimize resource allocation. A recent review identified multiple prediction models which have been developed for prediction of prognosis of COVID-19 patients (12). Those prediction models varied in their predictors and performance of the models. A large number of prediction models reflected difficulties in their application in the rapid risk stratification for general COVID-19 patients at their first intake in hospitals because some predictors cannot be easily obtained without professional devices or lab tests, such as C reactive protein, peripheral oxygen saturation, and urea level. Many prediction models showed moderate performance in aspects of discrimination and calibration, and no benefit to clinical decision making (12). In addition, the dental variables were not considered the potential predictors in the previously developed models.

Therefore, the aim of the present study is to develop and externally validate a prediction model for the critical outcomes of COVID-19 patients using predictors which can be easily obtained in clinical practice, including patients' demographic characteristics, self-reported medical conditions, and oral health.

Materials and Methods Participants We include hospitalized patients and outpatients from the Isala Hospital (Zwolle, the Netherlands) with confirmed COVID-19 who visited the Department of Oral and Maxillofacial Surgery (OMFS) between March 2020 and May 2021, if they have had a dental panoramic radiograph (OPG), obtained up to a maximum of 5 years until the end of the current study. The patients are used to develop the prediction model (derivation cohort).

We also include the hospitalized patients and outpatients from Noordwest Ziekenhuis (NWZ) (Alkmaar, the Netherlands) with confirmed COVID-19 to externally validate the prediction model (validation cohort).

Potential predictors

The potential predictors include patients' demographic characteristics, self-reported medical conditions, and oral health. All the potential predictors are collected at baseline. The potential predictors are presented below:

Demographic characteristics

• Gender
• Age
• BMI

Medical conditions

• Smoking
• Diabetes
• Hypertension
• Hypercholesterolemia
• COPD
• CVD
• Chronic kidney disease
• OSAS

Dental variables (based on OPG)

• Number of teeth
• Number of dental implants

Outcome (endpoint) The endpoint of the study is the presence or absence of the critical outcomes of COVID-19 (dichotomized). The course and outcome of the COVID-19 is classified into (1) ambulatory; (2) hospitalized; (3) ICU admission or death based on the WHO Clinical Progression Scale (13). In the study, the critical outcomes are defined as ICU admission or death, while the non-critical outcomes are defined that patients are ambulatory or hospitalized without ICU admission.

Statistical analysis The prediction modes will be developed and externally validated.

References

1. Wang X, Fang X, Cai Z, et al. Comorbid Chronic Diseases and Acute Organ Injuries Are Strongly Correlated with Disease Severity and Mortality among COVID-19 Patients: A Systemic Review and Meta-Analysis. Research (Wash D C) 2020; 2402961.

2. SeyedAlinaghi S, Afsahi AM, MohsseniPour M, et al. Late Complications of COVID-19; a Systematic Review of Current Evidence. Arch Acad Emerg Med 2021; 9: e14.

3. Villani L, McKee M, Cascini F, et al. Comparison of deaths rates for COVID-19 across Europe during the first wave of the COVID-19 pandemic. Front Public Health 2020; 8: 620416.

4. Macedo A, Gonçalves N, Febra C. COVID-19 fatality rates in hospitalized patients: systematic review and meta-analysis. Ann Epidemiol 2021; 57: 14-21.

5. Piroth L, Cottenet J, Mariet AS, et al. Comparison of the characteristics, morbidity, and mortality of COVID-19 and seasonal influenza: a nationwide, population-based retrospective cohort study. Lancet Respir Med 2021; 9: 251-259.

6. Abate SM, Ali SA, Mantfardo B, et al. Rate of intensive care unit admission and outcomes among patients with coronavirus: a systematic review and meta-analysis. PLoS One 2020; 15: e0235653.

7. Kim HJ, Hwang H, Hong H, et al. A systematic review and meta-analysis of regional risk factors for critical outcomes of COVID-19 during early phase of the pandemic. Sci Rep 2021; 11: 9784.

8. Botros N, Iyer P, Ojcius DM. Is there an association between oral health and severity of COVID-19 complications? Biomed J 2020; 43: 325-327.

9. Marouf N, Cai W, Said KN, et al. Association between periodontitis and severity of COVID-19 infection: a case-control study. J Clin Periodontol 2021; 48: 483-491.

10. Sukumar K, Tadepalli A. Nexus between COVID-19 and periodontal disease. J Int Med Res 2021; 49: 3000605211002695.

11. Knight SR, Ho A, Pius R, et al. Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical characterization protocol: development and validation of the 4C mortality score. BMJ 2020; 370: m3339.

12. Wynants L, Calster BV, Collins GS, et al. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ 2020; 369: m1328.

13. WHO Working Group on the Clinical Characterisation and Management of COVID-19 infection. A minimal common outcome measure set for COVID-19 clinical research. Lancet Infect Dis 2020; 20: e192-e197.

Conditions

Prediction Model; COVID-19; Oral Health; External Validation

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Study Groups

Patients with confirmed COVID-19 in the hospital setting

No intervention group

Intervention Type: OTHER

No intervention group

Interventions

No intervention group

No intervention group

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• patients who had a diagnosis of COVID-19 in the hospitals who visited the Department of Oral and Maxillofacial Surgery (OMFS) between March 2020 and May 2021, if they have had a dental panoramic radiograph (OPG), obtained up to a maximum of 5 years until the end of the current study.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 99 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Academic Centre for Dentistry Amsterdam (ACTA)

UNKNOWN

Sponsor Role: collaborator

Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)

OTHER

Sponsor Role: collaborator

Academic Centre for Dentistry in Amsterdam

OTHER

Sponsor Role: lead

Responsible Party

Naichuan Su

Dr.

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Noordwest Ziekenhuis (NWZ)

Alkmaar, , Netherlands

Isala Hospital

Zwolle, , Netherlands

Countries

Netherlands

Other Identifiers

2021.su

Identifier Type: -

Identifier Source: org_study_id