Analysis of Laboratory Markers for Severe COVID-19

June 12, 2024 updated by: Karaganda Medical University
The course of coronavirus infection was often severe and required hospitalization of patients in the intensive care unit. The new SARS-Cov-2 has been poor studied, so relatively reliable markers are needed to effectively monitor patients and predict complications and outcome. Taking into account the known mechanisms of pathogenesis, the biochemical markers as ferritin, procalcitonin, C-reactive protein and D-dimer were chosen for this purpose. Patients were divided according to the degree of pulmonary infiltration. We hypothesized that the markers would correlate with dynamics, complications, and outcomes.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

In the presented study, an analysis of the medical records of 193 patients hospitalized in severe condition to the intensive care unit with a confirmed diagnosis of Coronavirus infection COVID-19 was carried out. Taking into account the volume of pulmonary infiltration according to computer tomography (CT) of the chest organs, patients were divided into 4 groups in accordance with the approved classification: CT 1(up to 25% of lung tissue was infiltrated) - 27 patients, CT 2 (25-50%) - 60 patients, CT 3 (50-75%) - 67 patients, CT 4 (75% and more) - 39 patients. The following biochemical parameters were selected and used to monitor dynamics: procalcitonin (PCT), C-reactive protein (CRP), D-dimer (DD), ferritin (FRT). The duration of observation was 15 days.

In order to determine correlations between quantitative and qualitative data at different stages of treatment, a correlation analysis was carried out (Spearman's test was used). ROC analysis was performed to evaluate selected laboratory markers as predictors of outcome. Next, the odds ratio (OR) was assessed taking into account the obtained Youden's J index and the Associated criterion for each of the selected markers in relation to the patient's outcome. Preliminary contingency tables were compiled in relation to laboratory parameters and outcomes (2x2 tables).

Data were processed using statistical software jamovi (Computer Software ,Version 2.3.26), MedCalc (MedCalc Software Ltd, Ostend, Belgium), Microsoft Office Excel, 2016.

Study Type

Observational

Enrollment (Actual)

193

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Kazakhstan
      • Karaganda, Kazakhstan, 100008
        • Karaganda Medical University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

Patients hospitalized in the intensive care unit of the Regional Clinical Hospital of Karaganda, which is the clinical base of the Karaganda Medical University.

Description

Inclusion Criteria:

  • identified COVID-19 by nasopharyngeal material PCR, coronavirus associated lung infiltration, visualized by CT, and clinically severe condition

Exclusion Criteria:

  • pregnancy

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
hospitalized to ICU severe patients with coronavirus infection COVID-19
an analysis of the medical records was carried out
Diagnostic test: CT of the chest organs, blood biochemical parameters
Taking into account the clinical manifestations, all patients underwent chest computed tomography (CT) to diagnose COVID-19-associated pneumonia. According to the CT results, all patients were classified into one of 4 subgroups, according to the degree of pulmonary infiltration. The following biochemical parameters were selected and used to monitor dynamics: procalcitonin (PCT), C-reactive protein (CRP), D-dimer (DD), ferritin (FRT). Biochemical markers were determined daily during the stay in the intensive care unit. The duration of observation was 15 days was selected. Information was analysed retrospectively.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Biochemical markers' correlation with outcomes
Time Frame: Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
In the early stages of hospitalization was found the significant inverse correlation (p < 0.01, r -0.236) with the outcome of the stay for procalcitonin levels on the third day - larger concentrations of this marker were associated with death for the patient; on day 7 - weaker inverse correlation (p < 0.05, r -0.246), by the end of treatment - a significant inverse correlation at p < 0.001, r -0.393. A correlation between D-dimer and the outcome of the stay was revealed - on the 3rd day and at the end of treatment - in both cases the correlation is inverse, quite significant (p < 0.01, r-0.237and p < 0.001, r-0.512 respectively). Higher ferritin levels correlated with death when determined in the late period of hospitalization - inverse correlation at p < 0.001, r-0.447.
Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
Markers as outcome predictors
Time Frame: Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
According to the results of ROC analysis predictively significant for mortal outcome (*AUC values are close to 1.0, at the significance level P =0.05) were: procalcitonin level on days 3, 7 and 15, CRP level on days 7 and 15, levels of D-dimer on days 3, 7 and 15, ferritin on days 3 and 7
Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
the correlation between the level of biomarkers and the degree of infiltration of lung tissue
Time Frame: Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
The correlation between the level of biomarkers and the degree of infiltration of lung tissue (CRP, D-dimer, ferritin at the beginning of treatment and at the end of treatment, procalcitonin at the end of treatment) was identified. This correlation was direct in all cases.
Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
The level of D-dimer quite significantly negatively correlated with the duration of stay in the intensive care unit
Time Frame: Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
The level of D-dimer quite significantly (p < .001) negatively correlated with the duration of stay in the intensive care unit when assessed on days 1, 3 and at the end of treatment, but such a correlation was not detected on day 7.
Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
The inverse correlation was found for procalcitonin and the patient-bed-days in the intensive care unit
Time Frame: Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.
The inverse correlation was found for procalcitonin and the duration of patient's stay in the intensive care unit - on day 3 (p < .05) and at the end of treatment (p< .01).
Laboratory markers were measured daily. For correlation analysis, control days of measurements were chosen: days 1-3-7-15.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Karaganda Medical University

Investigators

  • Study Chair: Aissulu Issabekova, MD, Karaganda Medical University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 10, 2024

Primary Completion (Actual)

June 10, 2024

Study Completion (Actual)

June 10, 2024

Study Registration Dates

First Submitted

June 12, 2024

First Submitted That Met QC Criteria

June 12, 2024

First Posted (Actual)

June 14, 2024

Study Record Updates

Last Update Posted (Actual)

June 14, 2024

Last Update Submitted That Met QC Criteria

June 12, 2024

Last Verified

June 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SC19MI-ARICU-1T

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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