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NCT Number: NCT06460753

Analysis of Laboratory Markers for Severe COVID-19

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.

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Key information

Conditions

Coronavirus Infection COVID-19 COVID-19 Coronaviridae Infections Coronavirus Infections Infections Lung Diseases Nidovirales Infections Pneumonia Pneumonia, Viral RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Karaganda Medical University

Karaganda, 100008, Kazakhstan

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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

Exclusion criteria

  • pregnancy

Treatment and study plan

CT of the chest organs, blood biochemical parameters

Diagnostic Test

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.

Primary outcomes

  1. 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.

  2. 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

Secondary outcomes

  1. 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.

  2. 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.

  3. 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).

Sponsors and collaborators

Lead sponsor

Karaganda Medical University

Other

Registry information

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Jun 14, 2024
Registry last updated
Jun 14, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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