Alterations in Laboratory Parameters Related to Disease Severity in Vaccinated Patients Against SARS-CoV-2
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide with global financial and health care systems consequences. It is already well recognized that immunization against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a precondition for blocking mutations and prevent the emergence of variants. The aim of the study was to investigate the possible relationship between COVID-19 vaccines and the commonly used disease-related blood biomarkers. Methods: Adult patients with confirmed SARS-CoV-2 infection who were hospitalized from November 8, 2021, to December 31, 2021, were included. The retrospective study was conducted in Patras University Hospital, Greece. Two groups of patients were assessed, the ones who were previously vaccinated against SARS-CoV-2 (group A, n = 21), and those who were not (group B, n = 55). After analysis of peripheral blood, we calculated on admission day for each patient the total white blood cell (WBC), absolute lymphocytes count (ALC), absolute monocyte count, D-dimers, C-reactive protein (CRP) plasma levels, lactate dehydrogenase (LDH), ferritin, high-sensitive troponin, as well as the arterial oxygen partial pressure/fractional inspired oxygen (PO 2 /FiO 2 ) ratio. Results: The median age of all patients was 65.3 ± 15.2 years old; 68.4% were men and 31.6% were women. Comorbidities were present in 51 patients (67.1%). Hypertension and diabetes were observed as the most common comorbidities (33.3%). About 72.4% of the patients were unvaccinated or have received the first dose of vaccine, and 27.6% were completely vaccinated. No statistical difference was found in the total WBC count and ALC between the two groups (group A vs. group B: 8,168.95 ± 7,584.4 vs. 8,521.9 ± 6,571.3, P = 0.848 and 3,052.1 ± 7,230.7 vs. 1,279.6 ± 1,218.6, P = 0.087). Monocytes count in both groups did not show statistical difference: group A vs. group B: 672.6 ± 384.7 vs. 637.9 ± 477.8 (P = 0.754). Similarly, no difference for D-dimers (1,348.5 ± 1,397.6 vs. 1,850.9 ± 3,877.5, P = 0.575), ferritin (1,082.8 ± 1,399.5 vs. 1,327.4 ± 1,307.8, P = 0.508), high-sensitive troponin (113.6 ± 318.1 vs. 157.5 ± 48.8, P = 0.252), and CRP (6.92 ± 4.9 vs. 7.4 ± 5.9, P = 0.732). For LDH plasma levels, the statistical difference was significant (274.2 ± 85.6 vs. 387.5 ± 223.4, P = 0.003), as well as for the PO 2 /FiO 2 ratio (355.6 ± 129.7 vs. 260.5 ± 123.3, P = 0,006). Conclusions: In a mixed population hospitalized for COVID-19, only LDH plasma levels and the PaO 2 /FiO 2 on admission day showed statistically significant difference between vaccinated and unvaccinated patients. Although unvaccinated patients are more likely to develop severe illness, they did not express significantly higher values of commonly used plasma biomarkers such as ferritin, CRP, and D-dimers which are related to disease severity. J Clin Med Res. 2022;14(11):487-491 doi: https://doi.org/10.14740/jocmr4821
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".