Age-Dependent Biomarkers for Prediction of In-Hospital Mortality in COVID-19 Patients

Comparative analysis of CRP as a biomarker of the inflammatory response intensity among common viral infections affecting the lungs: COVID-19 versus influenza A, influenza B and respiratory syncytial virus

Severe acute respiratory syndrome-corona virus 2 (SARS-CoV-2) is associated with significant morbidity and mortality. C-reactive protein (CRP) is a useful inflammatory biomarker for patients admitted with an infection. This study aimed to compare CRP level as an indicator of inflammation severity between SARS-CoV-2 and common respiratory viral infections. A cross-sectional study of all adult patients hospitalized in the internal medicine department, geriatric department, or internal intensive care unit between 02/2012 and 06/2021 with laboratory-confirmed respiratory viral infection was performed. SARS-CoV-2, influenza A, influenza B, and respiratory syncytial virus (RSV) were studied. Patients with laboratory-confirmed concurrent viral or bacterial infections were excluded. Patients with malignancy were also excluded. Age, gender, comorbidities, and CRP level upon admission were compared between groups. Univariate and multivariable analyses were applied. Among 1124 patients, 18.2% had SARS‑CoV‑2, 48.3% influenza A, 18.9% RSV, and 14.6% influenza B. SARS‑CoV‑2 patients were significantly younger (median 69.4 vs. ≥ 76 years) and had lower Charlson score (median 3 vs. ≥ 4 in other groups) compared to patients with other viral pathogens. After adjustment for patients' age, gender and comorbidities, SARS‑CoV‑2 patients had a higher probability (OR = 1.84-2.02, p < 0.01) of having CRP values in the upper quartile (> 117 mg/L) compared to all other viral pathogens while between all others there was no significant difference. To conclude, a higher CRP level upon admission is approximately twice more common among SARS-CoV-2 patients compared to other widespread respiratory viruses which may demonstrate the higher intensity of inflammation caused by SARS-CoV-2.

Early signaling of bacteremia in patients who present to the Department of Emergency Medicine with relatively low C-Reactive Protein (CRP) concentrations

OBJECTIVES

Examiningthe usefulness of C-reactive protein velocity (CRPv) as an early biomarker for the presence of bacteraemia in patients presenting to the Department of Emergency Medicine with acute infection/inflammation and suspected bacteraemia.

METHODS

A retrospective study examining a cohort of patients who presented to the E.R and in whom blood cultures were taken. CRPv was calculated as the difference in mg/hour/litter between two consecutive CRP tests performed within 12 hours.

RESULTS

256 patients were included in the cohort. Using CRPv in patients who at first presented with a relatively low (17.9≤mg/L 1^stquartile) CRP concentration, we found an AUC of 0.808±0.038 (p<0.001) for the presence of positive versus negative blood cultures (what is AUC?). This was better than the AUC that was obtained when the WBC for the same purpose.

CONCLUSIONS

CRPv may be a useful biomarker in the identification of patients with suspected bacteremiaand a low CRP-a challenging situation for clinicians who may underestimate the severity of illness in this patient group.

Circulating mid-regional proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

BACKGROUND

Although there is increasing understanding of the changes in the laboratory parameters of Coronavirus disease 2019 (COVID-19), the correlation between circulating Mid-regional Proadrenomedullin (MR-proADM) and mortality of patients with COVID-19 is not fully understood. In this study, we conducted a systematic review and meta-analysis to evaluate the prognostic value of MR-proADM in patients with COVID-19.

METHODS

The PubMed, Embase, Web of Science, Cochrane Library, Wanfang, SinoMed and Chinese National Knowledge Infrastructure (CNKI) databases were searched from 1 January 2020 to 20 March 2022 for relevant literature. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess quality bias, STATA was employed to pool the effect size by a random effects model, and potential publication bias and sensitivity analyses were performed.

RESULTS

14 studies comprising 1822 patients with COVID-19 met the inclusion criteria, there were 1145 (62.8%) males and 677 (31.2%) females, and the mean age was 63.8 ± 16.1 years. The concentration of MR-proADM was compared between the survivors and non-survivors in 9 studies and the difference was significant (P < 0.01), I² = 46%. The combined sensitivity was 0.86 [0.73-0.92], and the combined specificity was 0.78 [0.68-0.86]. We drew the summary receiver operating characteristic (SROC) curve and calculated the area under curve (AUC) = 0.90 [0.87-0.92]. An increase of 1 nmol/L of MR-proADM was independently associated with a more than threefold increase in mortality (odds ratio (OR) 3.03, 95% confidence interval (CI) 2.26-4.06, I² = 0.0%, P = 0.633). The predictive value of MR-proADM for mortality was better than many other biomarkers.

CONCLUSION

MR-proADM had a very good predictive value for the poor prognosis of COVID-19 patients. Increased levels of MR-proADM were independently associated with mortality in COVID-19 patients and may allow a better risk stratification.

Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees

Background and objective

A hyperinflammatory environment is thought to be the distinctive characteristic of COVID-19 infection and an important mediator of morbidity. This study aimed to determine the effect of other immunological parameter levels, especially ferritin, as a predictor of COVID-19 mortality via decision-trees analysis.

Material and method

This is a retrospective study evaluating a total of 2568 patients who died (n = 232) and recovered (n = 2336) from COVID-19 in August and December 2021. Immunological laboratory data were compared between two groups that died and recovered from patients with COVID-19. In addition, decision trees from machine learning models were used to evaluate the performance of immunological parameters in the mortality of the COVID-19 disease.

Results

Non-surviving from COVID-19 had 1.75 times higher ferritin, 10.7 times higher CRP, 2.4 times higher D-dimer, 1.14 times higher international-normalized-ratio (INR), 1.1 times higher Fibrinogen, 22.9 times higher procalcitonin, 3.35 times higher troponin, 2.77 mm/h times higher erythrocyte-sedimentation-rate (ESR), 1.13sec times longer prothrombin time (PT) when compared surviving patients. In addition, our interpretable decision tree, which was constructed with only the cut-off values of ferritin, INR, and D-dimer, correctly predicted 99.7% of surviving patients and 92.7% of non-surviving patients.

Conclusions

This study perfectly predicted the mortality of COVID-19 with our interpretable decision tree constructed with INR and D-dimer, especially ferritin. For this reason, we think that it may be important to include ferritin, INR, and D-dimer parameters and their cut-off values in the scoring systems to be planned for COVID-19 mortality.

Epidemiological Characteristics and Mortality Risk Factors Comparison in Dialysis and Non-Dialysis CKD Patients with COVID-19-A Single Center Experience

(1) Background: Despite some controversies between studies, chronic kidney disease (CKD) has a negative impact on COVID-19 outcomes, with patients presenting a higher mortality risk than in the general population. Studies have shown an association between COVID-19 severe cases and different inflammatory biomarkers. The aim of this study was to emphasize the epidemiological characteristics of CKD patients diagnosed with COVID-19 and to determine if the risk of mortality, and the severity of this infection might be influenced by different parameters. (2) Methods: Our retrospective study included CKD patients with COVID-19—362 in the non-dialysis group and 132 in the dialysis group. (3) Results: There were significant statistical differences between our groups regarding age (p < 0.001), hemoglobin (p < 0.001), interleukin-6 (p < 0.001), serum albumin (p = 0.016), procalcitonin (p = 0.002), ferritin (p < 0.001), and of course serum creatinine (p < 0.001). Even if the risk of death was higher in the dialysis group (Exp(b) = 1.839), the survival proportions were similar in both groups. (4) Conclusions: High values of hemoglobin, serum creatinine, and LDH at admission, age, length of hospital stay ≤ 10 days, and a pulmonary impairment > 25% are responsible for an adverse outcome in non-dialysis and dialysis patients diagnosed with COVID-19.