Prognostic Utility of Procalcitonin, Presepsin, and the VACO Index for Predicting 30-day Mortality in Hospitalized COVID-19 Patients

Understanding long COVID myocarditis: A comprehensive review

Infectious diseases are a cause of major concern in this twenty-first century. There have been reports of various outbreaks like severe acute respiratory syndrome (SARS) in 2003, swine flu in 2009, Zika virus disease in 2015, and Middle East Respiratory Syndrome (MERS) in 2012, since the start of this millennium. In addition to these outbreaks, the latest infectious disease to result in an outbreak is the SARS-CoV-2 infection. A viral infection recognized as a respiratory illness at the time of emergence, SARS-CoV-2 has wreaked havoc worldwide because of its long-lasting implications like heart failure, sepsis, organ failure, etc., and its significant impact on the global economy. Besides the acute illness, it also leads to symptoms months later which is called long COVID or post-COVID-19 condition. Due to its ever-increasing prevalence, it has been a significant challenge to treat the affected individuals and manage the complications as well. Myocarditis, a long-term complication of coronavirus disease 2019 (COVID-19) is an inflammatory condition involving the myocardium of the heart, which could even be fatal in the long term in cases of progression to ventricular dysfunction and heart failure. Thus, it is imperative to diagnose early and treat this condition in the affected individuals. At present, there are numerous studies which are in progress, investigating patients with COVID-19-related myocarditis and the treatment strategies. This review focuses primarily on myocarditis, a life-threatening complication of COVID-19 illness, and endeavors to elucidate the pathogenesis, biomarkers, and management of long COVID myocarditis along with pipeline drugs in detail.

High Plasma Presepsin Levels in Children With Hemophagocytic Lymphohistiocytosis

Presepsin is reported as a novel diagnostic and prognostic biomarker for sepsis, and its optimal cutoff value is reported to be 600 to 650 pg/mL. Three children were diagnosed with hemophagocytic lymphohistiocytosis (HLH). The cause of HLH was unknown in cases 1 and 2, while Epstein-Barr virus infection was the cause in case 3. The plasma presepsin levels at the diagnosis were 1020, 1080, and 3160 pg/mL in cases 1, 2, and 3, respectively. In case 1, the plasma level of presepsin decreased to 164 pg/mL on day 19 of her sickness, when symptoms improved. Follow-up plasma presepsin levels were missing for cases 2 and 3. No microbiological pathogens were detected in the blood cultures of any of the patients. Our cases suggest that plasma presepsin levels can be elevated in childhood HLH.

Variation in presepsin and thrombomodulin levels for predicting COVID-19 mortality

Coronavirus disease (COVID-19) has caused extensive mortality globally; therefore, biomarkers predicting the severity and prognosis of COVID-19 are essential. This study aimed to evaluate the application of presepsin (P-SEP) and thrombomodulin (TM), which are biomarkers of sepsis and endothelial dysfunction, respectively, in the prognosis of COVID-19. Serum P-SEP and TM levels from COVID-19 patients (n = 183) were measured. Disease severity was classified as mild, moderate I, moderate II, or severe based on hemoglobin oxygen saturation and the history of intensive care unit transfer or use of ventilation at admission. Patients in the severe group were further divided into survivors and non-survivors. P-SEP and TM levels were significantly higher in the severe group than those in the mild group, even after adjusting for creatinine values. In addition, TM levels were significantly higher in non-survivors than in survivors. Changes in the P-SEP levels at two time points with an interval of 4.1 ± 2.2 days were significantly different between the survivors and non-survivors. In conclusion, TM and continuous P-SEP measurements may be useful for predicting mortality in patients with COVID-19. Moreover, our data indicate that P-SEP and TM values after creatinine adjustment could be independent predictive markers, apart from renal function.

Serial laboratory biomarkers are associated with ICU outcomes in patients hospitalized with COVID-19

BACKGROUND

Clinical utility of routinely measured serial biomarkers in predicting escalation of inpatient care intensity and mortality among hospitalized patients with COVID-19 remains unknown.

METHODS

This retrospective cohort study included patients with COVID-19 who admitted to the Massachusetts General Hospital between March and June 2020 and January to March 2021. White blood cell (WBC) count, platelet count, C-reactive protein (CRP), and D-dimer values were measured on days 1, 3, and 7 of admission. Clinical outcomes include 30- and 60-day morality, ICU transfer, and overall survival (OS) over a follow-up period of 90 days. The association between serial biomarkers and outcomes were assessed using multivariable logistic regression and Cox proportional hazards models.

MEASUREMENTS AND MAIN RESULTS

Of the 456 patients hospitalized with COVID-19, 199 (43.6%) were ICU, 179 (39.3%) were medical floor, and 78 (17.1%) were initially admitted to the medical floor and then transferred to the ICU. In adjusted analyses, each unit increase in the slope of CRP was associated with a 42% higher odds of ICU transfer after controlling for the initial admission level (OR = 1.42, 95% CI: 1.25-1.65, P < 0.001). Including serial change in CRP levels from initial level on admission achieved the greatest predictive accuracy for ICU transfer (AUC = 0.72, 95% CI: 0.64-0.79).

CONCLUSIONS

Serial change in CRP levels from admission is associated with escalations of inpatient care intensity and mortality among hospitalized patients with COVID-19.

Utility of Presepsin and Interferon-λ3 for Predicting Disease Severity and Clinical Outcomes in COVID-19 Patients

We explored the utility of novel biomarkers, presepsin and interferon-λ3 (IFN-λ3), for predicting disease severity and clinical outcomes in hospitalized Coronavirus (COVID-19) patients. In a total of 55 patients (non-critical, n = 16; critical, n = 39), presepsin and IFN-λ3 were compared with sequential organ failure assessment (SOFA) scores and age. Disease severity and clinical outcomes (in-hospital mortality, intensive care unit admission, ventilator use, and kidney replacement therapy) were analyzed using receiver operating characteristic (ROC) curves. In-hospital mortality was also analyzed using the Kaplan-Meier method with hazard ratios (HR). SOFA scores, age, presepsin, and IFN-λ3 predicted disease severity comparably (area under the curve [AUC], 0.67-0.73). SOFA score and IFN-λ3 predicted clinical outcomes comparably (AUC, 0.68-0.88 and 0.66-0.74, respectively). Presepsin predicted in-hospital mortality (AUC = 0.74). The combination of presepsin and IFN-λ3 showed a higher mortality risk than SOFA score or age (HR [95% confidence interval, CI], 6.7 [1.8-24.1]; 3.6 [1.1-12.1]; 2.8 [0.8-9.6], respectively) and mortality rate further increased when presepsin and IFN-λ3 were added to SOFA scores or age (8.5 [6.8-24.6], 4.2 [0.9-20.6], respectively). In the elderly (≥65 years), in-hospital mortality rate was significantly higher when both presepsin and IFN-λ3 levels increased than when either one or no biomarker level increased (88.9% vs. 14.3%, p < 0.001). Presepsin and IFN-λ3 predicted disease severity and clinical outcomes in hospitalized COVID-19 patients. Both biomarkers, whether alone or added to the clinical assessment, could be useful for managing COVID-19 patients, especially the elderly.

Daily combined measurement of platelet count and presepsin concentration can predict in-hospital death of patients with severe coronavirus disease 2019 (COVID-19)

The purpose of this study was to classify patients with severe COVID-19 into more detailed risk groups using coagulation/fibrinolysis, inflammation/immune response, and alveolar/myocardial damage biomarkers, as well as to identify prognostic markers for these patients. These biomarkers were measured every day for eight intensive care unit days in 54 adult patients with severe COVID-19. The patients were classified into survivor (n = 40) and non-survivor (n = 14) groups. Univariate and multivariate analyses showed that the combined measurement of platelet count and presepsin concentrations may be the most valuable for predicting in-hospital death, and receiver operating characteristic curve analysis further confirmed this result (area under the curve = 0.832). Patients were consequently classified into three groups (high-, medium-, and low-risk) on the basis of their cutoff values (platelet count 53 × 10³/µL, presepsin 714 pg/mL). The Kaplan-Meier curve for 90-day survival by each group showed that the 90-day mortality rate significantly increased as risk level increased (P < 0.01 by the log-rank test). Daily combined measurement of platelet count and presepsin concentration may be useful for predicting in-hospital death and classifying patients with severe COVID-19 into more detailed risk groups.

The performance of the WHO COVID-19 severity classification, COVID-GRAM, VACO Index, 4C Mortality, and CURB-65 prognostic scores in hospitalized COVID-19 patients: data on 4014 patients from a tertiary center registry

AIM

To evaluate the predictive properties of several common prognostic scores regarding survival outcomes in hospitalized COVID-19 patients.

METHODS

We retrospectively reviewed the medical records of 4014 consecutive COVID-19 patients hospitalized in our tertiary level institution from March 2020 to March 2021. Prognostic properties of the WHO COVID-19 severity classification, COVID-GRAM, Veterans Health Administration COVID-19 (VACO) Index, 4C Mortality Score, and CURB-65 score regarding 30-day mortality, in-hospital mortality, presence of severe or critical disease on admission, need for an intensive care unit treatment, and mechanical ventilation during hospitalization were evaluated.

RESULTS

All of the investigated prognostic scores significantly distinguished between groups of patients with different 30-day mortality. The CURB-65 and 4C Mortality Score had the best prognostic properties for prediction of 30-day mortality (area under the curve [AUC] 0.761 for both) and in-hospital mortality (AUC 0.757 and 0.762, respectively). The 4C Mortality Score and COVID-GRAM best predicted the presence of severe or critical disease (AUC 0.785 and 0.717, respectively). In the multivariate analysis evaluating 30-day mortality, all scores mutually independently provided additional prognostic information, except the VACO Index, whose prognostic properties were redundant.

CONCLUSION

Complex prognostic scores based on many parameters and comorbid conditions did not have better prognostic properties regarding survival outcomes than a simple CURB-65 prognostic score. CURB-65 also provides the largest number of prognostic categories (five), allowing more precise risk stratification than other prognostic scores.

The performance of the WHO COVID-19 severity classification, COVID-GRAM, VACO Index, 4C Mortality, and CURB-65 prognostic scores in hospitalized COVID-19 patients: data on 4014 patients from a tertiary center registry

AIM

To evaluate the predictive properties of several common prognostic scores regarding survival outcomes in hospitalized COVID-19 patients.

METHODS

We retrospectively reviewed the medical records of 4014 consecutive COVID-19 patients hospitalized in our tertiary level institution from March 2020 to March 2021. Prognostic properties of the WHO COVID-19 severity classification, COVID-GRAM, Veterans Health Administration COVID-19 (VACO) Index, 4C Mortality Score, and CURB-65 score regarding 30-day mortality, in-hospital mortality, presence of severe or critical disease on admission, need for an intensive care unit treatment, and mechanical ventilation during hospitalization were evaluated.

RESULTS

All of the investigated prognostic scores significantly distinguished between groups of patients with different 30-day mortality. The CURB-65 and 4C Mortality Score had the best prognostic properties for prediction of 30-day mortality (area under the curve [AUC] 0.761 for both) and in-hospital mortality (AUC 0.757 and 0.762, respectively). The 4C Mortality Score and COVID-GRAM best predicted the presence of severe or critical disease (AUC 0.785 and 0.717, respectively). In the multivariate analysis evaluating 30-day mortality, all scores mutually independently provided additional prognostic information, except the VACO Index, whose prognostic properties were redundant.

CONCLUSION

Complex prognostic scores based on many parameters and comorbid conditions did not have better prognostic properties regarding survival outcomes than a simple CURB-65 prognostic score. CURB-65 also provides the largest number of prognostic categories (five), allowing more precise risk stratification than other prognostic scores.

Soluble ST2 as a Useful Biomarker for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients

Soluble suppression of tumorigenesis-2 (sST2) is an emerging biomarker for sepsis as well as for heart failure. We investigated the prognostic utility of sST2 for predicting clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. In a total of 52 hospitalized COVID-19 patients, sST2 levels were measured using the ichroma ST2 assay (Boditech Med Inc., Chuncheon-si, Gang-won-do, Republic of Korea). Clinical outcomes included intensive care unit (ICU) admission, ventilator use, extracorporeal membrane oxygenation (ECMO) use, and 30-day mortality. sST2 was analyzed according to clinical outcomes. sST2, sequential organ failure assessment (SOFA) score, critical disease, and 4C mortality score were compared using the receiver operating characteristic (ROC) curve and Kaplan−Meier methods for clinical outcomes. The sST2 level differed significantly according to ICU admission, ventilator use, ECMO use, and 30-day mortality (all p < 0.05). On ROC curve analysis, sST2 predicted ICU admission, ventilator use, ECMO use, and 30-day mortality comparable to SOFA score but significantly better than critical disease. sST2 predicted ICU admission, ventilator use, and ECMO use significantly better than the 4C mortality score. On Kaplan−Meier survival analysis, hazard ratios (95% confidence interval) were 8.4 (2.7−26.8) for sST2, 14.8 (3.0−71.7) for SOFA score, 1.8 (0.5−6.5) for critical disease, and 11.7 (3.4−40.1) for 4C mortality score. This study demonstrated that sST2 could be a useful biomarker to predict ICU admission, ventilator use, ECMO use, and 30-day mortality in hospitalized COVID-19 patients. sST2 may be implemented as a prognostic COVID-19 biomarker in clinical practice.

Usefulness of KL-6 for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients

Background: Krebs von den Lungen 6 (KL-6) is a novel biomarker for interstitial lung disease, and it reflects acute lung injury. We explored the usefulness of KL-6 to predict clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: In a total of 48 hospitalized COVID-19 patients, KL-6 levels were measured using the HISCL KL-6 assay (Sysmex, Kobe, Japan) with the HISCL 5000 automated analyzer (Sysmex). Clinical outcomes (intensive care unit [ICU] admission, ventilator use, extracorporeal membrane oxygenation [ECMO] use, and 30-day mortality) were analyzed according to KL-6 percentiles. Age, initial KL-6 level, Charlson comorbidity index (CCI), and critical disease were compared using the receiver operating characteristic (ROC) curve and Kaplan-Meier methods for clinical outcomes. Results: KL-6 quartiles were associated with ICU admission, ventilator use, and ECMO use (all p < 0.05), except 30-day mortality (p = 0.187). On ROC curve analysis, initial KL-6 level predicted ICU admission, ventilator use, and ECMO use significantly better than age, CCI, and critical disease (all p < 0.05); age, initial KL-6 level, CCI, and critical disease predicted 30-day mortality comparably. On Kaplan−Meier survival analysis, hazard ratios (95% confidence interval) were 4.8 (1.2−19.3) for age, 4.7 (1.1−21.6) for initial KL-6 level, 3.9 (0.9−16.2) for CCI, and 2.1 (0.5−10.3) for critical disease. Conclusions: This study demonstrated that KL-6 could be a useful biomarker to predict clinical outcomes in hospitalized COVID-19 patients. KL-6 may contribute to identifying COVID-19 patients requiring critical care, including ICU admission and ventilator and/or ECMO use.

Performance of presepsin and procalcitonin predicting culture-proven bacterial infection and 28-day mortality: A cross sectional study

Presepsin is a highly specific biomarker for diagnosing bacterial infections, but its clinical usefulness is not well validated. A retrospective cross-sectional study was conducted. Among the patients suspected bacterial infection or fulfilled the criteria of systemic inflammatory response syndrome (SIRS) and patients who underwent blood culture, presepsin, procalcitonin (PCT), and C-reactive protein (CRP) at the same time were included. Receiver operating characteristic (ROC) curve analysis and logistic regression were used to compare performance of three biomarkers. A total of 757 patients were enrolled, including 256 patients (33.8%) with culture-proven bacterial infection and 109 patients (14.4%) with bacteremia. The 28-day mortality rate was 8.6%. ROC curve analysis revealed that the area under the curve (AUC) of PCT was higher than that of presepsin for both culture-proven bacterial infection (0.665 and 0.596, respectively; p = 0.003) and bacteremia (0.791 and 0.685; p < 0.001). In contrast, AUC of PCT for 28-day mortality was slower than presepsin (0.593 and 0.720; p = 0.002). In multivariable logistic regression analysis, PCT showed the highest ORs for culture-proven bacterial infection (OR 2.23, 95% CI 1.55–3.19; p < 0.001) and for bacteremia (OR 5.18, 95% CI 3.13–8.56; p < 0.001), while presepsin showed the highest OR for 28-day mortality (OR 3.31, 95% CI 1.67–6.54; p < 0.001). CRP did not show better performance than PCT or presepsin in any of the analyses. PCT showed the best performance predicting culture-proven bacterial infection and bacteremia, while presepsin would rather be useful as a prognostic marker.

Reference Interval for the Axis-Shield Clinical Chemistry Heparin-Binding Protein Assay

The newly developed Axis-Shield clinical chemistry heparin-binding protein (HBP) assay (Axis-Shield Diagnostics Ltd., Dundee, Scotland) can be applied to fully automated platforms. We aimed to establish a reference interval (RI) of HBP using the Axis-Shield HBP assay, and to evaluate the analytical performance of this assay. An RI was established in 212 sodium citrated plasma samples using the non-parametric method (2.5th and 97.5th percentiles). Precision, linearity, and carry-over were evaluated according to the Clinical and Laboratory Standards Institute guidelines. The RI of HBP was between 5.3 ng/mL and 171.0 ng/mL, which could be applied regardless of gender and age. Percentage coefficients of variations (%CVs) of repeatability and within-laboratory precision were 4.9% and 6.3%, respectively, for low-concentration control and 1.6% and 3.0%, respectively, for high-concentration control. The linearity was excellent (coefficient of determination (R²) = 0.99), and the carry-over rate was negligible (0.05%). This is the first study to establish an RI of HBP using the newly developed and fully automated Axis-Shield HBP assay. The Axis-Shield HBP assay showed an acceptable level of analytical performance and could be used to measure HBP concentrations effectively in routine clinical practice. Further studies are awaited to evaluate the clinical utility of HBP using this automated assay.

Presepsin levels in neonatal cord blood are not influenced by maternal SARS-CoV-2 infection

OBJECTIVES

Coronavirus disease (COVID-19) can present with various symptoms and can involve multiple organs. Women infected during pregnancy have a higher incidence of obstetrical complications and infants born to "positive" mothers may get the infection with different manifestations. Presepsin seems to be a promising sepsis biomarker in adults and neonates. The aim of this study was to assess if presepsin levels in neonatal cord blood could be influenced by maternal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

A total of 119 neonates born from women with a confirmed diagnosis of SARS-CoV-2 infection were enrolled and presepsin levels of cord blood samples were collected. All neonates were tested for SARS-CoV-2 infection at birth and after 48-72 h.

RESULTS

The median presepsin value in umbilical cord blood samples collected after birth was 455 pg/mL. Presepsin levels were not influenced by maternal symptoms of COVID-19, weight for gestational age, or delivery mode, and did not significantly differ between infants with and without adverse neonatal outcomes. Infants hospitalized for more than 5 days had a significantly higher presepsin level at birth rather than those discharged up to 4 days of life. Three infants with positive nasopharyngeal swab at birth had higher Presepsin levels than two infants tested positive at 48 h.

CONCLUSIONS

This is the first study reporting cord presepsin levels in term and preterm infants born to mothers with COVID-19, that appeared to be not influenced by maternal clinical presentation. However, further studies are needed to explain the mechanisms of P-SEP increase in neonates exposed to perinatal maternal SARS-CoV-2 infection or with an indeterminate/possible SARS-CoV-2 infection in the same neonates.

Presepsin: Hope in the Quest for the Holy Grail

How to cite this article: Samprathi A, Samprathi M, Reddy M. Presepsin: Hope in the Quest for the Holy Grail. Indian J Crit Care Med 2022;26(6):664–666.

Predictive Values of Procalcitonin and Presepsin for Acute Kidney Injury and 30-Day Hospital Mortality in Patients with COVID-19

Background and Objectives: Acute kidney injury (AKI) is a common complication in patients with coronavirus disease 2019 (COVID-19). We investigated the values of procalcitonin (PCT) and presepsin (PSS) for predicting AKI and 30-day hospital mortality in patients with COVID-19. Materials and Methods: We retrospectively evaluated 151 patients with COVID-19 who were admitted to the hospital via the emergency department. The diagnosis of AKI was based on the Kidney Disease: Improving Global Outcomes clinical practice guidelines. Results: The median patient age was 77 years, and 86 patients (57%) were male. Fifty-six patients (37.1%) developed AKI, and 19 patients (12.6%) died within 30 days of hospital admission. PCT and PSS levels were significantly higher in patients with AKI and non-survivors. The cutoff values of PCT levels for predicting AKI and mortality were 2.26 ng/mL (sensitivity, 64.3%; specificity, 89.5%) and 2.67 ng/mL (sensitivity, 68.4%; specificity, 77.3%), respectively. The cutoff values of PSS levels for predicting AKI and mortality were 572 pg/mL (sensitivity, 66.0%; specificity, 69.1%) and 865 pg/mL (sensitivity, 84.6%; specificity, 76.0%), respectively. Conclusion: PCT and PSS are valuable biomarkers for predicting AKI and 30-day hospital mortality in patients with COVID-19.