Soluble CD14 Subtype in Peripheral Blood is a Biomarker for Early Diagnosis of Sepsis

Analysis of the diagnostic and prognostic value of serum PAD2 in patients with sepsis in the intensive care unit

BACKGROUND

Sepsis is a common disease in the intensive care unit (ICU). In recent years, the incidence rate and mortality rate remain high. Early diagnosis of sepsis is crucial for treatment and can effectively reduce mortality. So far, the ability of serum peptidylarginine deaminase 2 (PAD2) in the diagnosis and prognosis of sepsis patients is still unclear. We conducted this study to reveal the clinical value of PAD2 as a biomarker for sepsis patients.

METHODS

A prospective study method was used to select 207 patients in the ICU of Renmin Hospital of Wuhan University from May 2022 to May 2023. They were divided into the sepsis group (n = 135) and control group (n = 72), and data were collected within 24 h of hospitalization. Sepsis patients were divided into a survival group (n = 80) and a non-survival group (n = 55) based on their 28-day survival status. Using statistical methods to evaluate the diagnostic and prognostic value of PAD2 in sepsis.

RESULTS

The serum PAD2 concentrations in the sepsis group were significantly higher than in the control group (median 16.70 vs 35.32 ng/ml, P < 0.001). Multivariate logistic regression analysis showed that the Quick Sequential Organ Failure Assessment (qSOFA), C-reactive protein (CRP), procalcitonin (PCT), and PAD2 were independent risk factors for sepsis. The Receiver operating characteristic (ROC) curve showed that the combined diagnostic value of qSOFA, CRP, PCT, and PAD2 was the highest. The serum PAD2 concentrations in the non-survival group of patients with sepsis were significantly higher than those in the survival group (median 29.26 vs 50.08 ng/ml, P < 0.05). The COX regression analysis showed that PAD2, sequential organ failure score Assessment (SOFA) score, and Acute Physiology and Chronic Health Evaluation (APACHE II) score were independent factors affecting the prognosis of sepsis patients. The ROC analysis showed that the combined prognostic value of PAD2, SOFA, and APACHE II scores was significantly higher than any single indicator. The Kaplan-Meier survival analysis showed that patients with PAD2 ≤ 48.62 ng/ml had a better prognosis.

CONCLUSION

The significant increase in serum PAD2 concentrations in patients is an independent risk factor affecting the occurrence of sepsis and 28-day mortality. The combination of PAD2 and other indicators can further improve the diagnostic and prognostic value for ICU sepsis patients.

Presepsin in the diagnosis of sepsis

OBJECTIVES

Sepsis is a life-threatening condition characterized by organ dysfunction. It occurs due to the host's dysregulated response to an infection. Clinicians use inflammatory biomarkers to evaluate patients at risk of sepsis in various settings.

METHODS

We included studies focusing on the diagnostic accuracy of presepsin in patients under suspicion of sepsis. The bivariate model of Reitsma was used for the quantitative synthesis, and summary estimates were calculated. The Zhou-Dendukuri approach was followed to assess heterogeneity. Subgroup analyses were performed based on settings and diagnostic criteria.

RESULTS

The summary sensitivity for diagnosing sepsis was 0.805 (95 % CI: 0.759-0.844), while the false positive rate (FPR) was 0.174 (95 % CI: 0.124-0.239). The area under the curve (AUC) for the summary receiver operating characteristic (SROC) curve was 0.875, with a slightly lower partial AUC of 0.833. The analysis using the Zhou-Dendukuri approach revealed low heterogeneity (I2 = 15.9 %). Subgroup analyses showed no significant differences in SROC curves and summary estimates between the ED and ICU settings, although the ED subgroup exhibited higher heterogeneity (I2 = 52.7 % vs. 20.2 %). The comparison between the diagnostic criteria, Sepsis 1 and Sepsis 3, demonstrated similar summary estimates and SROC curves. The examination of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool revealed a high risk of bias regarding the participants and their applicability. Also, there was an increased risk of bias in all the studies concerning the index test.

CONCLUSION

Based on our research, presepsin is a promising biomarker for triage and early diagnosis of sepsis.

Analysis of Biochemical and Inflammatory Markers for Predicting COVID-19 Severity: Insights From a Tertiary Healthcare Institution of Eastern India

Background Coronavirus disease-19 (COVID-19) patients often deteriorate rapidly based on viral infection-related inflammation and the subsequent cytokine storm. The clinical symptoms were found to be inconsistent with laboratory findings. There is a need to develop biochemical severity score to closely monitor COVID-19 patients. Methods This study was conducted in the department of biochemistry at All India Institute of Medical Sciences (AIIMS) Bhubaneswar in collaboration with the intensive care unit. Laboratory data of 7,395 patients diagnosed with COVID-19 during the first three waves of the pandemic were analyzed. The serum high sensitivity high-sensitivity C-reactive protein (hs-CRP, immuno-turbidity method), lactate dehydrogenase (LDH, modified Wacker et al. method), and liver enzymes (kinetic-UV method) were estimated by fully automated chemistry analyzer. Serum ferritin and interleukin-6 (IL-6) were measured by one-step immunoassay using chemiluminescence technology. Three models were used in logistic regression to check for the predictive potential of biochemical parameters, and a COVID-19 biochemical severity score was calculated using a non-linear regression algorithm. Results The receiver operating characteristic curve found age, urea, uric acid, CRP, ferritin, IL6, and LDH with the highest odds of predicting ICU admission for COVID-19 patients. COVID-19 biochemical severity scores higher than 0.775 were highly predictive (odds ratio of 5.925) of ICU admission (AUC=0.740, p<0.001) as compared to any other individual parameter. For the validation, 30% of the total dataset was used as testing data (n=2095) with a sensitivity of 68.3%, specificity of 74.5%, and odds ratio of 6.304. Conclusion Age, urea, uric acid, ferritin, IL6, LDH, and CRP-based predictive probability algorithm calculating COVID-19 severity was found to be highly predictive of ICU admission for COVID-19 patients.

The diagnostic utility of IL-10, IL-17, and PCT in patients with sepsis infection

Objective

The purpose of this study is to determine the diagnostic value and net clinical benefit of interleukin-10 (IL-10), interleukin-17 (IL-17), procalcitonin (PCT), and combination tests in patients with sepsis, which will serve as a standard for sepsis early detection.

Patients and methods

An investigation of 84 sepsis patients and 81 patients with local inflammatory diseases admitted to the ICU of Tongji University Hospital in 2021. In addition to comparing inter-group variability, indicators relevant to sepsis diagnosis and therapy were screened.

Results

LASSO regression was used to examine PCT, WBC, CRP, IL-10, IFN-, IL-12, and IL-17. Multivariate logistic regression linked IL-10, IL-17, and PCT to sepsis risk. The AUC values of IL-10, IL-17, PCT, and the combination of the three tests were much higher than those of standard laboratory infection indicators. The combined AUC was greater than the sum of IL-10, IL-17, and PCT (P < 0.05). A clinical decision curve analysis of IL-10, IL-17, PCT, and the three combined tests found that the three combined tests outperformed the individual tests in terms of total clinical benefit rate. To predict the risk of sepsis using IL-10, IL-17, and PCT had an AUC of 0.951, and the model's predicted probability was well matched. An examination of the nomogram model's clinical value demonstrated a considerable net therapeutic benefit between 3 and 87%.

Conclusion

The IL-10, IL-17, and PCT tests all have a high diagnostic value for patients with sepsis, and the combination of the three tests outperforms the individual tests in terms of diagnostic performance, while the combined tests have a higher overall clinical benefit rate.

Association between admission serum procalcitonin and the occurrence of acute kidney injury in patients with septic shock: A retrospective cohort study

BACKGROUND

Procalcitonin (PCT) is an effective and sensitive diagnostic biomarker that can facilitate the early detection of infection and septicemia, but whether it can similarly be utilized to predict the development of acute kidney injury (AKI) in patients suffering from septic shock remains to be established. Herein, the relationship between serum PCT at admission and the onset of AKI in septic shock patients was thus evaluated following adjustment for other potential covariates.

METHODS

This was a retrospective cohort study of 303 septic shock patients treated in a Chinese hospital between May 2015 and May 2019. All patients in whom PCT levels were measured on admission and who did not exhibit AKI or chronic kidney disease at the time of admission were assessed for AKI development within one week following intensive care unit (ICU) admission as per the KDIGO criteria. The relationship between serum PCT at admission and AKI incidence was then assessed for these patients.

RESULTS

These 303 patients were an average of 64 years old, and were 59.7% male. Of these patients, 50.5% developed AKI within the first 7 days following ICU admission. A dully-adjusted binary logistic regression analysis revealed PCT levels at admission to be associated with AKI following adjustment for potential confounding factors (odds ratio (OR) = 1.01, 95%CI (1.01,1.02), p = 0.0007). Receiver operating characteristic curve analysis further indicated that a PCT cutoff level of 52.59 ng/ml at admission was able to predict the incidence of AKI with respective sensitivity and specificity values of 50% and 84%. Interaction analysis revealed no significant interactive relationship between PCT and AKI, suggesting that serum PCT levels represent an early predictor of AKI incidence in septic shock patients.

CONCLUSIONS

Serum PCT at the time of admission can be used as a predictor of AKI in patients suffering from septic shock.

Predicting Disease Severity and Outcome in COVID-19 Patients: A Review of Multiple Biomarkers

CONTEXT.—

An abundance of clinical reports focused on specific laboratory parameters have been reported on coronavirus disease 19 (COVID-19), but a systematic analysis synthesizing these findings has not been performed.

OBJECTIVE.—

To review and summarize the current available literature on the predictive role of various biomarkers in COVID-19 patients.

DATA SOURCES.—

A literature search was performed using databases including PubMed, medRxiv, and bioRxiv. A total of 72 papers were reviewed, including 54 peer-reviewed papers and 18 non-peer-reviewed preprints.

CONCLUSIONS.—

Although the markers are considered nonspecific, acute-phase reactants, including C-reactive protein (CRP), ferritin, serum amyloid A (SAA), and procalcitonin, were reported as sensitive markers of acute COVID-19 disease. Significantly elevated white blood cell count; marked lymphopenia; decreased CD3, CD4, or CD8 T-lymphocyte counts; high neutrophil count; thrombocytopenia; and markedly elevated inflammatory biomarkers were associated with severe disease and the risk of developing sepsis with rapid progression. Trends observed by serial laboratory measurements during hospitalization, including progressive decrease of lymphocyte count, thrombocytopenia, elevated CRP, procalcitonin, increased liver enzymes, decreased renal function, and coagulation derangements, were more common in critically ill patient groups and associated with a high incidence of clinical complications. Elevated interleukin 6 level and markedly increased SAA were most often reported in severely and critically ill patients. Indicators of systemic inflammation, such as neutrophil to lymphocyte ratio, systemic immune-inflammation index, or COVID-19 Severity Score, may be used to predict disease severity, outcome, and mortality. Interpretation of the data reported in the studies reviewed here is limited because of the study design (mostly retrospective), limited sample size, and a lack of defined clinical criteria.