Procalcitonin, Interleukin-6 and C-reactive Protein Levels Predict Renal Adverse Outcomes and Mortality in Patients with Acute Type A Aortic Dissection

Clinical implication of NT-proBNP to predict mortality in patients with acute type A aortic dissection: a retrospective cohort study

OBJECTIVES

Acute type A aortic dissection is a life-threatening cardiovascular disease commonly seen in emergency department, resulting in substantial mortality and morbidity. We aimed to investigate the prognostic value of N-terminal pro-B type natriuretic peptide (NT-proBNP) among this critically ill population.

DESIGN

The design of this study was a retrospective cohort study.

SETTING

The study population was recruited in the Emergency Department of Fuwai hospital in China from 2018 to 2020.

PARTICIPANTS

We consecutively enrolled 829 patients with acute type A aortic dissection and measurable baseline NT-proBNP.

PRIMARY OUTCOME

The primary endpoint was 1-year all-cause death.

RESULTS

Based on tertiles of NT-proBNP (pg/mL), patients were stratified into low (≤150.3, n=276), intermediate (150.3-667.6, n=277) and high (>667.6, n=276) NT-proBNP groups. Compared with patients with low NT-proBNP, the Kaplan-Meier estimates for primary 1-year mortality were higher in intermediate (32.5% vs 18.1%; HR 1.91, 95% CI 1.35 to 2.69) and high (42.0% vs 18.1%; HR 2.56, 95% CI 1.84 to 3.57) NT-proBNP groups, respectively. After multivariable regression adjusted for confounders, NT-proBNP tertiles were independent predictors for 1-year mortality (adjusted HR for intermediate group 1.52, 95% CI 1.02 to 2.27; adjusted HR for high group 2.17, 95% CI 1.41 to 3.32). Notably, the predictive performance of NT-proBNP for 1-year mortality was greater in patients receiving surgery than conservative treatment (between-cohorts difference in area under the curve 0.13, Delong's test p=0.04).

CONCLUSION

NT-proBNP provides incremental prognostic information for mortality in patients with acute type A aortic dissection who underwent surgical repairment, which could aid in risk stratification as a pragmatic and versatile biomarker in this critically ill population while having limited prognostic value for those receiving conservative treatment.

A Narrative Review of Biomarkers and Imaging in the Diagnosis of Acute Aortic Syndrome

Acute aortic syndrome (AAS) encompasses a range of life-threatening conditions, including classical dissection, intramural hematoma, and penetrating aortic ulcer. Each of these conditions presents distinct clinical characteristics and carries the potential to progress to rupture. Because AAS can be asymptomatic or present with diverse symptoms, its diagnosis requires clinical evaluation, risk scoring, and biomarkers such as D-dimer (DD), C-reactive protein (CRP), homocysteine, natriuretic peptides (BNP), and imaging modalities like computed tomography (CT), magnetic resonance imaging (MRI), and echocardiography. While this review primarily focuses on widely used and clinically accessible biomarkers and imaging techniques, it also discusses alternative biomarkers proposed for diagnostic use. Although CT remains the gold standard for diagnosis, biomarkers facilitate rapid risk stratification, complementing imaging techniques. Emerging technologies, such as metabolomics, are reshaping diagnostic algorithms. Despite advances in diagnostic methods, challenges such as misdiagnosis and missed diagnoses persist. Ongoing research into novel biomarkers and innovative imaging techniques holds promise for improving diagnostic accuracy and patient outcomes.

Influence of false lumen status on systemic inflammatory response triggered by acute aortic dissection

We investigated the influence of false lumen (FL) status on the systemic inflammatory response triggered by acute aortic dissection (AAD) using cytokine profiling. The study included 44 patients with AAD. Patients were divided between those with a thrombosed FL (Group T, n = 21) and those with a non-thrombosed FL (Group P, n = 23). On-admission serum concentrations of 29 cytokines were compared between unmatched and propensity-score matched (n = 10 pairs) FL groups and a control group (non-ruptured thoracic aortic aneurysm, Group C, n = 20). Unmatched analysis showed 12 cytokines differed between groups and fell into three categories: Category A (increased expression in both FL groups: IL-6, IL-10, IL-15, G-CSF); Category B (increased expression only in Group P: IL-1Ra, IL-1β, IL-8, IL-12p70, GM-CSF); and Category C (others: IP-10, VEGF-A, eotaxin). The increases in Category A and Category B cytokines in Group T were attenuated, but not significantly, compared to their increases in Group P. Propensity-score matching analysis revealed a similar expression pattern with respect to all four Category A cytokines, four Category B cytokines (IL-1β, IL-1Ra, IL-12p70, and GM-CSF), and two Category C cytokines (IP-10 and VEGF-A). A robust inflammatory response occurs in patients with AAD, but the response is attenuated when the FL is thrombosed.

Biomarkers of inflammation and coagulation after minimally invasive mitral valve surgery: a prospective comparison to conventional surgery

OBJECTIVES

Minimally invasive cardiac surgery techniques are increasingly used but have longer cardiopulmonary bypass time, which may increase inflammatory response and negatively affect coagulation. Our aim was to compare biomarkers of inflammation and coagulation as well as transfusion rates after minimally invasive mitral valve repair and mitral valve surgery using conventional sternotomy.

DESIGN

A prospective non-randomized study was performed enrolling 71 patients undergoing mitral valve surgery (35 right mini-thoracotomy and 36 conventional sternotomy procedures). Blood samples were collected pre- and postoperatively to assess inflammatory response. Thromboelastometry (ROTEM) was performed to assess coagulation, and transfusion rates were monitored.

RESULTS

The minimally invasive group had longer cardiopulmonary bypass times compared to the sternotomy group: 127 min ([115-146] vs 79 min [65-112], p < 0.001) and were cooled to a lower temperature during cardiopulmonary bypass, 34 °C vs 36 °C (p = 0.04). IL-6 was lower in the minimally invasive group compared to the conventional sternotomy group when measured at the end of the surgical procedure, (38 [23-69] vs 61[41-139], p = 0.008), but no differences were found at postoperative day 1 or postoperative day 3. The transfusion rate was lower in the minimally invasive group (14%) compared to full sternotomy (35%, p = 0.04) and the chest tube output was reduced, (395 ml [190-705] vs 570 ml [400-1040], p = 0.04).

CONCLUSIONS

Our data showed that despite the longer use of extra corporal circulation during surgery, minimally invasive mitral valve repair is associated with reduced inflammatory response, lower rates of transfusion, and reduced chest tube output.

Combination of Creatinine with Inflammatory Biomarkers (PCT, CRP, hsCRP) for Predicting Postoperative ICU Admissions for Elderly Patients

INTRODUCTION

The number of elderly patients who require surgery as their primary treatment has increased rapidly in recent years. Among 300 million people globally who underwent surgery every year, patients aged 65 years and over accounted for more than 30% of cases. Despite medical advances, older patients remain at higher risk of postoperative complications. Early diagnosis and effective prediction are essential requirements for preventing serious postoperative complications. In this study, we aim to provide new biomarker combinations to predict the incidence of postoperative intensive care unit (ICU) admissions > 24 h in elderly patients.

METHODS

This investigation was conducted as a nested case-control study, incorporating 413 participants aged ≥ 65 years who underwent non-cardiac, non-urological elective surgeries. These individuals underwent a 30-day postoperative follow-up. Before surgery, peripheral venous blood was collected for analyzing serum creatinine (Scr), procalcitonin (PCT), C-reactive protein (CRP), and high-sensitivity CRP (hsCRP). The efficacy of these biomarkers in predicting postoperative complications was evaluated using receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values.

RESULTS

Postoperatively, 10 patients (2.42%) required ICU admission. Regarding ICU admissions, the AUCs with 95% confidence intervals (CIs) for the biomarker combinations of Scr × PCT and Scr × CRP were 0.750 (0.655-0.845, P = 0.007) and 0.724 (0.567-0.882, P = 0.015), respectively. Furthermore, cardiovascular events were observed in 14 patients (3.39%). The AUC with a 95% CI for the combination of Scr × CRP in predicting cardiovascular events was 0.688 (0.560-0.817, P = 0.017).

CONCLUSION

The innovative combinations of biomarkers (Scr × PCT and Scr × CRP) demonstrated efficacy as predictors for postoperative ICU admissions in elderly patients. Additionally, the Scr × CRP also had a moderate predictive value for postoperative cardiovascular events.

TRIAL REGISTRATION

China Clinical Trial Registry, ChiCTR1900026223.

Short- and Long-term survival prediction in patients with acute type A aortic dissection undergoing open surgery

BACKGROUND

Acute Type A aortic dissection (ATAAD) is a life-threatening cardiovascular disease associated with high mortality rates, where surgical intervention remains the primary life-saving treatment. However, the mortality rate for ATAAD operations continues to be alarmingly high. To address this critical issue, our study aimed to assess the correlation between preoperative laboratory examination, clinical imaging data, and postoperative mortality in ATAAD patients. Additionally, we sought to establish a reliable prediction model for evaluating the risk of postoperative death.

METHODS

In this study, a total of 384 patients with acute type A aortic dissection (ATAAD) who were admitted to the emergency department for surgical treatment were included. Based on preoperative laboratory examination and clinical imaging data of ATAAD patients, logistic analysis was used to obtain independent risk factors for postoperative in-hospital death. The survival prediction model was based on cox regression analysis and displayed as a nomogram.

RESULTS

Logistic analysis identified several independent risk factors for postoperative in-hospital death, including Marfan syndrome, previous cardiac surgery history, previous renal dialysis history, direct bilirubin, serum phosphorus, D-dimer, white blood cell, multiple aortic ruptures and age. A survival prediction model based on cox regression analysis was established and presented as a nomogram. The model exhibited good discrimination and significantly improved the prediction of death risk in ATAAD patients.

CONCLUSIONS

In this study, we developed a novel survival prediction model for acute type A aortic dissection based on preoperative clinical features. The model demonstrated good discriminatory power and improved accuracy in predicting the risk of death in ATAAD patients undergoing open surgery.

A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta

Background

Acute kidney injury (AKI) frequently occurs after aortic surgery and has a significant impact on patient outcomes. Early detection or prediction of AKI is crucial for timely interventions. This study aims to develop and validate a novel model for predicting AKI following aortic surgery.

Methods

We enrolled 156 patients who underwent on-pump aortic surgery in our hospital from February 2023 to April 2023. Postoperative levels of eight cytokines related to macrophage polarization analyzed using a multiplex cytokine assay. All-subset regression was used to select the optimal cytokines to predict AKI. A logistic regression model incorporating the selected cytokines was used for internal validation in combination with a bootstrapping technique. The model's ability to discriminate between cases of AKI and non-AKI was assessed using receiver operating characteristic (ROC) curve analysis.

Results

Of the 156 patients, 109 (69.87%) developed postoperative AKI. Interferon-gamma (IFN- γ ) and interleukin-4 (IL-4) were identified as candidate AKI predictors. The cytokine-based model including IFN- γ and IL-4 demonstrated excellent discrimination (C-statistic: 0.90) and good calibration (Brier score: 0.11). A clinical nomogram was generated, and decision curve analysis revealed that the cytokine-based model outperformed the clinical factor-based model in terms of net benefit. Moreover, both IFN- γ and IL-4 emerged as independent risk factors for AKI. Patients in the second and third tertiles of IFN- γ and IL-4 concentrations had a significantly higher risk of severe AKI, a higher likelihood of requiring renal replacement therapy, or experiencing in-hospital death. These patients also had extended durations of mechanical ventilation and intensive care unit stays, compared with those in the first tertile (all p for group trend < 0.001).

Conclusions

We successfully established a novel and powerful predictive model for AKI, and demonstrating the significance of IFN- γ and IL-4 as valuable clinical markers. These cytokines not only predict the risk of AKI following aortic surgery but are also linked to adverse in-hospital outcomes. This model offers a promising avenue for the early identification of high-risk patients, potentially improving clinical decision-making and patient care.

Predictive value of perioperative procalcitonin, C reactive protein and high-sensitivity C reactive protein for the risk of postoperative complications after non-cardiac surgery in elderly patients: a nested case-control study

OBJECTIVE

Little is known about the correlation between perioperative concentrations of inflammatory biomarkers and postoperative complications. This study explored whether the plasma concentrations and perioperative changes of procalcitonin (PCT), C reactive protein (CRP) and high-sensitivity CRP (hsCRP) could predict the risk of postoperative morbidity in elderly patients undergoing elective non-cardiac surgery.

DESIGN

A nested case-control study.

SETTING

A tertiary hospital in China.

PARTICIPANTS

A total of 498 patients aged ≥65 years from a prospective cohort who underwent elective non-cardiac surgery between June 2020 and April 2021.

PRIMARY OUTCOME MEASURES

The primary outcomes were the efficacy of plasma concentrations of PCT, CRP and hsCRP in predicting the risk of Clavien-Dindo Classification (CDC) ≥grade 3 and major complications. The major complications included mortality, an intensive care unit stay length >24 hour, cardiovascular events, acute kidney injury, postoperative cognitive dysfunction and infections.

RESULTS

For major complications, the area under the curve (AUC) (95% CI) of PCT-24 hours, PCT change and PCT change rate were 0.750 (0.698 to 0.803), 0.740 (0.686 to 0.795) and 0.711 (0.651 to 0.771), respectively. The AUC (95% CI) of CRP-24 hours, CRP change, CRP change rate and hsCRP baseline were 0.835 (0.789 to 0.881), 0.818 (0.770 to 0.867), 0.691 (0.625 to 0.756) and 0.616 (0.554 to 0.678), respectively. For complications ≥CDC grade 3, the AUC (95% CI) of PCT-24 hours, PCT change and PCT change rate were 0.662 (0.543 to 0.780), 0.643 (0.514 to 0.772) and 0.627 (0.494 to 0.761), respectively. The AUC (95% CI) of CRP-24 hours and hsCRP baseline were 0.649 (0.527 to 0.771) and 0.639 (0.530 to 0.748), respectively.

CONCLUSIONS

PCT-24 hours, CRP-24 hours, the change of perioperative PCT and CRP were valuable predictors of major complications occurring within 30 days after non-cardiac surgery in the elderly.

TRIAL REGISTRATION NUMBER

China Clinical Trial Registry: ChiCTR1900026223.

A prediction model to predict in-hospital mortality in patients with acute type B aortic dissection

BACKGROUND

Acute type B aortic dissection (ABAD) is a life-threatening cardiovascular disease. A practicable and effective prediction model to predict and evaluate the risk of in-hospital death for ABAD is required. The present study aimed to construct a prediction model to predict the risk of in-hospital death in ABAD patients.

METHODS

A total of 715 patients with ABAD were recruited in the first affiliated hospital of Xinjiang medical university from April 2012 to May 2021. The information on the demographic and clinical characteristics of all subjects was collected. The logistic regression analysis, receiver operating characteristic (ROC) curve analysis, and nomogram were applied to screen the appropriate predictors and to establish a prediction model for the risk of in-hospital mortality in ABAD. The receiver operator characteristic curve and calibration plot were applied to validate the performance of the prediction model.

RESULTS

Of 53 (7.41%) subjects occurred in-hospital death in 715 ABAD patients. The variables including diastolic blood pressure (DBP), platelets, heart rate, neutrophil-lymphocyte ratio, D-dimer, C-reactive protein (CRP), white blood cell (WBC), hemoglobin, lactate dehydrogenase (LDH), procalcitonin, and left ventricular ejection fraction (LVEF) were shown a significant difference between the in-hospital death group and the in-hospital survival group (all P < 0.05). Furthermore, all these factors which existed differences, except CRP, were associated with in-hospital deaths in ABAD patients (all P < 0.05). Then, parameters containing LVEF, WBC, hemoglobin, LDH, and procalcitonin were identified as independent risk factors for in-hospital deaths in ABAD patients by adjusting compound variables (all P < 0.05). In addition, these independent factors were qualified as predictors to build a prediction model (AUC > 0.5, P < 0.05). The prediction model was shown a favorable discriminative ability (C index = 0.745) and demonstrated good consistency.

CONCLUSIONS

The novel prediction model combined with WBC, hemoglobin, LDH, procalcitonin, and LVEF, was a practicable and valuable tool to predict in-hospital deaths in ABAD patients.

Identification of pathological-related and diagnostic potential circular RNAs in Stanford type A aortic dissection

Introduction

Stanford type A aortic dissection (TAAD) is one of the lethal macrovascular diseases caused by the invasion of blood into the media layer of ascending aortic wall. Inflammation, smooth muscle dysfunction, and extracellular matrix (ECM) degradation were regarded as the major pathology in affected tissue. However, the expression pattern and its regulation especially through circular RNAs (circRNAs) as an overall characteristic of TAAD molecular pathology remain unclear.

Methods

We employed CIRCexplorer2 to identify circRNAs based on the RNA sequencing (RNA-seq) data of human ascending aortic tissues to systematically assess the role of circRNA in the massive alterations of gene expression in TAAD aortas. The key circRNAs were determined by LASSO model and functionally annotated by competing endogenous RNAs (ceRNA) network and co-analysis with mRNA profile. The expression level and diagnostic capability of the 4 key circRNAs in peripheral serum were confirmed by real-time polymerase chain reaction (RT-PCR).

Results

The 4 key circRNAs, namely circPTGR1 (chr9:114341075-114348445[-]), circNOX4 (chr11:89069012-89106660[-]), circAMN1 (chr12:31854796-31862359[-]) and circUSP3 (chr15:63845913-63855207[+]), demonstrated a high power to discriminate between TAAD and control tissues, suggesting that these molecules stand for a major difference between the tissues at gene regulation level. Functionally, the ceRNA network of circRNA-miRNA-mRNA predicted by the online databases, combining gene set enrichment analysis (GSEA) and cell component prediction, revealed that the identified circRNAs covered all the aspects of primary TAAD pathology, centralized with increasing inflammatory factors and cells, and ECM destruction and loss of vascular inherent cells along with the circRNAs. Importantly, we validated the high concentration and diagnostic capability of the 4 key circRNAs in the peripheral serum in TAAD patients.

Discussion

This study reinforces the vital status of circRNAs in TAAD and the possibility of serving as promising diagnostic biomarkers.