Preoperative systemic inflammatory response index predicts long-term outcomes in type B aortic dissection after endovascular repair

Association between systemic inflammatory response index and bone turnover markers in Chinese patients with osteoporotic fractures: a retrospective cross-sectional study

Background

The systemic inflammatory response index (SIRI) is a novel composite biomarker of inflammation. However, there is limited information on its use in the context of osteoporotic fractures. Hence, this study aimed to investigate the association between baseline SIRI values and bone turnover markers (BTMs) in Chinese patients diagnosed with osteoporotic fractures (OPFs), to offer a more precise method for assessing bone health and inflammation in clinical settings.

Methods

A retrospective cross-sectional study was conducted on 3,558 hospitalized patients with OPFs who required surgery or hospitalization at the First People's Hospital of Kunshan City from January 2017 to July 2022. Baseline measurements of SIRI, β-CTX (beta-C-terminal telopeptide of type I collagen), and P1NP (procollagen type I N-terminal propeptide) were obtained. The analyses were adjusted for variables, including age, sex, body mass index (BMI), and other initial laboratory and clinical findings. Furthermore, multivariable logistic regression, smooth curve fitting, and threshold analysis were also performed.

Results

The results revealed a negative correlation between baseline SIRI values and both β-CTX and P1NP levels. After adjusting for covariates in the regression analysis, each unit increase in SIRI was found to be inked to a reduction of 0.04 (β = -0.04; 95% confidence interval [CI], -0.05 to -0.03; with p-value <0.001) in β-CTX levels and a decrease of 3.77 (β = 3.77; 95% CI, 5.07 to 2.47; with p-value <0.001) in P1NP levels. Furthermore, a curvilinear relationship and threshold effect were also identified. Turning points were identified at SIRI values of 1.41 and 1.63 on the adjusted smooth curve.

Conclusion

The results showed a negative correlation between the baseline SIRI value and β-CTX level, as well as the level of P1NP. This suggests a possible link between the systemic inflammatory response and reduced bone metabolism. If these findings are verified, SIRI has the potential to function as a predictive indicator for BTMs. Nevertheless, additional research is necessary to verify these findings.

Relationship between the clinical outcomes and the systemic inflammatory response index and systemic immune inflammation index after total knee arthroplasty

BACKGROUND

Periprosthetic joint infection (PJI) is an extremely damaging complication that can occur after total knee arthroplasty (TKA). There is no study in the literature investigating the relationship between systemic inflammatory response index (SIRI) and systemic inflammation immune index (SII) values and prognosis and infection in patients who have undergone TKA. The aim of the study was to determine the relationship between the inflammatory index values and the rate of PJI in patients who had previously had TKA.

METHODS

A total of 187 patients who underwent TKA between 2015 and 2023 years were retrospectively analyzed.

RESULTS

The median value of the postoperative SII index was 1862.3 (1146.6-2630.4) in the infected group, while it was 1058.2 (605.0-1762.8) in the non-infected group (p < 0.001). In the infected group, the median value of preoperative SIRI was observed as 2.3 (1.7-3.5), while in the non-infected group it was 0.9 (0.7-1.5) (p < 0.001). The cutoff value for postoperative SIRI was observed to be 2.19, with a sensitivity value of 95%, a specificity value of 46%, the AUC value observed was 65%. The cutoff value for the postoperative SII index was observed to be 1058.96, with a sensitivity value of 100%, a specificity value of 50%.

CONCLUSIONS

Our study has associated the inflammatory markers SIRI, SII, neutrophil lymphocyte ratio, and platelet lymphocyte ratio with PJI, which are easy and inexpensive to obtain. There is no widely recognized serum biomarker that can be used alone with good sensitivity and specificity. This study contributes to finding the gold standard inflammatory marker for diagnosing PJI.

Novel Systemic Inflammatory Markers Predict All-Cause Mortality in Patients Undergoing Endovascular Abdominal Aortic Aneurysm Repair

Background

Clinically useful predictors for risk stratification of long-term survival may assist in selecting patients for endovascular abdominal aortic aneurysm (EVAR) procedures. This study aimed to analyze the prognostic significance of peroperative novel systemic inflammatory markers (SIMs), including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), hemoglobin-to-red cell distribution width ratio (HRR), systemic immune-inflammatory index (SIII), and systemic inflammatory response index (SIRI), for long-term mortality in EVAR.

Methods

A retrospective analysis was performed on 147 consecutive patients who underwent their first EVAR procedure at the Department of Vascular Surgery, Beijing Hospital. The patients were divided into the mortality group (n = 37) and the survival group (n = 110). The receiver operating characteristic curves were used to ascertain the threshold value demonstrating the most robust connection with mortality. The Kaplan-Meier survival analysis was performed between each SIM and mortality. The relationship between SIMs and survival was investigated using restricted cubic splines and multivariate Cox regression analysis.

Results

The study included 147 patients, with an average follow-up duration of 34.28 ± 22.95 months. Deceased patients showed significantly higher NLR (p < 0.001) and reduced HRR (p < 0.001). The Kaplan-Meier estimates of mortality were considerably greater in the higher-NLR group (NLR > 2.77) and lower-HRR group (HRR < 10.64). The hazard ratio (HR) of 0.833 (95% confidence interval (95% CI): 0.71-0.97, p < 0.021) was determined to be statistically significant in predicting death in the multivariable analysis.

Conclusions

Preoperative higher-NLR and lower-HRR have been associated with a lower long-term survival rate in abdominal aortic aneurysm (AAA) patients undergoing elective EVAR. Multivariate Cox regression showed that decreased preoperative HRR is an independent risk factor that increases mortality risk following EVAR. SIMs, such as the NLR and HRR, could be used in future clinical risk prediction methodologies for AAA patients undergoing EVAR. However, additional prospective cohort studies are needed to identify these findings.

Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio predict the prognosis in patients with type B aortic dissection receiving thoracic endovascular aortic repair

Background

The triglyceride-glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio are both reliable surrogate indicator of insulin resistance and have been shown to be valuable in predicting various cardiovascular diseases. However, few studies have explored its association with the prognosis of type B aortic dissection (TBAD) patients receiving thoracic endovascular aortic repair (TEVAR).

Methods

A total of 1,425 consecutive patients who underwent TEVAR were included. Data from 935 patients were analyzed in the study. The endpoint was defined as 30-day and 1-year aortic-related adverse events (ARAEs), all-cause mortality, and major adverse cardiovascular and cerebrovascular events (MACCEs).

Results

There were 935 patients included during a mean follow-up time of 2.8 years. After adjusting for multiple confounding factors, continuous TG/HDL-c [hazard ratio (HR) =1.07; 95% confidence interval (CI): 1.00-1.15; P=0.041] was independently associated with 1-year all-cause mortality. Both a high (Quintile 5: TG/HDL-c ratio ≥4.11) (HR =4.84; 95% CI: 1.55-15.13; P=0.007) and low TG/HDL-c ratio (Quintile 1: TG/HDL-c ratio <1.44) (HR =4.67; 95% CI: 1.46-14.94; P=0.001) were still independent risk factors for 1-year all-cause mortality.

Conclusions

Elevated baseline TG/HDL-c ratio and TG/HDL-c ≥4.11 were significantly related to a higher risk of 1-year all-cause mortality among TBAD patients undergoing TEVAR. At the same time, the low TG/HDL-c ratio was also independently associated with 1-year all-cause mortality. Special attention should be paid to TBAD patients with a higher or an overly low TG/HDL-c ratio.

Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures

Deep vein thrombosis (DVT) is a common complication in patients with lower extremity fractures. Once it occurs, it will seriously affect the quality of life and postoperative recovery of patients. Therefore, early prediction and prevention of DVT can effectively improve the prognosis of patients. This study constructed different machine learning models to explore their effectiveness in predicting DVT. Five prediction models were applied to the study, including Extreme Gradient Boosting (XGBoost) model, Logistic Regression (LR) model, RandomForest (RF) model, Multilayer Perceptron (MLP) model, and Support Vector Machine (SVM) model. Afterwards, the performance of the obtained prediction models was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Kappa. The prediction performances of the models based on machine learning are as follows: XGBoost model (AUC = 0.979, accuracy = 0.931), LR model (AUC = 0.821, accuracy = 0.758), RF model (AUC = 0.970, accuracy = 0.921), MLP model (AUC = 0.830, accuracy = 0.756), SVM model (AUC = 0.713, accuracy = 0.661). On our data set, the XGBoost model has the best performance. However, the model still needs external verification research before clinical application.

Downregulation of LILRB4 Promotes Human Aortic Smooth Muscle Cell Contractile Phenotypic Switch and Apoptosis in Aortic Dissection

Aortic dissection (AD) is a severe vascular disease with high rates of mortality and morbidity. However, the underlying molecular mechanisms of AD remain unclear. Differentially expressed genes (DEGs) were screened by bioinformatics methods. Alterations of histopathology and inflammatory factor levels in β-aminopropionitrile (BAPN)-induced AD mouse model were evaluated through Hematoxylin-Eosin (HE) staining and Enzyme-linked immunosorbent assay (ELISA), respectively. Reverse transcription quantitative real-time polymerase chain reaction was performed to detect DEGs expression. Furthermore, the role of LILRB4 in AD was investigated through Cell Counting Kit-8 (CCK-8), wound healing, and flow cytometry. Western blotting was employed to assess the phenotypic switch and extracellular matrix (ECM)-associated protein expressions in platelet-derived growth factor-BB (PDGF-BB)-stimulated in vitro model of AD. In the AD mouse model, distinct dissection formation was observed. TNF-α, IL-1β, IL-8, and IL-6 levels were higher in the AD mouse model than in the controls. Six hub genes were identified, including LILRB4, TIMP1, CCR5, CCL7, MSR1, and CLEC4D, all of which were highly expressed. Further exploration revealed that LILRB4 knockdown inhibited the cell vitality and migration of PDGF-BB-induced HASMCs while promoting apoptosis and G0/G1 phase ratio. More importantly, LILRB4 knockdown promoted the protein expression of α-SMA and SM22α, while decreasing the expression of Co1, MMP2, and CTGF, which suggested that LILRB4 silencing promoted contractile phenotypic transition and ECM stability. LILRB4 knockdown inhibits the progression of AD. Our study provides a new potential target for the clinical treatment of AD.

The Systemic Immune Inflammatory Response Index Can Predict the Clinical Prognosis of Patients with Initially Diagnosed Coronary Artery Disease

Background

Recently, the systemic immune inflammatory response index (SIIRI), a novel and expanded inflammatory response marker, has been an independent predictor of lesion severity in patients with acute coronary syndrome (ACS). However, its predictive role in patients with initially diagnosed coronary artery disease (CAD) remains to be explored.

Patients and Methods

We evaluated 959 patients with CAD undergoing an initial coronary intervention. Each patient had laboratory measurements, including blood cell counts, taken after admission and before interventional treatment. The primary endpoint was major cardiovascular events (MACEs), defined as cardiovascular death, nonfatal myocardial infarction(MI), and nonfatal stroke. The secondary endpoints included MACEs and readmission for congestive heart failure(HF).

Results

During a mean follow-up period of 33.3±9.9 months, 229 (23.9%) MACEs were recorded. ROC curve analysis displayed that the best cut-off value of SIIRI for predicting MACEs was 247.17*1018/L2. Kaplan-Meier survival curve analysis showed that the survival rate of the low SIIRI group was higher than that of the high SIIRI group (P<0.001). Compared with the low SIIRI group, the high SIIRI group had a significantly higher risk of MACEs (187 cases (39.53%) vs.42 patients (8.64%), P<0.001). Univariate and multivariate Cox regression analyses displayed that high SIIRI levels were independently associated with the occurrence of MACEs in patients with initially diagnosed CAD undergoing percutaneous coronary intervention (PCI) (adjusted hazard ratio [HR]: 3.808, 95% confidence interval [CI%]: 2.643-5.486, P<0.001). Adding SIIRI to conventional risk factor models improved the predictive value of MACEs.

Conclusion

Elevated SIIRI is associated with adverse cardiovascular prognosis in patients with initially diagnosed CAD. SIIRI can be a simple and practical index to identify high-risk patients with CAD after PCI.

Association of systemic immune inflammation index and system inflammation response index with clinical risk of acute myocardial infarction

Background

Systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) are combinations of non-specific inflammatory and adaptive immune response impairments associated with cardiovascular disease. Yet little analysis has been done on SII, SIRI and acute myocardial infarction (AMI) prognosis. The purpose of this study was to investigate the correlation of SII and SIRI with clinical risk factors such as GRACE, Gensini, and QTc after acute myocardial infarction.

Methods

This study enrolled 310 patients with AMI from February 1, 2018, to December 31, 2022, at our institution. Routine blood items calculated SII and SIRI. Two groups were divided according to whether MACE occurred: the MACE group (81 cases) and the NMACE group (229 cases); each group was divided into three groups according to the SII and SIRI tertiles. The relationship between SII, SIRI and MACE was analyzed using multifactorial logistic regression analysis after adjusting for confounders; ROC curves were plotted to examine the predictive value of SII and SIRI for MACE. The correlation between SII and SIRI and potential risk factors such as Gensini, QTc and GRACE was further analyzed.

Results

The study enrolled 310 patients, comprising 248 men (80%, mean age 60.73 ± 13.695 years) and 62 women (20%, mean age 69.79 ± 11.555 years). In the regression model completely adjusted for confounders, the risk of MACE was higher in AMI patients with SII > 11.00 [OR = 1.061,95% CI (1.018,1.105)] than in SII < 5.98; the risk of MACE was 115.3% higher in AMI patients with SIRI (1.72-3.68) [OR = 2.153, 95% CI (1.251, 3.705)] was 115.3% higher in AMI patients with SIRI < 1.72 and the risk of MACE was 25.1% higher in AMI patients with SIRI > 3.68 [OR = 1.251, 95% CI (1.123, 1.394)] than in AMI patients with SIRI < 1.72. In addition, SII, SIRI, and potential post-infarction risk factors (Gensini, QTc, and GRACE) were also associated.

Conclusion

SII and SIRI have been significantly associated with post-myocardial infarction MACE and the predictive potential clinically integrated risk factors in AMI patients, for which more attention should be paid to targeted anti-inflammatory therapy in AMI patients to further reduce the incidence of prognostic MACE in AMI patients.

Preoperative Immature Neutrophils Predict Clinical Outcomes in Patients with Uncomplicated Type-B Aortic Dissection After Thoracic Endovascular Aortic Repair

Purpose

Inflammation is a hallmark of the initial development and progression of aortic dissection. This study aimed to investigate the predictive value of preoperative neutrophils in aorta-related adverse events (AAEs) after thoracic endovascular aortic repair (TEVAR) for type B aortic dissection (TBAD).

Patients and Methods

A total of 80 patients with TBAD undergoing TEVAR were enrolled in our hospital. Preoperative inflammatory markers, including white blood cells (WBCs), neutrophils, neutrophil-to-lymphocyte ratio (NLR) and plasma high-sensitivity C-reactive protein (hs-CRP), were measured. Circulating neutrophil subpopulation was determined by flow cytometry. Kaplan-Meier curve was performed to determine whether neutrophil subsets independently predicted aorta-related adverse events (AAEs) after TEVAR.

Results

Compared with control group, the prevalence of hypertension and the levels of inflammatory indicators including WBCs, total neutrophils, NLR, immature neutrophils and hs-CRP were significantly higher in TBAD patients. Receiver operating characteristic (ROC) curve showed that NLR, absolute number of total neutrophils and percent CD10- immature neutrophils had excellent area under curves. During the 18-month follow-up, 16 (20.0%) were reported to occur AAEs, while 4 deaths (5.0%) were documented. Percent immature neutrophil was markedly higher in TBAD patients experiencing AAEs as compared with those without AAEs. Kaplan-Meier curve and Cox regression analysis demonstrated that percent immature neutrophil was the only predictor correlated with the occurrence of AAEs (hazard ratio 7.66, 95% CI: 2.91, 20.17, P = 0.018).

Conclusion

Increased CD10- immature neutrophils could act as a potential biomarker related to long-term adverse outcomes in TBAD patients following TEVAR.

Relationship between preoperative lymphocyte to monocyte ratio and surgery outcome in type A aortic dissection

Background

Lymphocyte-to-monocyte ratio (LMR) is associated with the mortality of cardiovascular diseases. However, the relationship between preoperative LMR and the prognosis of patients with Stanford type A aortic dissection (TAAD) undergoing surgical treatment remains to be determined.

Methods

We enrolled 879 patients with TAAD undergoing surgical treatment between January 2018 and December 2021. Patients were divided into two groups: the Deceased group and the Survived group. The baseline clinical and operative characteristics of the two groups were compared and analyzed.

Results

In univariate and multivariate logistic regression analysis, the association between LMR and in-hospital mortality was significant, and LMR (OR = 1.598, 95% CI 1.114-2.485, P = 0.022) remained significant after adjusting for confounders.

Conclusion

Lower LMR may be independently associated with higher in-hospital mortality in TAAD undergoing surgical treatment.