Predictive value of systemic immune-inflammation index combined with N-terminal pro-brain natriuretic peptide for contrast-induced acute kidney injury in patients with STEMI after primary PCI.

OBJECTIVE: To investigate the relationship between the incidence of contrast-induced acute kidney injury (CI-AKI) after emergency percutaneous coronary intervention (PCI) and preoperative systemic immune-inflammation index (SII) and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels in patients with acute ST-segment elevation myocardial infarction (STEMI), and to further analyze the predictive value of the combination of SII and NT-proBNP for CI-AKI. METHODS: The clinical data of 1543 patients with STEMI who underwent emergency PCI in our hospital from February 2019 to December 2022 were retrospectively analyzed. All patients were divided into training cohort (n = 1085) and validation cohort (n = 287) according to chronological order. The training cohort was divided into CI-AKI (n = 95) and non-CI-AKI (n = 990) groups according to the 2018 European Society of Urogenital Radiology definition of CI-AKI. Multivariate Logistic regression analysis was used to determine the independent risk factors for CI-AKI. Restricted cubic spline (RCS) was used to explore the relationship between SII, NT-proBNP, and the risk of CI-AKI. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SII, NT-proBNP, and their combination in CI-AKI. RESULTS: The incidence of CI-AKI was 8.8% (95/1085). Multivariate logistic regression analysis showed that SII, NT-proBNP, age, baseline creatinine, fasting blood glucose, and diuretics were independent risk factors for CI-AKI. RCS analysis showed that SII > 1084.97 × 109/L and NT-proBNP > 296.12 pg/mL were positively associated with the incidence of CI-AKI. ROC curve analysis showed that the area under the curve of SII and NT-proBNP combined detection in predicting CI-AKI was 0.726 (95% CI 0.698-0.752, P < 0.001), the sensitivity was 60.0%, and the specificity was 77.7%, which were superior to the detection of SII or NT-proBNP alone. CONCLUSION: Preprocedural high SII and NT-proBNP are independent risk factors for CI-AKI after emergency PCI in patients with STEMI. The combined detection of SII and NT-proBNP can more accurately predict CI-AKI risk than the single detection.

Prognostic Value of Systemic Immune-Inflammation Index and NT-proBNP in Patients with Acute ST-Elevation Myocardial Infarction.

Objective: Our aim was to assess systemic immune-inflammation index (SII) and NT-proBNP value either in singly or in combination to predict acute ST-elevation myocardial infarction (STEMI) patient prognosis. Methods: Analyzed retrospectively the clinical features and laboratory data of STEMI confirmed patients in our hospital from January to December 2020. The levels of SII and NT-proBNP were detected. The Kaplan-Meier approach and Spearman's rank correlation coefficient were used to construct the overall major adverse cardiac event (MACE) curve. Multivariate Cox regression analysis was applied to detect MACE predictors. In addition, the Delong test and receiver operating characteristic (ROC) curve analyzed each factor performance on its own and composite multivariate index to predict MACEs. Results: The MACE group showed statistically significant differences in SII, NT- proBNP in comparison to the non-MACE group (P=0.003, P <0.001). Based on Kaplan-Meier analysis, SII and NT-proBNP showed positive correlation with MACE (log-rank P < 0.001). SII and NT-proBNP were independent predicting factors for long-term MACEs in multivariate Cox regression analysis (P <0.001, HR: 2.952, 95% CI 1.565-5.566; P <0.001, HR: 2.112, 95% CI 1.662-2.683). SII and NT-proBNP exhibited a positive correlation (R = 0.187, P < 0.001) in correlation analysis. According to the ROC statistical analysis, the combination exhibited 78.0% sensitivity and 88.0% specificity in the prediction of MACE. According to the results of the AUC and Delong test, the combined SII and NT-proBNP performed better as a prognostic index than each of the individual factor indexes separately (Z = 2.622, P = 0.009; Z = 3.173, P < 0.001). Conclusion: SII and NT-proBNP were independent indicators of clinical prognosis in acute STEMI patients, and they correlated positively. These factors could be combined to improve clinical prognosis.

A Predictive Model for Contrast-Induced Acute Kidney Injury After Percutaneous Coronary Intervention in Elderly Patients with ST-Segment Elevation Myocardial Infarction.

Purpose: Development and validation of a nomogram model to predict the risk of Contrast-Induced Acute Kidney Injury (CI-AKI) after emergency percutaneous coronary intervention (PCI) in elderly patients with acute ST-segment elevation myocardial infarction (STEMI). Patients and Methods: Retrospective analysis of 542 elderly (≥65 years) STEMI patients undergoing emergency PCI in our hospital from January 2019 to June 2022, with all patients randomized to the training cohort (70%; n=380) and the validation cohort (30%; n=162). Univariate analysis, LASSO regression, and multivariate logistic regression analysis were used to determine independent risk factors for developing CI-AKI in elderly STEMI patients. R software is used to generate a nomogram model. The predictive power of the nomogram model was compared with the Mehran score 2. The area under the ROC curve (AUC), calibration curves, and decision curve analysis (DCA) was used to evaluate the prediction model's discrimination, calibration, and clinical validity, respectively. Results: The nomogram model consisted of five variables: diabetes mellitus (DM), left ventricular ejection fraction (LVEF), Systemic immune-inflammatory index (SII), N-terminal pro-brain natriuretic peptide (NT-proBNP), and highly sensitive C-reactive protein(hsCRP). In the training cohort, the AUC is 0.84 (95% CI: 0.790-0.890), and in the validation cohort, it is 0.844 (95% CI: 0.762-0.926). The nomogram model has better predictive ability than Mehran score 2. Based on the calibration curves, the predicted and observed values of the nomogram model were in good agreement between the training and validation cohort. Decision curve analysis (DCA) and clinical impact curve showed that the nomogram prediction model has good clinical utility. Conclusion: The established nomogram model can intuitively and specifically screen high-risk groups with a high degree of discrimination and accuracy and has a specific predictive value for CI-AKI occurrence in elderly STEMI patients after PCI.

Predictive value of systemic immune-inflammatory index combined with CHA2DS2-VASC score for contrast-induced acute kidney injury in patients with acute coronary syndrome undergoing percutaneous coronary intervention.

OBJECTIVE: To investigate the value of systemic immune-inflammation index (SII) combined with CHA2DS2-VASC score in predicting the risk of contrast-induced acute kidney injury (CI-AKI) in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI) treatment. METHODS: 1531 consecutive patients with ACS and undergoing PCI were recruited from January 2019 to December 2021. All patients were divided into CI-AKI and non-CI-AKI groups according to the pre-procedure and post-procedure creatinine changes, and the baseline data were compared between the two groups. Binary logistic regression analysis was used to investigate the factors influencing CI-AKI in ACS patients after PCI. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of SII, CHA2DS2-VASC, and their combined levels on CI-AKI after PCI. RESULTS: Patients with high SII and high CHA2DS2-VASC score had a higher incidence of CI-AKI. For SII, the area under the ROC curve (AUC) for predicting CI-AKI was 0.686. The optimal cut-off value was 736.08 with a sensitivity of 66.8% and a specificity of 66.3% [95% confidence interval (CI) 0.662-0.709; P < 0.001]. For CHA2DS2-VASC score, the AUC was 0.795, the optimal cut-off value was 2.50 with a sensitivity of 80.3% and a specificity of 62.7% (95% CI 0.774-0.815; P < 0.001). When combining SII and CHA2DS2-VASC score, the AUC was 0.830, the optimal cut-off value was 0.148 with a diagnostic sensitivity of 76.1% and a specificity of 75.2% (95% CI 0.810-0.849; P < 0.001). The results showed that SII combined with CHA2DS2-VASC score resulted in improved predictive accuracy of CI-AKI. Multifactorial logistic regression analysis showed that albumin level (OR = 0.967, 95% CI 0.936-1.000; P = 0.047), lnSII level (OR = 1.596, 95% CI 1.010-1.905; P < 0.001), and CHA2DS2-VASC score level (OR = 1.425, 95% CI 1.318-1.541; P < 0.001) were independent risk factors for CI-AKI in patients with ACS treated with PCI. CONCLUSION: High SII and high CHA2DS2-VASC score are risk factors for the development of CI-AKI, and the combination of the two improves the accuracy of predicting the occurrence of CI-AKI in patients with ACS undergoing PCI.

Predictive Value of Neutrophil to High-Density Lipoprotein Ratio for Contrast-Induced Acute Kidney Injury for Patients with Acute Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention.

Background: To investigate the incidence of contrast-induced acute kidney injury (CI-AKI) in patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention (PCI) in relation to the neutrophil to high-density lipoprotein cholesterol ratio (NHR), and to further compare the predictive value of NHR and the neutrophil to lymphocyte ratio (NLR) for CI-AKI. Methods: We retrospectively analyzed 1243 AMI patients undergoing PCI from January 2019 to December 2021, and collected creatinine within 72 h after PCI. All patients were divided into a CI-AKI group and non-CI-AKI group according to the definition of CI-AKI, and the clinical information of the two groups was compared. Potential risk factors for CI-AKI in AMI patients undergoing primary PCI were screened by using logistic regression analysis, and receiver operating characteristic (ROC) curves were used to compare the predictive value of NHR and NLR. Results: A high NHR and high NLR were correlated with a high incidence of CI-AKI in AMI patients undergoing primary PCI, and NHR (odds ratio (OR): 1.313, 95% confidence interval (CI): 1.199-1.438) and NLR (OR: 1.105, 95% CI: 1.041-1.174) were independent risk factors for CI-AKI (p < 0.05). Compared with NLR, the area under the curve (AUC) of NHR was larger (AUC = 0.668, 95% CI: 0.641-0.694 vs. AUC = 0.723, 95% CI: 0.697-0.748), and the difference was significant (p < 0.05), with higher sensitivity (61.67% vs. 70.83%) and specificity (64.91% vs. 66.10%). Conclusions: Compared with the NLR, the NHR is more valuable in predicting the incidence of CI-AKI in AMI patients undergoing primary PCI.

Development and Validation of a Risk Nomogram Model for Predicting Contrast-Induced Acute Kidney Injury in Patients with Non-ST-Elevation Acute Coronary Syndrome Undergoing Primary Percutaneous Coronary Intervention.

OBJECTIVE: To establish a nomogram model to predict the risk of contrast-induced acute kidney injury (CI-AKI) by analyzing the risk factors of CI-AKI and to evaluate its effectiveness. METHODS: Retrospectively analyze the clinical data of non-ST-elevation acute coronary syndrome (NSTE-ACS) patients who underwent percutaneous coronary intervention (PCI) in our cardiology department from September 2018 to June 2021. Of these, patients who underwent PCI in an earlier period formed the training cohort (70%; n = 809) for nomogram development, and those who underwent PCI thereafter formed the validation cohort (30%; n = 347) to confirm the model's performance. The independent risk factors of CI-AKI were determined by LASSO regression and multivariable logistic regression analysis. By using R software from which nomogram models were subsequently generated. The nomogram was developed and evaluated based on discrimination, calibration, and clinical efficacy using the concordance statistic (C-statistic), calibration plot, and decision curve analysis (DCA), respectively. RESULTS: The nomogram consisted of six variables: age >75, left ventricular ejection fraction, diabetes mellitus, fibrinogen-to-albumin ratio, high-sensitive C-reactive protein, and lymphocyte count. The C-index of the nomogram is 0.835 (95% CI: 0.800-0.871) in the training cohort and 0.767 (95% CI: 0.711-0.824) in the validation cohort, respectively. The calibration plots exhibited that the nomogram was in good agreement between prediction and observation in the training and validation cohorts. Decision curve analysis and clinical impact curve suggested that the predictive nomogram had clinical utility. CONCLUSION: The nomogram model established has a good degree of differentiation and accuracy, which is intuitively and individually to screen high-risk groups and has a certain predictive value for the occurrence of CI-AKI in NSTE-ACS patients after PCI.

Impact of small and dense low-density lipoprotein (sd-LDL)on contrast-induced acute kidney injury in patients with acute ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention.

OBJECTIVE: To investigate the impact of serum small and dense low-density lipoprotein (sd-LDL) on contrast-induced acute kidney injury (CI-AKI) after emergency percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI). METHOD: From November 2019 to August 2020, 352 patients with STEMI who underwent primary PCI were recruited consecutively. Patients were divided into CI-AKI group (n = 71) and non-CI-AKI group (n = 281). CI-AKI was defined as an increase in serum creatinine (≥ 25% or ≥ 0.5 mg/dL) from baseline occurring 72 h after PCI. All subjects were tested for sd-LDL. RESULTS: In the 352 eligible patients with STEMI receiving emergency PCI, 71 patients (20.2%) developed CI-AKI. The levels of sd-LDL in CI-AKI group was higher than those in the non-CI-AKI group, and the difference was statistically significant (P < 0.05). The area under the curve (AUC) of the sd-LDL was 0.741 [95% confidence interval (CI) 0.538-0.636] in the STEMI patients receiving emergency PCI. CI-AKI model included the following five predictors: sd-LDL, NLR, Diabetes, Pre-PCI eGFR, and Log NT-proBNP. The AUC of forecast probability was 0.835 [95% confidence interval (CI) 0.786-0.883].The Hosmer-Lemeshow test has a P value of 0.519, which confirms the model's goodness of fit. CONCLUSION: Increased sd-LDL is independently associated with risk of CI-AKI in STEMI patients treated by primary PCI.

Biomechanical effects of morphological variations of the cortical wall at the bone-cement interface.

BACKGROUND: The integrity of bone-cement interface is very important for the stabilization and long-term sustain of cemented prosthesis. Variations in the bone-cement interface morphology may affect the mechanical response of the shape-closed interlock. METHODS: Self-developed new reamer was used to process fresh pig reamed femoral canal, creating cortical grooves in the canal wall of experimental group. The biomechanical effects of varying the morphology with grooves of the bone-cement interface were investigated using finite element analysis (FEA) and validated using companion experimental data. Micro-CT scans were used to document interlock morphology. RESULTS: The contact area of the bone-cement interface was greater (P < 0.05) for the experimental group (5470 ± 265 mm(2)) when compared to the specimens of control group (5289 ± 299 mm(2)). The mechanical responses to tensile loading and anti-torsion showed that the specimens with grooves were stronger (P < 0.05) at the bone-cement interface than the specimens without grooves. There were positively significant correlation between the contact area and the tensile force (r (2) = 0.85) and the maximal torsion (r (2) = 0.77) at the bone-cement interface. The volume of cement of the experimental group (7688 ± 278 mm(3)) was greater (P < 0.05) than of the control group (5764 ± 186 mm(3)). There were positively significant correlations between the volume of cement and the tensile force (r (2) = 0.90) and the maximal torsion (r (2) = 0.97) at the bone-cement interface. The FEA results compared favorably to the tensile and torsion relationships determined experimentally. More cracks occurred in the cement than in the bone. CONCLUSIONS: Converting the standard reaming process from a smooth bore cortical tube to the one with grooves permits the cement to interlock with the reamed bony wall. This would increase the strength of the bone-cement interface.

A long non-coding RNA contributes to doxorubicin resistance of osteosarcoma.

Long non-coding RNAs (lncRNAs) are emerging in molecular biology as crucial regulators of cancer. Although the aberrant expression of lncRNAs has been observed in osteosarcoma (OS), the molecular mechanisms underlying lncRNAs in doxorubicin resistance of OS still unknown. In the current study, we investigated a novel lncRNA, termed ODRUL (osteosarcoma doxorubicin-resistance related up-regulated lncRNA), and evaluated its role in the occurrence of doxorubicin resistance in OS. LncRNA microarray revealed that lncRNA ODRUL was the most up-regulated expressed in the doxorubicin-resistant OS cell line. Quantitative real-time PCR (qRT-PCR) confirmed that lncRNA ODRUL was higher in different doxorubicin-resistant OS cell lines and lower in different doxorubicin-sensitive OS cell lines. Moreover, we showed that lncRNA ODRUL was increased in specimens of OS patients with a poor chemoresponse and lung metastasis. We further demonstrated that lncRNA ODRUL inhibition could inhibit OS cell proliferation, migration, and partly reversed doxorubicin resistance in vitro. In addition, we found that the expression of classical drug resistance-related ATP-binding cassette, subfamily B, member 1 (ABCB1) gene was decreased after the lncRNA ODRUL knockdown. Thus, we concluded that lncRNA ODRUL may act as a pro-doxorubicin-resistant molecule through inducing the expression of the classical multidrug resistance-related ABCB1 gene in osteosarcoma cells .These findings may provide a novel target for reversing doxorubicin resistance in OS.

Long noncoding RNA expression profiles of the doxorubicin-resistant human osteosarcoma cell line MG63/DXR and its parental cell line MG63 as ascertained by microarray analysis.

Long non-coding RNAs (lncRNAs) are emerging in molecular biology as crucial regulators of cancer. The efficacy of doxorubicin--based chemotherapy in osteosarcoma (OS) is usually limited by acquired drug resistance. To explore the mechanism of chemoresistance of OS in terms of lncRNA, using a human lncRNA-mRNA combined microarray, we identified 3,465 lncRNAs (1,761 up and 1,704 down) and 3,278 mRNAs (1,607 up and 1,671 down) aberrantly expressed in all three sets of doxorubicin-resistant MG63/DXR and their paired parental MG63 cells (fold-change >2.0, P<0.05 and FDR <0.05). Fifteen randomly selected lncRNAs were dysregulated in MG63/DXR cells relative to MG63 cells by qRT-PCR detection, which were consistent with our microarray data. Bioinformatics analysis identified that classical genes and pathways involved in cell proliferation, apoptosis, and drug metabolism were differently expressed in these cell lines. A lncRNA-mRNA co-expression network identified lncRNAs, including ENST00000563280 and NR-036444, may play a critical role in doxorubicin-resistance of OS by interacting with important genes such as ABCB1, HIF1A and FOXC2. Besides, we found that lncRNA ENST00000563280 was distinctly increased in specimens of OS patients with a poor chemoresponse compared to those with a good chemoresponse and the patients of lower expression of it may survive longer than those of higher expression, which suggest that it may serve as a biomarker to predict the chemoresponse and prognosis of osteosarcoma patients. These results provide important insights about the lncRNAs involved in osteosarcoma chemoresistance and lay a solid foundation for uncovering the mechanism ultimately.