Predictive value of admission D-dimer for contrast-induced acute kidney injury and poor outcomes after primary percutaneous coronary intervention

Sex differences in the association between D-dimer and the incidence of acute kidney injury in patients admitted with ST-segment elevation myocardial infarction: a retrospective observational study

Identifying the predictors of acute kidney injury (AKI) in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI) remains important. We aimed to investigate the predictive value of D-dimer levels for the incidence of AKI in such a population, with particular attention paid to sex differences. A total of 2668 patients with STEMI who underwent PPCI were retrospectively included in this study and divided into quartiles according to their plasma D-dimer levels upon admission (Q1: < 0.36; Q2: 0.36-0.67; Q3: 0.68-1.17; Q4: > 1.17 mg/L). The primary endpoint was the occurrence of AKI during hospitalization. AKI was observed in 503 (18.8%) patients. The mean age of the patients was 63.0 ± 13.2 years, 2155 (80.8%) of whom were men. Multivariate analysis indicated that higher D-dimer levels were associated with a significantly increased risk of AKI (Q4 vs. Q1: OR: 1.57; 95% CI 1.11-2.23; P = 0.011). However, the prognostic effect of D-dimer was only observed in male patients (Q4 vs. Q1: OR: 2.07; 95% CI 1.37-3.13; P < 0.001), not in female patients (Q4 vs. Q1: OR: 0.72; 95% CI 0.37-1.41; P = 0.342) (P for interaction = 0.003). We demonstrated a notable sex difference in the association between D-dimer level upon admission and AKI in a large STEMI patient sample. A higher D-dimer level was associated with an increased risk of AKI in male patients but not in female patients.

The predictive value of the neutrophil/platelet ratio on in-hospital adverse events and long-term prognosis in patients with coronary artery disease after percutaneous coronary intervention and its possible internal mechanism

The neutrophil-to-platelet ratio (NPR) is considered to be an indicator of inflammatory status. The value of the NPR in predicting in-hospital adverse events (AEs) and long-term prognosis after percutaneous coronary intervention (PCI) in coronary artery disease (CAD) patients has not yet been reported. Meanwhile, the mechanisms behind its predictive value for long-term prognosis remain unreported as well. The study retrospectively enrolled 7284 consecutive patients with CAD undergoing PCI from January 2012 to December 2018. Multivariable logistic regression analysis, multivariable Cox regression analysis, Kaplan‒Meier (KM) curve analysis, restricted cubic spline (RCS) curve analysis, and sensitivity analysis were used in the study. All-cause death was the endpoint of the study. According to the median value of the NPR, the patients were divided into two groups: the high group (NPR ≥ 0.02, n = 3736) and the low group (NPR < 0.02, n = 3548). Multivariate logistic regression analysis demonstrated that a high NPR was a risk factor for in-hospital AEs [odds ratio (OR) = 1.602, 95% CI 1.347-1.909, p = 0.001]. During a mean follow-up period of 3.01 ± 1.49 years, the multivariate Cox regression analysis showed that a high NPR affected the long-term prognosis of patients (HR 1.22, 95% CI 1.03-1.45, p = 0.025) and cardiac death (HR 1.49, 95% CI 1.14-1.95, p = 0.003). The subgroup analysis showed that the NPR was affected by age and sex. The mediation analysis identified that the effect of the NPR on long-term outcomes is partially mediated by serum creatinine (Scr) and triglycerides. The NPR may be a convenient indicator of in-hospital AEs and poor long-term and cardiac outcomes in CAD patients. It might have impacted prognosis through effects on kidney function and lipid metabolism.

Comparison of cardiac biomarkers on risk assessment of contrast-associated acute kidney injury in patients undergoing cardiac catheterization: A multicenter retrospective study

AIM

Cardiac biomarkers' predictive value of contrast-associated acute kidney injury (CA-AKI) remains unclear. We analysed whether creatine kinase isoenzyme-MB (CKMB), cardiac troponin I (cTnI) and preoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) are tied to CA-AKI patients undergoing cardiac catheterization.

METHODS

In the multi-center study, we included 3553 people underwent cardiac catheterization for analysis. CA-AKI was defined as the absolute increase of over 0.3 mg/dL or an increase of more than 50% compared with the baseline serum creatinine within 48 hours following cardiac catheterization. Logistic regression model and receiver operating characteristic (ROC) curves were used to examine the association between cardiac biomarkers and CA-AKI and the efficacy of Mehran risk score (MRS) model on CA-AKI prediction with and without cardiac biomarkers.

RESULTS

Among 3553 people, 200 people eventually developed CA-AKI. The logistic regression model showed that log10 CKMB (odds ratio (OR): 1.97, 95%CI:1.51-2.57, p < .001), cTnI (OR: 1.03, 95%CI: 1.02-1.04, p < .001) and log10 NT-proBNP (OR: 3.19, 95%CI: 2.46-4.17, p < .001) were independent predictors of CA-AKI. The ROC curve demonstrated that area under the curve (AUC) of MRS was 0.733. CKMB, cTnI and NT-proBNP all significantly improved the AUC value in combination with MRS model. (NT-proBNP: 0.798, p < .001; CKMB: 0.758, p = .003; cTnI: 0.755, p = .002), among which the NT-proBNP had the best predictive efficacy improvement.

CONCLUSION

Cardiac biomarkers of CKMB, cTnI and NT-proBNP are all independently associated with CA-AKI among patients undergoing cardiac catheterization while NT-proBNP remains the best indicator. Adding CKMB, cTnI and NT-proBNP to MRS improved the prognostic efficacy and may be considered effective tools to predict the risk of CA-AKI in clinical practice.

Elevated D-Dimer levels correlate with the development of hepatorenal syndrome and a poor outcome in patients with cirrhosis

OBJECTIVES

Whether hemostatic status was correlated with the diverse types of acute kidney injury in cirrhotic patients is unclear. The present study aimed to investigate the relationship between hemostatic markers and the diverse types of acute kidney injury (AKI) in liver cirrhosis.

PATIENTS AND METHODS

Cirrhotic patients with consecutive treatment at the First Affiliated Hospital of Medicine School, Zhejiang University, were pooled in a cohort. Their demographic and clinical data, biochemistry parameters and hemostatic markers were assessed to identify risk factors for the development and prognosis of AKI.

RESULTS

A total of 773 cirrhotic patients were included in this cohort. Patients with hepatorenal syndrome (HRS) had significantly higher D-Dimer than those with the other types of AKI. In univariate COX regression, APTT, TT, INR, D-Dimer and Fib were correlated with the development of AKI, HRS and acute tubular necrosis (ATN), however, only D-Dimer remained independently associated with the development of AKI and HRS in multivariate COX regression. The area under the ROC curve of D-Dimer was 0.755 (95%CI, 0.718-0.793) in predicting the development of AKI, 0.879 (95%CI, 0.791-0.967) in predicting the development of HRS, respectively. D-Dimer was used for diagnosis of HRS with a sensitivity of 87.3% and specificity of 72.9% at the cutoff of 3.7 (mg/L FEU). Survival rates differed significantly between groups by D-Dimer level.

CONCLUSIONS

Hemostatic markers were significantly associated with the diverse types of AKI. D-Dimer was an independent risk factor for HRS and correlated with a poor outcome in cirrhotic patients.

Fibrinogen-to-Albumin Ratio Predicts Postcontrast Acute Kidney Injury in Patients with Non-ST Elevation Acute Coronary Syndrome after Implantation of Drug-Eluting Stents

Background

Postcontrast acute kidney injury (PC-AKI) is an adverse reaction to iodinated contrast agents. In this study, we investigated the use of fibrinogen-to-albumin ratio (FAR) as a novel inflammatory marker to track the development and progression of PC-AKI in patients with non-ST elevation acute coronary syndrome (NSTE-ACS) after the implantation of drug-eluting stents (DESs).

Methods

A total of 872 patients with NSTE-ACS were enrolled in this study. PC-AKI was identified when serum creatinine (SCr) levels increased >26.5 mol/L (0.3 mg/dL) or was 1.5 times the baseline level within 48-72 h of exposure to an iodinated contrast agent. The effects of different variables on PC-AKI were evaluated using univariate regression analysis. Multivariate logistic regression analysis was used to determine the independent predictors of PC-AKI. The predictive value of FAR was assessed by estimating the area under the receiver operating characteristic (ROC) curve.

Results

In total, 114 (13.1%) patients developed PC-AKI. The patients with PC-AKI had lower albumin levels (40.5 ± 3.4 vs. 39.0 ± 3.5, P < 0.001), higher fibrinogen levels (3.7 ± 0.6 vs. 4.1 ± 0.5, P < 0.001), and higher FAR levels (9.2 ± 1.7 vs. 10.5 ± 1.7, P < 0.001) than those with non-PC-AKI. There were no significant differences in the preoperative SCr levels between the two groups. After adjusting for confounding factors, FAR was found to be an independent predictor of PC-AKI (OR = 1.478, 95% CI = 1.298-1.684, P < 0.001). ROC analysis revealed that for PC-AKI prediction, the area under the curve for FAR was 0.702. The optimum cut-off value of FAR was 10.0, with a sensitivity of 64.9% and a specificity of 69.8%. Moreover, FAR had a higher predictive value for PC-AKI than the Mehran score (0.702 vs. 0.645).

Conclusion

Our study showed that elevated preoperative FAR was closely associated with the development of PC-AKI in patients with NSTE-ACS after implantation of DESs. Therefore, it may be worth monitoring FAR as a guide for using preventive measures to avoid the development of PC-AKI.

Risk factors for acute renal injury caused by contrast media after percutaneous coronary intervention and coronary angiography: A protocol for systematic review and meta-analysis

BACKGROUND

Contrast-induced acute kidney injury (CI-AKI) caused by contrast medium is one of the common complications of percutaneous coronary intervention (PCI)/coronary angiography (CAG). Early identification of the risk factors of CI-AKI in patients with PCI/CAG and help clinical staff to prevent and intervene as soon as possible is very important to improve the clinical outcome of patients. Although domestic and foreign scholars have studied and summarized the risk factors of CI-AKI in PCI/CAG, the conclusions are not the same. Therefore, in this study, meta-analysis was used to summarize the risk factors of CI-AKI in patients with PCI/CAG, and to explore the characteristics of high-risk groups of CI-AKI, to provide reference for early identification and prevention of clinical doctors and nurses.

METHODS

We will search related literature of PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine Database, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Database. Eligible studies will be screened based on inclusion criteria, and data extraction, risk of bias assessment, publication bias assessment, subgroup analysis, and quality assessment will be performed. Review Manager version 5.3 software will be used for data analysis. Each process is independently conducted by 2 researchers, and if there is any objection, it will be submitted to the third researcher for resolution.

RESULTS

We will disseminate the findings of this systematic review and meta-analysis via publications in peer-reviewed journals.

CONCLUSIONS

The results of this analysis can be used to generate a risk prediction model and provide an intervention strategy for the occurrence of CI-AKI in PCI/CAG.

Predictive Role of the D-Dimer Level in Acute Kidney Injury in Living Donor Liver Transplantation: A Retrospective Observational Cohort Study

This study aimed to determine the association between serum D-dimer levels and the risk of acute kidney injury (AKI) in patients undergoing living donor liver transplantation (LDLT). Clinical data of 675 patients undergoing LDLT were retrospectively analyzed. The exclusion criteria included a history of kidney dysfunction, emergency cases, and missing data. The final study population of 617 patients was divided into the normal and high D-dimer groups (cutoff: 0.5 mg/L). After LDLT, 145 patients (23.5%) developed AKI. A high D-dimer level (>0.5 mg/L) was an independent predictor of postoperative development of AKI in the multivariate analysis when combined with diabetes mellitus [DM], platelet count, and hourly urine output. AKI was significantly higher in the high D-dimer group than in the normal D-dimer group (odds ratio [OR], 2.792; 95% confidence interval [CI], 1.227-6.353). Patients with a high D-dimer exhibited a higher incidence of early allograft dysfunction, longer intensive care unit stay, and a higher mortality rate. These results could improve the risk stratification of postoperative AKI development by encouraging the determination of preoperative D-dimer levels in patients undergoing LDLT.

D-dimer for risk stratification and antithrombotic treatment management in acute coronary syndrome patients: asystematic review and metanalysis

BACKGROUND

Data on the prognostic role of D-dimer in patients with acute coronary syndrome (ACS) are controversial. Our aim was to summarize current evidence on the association between D-dimer levels and short/long-term poor prognosis of ACS patients. We also investigated the association between D-dimer and no-reflow phenomenon.

METHODS

Systematic review and metanalysis of observational studies including ACS patients and reporting data on D-dimer levels. PubMed and SCOPUS databases were searched. Data were combined with hazard ratio (HR) and metanalysed. The principal endpoint was a composite of cardiovascular events (CVEs) including myocardial infarction, all-cause and cardiovascular mortality.

RESULTS

Overall, 32 studies included in the systematic review with 28,869 patients. Of them, 6 studies investigated in-hospital and 26 studies long-term outcomes. Overall, 23 studies showed positive association of high D-dimer levels with CVEs. D-dimer levels predicted poor prognosis in all studies reporting in-hospital outcomes. Five studies satisfied inclusion criteria and were included in the metanalysis, with a total of 8616 patients. Median follow-up was 13.2 months with 626 CVEs. The pooled HR for D-dimer levels and CVEs was 1.264 (95% CI 1.134-1.409). Five out of 7 studies (4195 STEMI patients) investigating the association between D-dimer levels and no-reflow showed a positive correlation of D-dimer levels with no-reflow.

CONCLUSIONS

In patients with ACS, D-dimer was associated with higher in-hospital and short/long-term complications. D-dimer was also higher in patients with no-reflow phenomenon. The use of D-dimer may help to identify patients with residual thrombotic risk after ACS.

TRIAL REGISTRATION

The review protocol was registered in PROSPERO International Prospective Register of Systematic Reviews: CRD42021267233 .

Analysis of the dynamic relationship between immune profiles and the clinical features of patients with COVID-19

Background

The novel coronavirus disease (COVID-19) has been declared a global pandemic, with the cumulative number of confirmed cases and deaths exceeding 150 million and 3 million, respectively. Here, we examined the dynamic changes in the immune and clinical features of patients with COVID-19.

Methods

Clinical data of 98 patients with confirmed COVID-19 diagnosis were acquired from electronic medical records and curated. The data were analyzed based on the stage of the admission, deterioration, and convalescence, which included age, sex, severity, disease stages, biochemical indicators, immune cells, inflammatory cytokines, and immunoglobulins. Additionally, temporal changes in the immune response in patients undergoing continuous renal replacement therapy (CRRT) were also examined.

Results

Compared to mild stage patients, severe stage patients with COVID-19 exhibited a significant reduction in lymphocyte [23.10 (17.58-33.55) vs. 4.80 (2.95-6.50), P<0.001], monocyte [8.65 (7.28-10.00) vs. 3.45 (2.53-4.58), P<0.001], and NK cell levels [244.00 (150.50-335.00) vs. 59.00 (40.00-101.00), P<0.001] but showed elevated levels of neutrophils [64.90 (56.30-73.70) vs. 90.95 (87.60-93.68), P<0.001], inflammatory cytokines [Interleukin-10, 3.05 (1.37-3.86) vs. 5.94 (3.84-8.35), P=0.001; and tumor necrosis factor-α, 11.50 (6.55-26.45) vs. 12.96 (12.22-36.80), P=0.029], which improved during convalescence. Besides, the number of immune cells-T lymphocytes, B lymphocytes, helper T cells, suppressor T cells, NK cells, and monocytes, except neutrophils-slowly increased in critically ill patients receiving CRRT from 0 to 3 weeks.

Conclusions

Our results indicate that the surveillance of immune cells may contribute to monitoring COVID-19 disease progression, and CRRT is a potential therapeutic strategy to regulate the immune balance in critically ill patients.

Machine Learning to Predict Contrast-Induced Acute Kidney Injury in Patients With Acute Myocardial Infarction

Objective: To develop predictive models for contrast induced acute kidney injury (CI-AKI) among acute myocardial infarction (AMI) patients treated invasively.

Methods: Patients with AMI who underwent angiography therapy were enrolled and randomly divided into training cohort (75%) and validation cohort (25%). Machine learning algorithms were used to construct predictive models for CI-AKI. The predictive models were tested in a validation cohort.

Results: A total of 1,495 patients with AMI were included. Of all the patients, 226 (15.1%) cases developed CI-AKI. In the validation cohort, Random Forest (RF) model with top 15 variables reached an area under the curve (AUC) of 0.82 (95% CI: 0.76–0.87), while the best logistic model had an AUC of 0.69 (95% CI: 0.62–0.76). ACEF (age, creatinine, and ejection fraction) model reached an AUC of 0.62 (95% CI: 0.53–0.71). RF model with top 15 variables achieved a high recall rate of 71.9% and an accuracy of 73.5% in the validation group. Random Forest model significantly outperformed logistic regression in every comparison.

Conclusions: Machine learning algorithms especially Random Forest algorithm improves the accuracy of risk stratifying patients with AMI and should be used to accurately identify the risk of CI-AKI in AMI patients.