A risk score model to predict in-hospital mortality of patients with end-stage renal disease and acute myocardial infarction

Fu, Yuan; Sun, Hao; Guo, Zongsheng; Xu, Li; Yang, Xinchun; Wang, Lefeng; Li, Kuibao; Chen, Mulei; Gao, Yuanfeng

doi:10.1007/s11739-020-02529-3

Cited by 5 publications

(6 citation statements)

References 32 publications

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“…Ethnicity and age are known as root variables as they have no parents. A few studies among the Japanese population state that renal disease and Killip class appear to be related, where acute renal diseases are associated with older age and Killip class II and higher 30–32. This trend is similarly observed in Malaysian STEMI male patients in this study.…”

Section: Discussionsupporting

confidence: 81%

Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis

Juhan,

Zubairi,

Mahmood Zuhdi

et al. 2023

BMJ Open

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ObjectivesDespite extensive advances in medical and surgical treatment, cardiovascular disease (CVD) remains the leading cause of mortality worldwide. Identifying the significant predictors will help clinicians with the prognosis of the disease and patient management. This study aims to identify and interpret the dependence structure between the predictors and health outcomes of ST-elevation myocardial infarction (STEMI) male patients in Malaysian setting.DesignRetrospective study.SettingMalaysian National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry years 2006–2013, which consists of 18 hospitals across the country.Participants7180 male patients diagnosed with STEMI from the NCVD-ACS registry.Primary and secondary outcome measuresA graphical model based on the Bayesian network (BN) approach has been considered. A bootstrap resampling approach was integrated into the structural learning algorithm to estimate probabilistic relations between the studied features that have the strongest influence and support.ResultsThe relationships between 16 features in the domain of CVD were visualised. From the bootstrap resampling approach, out of 250, only 25 arcs are significant (strength value ≥0.85 and the direction value ≥0.50). Age group, Killip class and renal disease were classified as the key predictors in the BN model for male patients as they were the most influential variables directly connected to the outcome, which is the patient status. Widespread probabilistic associations between the key predictors and the remaining variables were observed in the network structure. High likelihood values are observed for patient status variable stated alive (93.8%), Killip class I on presentation (66.8%), patient younger than 65 (81.1%), smoker patient (77.2%) and ethnic Malay (59.2%). The BN model has been shown to have good predictive performance.ConclusionsThe data visualisation analysis can be a powerful tool to understand the relationships between the CVD prognostic variables and can be useful to clinicians.

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Section: Discussionsupporting

confidence: 81%

Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis

Juhan,

Zubairi,

Mahmood Zuhdi

et al. 2023

BMJ Open

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“…Indeed, the addition of D-dimer has been investigated to some biomarkers such as C-reactive protein (CRP), NT-proBNP and clinical scores, such as the Global Registry of Acute Coronary Events (GRACE) risk score has been investigated. Fu et al included D-dimer levels ≥2.4 mg/L FEU in a risk score model together with CRP, left ventricular ejection fraction, age ≥ 65 years old and heart rate [ 32 ]. In ROC curve analysis, this model demonstrated a good power in predicting in-hospital mortality (AUC = 0.895, 95% CI 0.814–0.96; p < 0.001), better than the predictive power of the GRACE risk score alone (AUC = 0.754, 95% CI 0.641–0.868; p < 0.001).…”

Section: Discussionmentioning

confidence: 99%

“… Tello-Montoliu 2007 [ 31 ] NSTEMI 358 67.4 35.8 R 6 Death, new ACS, revascularization, and HF Overall D-dimer level: 340 (211–615) ng/mL Admission D-dimer levels did not predict events [HR: 1.26 (0.79–2.02), p = 0.337). AMI Fu 2020 [ 32 ] AMI with ESRD 113 69.2 33.6 R In-hospital Mortality Mortality: 3.2 mg/L Survival: 1.1 mg/L p = 0.023 D-dimer ≥2.4 mg/L predicted in-hospital mortality (OR 2.771 [95% CI, 1.017–8.947], p < 0.001). Wang 2020 [ 33 ] AMI 197 Male 61.8 Female 74.2 20 P 6 All-cause mortality (in- and out-of-hospital deaths) or readmission.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2021

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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.

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“…ROC curve analyses were performed, and the AUC of plasma Phe and PAGln levels in predicting ISR was 0.732 (95% CI, 0.606–0.858; P = 0.002) ( Figure 3 ) and 0.861 (95% CI, 0.766–0.957; P < 0.001) ( Figure 4 ), respectively. The maximum value of the Youden index was a criterion for best cutoff value selection ( 23 ), and the best cutoff values of Phe and PAGln for predicting ISR were 1,370.48 μg/mL (sensitivity: 75%, specificity: 66.7%) and 423.63 ng/mL (sensitivity: 96.4%, specificity: 72.7%), respectively. Both Phe and PAGln had good discriminatory power in predicting ISR, and after the Z-test, the predictive value of PAGln was significantly better ( P = 0.031) ( Figure 5 ).…”

Section: Resultsmentioning

confidence: 99%

Prognostic value of plasma phenylalanine and gut microbiota-derived metabolite phenylacetylglutamine in coronary in-stent restenosis

Yang

Chen

et al. 2022

Front. Cardiovasc. Med.

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ObjectiveThis study was designed to explore the predictive value of plasma phenylalanine (Phe) and gut microbiota-derived metabolite phenylacetylglutamine (PAGln) in coronary in-stent restenosis (ISR).MethodsPatients with coronary ISR, in-stent hyperplasia (ISH), and in-stent patency (ISP) were retrospectively enrolled in this study. Multivariable logistic regression analyses were used to identify independent risk factors of ISR. The predictive value of plasma Phe and PAGln levels was evaluated by receiver operating characteristic (ROC) curve analysis. The areas under the ROC curve (AUCs) were compared using the Z-test. The correlation between PAGln and clinical characteristics were examined using Spearman's correlation analysis.ResultsSeventy-two patients (mean age, 64.74 ± 9.47 years) were divided into three groups according to coronary stent patency: ISR (n = 28), ISH (n = 11), and ISP (n = 33) groups. The plasma levels of Phe and PAGln were significantly higher in the ISR group than in the ISP group. PAGln was positively associated with the erythrocyte sedimentation rate, homocysteine, SYNTAX score, triglyceride to high-density lipoprotein ratio, Phe, and microbiota-related intermediate metabolite phenylacetic acid (PA). In the ISR group, with the aggravation of restenosis, PAGln levels were also elevated. In multivariate regression analyses, Phe, PAGln and SYNTAX score were independent predictors of coronary ISR (all P < 0.05). In the ROC curve analyses, both Phe [AUC = 0.732; 95% confidence interval (CI), 0.606–0.858; P = 0.002] and PAGln (AUC = 0.861; 95% CI, 0.766–0.957; P < 0.001) had good discrimination performance in predicting coronary ISR, and the predictive power of PAGln was significantly better (P = 0.031).ConclusionPlasma Phe and PAGln are valuable indices for predicting coronary ISR, and gut microbes may be a promising intervention target to prevent ISR progression.

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A risk score model to predict in-hospital mortality of patients with end-stage renal disease and acute myocardial infarction

Cited by 5 publications

References 32 publications

Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis

Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis

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

Prognostic value of plasma phenylalanine and gut microbiota-derived metabolite phenylacetylglutamine in coronary in-stent restenosis

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