Risk assessment of acute heart failure after endovascular therapy in acute ischemic stroke: a nomogram-based study

A prediction model for functional outcome following rescue therapy in patients with acute ischemic stroke undergoing endovascular treatment

Abstract Objective To evaluate the association between key preoperative and intraoperative factors and 90-day functional outcomes in acute ischemic stroke (AIS) patients undergoing endovascular treatment (EVT) with rescue therapy, and to establish a prognostic model for estimating 90-day functional outcomes. Methods We retrospectively enrolled AIS patients with EVT plus rescue therapy from January 2018 to December 2024. The primary endpoint was a 90-day modified Rankin Scale (mRS) score >2. Logistic regression identified predictors incorporated into a nomogram. Model performance was assessed with receiver operating characteristic (ROC) curves, the Hosmer–Lemeshow test, and decision curve analysis (DCA). Bootstrap resampling and 10-fold cross-validation assessed robustness. Results In total, 445 individuals were analyzed (training: 312; validation: 133). Multivariable analysis identified glycated hemoglobin (HbA1c; OR = 1.345, 95% CI: 1.145–1.608, p < 0.001), baseline National Institutes of Health Stroke Scale (NIHSS) score (OR = 1.084, 95% CI: 1.047–1.127, p < 0.001), onset-to-puncture time (OPT; OR = 1.000, 95% CI: 1.000–1.000, p = 0.003), and puncture-to-reperfusion time (PRT; OR = 1.008, 95% CI: 1.001–1.015, p = 0.026) as independent predictors. The value of the area under the ROC curve (AUC) was 0.741 in the training cohort and 0.781 in the validation cohort. Calibration was adequate (Hosmer–Lemeshow p > 0.05 in both cohorts), and DCA demonstrated consistent clinical benefit. Bootstrap and cross-validation confirmed model reliability. Conclusion Our model integrating HbA1c, NIHSS, OPT, PRT, and refractory thrombectomy demonstrated acceptable performance in predicting 90-day outcomes after rescue therapy. However, as a development-phase model, its clinical applicability should be interpreted with caution.

Analysis of the Incidence, Risk Factors, and Prognosis of Early Acute Heart Failure After TEVAR for Complex Acute Type B Aortic Dissection

Background:Complex acute type B aortic dissection (ATBAD) is an aortic emergency associated with high mortality. Thoracic endovascular aortic repair (TEVAR) has become the treatment of choice for complex ATBAD. However, early acute heart failure (AHF) after TEVAR can significantly increase perioperative mortality risk, and systematic studies on its incidence, multidimensional risk factors, and independent impact on mid- and long-term prognosis remain insufficient.Methods:A total of 225 patients with complex ATBAD who underwent TEVAR at our hospital from January 2021 to January 2025 were prospectively enrolled. Patients were divided into an AHF group (n = 34) and a non-AHF group (n = 191) according to whether AHF occurred within 30 days postoperatively. Baseline data, imaging characteristics, laboratory parameters, and perioperative data were collected. Univariable and multivariable binary logistic regression analyses were used to identify independent risk factors for AHF. Receiver operating characteristic (ROC) curves were plotted to evaluate predictive performance, and internal validation was conducted using Bootstrap resampling (B = 1000); Kaplan-Meier analysis and Cox proportional hazards regression (Fine-Gray competing risks model) were used to assess the impact of AHF on 1-year all-cause mortality.Results:Among 225 patients, the incidence of AHF within 30 days after TEVAR was 15.1% (34/225). Multivariable logistic regression identified four independent risk factors: preoperative B-type natriuretic peptide (BNP) ≥100 pg/mL (odds ratio [OR] = 7.84, 95% confidence interval [CI] 3.12–19.68), concomitant coronary artery disease (CAD) (OR = 3.10, 95% CI 1.05–9.13), admission heart rate per 10 beats/min increase (OR = 1.72, 95% CI 1.28–2.31), and stent coverage length per 10 mm increase (OR = 1.14, 95% CI 1.04–1.25) (all p < 0.05). The combined prediction model constructed from these four factors achieved an area under the curve (AUC) of 0.897 (95% CI 0.842–0.952); Bootstrap-corrected AUC was 0.868 (95% CI 0.801–0.935); the AUC for preoperative BNP alone was 0.842 (optimal cutoff 98.5 pg/mL). The AHF group had significantly higher 30-day all-cause mortality (17.6% vs 2.6%, p = 0.002) and 30-day major adverse cardiac and cerebrovascular events (MACCE) rate (35.3% vs 9.4%, p < 0.001) than the non-AHF group. Kaplan-Meier analysis showed a lower 1-year cumulative survival rate in the AHF group (73.5%) compared with the non-AHF group (93.7%, Log-rank p < 0.001). After adjusting for confounders, AHF remained an independent risk factor for 1-year all-cause mortality (hazard ratio [HR] = 4.32, 95% CI 1.86–10.04, p = 0.001).Conclusions:The incidence of early AHF after TEVAR in complex ATBAD patients is 15.1%. Preoperative BNP ≥100 pg/mL, concomitant CAD, elevated admission heart rate, and longer stent coverage length are independent risk factors. AHF independently increases perioperative and 1-year all-cause mortality risk.

Development and validation of the FLATS score to predict periprocedural ischemic events after stent-assisted coiling for ruptured intracranial aneurysms in the acute phase: a nationwide chinese registry

Predicting stroke-associated pneumonia for acute ischemic stroke patients post intravenous thrombolysis: the post-IVT-SAP risk score

Few prediction tools have been developed specifically for stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT). This study aimed to develop and externally evaluate a simple risk score for SAP after IVT. This multicenter retrospective study included 836 patients with AIS treated with IVT at three hospitals. Patients from two hospitals formed the training cohort, and those from the third hospital formed the external validation cohort. Univariable and multivariable logistic regression analyses were performed to identify independent predictors and develop a simple risk prediction score. Model discrimination was evaluated using receiver operating characteristic curve analysis. Among 836 patients, 145 (17.3%) developed SAP. Age >75 years, atrial fibrillation, a higher pre-thrombolysis National Institutes of Health Stroke Scale score, and a lower pre-thrombolysis Alberta Stroke Program Early CT Score were independently associated with SAP and incorporated into the PISRS. The PISRS yielded an area under the curve of 0.718 in the training cohort and 0.801 (95% CI, 0.684–0.919) in the external validation cohort. Each 1-point increase in the PISRS was associated with increased odds of SAP within 7 days (OR = 2.623; 95% CI, 2.143–3.212). The PISRS is a simple admission-based score that may facilitate early risk stratification for SAP in patients with AIS undergoing IVT. Further prospective validation in larger and more diverse cohorts is required.

Development and Evaluation of a Clinical Prediction Model for Acute Kidney Injury Risk in Elderly Patients with Heart Failure with Reduced Ejection Fraction

Background: Acute kidney injury (AKI) is a significant complication among patients with heart failure with reduced ejection fraction (HFrEF). Once AKI occurs, therapeutic options are limited to supportive care, underscoring the clinical importance of early identification of patients at risk. This study sought to identify independent predictors of AKI development in geriatric HFrEF patients and subsequently establish a clinically applicable bedside risk quantification. Method: A total of 1,496 elderly patients (≥60 years) diagnosed with HFrEF at Guangdong Provincial People’s Hospital from January 2010 to December 2024 were enrolled according to predefined inclusion/exclusion criteria and stratified into an AKI group (n = 300) and a non-AKI group (n = 1196). Relevant parameters were screened using LASSO (Least Absolute Shrinkage and Selection Operator) regression, and risk factors for AKI in HFrEF patients were identified through univariate and multivariate logistic regression analyses. A nomogram was developed based on multivariate logistic regression results, accompanied by a corresponding heatmap. The predictive accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves and calibration plots, while its clinical utility was demonstrated through decision curve analysis (DCA). Result: This study identified four independent predictors of AKI in patients with HFrEF, including N-terminal pro-B-type natriuretic peptide (NT-proBNP), uric acid (UA), CRP (C-reaction protein) and urea. A nomogram was developed based on these factors. The evaluation results demonstrated that the model exhibited good diagnostic accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.721 (95% CI: 0.658–0.785). The calibration curve and DCA further indicated that the model possesses favorable clinical applicability. Conclusion: This study developed and validated a nomogram model for predicting AKI in patients with HFrEF. Clinicians can utilize this model to optimize clinical decision-making based on individualized patient characteristics, enabling personalized risk stratification for therapeutic interventions and prognostic evaluations.

Validated 1-Year Mortality Prediction in Patients with Three-Vessel Disease Undergoing Contemporary PCI: Insights from the Multivessel TALENT trial.

BACKGROUND Accurate risk stratification for patients with three-vessel coronary artery disease (3VD) undergoing percutaneous coronary intervention (PCI) remains important in contemporary practice. SYNTAX-based mortality prediction models require reassessment in modern PCI populations. METHODS This post-hoc analysis of the Multivessel TALENT trial evaluated the core and extended logistic clinical SYNTAX Score (LCSS) for predicting 1-year all-cause mortality. Discrimination was assessed using the area under the receiver-operating characteristic curve (AUC), and calibration using calibration intercept, calibration slope, graphical calibration, and the E-statistic. Prediction scores were calculated within each of 20 imputed datasets, with model performance evaluated within each imputation and summarised across imputations. Intercept-and-slope recalibration and decision curve analysis were also performed. RESULTS At 1 year, 46 (3.0%) of 1,548 enrolled patients had died. The pooled AUCs were 0.716 for the LCSS core model and 0.744 for the extended model, compared with 0.629 for the anatomical SYNTAX Score and 0.632 for the functional SYNTAX Score. LCSS models systematically overestimated absolute risk, although observed mortality increased across predicted-risk quintiles. Decision curve analysis showed a positive net benefit for the original and recalibrated LCSS models across threshold probabilities of 1% to 10%, with numerically higher net benefit for the recalibrated extended model across much of the evaluated threshold range. CONCLUSION In contemporary PCI for 3VD, the LCSS showed moderate discrimination for 1-year all-cause mortality while overestimating its absolute risk. Recalibration improved agreement with observed risk in this cohort and may inform future validation and model refinement.