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Although anti-cancer therapy-induced cardiotoxicity is known, until now it lacks a reliable risk predictive model of the subsequent cardiotoxicity in breast cancer patients receiving anthracycline therapy. An artificial intelligence (AI) with a machine learning approach has yet to be applied in cardio-oncology. Herein, we aimed to establish a predictive model for differentiating patients at a high risk of developing cardiotoxicity, including cancer therapy-related cardiac dysfunction (CTRCD) and symptomatic heart failure with reduced ejection fraction. This prospective single-center study enrolled patients with newly diagnosed breast cancer who were preparing for anthracycline therapy from 2014 to 2018. We randomized the patients into a 70%/30% split group for ML model training and testing. We used 15 variables, including clinical, chemotherapy, and echocardiographic parameters, to construct a random forest model to predict CTRCD and heart failure with a reduced ejection fraction (HFrEF) during the 3-year follow-up period (median, 30 months). Comparisons of the predictive accuracies among the random forest, logistic regression, support-vector clustering (SVC), LightGBM, K-nearest neighbor (KNN), and multilayer perceptron (MLP) models were also performed. Notably, predicting CTRCD using the MLP model showed the best accuracy compared with the logistic regression, random forest, SVC, LightGBM, and KNN models. The areas under the curves (AUC) of MLP achieved 0.66 with the sensitivity and specificity as 0.86 and 0.53, respectively. Notably, among the features, the use of trastuzumab, hypertension, and anthracycline dose were the major determinants for the development of CTRCD in the logistic regression. Similarly, MLP, logistic regression, and SVM also showed higher AUCs for predicting the development of HFrEF. We also validated the AI prediction model with an additional set of patients developing HFrEF, and MLP presented an AUC of 0.81. Collectively, an AI prediction model is promising for facilitating physicians to predict CTRCD and HFrEF in breast cancer patients receiving anthracycline therapy. Further studies are warranted to evaluate its impact in clinical practice.

Background Triglyceride glucose (TyG) index is considered a reliable alternative marker of insulin resistance and an independent predictor of cardiovascular (CV) outcomes. However, the prognostic value of TyG index in patients with type 2 diabetes mellitus (T 2 DM) and acute myocardial infarction (AMI) remains unclear. Methods A total of 1932 consecutive patients with T 2 DM and AMI were enrolled in this study. Patients were divided into tertiles according to their TyG index levels. The incidence of major adverse cardiac and cerebral events (MACCEs) was recorded. The TyG index was calculated as the ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2]. Results Competing risk regression revealed that the TyG index was positively associated with CV death [2.71(1.92 to 3.83), p  < 0.001], non-fatal MI [2.02(1.32 to 3.11), p  = 0.001], cardiac rehospitalization [2.42(1.81 to 3.24), p  < 0.001], revascularization [2.41(1.63 to 3.55), p  < 0.001] and composite MACCEs [2.32(1.92 to 2.80), p  < 0.001]. The area under ROC curve of the TyG index for predicting the occurrence of MACCEs was 0.604 [(0.578 to 0.630), p  < 0.001], with the cut-off value of 9.30. The addition of TyG index to a baseline risk model had an incremental effect on the predictive value for MACCEs [net reclassification improvement (NRI): 0.190 (0.094 to 0.337); integrated discrimination improvement (IDI): 0.027 (0.013 to 0.041); C-index: 0.685 (0.663 to 0.707), all p  < 0.001]. Conclusions The TyG index was significantly associated with MACCEs, suggesting that the TyG index may be a valid marker for risk stratification and prognosis in patients with T 2 DM and AMI. Trial registration Retrospectively registered.

Background Dyslipidemia is prominently associated with adverse outcomes in patients with coronary artery disease (CAD). The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a novel comprehensive lipid index. However, limited evidence exists on the relationship of the NHHR with the risk of adverse outcomes in patients with CAD. This study aimed to explore the associations between the NHHR and adverse outcomes and identify the optimal NHHR ranges linked to the lowest adverse outcome risk in patients with CAD undergoing percutaneous coronary intervention (PCI). Methods Among 2253 patients with CAD undergoing PCI, 2251 with available total cholesterol and HDL-C levels were analyzed. Furthermore, all patients were classified into quintiles based on the NHHR. The primary outcome was the incidence of MACCEs, comprising cardiac mortality, acute myocardial infarction, stroke, and repeat revascularization. Multivariable logistic regression analysis was used to assess the relationship between the NHHR and MACCEs. Moreover, restricted cubic spline (RCS) analysis was performed to quantify nonlinearity. Lastly, the consistency between these associations was confirmed by conducting subgroup and interaction analyses. Results A total of 270 patients experienced MACCEs over a median follow-up of 29.8 months (interquartile range, 25.6–34 months). After adjustment for confounding variables, the adjusted ORs (95% CIs) of the patients in quintiles 2, 3, 4, and 5 were 0.79 (0.52–1.20), 0.64 (0.42–0.99), 1.00 (0.67–1.48), and 1.17 (0.74–1.64), respectively (reference group: quintile 1). Additionally, RCS analysis demonstrated a U-shaped relationship between the NHHR and MACCEs, with an inflection point at an NHHR of 3.119 using a two-piecewise regression model. This relationship was consistent across the various subgroups, while significant interactions were not observed in these associations.The ORs and 95% CIs to the left and right of the inflection point were 0.734 (0.551–0.978) and 1.231 (1.038–1.460), respectively. Conclusions This study reveals a U-shaped association between baseline NHHR and MACCE incidence in patients with CAD undergoing PCI.

The Aggregate Index of Systemic Inflammation (AISI) has emerged as a novel marker for inflammation and prognosis, but its role in patients with acute myocardial infarction has not been studied. Therefore, this study aimed to investigate the impact of different AISI levels on the clinical outcomes of patients with acute myocardial infarction. This study was a retrospective study, including 1044 patients with acute myocardial infarction (AMI) who were treated at the Fujian Medical University Affiliated Union Hospital, China from May 2017 to December 2022. The patients were divided into high and low AISI groups based on the median value (Q1 Group, ≤ 416.15, n=522; Q2 Group, ≥ 416.16, n=522), and the differences in baseline characteristics and clinical outcomes between the two groups were analyzed. The primary outcome included major adverse cardiovascular and cerebrovascular events (MACCEs), while the secondary outcomes included contrast-induced nephropathy (CIN) risk and all-cause rehospitalization rate. The findings of the single-factor analysis suggest that a significant association between high AISI levels and the occurrence of MACCEs in AMI patients. After adjusting for confounding factors, the results indicated that compared to Q1, patients in the Q2 group had a higher risk of all-cause mortality [adjusted odds ratio (aOR) 4.64; 95% CI 1.37-15.72; =0.032], new-onset atrial fibrillation (aOR 1.75; 95% CI 1.02-3.00; =0.047), and CIN (aOR 1.75; 95% CI 1.02-3.01; =0.043), with all differences being statistically significant. In the population of AMI patients, an elevated AISI level is significantly associated with an increased risk of cardiovascular death and can serve as an early marker for adverse prognosis.

Background: Assessment of risk factors is essential for clinical diagnosis and prevention in patients with both diabetes mellitus (DM) and coronary heart disease (CHD). In the present study we investigated correlation of the Gensini score with the incidence of major adverse cardiac and cerebrovascular events (MACCEs) in patients with DM and CHD. Methods: A total of 802 DM patients with CHD admitted to the First Affiliated Hospital of Zhengzhou University and who met the inclusion criteria were enrolled in the study. The median follow-up time for these patients was 3000 days (range 382.5–3000). Receiver operating characteristic (ROC) curves for the Gensini score were generated and the area under the curve (AUC) was calculated. Patients were divided into two groups based on the Gensini score cut-off value. Univariate and multivariate Cox proportional hazard regression analysis was used to identify the risk factors associated with MACCEs. The incidence of MACCEs in the two groups was compared using Kaplan-Meier analysis. Results: The AUC of the ROC curve was 0.675. The maximum Youden’s index was 0.248 at a Gensini score cut-off value of 74.8605. This gave a sensitivity and specificity for the prediction of MACCE of 68.8% and 56%, respectively. A high Gensini score was a risk factor for MACCEs, and the incidence of MACCEs was significantly greater in the high Gensini score group compared to the low Gensini score group. Conclusions: A high Gensini score is a risk factor for patients with DM and CHD and is associated with a high incidence of MACCEs. Clinical Trial Registration: The details of study design are registered on http://www.chictr.org.cn (identifier: ChiCTR-2200055450).

Patients in the intensive care unit (ICU) commonly receive stress ulcer prophylaxis drugs, either proton pump inhibitors (PPIs) or histamine-2 receptor blockers (H2RBs). The goal of this research was to evaluate the impact of these drugs on mortality among ICU patients hospitalized for major adverse cardiovascular and cerebrovascular events (MACCEs). ICU patients hospitalized for MACCEs were sourced from the Medical Information Mart for Intensive Care-III database. We performed a propensity score matching analysis to match patients treated with PPIs to those treated with H2RBs for stress ulcer prophylaxis. The outcome was 90-day mortality. We used multivariable Cox regression analyses to compare the effect. Hazard ratio (HR), 95% CIs, and P values were reported from the model. From 2001 to 2012, a total of 3577 patients hospitalized for MACCEs (1997 received PPIs and 1580 received H2RBs) were admitted. The 90-day mortality was 23.7% (848/3577); it was 27% (540/1997) and 19.5% (308/1580) for PPIs and H2RBs users, respectively. The PPI group exhibited a greater 90‑day mortality in comparison to the H2RBs group (relative risk = 1.17; P = 0.036), after conditioning on potential confounder. The results remained robust in propensity score matching, sensitivity analyses, and subgroup analyses. PPIs for stress ulcer prophylaxis were linked to an increased risk of in-hospital mortality than H2RBs in patients hospitalized for MACCEs. Further investigation of this association and validation of its clinical significance is needed.

Background Current guidelines recommend angiotensin-converting-enzyme inhibitors (ACEI)/angiotensin receptor blockers (ARB) as a first-line therapy in diabetic hypertensive patients and for secondary prevention in patients with obstructive coronary artery disease (OCAD). However, the effects of using ACEI/ARB before the initial diagnosis of OCAD on major adverse cardiac and cerebral event (MACCE) in diabetic hypertensive patients remain unclear. This study investigated whether using ACEI/ARB before the initial diagnosis of OCAD could be associated with improved clinical outcomes in diabetic hypertensive patients. Methods A total of 2501 patients with hypertension and diabetes, who were first diagnosed with OCAD by coronary angiography, were included in the analysis. Of the 2501 patients, 1300 did not used ACEI/ARB before the initial diagnosis of OCAD [the ACEI/ARB(-) group]; 1201 did [the ACEI/ARB(+) group]. Propensity score matching at 1:1 was performed to select 1050 patients from each group. Incidence of acute myocardial infarction (AMI), infarct size in patients with AMI, heart function, and subsequent MACCE during a median of 25.4-month follow-up were determined and compared between the 2 groups. Results Compared with the ACEI/ARB(-) group, the ACEI/ARB(+) group had significantly lower incidence of AMI (22.5% vs. 28.4%, p < 0.05), smaller infarct size in patients with AMI (pTNI: 5.7 vs. 6.8 ng/ml, p < 0.05; pCKMB: 21.7 vs. 28.7 ng/ml, p < 0.05), better heart function (LVEF: 60.0 vs. 58.5%, p < 0.05), and lower incidences of non-fatal stroke (2.4% vs. 4.6%, p < 0.05) and composite MACCE (23.1% vs. 29.7%, p < 0.05). No prior ACEI/ARB therapy was significantly and independently associated with non-fatal stroke and composite MACCE. Conclusions In diabetic hypertensive patients, treatment with ACEI/ARB before the initial diagnosis with OCAD was associated with decreased incidence of AMI, smaller infarct size, improved heart function, and lower incidences of non-fatal stroke and composite MACCE. Trial registration Retrospectively registered

IntroductionConventional risk prediction models for Major Adverse Cardio/Cerebrovascular Events (MACCE) primarily rely on non-modifiable factors such as age, sex, and physiological measurements, including LDL/HDL cholesterol and blood pressure readings, that are prone to variations across medical practices and are often unavailable in many parts of the world. In this study, we investigate the potential of inexpensive wearable measurements of physical activity to enhance MACCE prediction when physiological measurements are unavailable.MethodsWe obtained accelerometer-measured physical activity over 7 days between 2013 and 2015 from 69,898 UK Biobank (UKB) participants without a prior history of MACCE, defined as death or hospitalisation due to (1) myocardial infarction, (2) heart failure, or (3) Stroke/transient ischaemic attack. We assessed the added value of daily step counts, sleep duration, and a deep learning-derived activity health score (Fig 1), calculated from complete 7-day accelerometer recordings, to established clinical risk models (SCORE2, QRISK3 and AHA) before and after excluding measurements of cholesterol and systolic blood pressure (SBP). The primary outcome was the first recorded MACCE within 6 years. Risk scores were developed in men and women using Cox proportional hazards models. We assessed predictive performance using Harrel’s C-index, net reclassification index (NRI), and net benefit at the recommended treatment threshold for each model.ResultsOf the 69,898 UKB participants in the study, 3,386 (4.8%) experienced a MACCE over a 6-year follow-up period. In place of HDL ratio and SBP, the addition of deep-learned activity health scores modestly improved performance in the best clinical baseline, QRISK3 for Female participants ΔC-index women:0.003 (95% CI 0.002–0.004); Δnet benefit 0.02(0.01–0.03); NRI 0.04, (0.02–0.07), and outperformed manually extracted steps and sleep measurements. We report no significant improvements for men. We find a greater increase in model performance when both HDL ratio and SBP, plus activity health scores, are included in the model. ΔC-index women:0.008, (0.007–0.009); men: 0.003 (0.002–0.004) (Fig 2).ConclusionOur findings indicate that in the absence of cholesterol and systolic blood pressure, the addition of device-measured physical activity modestly improves the performance of clinical risk scores among individuals without prior cardiovascular disease (CVD). These findings could further refine intervention strategies for targeted prevention of CVD, particularly in settings where physiological measurements may be unavailable.Abstract 36 Figure 1Derivation of deep learning activity risk scores from 7-days of raw accelerometer recording in a free-living environmentAbstract 36 Figure 2Added value of deep learned Activity risk scores (ARS) to QRISK3, excluding and including HDL Cholesterol and systolic blood pressure, measured by the change in C-indexConflict of InterestNA

Background The C‑reactive protein–triglyceride glucose index (CTI), a composite marker of systemic inflammation and metabolic status, has been associated with cardiovascular and cerebrovascular risk. Its role in central retinal artery occlusion (CRAO) and subsequent adverse outcomes is unclear. Methods In this cohort study, 122 CRAO patients and 488 matched controls who underwent coronary angiography without coronary artery disease were analyzed. CTI was calculated as 0.412 × ln [CRP (mg/L) + 0.5 × ln [TG × FPG(mg/dL)]. Logistic regression adjusted for demographic, clinical, laboratory, and medication variables was used to explore the relationship between CTI and the risk of CRAO. Restricted cubic spline models assessed the dose–response relationship between CTI and CRAO risk. The primary endpoint was CRAO and the secondary endpoint was major adverse cardiovascular and cerebrovascular events (MACCEs) during the 36‑month follow‑up. Results Higher CTI was independently associated with CRAO (adjusted OR = 1.46, 95% CI 1.14–1.88; P  = 0.003). Restricted cubic spline analysis identified a CTI threshold of 9.810. CRAO patients with CTI > 9.810 had a higher incidence of MACCEs (31.1% vs. 10.1%, P  < 0.001), particularly acute coronary syndromes (20.3% vs. 7.1%, P  < 0.001). In subgroup analysis, CRAO patients with CTI > 9.810 had the highest MACCEs rate (40.0%) and significantly greater risk of all‑cause death, stroke, and acute coronary syndromes (all adjusted P  < 0.05) compared with other groups. Time‑to‑event analysis revealed that among all groups, CRAO patients with CTI > 9.810 had the shortest median time to MACCEs occurrence at 6 months (IQR,  4–11). Conclusions Elevated CTI is independently associated with increased CRAO risk and predicts higher adverse MACCEs outcomes, suggesting CTI as a potential biomarker for risk stratification and secondary prevention in CRAO patients. Highlights/Importance Higher CTI was independently associated with an increased risk of CRAO, with restricted cubic spline analysis identifying a threshold of 9.810 for elevated risk. Patients with elevated CTI presented a higher incidence and earlier onset of MACCEs, particularly acute coronary syndromes, stroke, and all‑cause death. These findings suggest that CTI may serve as a practical biomarker for risk stratification and to guide early preventive strategies in CRAO patients, potentially reducing subsequent cardiovascular and cerebrovascular complications.

Background The postoperative period is critical for a patient’s recovery, and postoperative hypotension, specifically, is associated with adverse clinical outcomes and significant harm to the patient. However, little is known about the association between postoperative hypotension in patients in the intensive care unit (ICU) after non-cardiac surgery, and morbidity and mortality, specifically among patients who did not experience intraoperative hypotension. The goal of this study was to assess the impact of postoperative hypotension at various absolute hemodynamic thresholds (≤ 75, ≤ 65 and ≤ 55 mmHg), in the absence of intraoperative hypotension (≤ 65 mmHg), on outcomes among patients in the ICU following non-cardiac surgery. Methods This multi-center retrospective cohort study included specific patient procedures from Optum® healthcare database for patients without intraoperative hypotension (MAP ≤ 65 mmHg) discharged to the ICU for ≥ 48 h after non-cardiac surgery with valid mean arterial pressure (MAP) readings. A total of 3185 procedures were included in the final cohort, and the association between postoperative hypotension and the primary outcome, 30-day major adverse cardiac or cerebrovascular events, was assessed. Secondary outcomes examined included all-cause 30- and 90-day mortality, 30-day acute myocardial infarction, 30-day acute ischemic stroke, 7-day acute kidney injury stage II/III and 7-day continuous renal replacement therapy/dialysis. Results Postoperative hypotension in the ICU was associated with an increased risk of 30-day major adverse cardiac or cerebrovascular events at MAP ≤ 65 mmHg (hazard ratio [HR] 1.52; 98.4% confidence interval [CI] 1.17–1.96) and ≤ 55 mmHg (HR 2.02, 98.4% CI 1.50–2.72). Mean arterial pressures of ≤ 65 mmHg and ≤ 55 mmHg were also associated with higher 30-day mortality (MAP ≤ 65 mmHg, [HR 1.56, 98.4% CI 1.22–2.00]; MAP ≤ 55 mmHg, [HR 1.97, 98.4% CI 1.48–2.60]) and 90-day mortality (MAP ≤ 65 mmHg, [HR 1.49, 98.4% CI 1.20–1.87]; MAP ≤ 55 mmHg, [HR 1.78, 98.4% CI 1.38–2.31]). Furthermore, we found an association between postoperative hypotension with MAP ≤ 55 mmHg and acute kidney injury stage II/III (HR 1.68, 98.4% CI 1.02–2.77). No associations were seen between postoperative hypotension and 30-day readmissions, 30-day acute myocardial infarction, 30-day acute ischemic stroke and 7-day continuous renal replacement therapy/dialysis for any MAP threshold. Conclusions Postoperative hypotension in critical care patients with MAP ≤ 65 mmHg is associated with adverse events even without experiencing intraoperative hypotension.