Effect of orthostatic hypotension on long-term prognosis of elderly patients with stable coronary artery disease: a retrospective cohort study.

Background: The long-term prognosis of patients with stable coronary artery disease (CAD) combined with orthostatic hypotension (OH) has rarely been reported. This research was designed to examine whether OH increases the risk of all-cause mortality and cardiovascular death among patients with stable CAD. Methods: We retrospectively analyzed retired military personnel over 65 years of age who were hospitalized at the General Hospital of Southern Theater Command of the Chinese People's Liberation Army between March and July 2010. A total of 924 patients with stable CAD were included, among whom 263 had OH. The risk of all-cause mortality and cardiovascular death in OH and non-OH groups were analyzed with the Cox proportional hazards models, and restricted cubic spline plots were utilized for subgroup analyses. Furthermore, competing risk models were applied for sensitivity analyses. Results: The median age of the patients was 82.00 (80.00-85.00) years. Over 159 months of follow-up, the loss to follow-up rate was 2.27%, and all-cause mortality was observed in 574 (63.57%) patients, including 184 with OH. Moreover, cardiovascular death occurred in 127 patients (13.73%), with 58 cases associated with OH. Although the relationship between OH and all-cause mortality was non-significant [body mass index (BMI) < 25 group, adjusted hazard ratio (HR) = 1.10 with a 95% confidence interval (CI): 0.82-1.40; BMI ≥ 25 group, adjusted HR = 1.30, 95% CI: 0.98-1.70], it was independently related to a growing risk of cardiovascular death (adjusted HR = 1.80, 95% CI: 1.20-2.60). This finding was further validated by using a competing risk model (subdistribution HR = 1.74, 95% CI: 1.22-2.49). Moreover, age, low-density lipoprotein cholesterol, and frequency of hospital admissions were identified as risk factors of cardiovascular death among patients with OH (P < 0.05). Conclusion: Our study, based on retired military personnel with stable CAD, found that OH led to a significantly higher risk of cardiovascular death, but it was not noticeably associated with all-cause mortality on long-term prognosis.

A nomogramic model for predicting the left ventricular ejection fraction of STEMI patients after thrombolysis-transfer PCI.

Background: The prognosis of ST-segment elevation myocardial infarction (STEMI) is closely linked to left ventricular ejection fraction (LVEF). In contrast to primary percutaneous coronary intervention (PPCI), thrombolysis-transfer PCI (TTPCI) is influenced by multiple factors that lead to heterogeneity in cardiac function and prognosis. The aim of this study is to develop a nomogram model for predicting early LVEF in STEMI patients with TTPCI, based on routine indicators at admission. Method: We retrospectively reviewed data from patients diagnosed with STEMI at five network hospitals of our PCI center who performed TTPCI as door-to-balloon time (the interval between arrival at the hospital and intracoronary balloon inflation) over 120 min, from February 2018 to April 2022. Categorical variables were analyzed using Pearson χ2 tests or Fisher exact tests, while Student's t-test or Mann-Whitney U-test was used to compare continuous variables. Subsequently, independent risk factors associated with reduced LVEF one week after TTPCI were identified through comprehensive analysis by combining All-Subsets Regression with Logistic Regression. Based on these indicators, a nomogram model was developed, and validated using the area under the receiver operating characteristic (ROC) curve and the Bootstrap method. Results: A total of 288 patients were analyzed, including 60 with LVEF < 50% and 228 with LVEF ≥ 50%. The nomogram model based on six independent risk factors including age, heart rate (HR), hypertension, smoking history, Alanine aminotransferase (ALT), and Killip class, demonstrated excellent discrimination with an AUC of 0.84 (95% CI: 0.78-0.89), predicted C-index of 0.84 and curve fit of 0.713. Conclusions: The nomogram model incorporating age, HR, hypertension, smoking history, ALT and Killip class could accurately predict the early LVEF ≥ 50% probability of STEMI patients undergoing TTPCI, and enable clinicians' early evaluation of cardiac function in STEMI patients with TTPCI and early optimization of treatment.

The prognostic nutritional index predicts all-cause mortality in critically ill patients with acute myocardial infarction.

BACKGROUND: Malnutrition is common in patients with acute myocardial infarction (AMI) and is associated with a poor prognosis. The prognostic value of the prognostic nutritional index (PNI) in patients with AMI remains controversial. We aimed to explore the relationship between PNI and all-cause mortality in critically ill patients with AMI and evaluate the incremental prognostic value of PNI to commonly used prognostic assessment tools. METHODS: The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 1180 critically ill patients with AMI. The primary endpoints were defined as 6-month and 1-year all-cause mortality. Cox regression analysis was used to investigate the relationship between admission PNI and all-cause mortality. The effect of adding PNI to sequential organ failure assessment (SOFA) score, or charlson comorbidity index (CCI) on its discriminative ability was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). RESULTS: Multivariate cox regression analysis demonstrated that the low PNI was regarded as an independent predictor of 1-year all-cause mortality in AMI patients admitted to ICU (adjusted Hazard Ratio: 95% CI = 1.75 (1.22-2.49)). The ROC test showed that admission PNI had a moderate predictive ability to predict all-cause mortality of critically ill patients with AMI. Furthermore, the net reclassification and integrated discrimination of the CCI alone model improved significantly with PNI. [C-statistic increased from 0.669 to 0.752, p < 0.001; NRI = 0.698, p < 0.001; IDI = 0.073, p < 0.001]. When PNI was added to the SOFA score, the C-statistic significantly improved from 0.770 to 0.805 (p < 0.001), and the NRI and IDI were estimated at 0.573 (p < 0.001) and 0.041 (p < 0.001), respectively. CONCLUSION: PNI could be a novel predictor for identifying patients at high risk of 1-year all-cause mortality in critically ill patients with AMI. The addition of PNI to the SOFA score or CCI may be useful for very early risk stratification.

Coordination-Driven Self-Assembly of Biomedicine to Enhance Photodynamic Therapy by Inhibiting Proteasome and Bcl-2.

Tumor cells resist oxidative damage and apoptosis by activating defense mechanisms. Herein, a self-delivery biomedicine (designated as BSC) is developed by the self-assembly of Bortezomib (BTZ), Sabutoclax (Sab) and Chlorin e6 (Ce6). Interestingly, BTZ can be coordinated with Sab to promote the assembly of uniform ternary biomedicine through non-covalent intermolecular interactions. Moreover, BTZ as a proteasome inhibitor can prevent tumor cells from scavenging damaged proteins to reduce their oxidative resistance. Sab can downregulate B-cell lymphoma 2 (Bcl-2) to decrease the antiapoptotic protein. Both the proteasome and Bcl-2 inhibitions contribute to increasing cell apoptosis and amplifying photodynamic therapy (PDT) efficacy of Ce6. Encouragingly, carrier-free BSC receives all biological activities of these assembly elements, including photodynamic performance as well as inhibitory capabilities of proteasome and Bcl-2. Besides, BSC has a preferable cellular uptake ability and tumor retention property, which increase the drug delivery efficiency and bioavailability. In vitro and in vivo research demonstrate the superior PDT efficiency of BSC by proteasome and Bcl-2 inhibitions. Of special note, the coordination-driven self-assembly of BSC is pH-responsive, which can be disassembled for controlled drug release upon tumor acidic microenvironment. This study will expand the applicability of self-delivery nanomedicine with sophisticated mechanisms for tumor treatment.

Prognostic impact of in-hospital hemoglobin decline in non-overt bleeding ICU patients with acute myocardial infarction.

BACKGROUND: The prognostic value of in-hospital hemoglobin drop in non-overt bleeding patients with acute myocardial infarction (AMI) admitted to the intensive care unit (ICU) remains insufficiently investigated. METHODS: A retrospective analysis was performed based on the Medical Information Mart for Intensive Care (MIMIC)-IV database. 2,334 ICU-admitted non-overt bleeders diagnosed with AMI were included. In-hospital hemoglobin values (baseline value on admission and nadir value during hospitalization) were available. Hemoglobin drop was defined as a positive difference between admission and in-hospital nadir hemoglobin. The primary endpoint was 180-day all-cause mortality. The time-dependent Cox proportional hazard models were structured to analyze the connection between hemoglobin drop and mortality. RESULTS: 2,063 patients (88.39%) experienced hemoglobin drop during hospitalization. We categorized patients based on the degree of hemoglobin drop: no hemoglobin drop (n = 271), minimal hemoglobin drop (< 3 g/dl; n = 1661), minor hemoglobin drop (≥ 3 g/dl & < 5 g/dl, n = 284) and major hemoglobin drop (≥ 5 g/dl; n = 118). Minor (adjusted hazard ratio [HR] = 12.68; 95% confidence interval [CI]: 5.13-31.33; P < 0.001) and major (adjusted HR = 13.87; 95% CI: 4.50-42.76; P < 0.001) hemoglobin drops were independently associated with increased 180-day mortality. After adjusting the baseline hemoglobin level, a robust nonlinear relationship was observed in the association between hemoglobin drop and 180-day mortality, with 1.34 g/dl as the lowest value (HR = 1.04; 95% CI: 1.00-1.08). CONCLUSION: In non-overt bleeding ICU-admitted patients with AMI, in-hospital hemoglobin drop is independently associated with higher 180-day all-cause mortality.

Development and validation of a nomogram for predicting significant coronary artery stenosis in suspected non-ST-segment elevation acute coronary artery syndrome with low-to-intermediate risk stratification.

Background: Patients with non-ST-segment coronary artery syndrome (NSTE-ACS) have significant heterogeneity in their coronary arteries. A better assessment of significant coronary artery stenosis (SCAS) in low-to-intermediate risk NSTE-ACS patients would help identify who might benefit from invasive coronary angiography (ICA). Our study aimed to develop a multivariable-based model for pretesting SCAS in suspected NSTE-ACS with low-to-intermediate risk. Methods: This prediction nomogram was constructed retrospectively in 469 suspected NSTE-ACS patients with low-to-intermediate risk. Patients were divided into a development group (n = 331, patients admitted to hospital before 1 May 2021) and a temporal validation group (n = 138, patients admitted to hospital since 1 May 2021). The outcome was existing SCAS, including left main artery stenosis ≥50% or any subepicardial coronary artery stenosis ≥70%, all confirmed by invasive coronary angiography. Pretest predictors were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and stepwise logistic regression. Results: Derivation analyses from the development group (n = 331, admitted before 1 May 2021) generated the 7 strongest predictors out of 25 candidate variables comprising smoker, diabetes, heart rate, cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-density lipoprotein cholesterol, and left atrial diameter. This nomogram model showed excellent discrimination ability with an area under the receiver operating characteristic curve (AUC) of 0.83 in the development set and 0.79 in the validation dataset. Good calibration was generally displayed, although it slightly overestimated patients' SCAS risk in the validation group. Decision curve analysis demonstrated the clinical benefit of this model, indicating its value in clinical practice. Furthermore, an optimal cut-off of prediction probability was assigned as 0.61 according to the Youden index. Conclusion: A prediction nomogram consisting of seven readily available clinical parameters was established to pretest the probability of SCAS in suspected NSTE-ACS patients with low-to-intermediate risk, which may serve as a cost-effective risk stratification tool and thus assist in initial decision making.

Proteinuria is independently associated with carotid atherosclerosis: a multicentric study.

BACKGROUND AND AIMS: Atherosclerosis is a vital cause of cardiovascular diseases. The correlation between proteinuria and atherosclerosis, however, has not been confirmed. This study aimed to assess whether there is a relationship between proteinuria and atherosclerosis. METHODS: From January 2016 to September 2020, 13,545 asymptomatic subjects from four centres in southern China underwent dipstick proteinuria testing and carotid atherosclerosis examination. Data on demography and past medical history were collected, and laboratory examinations were performed. The samples consisted of 7405 subjects (4875 males and 2530 females), excluding subjects failing to reach predefined standards and containing enough information. A multivariate logistic regression model was used to adjust the influence of traditional risk factors for atherosclerosis on the results. RESULTS: Compared with proteinuria-negative subjects, proteinuria-positive subjects had a higher prevalence rate of carotid atherosclerosis. The differences were statistically significant (22.6% vs. 26.7%, χ2 = 10.03, p = 0.002). After adjusting for common risk factors for atherosclerosis, age, sex, BMI, blood lipids, blood pressure, renal function, hypertensive disease, diabetes mellitus and hyperlipidaemia, proteinuria was an independent risk factor for atherosclerosis (OR = 1.191, 95% CI 1.015-1.398, p = 0.033). The Hosmer-Lemeshow test was used to test the risk prediction model of atherosclerosis, and the results showed that the model has high goodness of fit and strong independent variable prediction ability. CONCLUSIONS: Proteinuria is independently related to carotid atherosclerosis. With the increase in proteinuria level, the risk of carotid atherosclerotic plaque increases. For patients with positive proteinuria, further examination of atherosclerosis should not be ignored.