Association of triglyceride-glucose index trajectory and frailty in urban older residents: evidence from the 10-year follow-up in a cohort study.

BACKGROUND: Frailty is an age-related geriatric syndrome that leads to a series of clinically negative events. A better understanding of the factors associated with frailty assists in preventing its progression. The triglyceride-glucose (TyG) index, a simple alternative index of insulin resistance, has not yet been proven to be associated with frailty. The present study aimed to investigate the association between the TyG index and its trajectory with frailty from a cross-sectional, retrospective and prospective level based on an ongoing cohort. METHODS: This longitudinal study included 1,866 older residents from the "Fujian prospective aging cohort" (ChiCTR 2,000,032,949). The TyG index was calculated as ln [fasting triglyceride (mg/dL) ╳ fasting plasma glucose (mg/dL)/2] and group-based trajectory model (GBTM) was applied to identify the trajectory of TyG index. The association between different trajectory groups of TyG index with frailty risk were estimated using multinomial logistic regression analysis. RESULTS: In the cross-sectional analysis, the highest quartile of the TyG index was associated with an increased risk of frailty (TyG index Q4 vs. Q1, OR = 1.50, 95% CI 1.00-2.25, P = 0.048). Restricted cubic splines demonstrated an increasing trend for TyG index and frailty risk. During a follow-up of ten years, three distinct trajectories of the TyG index were identified: low-stable (n = 697, 38.3%), moderate-stable (n = 910, 50.0%) and high-stable (n = 214, 11.7%). Compared with those in the stable-low group of TyG index trajectory, the ORs (95% CI) of prefrailty and frailty risk were 1.79 (95% CI 1.11-2.88) and 2.17 (95% CI 1.01-3.88) for the high-stable group, respectively (P = 0.017 and P = 0.038). In the subgroup analysis, the association of the high-stable trajectory of TyG and frailty status were only observed in subjects with BMI ≥ 24 kg/m2. Prospectively, the highest quartile of the TyG index was associated with a 2.09-fold significantly increased risk of one-year ADL/IADL decline (P = 0.045). CONCLUSIONS: The present study suggests a potential role for a high and sustainable level of TyG index in the risk of frailty. The trajectories of the TyG index can help to identify older individuals at a higher risk of frailty who deserve primitive preventive and therapeutic approaches.

Implementation of pollution source assessment and treatment strategy for plateau railway construction in China: an AHP-cloud model approach.

During the construction process of railways in the plateau region, various types of pollution sources can have serious or even irreversible impacts on the plateau ecology. To address pollution source treatment during the construction process, protect the ecological environment along the railway, and maintain the ecological balance, we collected geological and environmental data and analyzed the influencing factors of pollution sources. Taking sewage as the main research subject, we propose a new method based on the Analytic Hierarchy Process (AHP)-cloud model to classify the pollution source treatment level, establish an index system, and select the ecological environment level, sewage rate, and pollutant characteristics as the three main influencing factors. Finally, we divide the pollution source treatment level into I, II, and III, corresponding to V1 = {I-level} = {high impact}, V2 = {II-level} = {moderate impact}, and V3 = {III-level} = {low impact}. Based on the comprehensive factor weight analysis and the field engineering conditions of the studied railway in the western plateau of China, we classify the pollution source treatment level of six tunnels and propose treatment suggestions for each level. To advance the efficient implementation of environmental protection during the construction of the plateau railway, we propose three policy recommendations that can positively contribute to environmental protection and green development. This work provides theoretical and technical guidance for the treatment of pollution sources in the construction of the plateau railway, which also serves as a significant reference for other similar projects.

Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer's disease.

Background: We developed a novel system for quantifying DNA damage response (DDR) to help diagnose and predict the risk of Alzheimer's disease (AD). Methods: We thoroughly estimated the DDR patterns in AD patients Using 179 DDR regulators. Single-cell techniques were conducted to validate the DDR levels and intercellular communications in cognitively impaired patients. The consensus clustering algorithm was utilized to group 167 AD patients into diverse subgroups after a WGCNA approach was employed to discover DDR-related lncRNAs. The distinctions between the categories in terms of clinical characteristics, DDR levels, biological behaviors, and immunological characteristics were evaluated. For the purpose of choosing distinctive lncRNAs associated with DDR, four machine learning algorithms, including LASSO, SVM-RFE, RF, and XGBoost, were utilized. A risk model was established based on the characteristic lncRNAs. Results: The progression of AD was highly correlated with DDR levels. Single-cell studies confirmed that DDR activity was lower in cognitively impaired patients and was mainly enriched in T cells and B cells. DDR-related lncRNAs were discovered based on gene expression, and two different heterogeneous subtypes (C1 and C2) were identified. DDR C1 belonged to the non-immune phenotype, while DDR C2 was regarded as the immune phenotype. Based on various machine learning techniques, four distinctive lncRNAs associated with DDR, including FBXO30-DT, TBX2-AS1, ADAMTS9-AS2, and MEG3 were discovered. The 4-lncRNA based riskScore demonstrated acceptable efficacy in the diagnosis of AD and offered significant clinical advantages to AD patients. The riskScore ultimately divided AD patients into low- and high-risk categories. In comparison to the low-risk group, high-risk patients showed lower DDR activity, accompanied by higher levels of immune infiltration and immunological score. The prospective medications for the treatment of AD patients with low and high risk also included arachidonyltrifluoromethane and TTNPB, respectively. Conclusions: In conclusion, immunological microenvironment and disease progression in AD patients were significantly predicted by DDR-associated genes and lncRNAs. A theoretical underpinning for the individualized treatment of AD patients was provided by the suggested genetic subtypes and risk model based on DDR.

Identification of immune microenvironment subtypes and signature genes for Alzheimer's disease diagnosis and risk prediction based on explainable machine learning.

Background: Using interpretable machine learning, we sought to define the immune microenvironment subtypes and distinctive genes in AD. Methods: ssGSEA, LASSO regression, and WGCNA algorithms were used to evaluate immune state in AD patients. To predict the fate of AD and identify distinctive genes, six machine learning algorithms were developed. The output of machine learning models was interpreted using the SHAP and LIME algorithms. For external validation, four separate GEO databases were used. We estimated the subgroups of the immunological microenvironment using unsupervised clustering. Further research was done on the variations in immunological microenvironment, enhanced functions and pathways, and therapeutic medicines between these subtypes. Finally, the expression of characteristic genes was verified using the AlzData and pan-cancer databases and RT-PCR analysis. Results: It was determined that AD is connected to changes in the immunological microenvironment. WGCNA revealed 31 potential immune genes, of which the greenyellow and blue modules were shown to be most associated with infiltrated immune cells. In the testing set, the XGBoost algorithm had the best performance with an AUC of 0.86 and a P-R value of 0.83. Following the screening of the testing set by machine learning algorithms and the verification of independent datasets, five genes (CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12) that were closely associated with AD pathological biomarkers and allowed for the accurate prediction of AD progression were found to be immune microenvironment-related genes. The feature gene-based nomogram may provide clinical advantages to patients. Two immune microenvironment subgroups for AD patients were identified, subtype2 was linked to a metabolic phenotype, subtype1 belonged to the immune-active kind. MK-866 and arachidonyltrifluoromethane were identified as the top treatment agents for subtypes 1 and 2, respectively. These five distinguishing genes were found to be intimately linked to the development of the disease, according to the Alzdata database, pan-cancer research, and RT-PCR analysis. Conclusion: The hub genes associated with the immune microenvironment that are most strongly associated with the progression of pathology in AD are CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12. The hypothesized molecular subgroups might offer novel perceptions for individualized AD treatment.

Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning.

Introduction: Alzheimer's disease (AD) is a severe dementia with clinical and pathological heterogeneity. Our study was aim to explore the roles of endoplasmic reticulum (ER) stress-related genes in AD patients based on interpretable machine learning. Methods: Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. We performed nine machine learning algorithms including AdaBoost, Logistic Regression, Light Gradient Boosting (LightGBM), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), Random Forest, K-nearest neighbors (KNN), Naïve Bayes, and support vector machines (SVM) to screen ER stress-related feature genes and estimate their efficiency of these genes for early diagnosis of AD. ROC curves were performed to evaluate model performance. Shapley additive explanation (SHAP) was applied for interpreting the results of these models. AD patients were classified using a consensus clustering algorithm. Immune infiltration and functional enrichment analysis were performed via CIBERSORT and GSVA, respectively. CMap analysis was utilized to identify subtype-specific small-molecule compounds. Results: Higher levels of immune infiltration were found in AD individuals and were markedly linked to deregulated ER stress-related genes. The SVM model exhibited the highest AUC (0.879), accuracy (0.808), recall (0.773), and precision (0.809). Six characteristic genes (RNF5, UBAC2, DNAJC10, RNF103, DDX3X, and NGLY1) were determined, which enable to precisely predict AD progression. The SHAP plots illustrated how a feature gene influence the output of the SVM prediction model. Patients with AD could obtain clinical benefits from the feature gene-based nomogram. Two ER stress-related subtypes were defined in AD, subtype2 exhibited elevated immune infiltration levels and immune score, as well as higher expression of immune checkpoint. We finally identified several subtype-specific small-molecule compounds. Conclusion: Our study provides new insights into the role of ER stress in AD heterogeneity and the development of novel targets for individualized treatment in patients with AD.

Identification and immunological characterization of cuproptosis-related molecular clusters in Alzheimer's disease.

Introduction: Alzheimer's disease is the most common dementia with clinical and pathological heterogeneity. Cuproptosis is a recently reported form of cell death, which appears to result in the progression of various diseases. Therefore, our study aimed to explore cuproptosis-related molecular clusters in Alzheimer's disease and construct a prediction model. Methods: Based on the GSE33000 dataset, we analyzed the expression profiles of cuproptosis regulators and immune characteristics in Alzheimer's disease. Using 310 Alzheimer's disease samples, we explored the molecular clusters based on cuproptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were identified using the WGCNA algorithm. Subsequently, the optimal machine model was chosen by comparing the performance of the random forest model, support vector machine model, generalized linear model, and eXtreme Gradient Boosting. Nomogram, calibration curve, decision curve analysis, and three external datasets were applied for validating the predictive efficiency. Results: The dysregulated cuproptosis-related genes and activated immune responses were determined between Alzheimer's disease and non-Alzheimer's disease controls. Two cuproptosis-related molecular clusters were defined in Alzheimer's disease. Analysis of immune infiltration suggested the significant heterogeneity of immunity between distinct clusters. Cluster2 was characterized by elevated immune scores and relatively higher levels of immune infiltration. Functional analysis showed that cluster-specific differentially expressed genes in Cluster2 were closely related to various immune responses. The Random forest machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.9829). A final 5-gene-based random forest model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.8529 and 0.8333). The nomogram, calibration curve, and decision curve analysis also demonstrated the accuracy to predict Alzheimer's disease subtypes. Further analysis revealed that these five model-related genes were significantly associated with the Aß-42 levels and ß-secretase activity. Conclusion: Our study systematically illustrated the complicated relationship between cuproptosis and Alzheimer's disease, and developed a promising prediction model to evaluate the risk of cuproptosis subtypes and the pathological outcome of Alzheimer's disease patients.

A convenient and practical triaxial coupled seepage testing apparatus for deep buried coal.

As the world's shallow coal resources are being depleted, resource development continues to progress faster. To explore the coupled hydromechanical behavior of coal reserves that are buried deep underground under high stress, complex seepage, high temperature, adsorption, and desorption, we have developed a triaxial seepage testing apparatus under multifactor coupling effect. The system consists of a high-pressure and high-precision servo control loading system, a triaxial core holder (TEMCO), a seepage dynamic control system, a low-field Nuclear Magnetic Resonance (NMR) test system, a constant temperature control system, and a data acquisition and monitoring system. This system is capable of applying high pressure and long-term loading for specimens under adsorption or desorption. In addition, both steady-state method and pressure transient methods can be applied, thus covering the entire range for coal reserves buried deep from ultralow permeability to high permeability and significantly shortening the testing time. The characteristics of pores and fractures in the specimens and their impacts on permeability can be quantitatively evaluated by the low-field NMR experimental technique. We conducted experiments to understand the evolution of permeability of different gases under different stress conditions and to study the impact of adsorption on pore size distribution. Our experimental results show that the performance of this system is stable and reliable, which allow it to reflect the coupled hydromechanical response of coal buried deep underground. We envision this apparatus has a wide range of application value and can provide a scientific experimental basis for improving the recovery of coalbed methane and geological sequestration of CO2 in the future.

Comprehensive Analysis of Molecular Subtypes and Hub Genes of Sepsis by Gene Expression Profiles.

Background: Sepsis is a systemic inflammatory response syndrome (SIRS) with heterogeneity of clinical symptoms. Studies further exploring the molecular subtypes of sepsis and elucidating its probable mechanisms are urgently needed. Methods: Microarray datasets of peripheral blood in sepsis were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) analysis was conducted to screen key module genes. Consensus clustering analysis was carried out to identify distinct sepsis molecular subtypes. Subtype-specific pathways were explored using gene set variation analysis (GSVA). Afterward, we intersected subtype-related, dramatically expressed and module-specific genes to screen consensus DEGs (co-DEGs). Enrichment analysis was carried out to identify key pathways. The least absolute shrinkage and selection operator (LASSO) regression analysis was used for screen potential diagnostic biomarkers. Results: Patients with sepsis were classified into three clusters. GSVA showed these DEGs among different clusters in sepsis were assigned to metabolism, oxidative phosphorylation, autophagy regulation, and VEGF pathways, etc. In addition, we identified 40 co-DEGs and several dysregulated pathways. A diagnostic model with 25-gene signature was proven to be of high value for the diagnosis of sepsis. Genes in the diagnostic model with AUC values more than 0.95 in external datasets were screened as key genes for the diagnosis of sepsis. Finally, ANKRD22, GPR84, GYG1, BLOC1S1, CARD11, NOG, and LRG1 were recognized as critical genes associated with sepsis molecular subtypes. Conclusion: There are remarkable differences in and enriched pathways among different molecular subgroups of sepsis, which may be the key factors leading to heterogeneity of clinical symptoms and prognosis in patients with sepsis. Our current study provides novel diagnostic and therapeutic biomarkers for sepsis molecular subtypes.

Assessment of the anesthetic effect of modified pentothal sodium solution on Sprague-Dawley rats.

Clinically, pentothal sodium has been widely used for primary and general anesthesia induction. Also, it has been used to effectively inhibit convulsion. Pentothal sodium has a strong inhibitory effect on the respiratory center, excessive drug administration, and rapid dose rate that cause death of experimental animals on the respiratory depression. This study used a modified pentothal sodium solution to investigate its anesthetic effect. The pentothal sodium solution was modified based on pentothal sodium upon additions of magnesium sulfate, propylene glycol, and pure ethanol. The anesthetic effect of the modified pentothal sodium on Sprague-Dawley (SD) rats was investigated by comparing traditional pentothal sodium and ketamine; 60 SD rats were randomly divided into three groups. Each group was treated with traditional pentothal sodium, modified pentothal sodium, or ketamine, respectively, via intraperitoneal injection. The symptoms of experimental rats were observed, and onset time and anesthetic time were both recorded. The data were analyzed using statistical software. There were no significant differences in onset time and anesthetic time between the three groups. The variation of onset time and anesthetic time of the group treated with modified pentothal sodium was shorter than that of the other two groups. Furthermore, the number of anesthetic rats after the first injection was significantly higher than that of the other two groups. The modified pentothal sodium is capable of providing a stable anesthetic effect. The function and effect are much better than traditional pentothal sodium and ketamine.

COVID-19 and coagulation dysfunction in adults: A systematic review and meta-analysis.

The outbreak of 2019 novel coronavirus disease (COVID-19) has posed a grave threat to the global public health. The COVID-19-induced infection is closely related to coagulation dysfunction in the affected patients. This paper attempts to conduct a meta-analysis and systematically review the blood coagulation indicators in patients with severe COVID-19. A meta-analysis of eligible studies was performed to compare the blood coagulation indicators in patients with severe and nonsevere COVID-19. PubMed, Embase, Web of Science, and the Cochrane Library were searched for studies published between 1 December 2019 and 7 May 2020. A total of 13 studies with 1341 adult patients were enrolled in this analysis. Platelet (weighted mean difference [WMD] = -24.83, 95% confidence interval [CI]: -34.12 to -15.54; P < .001), d-dimer (WMD = 0.19, 95% CI: 0.09-0.29; P < .001), and fibrinogen (WMD = 1.02, 95% CI: 0.50-1.54; P < .001) were significantly associated with the severity in patients with COVID-19. The meta-analysis revealed that no correlation was evident between an increased severity risk of COVID-19 and activated partial thromboplastin time (WMD = -1.56, 95% CI: -5.77 to 2.64; P = .468) or prothrombin time (WMD = 0.19, 95% CI: -0.13 to 0.51; P = .243). The single arm meta-analysis showed that compared with the nonsevere group, the severe group had a lower pooled platelet (165.12 [95% CI: 157.38-172.85] vs 190.09 [95% CI: 179.45-200.74]), higher d-dimer (0.49 [95% CI: 0.33-0.64] vs 0.27 [95% CI: 0.20-0.34]), and higher fibrinogen (4.34 [95% CI: 1.98-6.70] vs 3.19 [95% CI: 1.13-5.24]). Coagulation dysfunction is closely related to the severity of patients with COVID-19, in which low platelet, high d-dimer, and fibrinogen upon admission may serve as risk indicators for increased aggression of the disease. These findings are of great clinical value for timely and effective treatment of the COVID-19 cases.

Fibrinogen-to-Albumin Ratio Predicts Contrast-Induced Nephropathy in Patients after Emergency Percutaneous Coronary Intervention.

BACKGROUND: The aim of the present study was to investigate the association between fibrinogen-to-albumin ratio (FAR) with contrast-induced nephropathy (CIN) in patients undergoing emergency percutaneous coronary intervention (PCI). METHODS: 565 patients with emergency PCI were consecutively enrolled. The primary outcome was CIN defined as either a 25% increase in baseline serum creatinine levels or a 0.5 mg/dL (44 µmol/L) increase in absolute serum creatinine levels within 72 h after the contrast medium exposure. Logistic regression analysis was applied to analyze whether FAR was an independent risk factor for CIN. RESULTS: Overall, 29 (5.1%) patients developed CIN. Compared with the patients without CIN, the patients developing CIN had lower albumin (39.79 ± 3.95 vs. 37.14 ± 5.21, P=0.012) and higher fibrinogen levels (3.51 ± 0.94 vs. 4.14 ± 0.96, P < 0.001). In the multivariate logistic analysis, FAR was an independent predictor of CIN (OR = 3.97; 95% CI, 1.61-9.80; P=0.003) along with perihypotension, age >75 years, and LVEF <45%, and 0.106 was the optimal cutoff value of preprocedural FAR to predict CIN. CONCLUSION: Preprocedural levels of FAR were associated with CIN in patients after emergency PCI.

Low free triiodothyronine is associated with contrast-induced acute kidney injury and long-term outcome in elderly patients who underwent percutaneous coronary intervention.

OBJECTIVE: Low free triiodothyronine (fT3) is common in elderly patients with cardiovascular disease. The purpose of this study was to evaluate the relationship between low fT3 and contrast-induced acute kidney injury (CI-AKI), including the long-term outcomes, in elderly patients after a percutaneous coronary intervention (PCI). METHODS: A total of 350 patients aged ≥75 years who underwent PCI between January 2012 and December 2015 were consecutively enrolled. The perioperative thyroid function, including fT3, was measured before PCI. A low fT3 was defined as fT3<3.1 pmol/L with normal thyrotropin and free thyroxine. CI-AKI was defined as an absolute serum creatinine (SCr) increase ≥0.30 mg/dL or a relative increase in SCr ≥50% from the baseline value within 48 hours after contrast media exposure. A multivariate logistic regression analysis was applied to analyze whether low fT3 was an independent risk factor for CI-AKI. The Cox regression analysis was used to evaluate the relationship between low fT3 and long-term prognosis. RESULTS: A total of 46 (13.1%) patients developed CI-AKI. The incidence of CI-AKI was significantly higher in the low fT3 group than in the normal group (26.5% vs. 9.9%, p<0.01). A multivariable logistic analysis demonstrated that a low fT3 level was significantly related to CI-AKI [odds ratio (OR)=2.41; 95% confidence interval (CI), 1.11-5.27; p=0.027]. The Cox regression analysis showed that a low fT3 was associated with long-term mortality [adjusted hazard ratio (HR)=2.00; 95% CI, 1.04-3.83; p=0.037] during the follow-up of mean 1.67 years. CONCLUSION: A low fT3 concentration was independently associated with CI-AKI and poor prognosis in elderly patients who had undergone PCI.

Simplified synchronous disconnection of pulmonary arteries and veins for right upper lobectomy.

BACKGROUND: Video-assisted thoracoscopic lobectomy with lymphadenectomy is considered one of the most effective treatments for early non-small cell lung cancer. We developed a novel approach for lobectomy in patients with right upper lung cancer through simplified synchronous disconnection of pulmonary arteries and veins. This study aimed to evaluate the feasibility, efficacy, safety, and cost-effectiveness of this minimally invasive technique in managing right upper lobectomy. PATIENTS AND METHODS: From March 2016 to September 2017, 62 patients with right upper lung cancer underwent lobectomy via simplified synchronous disconnection of pulmonary arteriovenous by video-assisted thoracoscopic surgery. All patients were followed up for 6-12 months after the procedure through clinic visits or telephone/e-mail interviews. RESULTS: Of the 62 patients (mean age, 57.2 ± 8.7 years), 28 were men (45.2%) and 34 (54.8%) were women. All procedures were successfully performed by thoracoscopy, with a mean operating time of 66.2 ± 9.0 min. The mean blood loss was 40.3 ± 19.5 mL. Only 1 (1.61%) patient required blood transfusion. The mean number of endoscopic linear stapling devices used was 2.6 ± 0.7. The mean number of lymph nodes harvested was 16.0 ± 1.6. Postoperative pneumonia was encountered in 4 (6.45%) patients. There was no postoperative mortality. The mean length of hospital stay was 5.3 ± 1.3 days. Six-month follow-up revealed an excellent clinical result and degree of satisfaction. CONCLUSIONS: Simplified synchronous disconnection of pulmonary arteries and veins is a feasible, economical, safe, and effective therapeutic procedure for right upper lung carcinoma. This novel procedure shows promise as a viable surgical approach for right upper lobectomy.

Pre-Procedural N-Terminal Pro-B Type Natriuretic Peptide Predicts Contrast-Induced Acute Kidney Injury and Long-Term Outcome in Elderly Patients After Elective Percutaneous Coronary Intervention.

The aim of the study is to evaluate the association of pre-procedural N-terminal pro-B type natriuretic peptide (NT-proBNP) with contrast-induced acute kidney injury (CI-AKI) and long-term outcomes in elderly patients undergoing elective percutaneous coronary intervention (PCI).A total of 540 patients aged ≥ 75 years who had undergone elective PCI between January 2012 and December 2015 were enrolled in this study. Admission NT-proBNP levels were measured before PCI. CI-AKI was defined as a relative increase in serum creatinine (SCr) of ≥50%, or an absolute increase of ≥ 0.3 mg/dL, occurring within 48 hours after contrast medium exposure. The predictive value of NT-proBNP for predicting CI-AKI was assessed by receiver operating characteristic (ROC) and multivariable logistic regression analysis.A total of 54 (10.0%) patients developed CI-AKI. The best cutoff value of NT-pro-BNP for detecting CI-AKI was 1133 pg/mL with 66.7% sensitivity and 70.8% specificity according to the ROC analysis (C statistic = 0.719; 95% CI, 0.679-0.756). Multivariable analysis demonstrated that Lg-NT-proBNP is significantly related to CI-AKI (odds ratio [OR] = 3.892; 95% CI, 1.996-7.590; P < 0.001). Cox regression analysis showed that Lg-NT-proBNP is associated with long-term mortality (adjusted hazard ratio [HR] = 2.158; 95% CI, 1.246-3.740; P = 0.006) during follow-up.Pre-procedural NT-proBNP is a significant and independent predictor of CI-AKI and long-term mortality in elderly patients following elective PCI, and the best cutoff point for predicting CI-AKI was 1133 pg/mL.

Association of prealbumin levels with contrast-induced acute kidney injury in elderly patients with elective percutaneous coronary intervention.

PURPOSE: Inflammatory factors play a critical role in contrast-induced acute kidney injury (CI-AKI). Prealbumin, a nutritional and inflammatory indicator, is a well-established predictor of short- and long-term outcomes in numerous clinical conditions. The current study investigated the association of pre-procedural prealbumin levels with CI-AKI and long-term outcomes in geriatric patients after elective percutaneous coronary intervention (PCI). PATIENTS AND METHODS: A total of 558 patients aged≥75 years, who underwent elective PCI between January 2012 and December 2015, were selected for the current study. Pre-procedural prealbumin levels were measured before PCI. Multivariable logistic regression and Cox proportional hazard regression analyses were performed to identify the independent risk factors for CI-AKI and long-term mortality. RESULTS: Out of 558 patients, 54 developed CI-AKI. The optimal cutoff value of prealbumin for detecting CI-AKI was 185.5 mg/L with 62.7% sensitivity and 70.4% specificity based on the receiver operating characteristic analysis (C-statistic=0.710; 95% confidence interval [CI] 0.673-0.751). Multivariable analysis demonstrated that prealbumin≤185.5 mg/L was significantly associated with CI-AKI (odds ratio [OR] 0.397; 95% CI 0.195-0.808; P=0.011). Cox regression analysis demonstrated that prealbumin≤185.5 mg/L was associated with long-term mortality (adjusted hazard ratio [HR] 0.525; 95% CI 0.289-0.952; P=0.034) during the follow-up. CONCLUSION: Pre-procedural levels of prealbumin were independently associated with an increased risk of CI-AKI and long-term mortality in elderly patients undergoing elective PCI.

Association of Preprocedural Hyperglycemia With Contrast-Induced Acute Kidney Injury and Poor Outcomes After Emergency Percutaneous Coronary Intervention.

We investigated whether preprocedural hyperglycemia was associated with contrast-induced acute kidney injury (CI-AKI) and long-term outcomes in patients with acute coronary syndrome (ACS) who underwent emergency percutaneous coronary intervention (PCI). Patients (n = 558) with ACS who underwent emergency PCI were consecutively enrolled. Preprocedural hyperglycemia was defined as glucose levels >198 mg/dL (11 mmol/L). The primary outcome was CI-AKI (≥0.3 mg/dL absolute or ≥50% relative serum creatinine increase 48 hours after contrast medium exposure). Overall, 103 (18.5%) patients had preprocedural hyperglycemia and 89 (15.9%) patients developed CI-AKI. The incidence of CI-AKI was significantly higher in patients with hyperglycemia than without (28.2% vs 13.2%; P < .01). Multivariate analysis indicated that preprocedural hyperglycemia was an independent predictor of CI-AKI (odds ratio = 1.971, 95% confidence interval [CI]: 1.129-3.441; P < .05). In addition, preprocedural hyperglycemia was associated with an increased risk of all-cause mortality during the 2-year follow-up (hazard ratio = 2.440, 95% CI: 1.394-4.273; P = .002). Preprocedural hyperglycemia is a significant and independent predictor of CI-AKI and long-term outcomes.

Influence of changes in serum uric acid levels on renal function in elderly patients with hypertension: a retrospective cohort study with 3.5-year follow-up.

BACKGROUND: Hyperuricemia is closely related to renal diseases. Therefore, the aim of this study was to explore the relationship between the longitudinal changes in serum uric acid and the estimated glomerular filtration rate (eGFR) in a cohort of elderly hypertensive patients. METHODS: Eighty hundred and thirty-seven re-hospitalized patients with hypertension were included in this retrospective cohort study. Multiple regression analysis was used to investigate the relationship between changes in serum uric acid and renal function after 3.5 years follow-up. RESULTS: The average age at baseline was 69.0+/-10.0 years, and the average follow-up duration was 3.5 years. Multiple linear regression analysis showed that the baseline uric acid levels had a linearly negative correlation with baseline eGFR (P < 0.01), after adjustment for age, gender, blood pressure, and body mass index, et al. An increase of 100 µmol/L baseline uric acid level resulted in a decrease of 5.684 ml/min/1.73 m(2) in eGFR [95% confidence interval (CI): 7.735-3.633]. Patients with increased uric acid levels had higher risk of renal function decline over the follow-up period, with an adjusted odds ratio of 1.639 (95% CI: 1.129-2.378, P = 0.009) , whereas eGFR was remained unchanged in patients with hyperuricemia at baseline and with normal uric acid level 3.5-year later. CONCLUSIONS: Longitudinal changes in uric acid levels were independently associated with the renal function decline in elderly patients with hypertension. Uric acid level should be considered in hypertension management in the elderly.

Effect of hyperuricemia on the blood pressure response to antihypertensive agents in hospitalized elderly patients.

AIMS: As elevated serum uric acid (SUA) is an independent risk factor for hypertension, we examined whether baseline SUA may influence the blood pressure (BP) response to antihypertensive medications. METHODS: Data from 1648 inpatients with essential, uncontrolled hypertension on admission were analyzed retrospectively. Patients taking loop or thiazide diuretics or hypouricemic agents were excluded. The BP response to treatment was based on the BP change from admission (baseline) to discharge. RESULTS: The mean age was 66.7 ±â€Š11.5 years, the average BP was 156.1/85.5 mmHg and the average estimated glomerular filtration rate (eGFR) was 80.07 ±â€Š21.69 ml/min per 1.73 m. Twenty-five percent of the patients had chronic kidney disease and 32% had diabetes. The average duration of hospitalization was 14.3 ±â€Š5.3 days. In 1149 patients with normal renal function (eGFR ≥60 ml/min per 1.73 m), those with hyperuricemia (SUA >420 µmol/l in men and >360 µmol/l in women) had more metabolic disorders (P < 0.05), higher baseline diastolic BP (P < 0.05), greater antihypertensive therapeutic intensity score (TIS) at baseline and discharge (P < 0.01), more diuretic use at discharge (P < 0.01) and less systolic BP reduction in response to antihypertensive therapy (P < 0.01). After adjustment for age, diabetes, BMI, baseline BP, lipid disorders, baseline TIS and eGFR, multiple linear regression using the data from all patients indicated that hyperuricemia was associated with a 5.3 mmHg less systolic BP reduction [95% confidence interval (CI): 3.1-7.4 mmHg, P < 0.01] in men, and a 2.6 mmHg less systolic BP reduction (95% CI: 0.5-4.6 mmHg, P = 0.02) in women. CONCLUSION: Hyperuricemia may be an independent risk factor for BP control in elderly hypertensive patients during hospitalization.