Objective: This study aimed to analyze the safety and mid-term outcomes of a hybrid treatment method combining rotational atherectomy (RA) with drug-coated balloon (DCB) angioplasty in patients with femoropopliteal artery in-stent restenosis (ISR).
Methods: This single-center retrospective study enrolled patients from January 2018 to March 2022 who had femoropopliteal artery in-stent restenosis treated by RA and DCB. Preoperative demographics, operative details, and postoperative 12-month follow-up outcomes were analyzed statistically.
Background: The optimal endovascular method to treat infrapopliteal chronic limb-threatening ischemia (CLTI) remains to be determined, given the limitations of stent use in infrapopliteal artery disease. We performed a network meta-analysis (NWM) of randomized controlled trials (RCTs) to simultaneously compare the outcomes of different balloon angioplasty procedures for infrapopliteal artery lesions in CLTI patients.
Methods: We searched the Cochrane Central Register of Controlled Trials, Embase, and PubMed.
Background: This study aimed to examine the association between the American Heart Association's (AHA) newly revised Life's Essential 8 (LE8) algorithm, designed for assessing cardiovascular health (CVH), and cognitive impairment among older adults in the United States.
Methods: This study employed a cross-sectional design, utilizing data from the 2011-2014 National Health and Nutrition Examination Survey to explore the relationship between CVH and cognitive impairment in older adults. CVH scores are assessed based on the AHA definition of the LE8, categorized into three tiers: low (0-49), medium (50-79), and high (80-100).
Despite the growing recognition of the impact of urban environments on social health, limited research explores the combined associations of multiple urban exposures, particularly in dense cities. This study examines the interplay between greenspace, air pollution, and social health as well as the underlying pathways and population heterogeneity in Hong Kong using cross-sectional survey data from 1977 adults and residential environmental data. Social health includes social contacts, relations, and support.
View Article and Find Full Text PDFObjective: This study aims to assess the performance of various scoring systems in predicting the 28-day mortality of patients with aortic aneurysms (AA) admitted to the intensive care unit (ICU).
Methods: We utilized data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) to perform a comparative analysis of various predictive systems, including the Glasgow Aneurysm Score (GAS), Simplified Acute Physiology Score (SAPS) III, SAPS II, Logical Organ Dysfunction System (LODS), Sequential Organ Failure Assessment (SOFA), Systemic Inflammatory Response Syndrome (SIRS), and The Oxford Acute Illness Severity Score (OASIS). The discrimination abilities of these systems were compared using the area under the receiver operating characteristic curve (AUROC).
Purpose: Femoropopliteal artery disease (FPAD) is a common vascular disease that usually requires surgical treatment. The aim of this study was to apply predictive modeling to develop predictive models for predicting clinically driven target revascularization (CD-TLR) events 1 year after intervention in patients with FPAD.
Materials And Methods: In this study, clinical data were collected from a total of 484 patients who underwent FPAD endovascular intervention from 2014 to 2019.
The purpose of this study is to establish a predictive model of cognitive impairment in elderly people with diabetes. We analyzed a total of 878 elderly patients with diabetes who were part of the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014. The data were randomly divided into training and validation cohorts at a ratio of 6:4.
View Article and Find Full Text PDFThe accurate prediction of chlorophyll-a (chl-a) concentration in coastal waters is essential to coastal economies and ecosystems as it serves as the key indicator of harmful algal blooms. Although powerful machine learning methods have made strides in forecasting chl-a concentrations, there remains a gap in effectively modeling the dynamic temporal patterns and dealing with data noise and unreliability. To wiggle out of quagmires, we introduce an innovative deep learning prediction model (termed ChloroFormer) by integrating Transformer networks with Fourier analysis within a decomposition architecture, utilizing coastal in-situ data from two distinct study areas.
View Article and Find Full Text PDFBackground: Drawing on prospective data from the National Health and Nutrition Examination Survey (NHANES), our goal was to construct and validate a 5-year survival prediction model for individuals with cognitive impairment (CI).
Methods: This study entailed a prospective cohort design utilizing information from the 2011-2014 NHANES dataset, encompassing individuals aged 40 years or older, with updated mortality status as of December 31, 2019. Predictive models within the derivation and validation cohorts were assessed using logistic proportional risk regression, column-line plots, and least absolute shrinkage and selection operator (LASSO) binomial regression models.
Carbonates or carbon-bearing materials may release gases under high pressure and high temperature (HP-HT) conditions. Characterizing the species and quantifying the volumes of these carbonaceous gases are critical for understanding carbon chemistry. However, the volatile nature of carbonaceous gas poses technical challenges in their collection, speciation, and quantification during HP-HT experiments.
View Article and Find Full Text PDFBackground: Vascular diseases represent a significant causes of disability and death worldwide. The demand for artificial blood vessels is increasing due to the scarce supply of healthy autologous vessels. Nevertheless, the literature in this area remains sparse and inconclusive.
View Article and Find Full Text PDFBackground: Carotid endarterectomy (CEA) is a surgical procedure that can reduce the risk of stroke in patients with carotid artery stenosis. However, controversy still exists regarding the optimal surgical technique for CEA.
Objective: To compare the safety and effectiveness of different techniques.
Background: This study aimed to investigate the role of uric acid (UA) in diabetic nephropathy (DN) from epidemiological and genetic perspectives.
Methods: We used data from the 2007-2016 National Health and Nutrition Examination Survey to evaluate the relationship between UA and DN risk using weighted multivariate-adjusted logistic regression. Subsequently, a two-sample Mendelian randomization study was conducted using genome-wide association study summary statistics.
Purpose: The impact of carotid revascularization on cognitive function for patients with severe carotid artery stenosis remains uncertain. This study is aimed to investigate the 1-year neurocognitive outcomes of patients who accept carotid revascularization and identify the risk factors associated with postoperative cognitive decline.
Methods: From April 2019 to April 2021, patients with ≥70% carotid artery stenosis who were treated with carotid endarterectomy (CEA) or carotid artery stenting (CAS) were recruited for this study.
Background And Aim: The impact of environmental chemical exposure on blood pressure (BP) is well-established. However, the relationship between secondhand smoke exposure (SHSE) and mortality in hypertensive patients in the general population remains unclear.
Methods And Results: This cohort study included US adults in the National Health and Nutrition Examination Survey from 2007 to 2018.
Objective: This study aims to establish and validate a nomogram model for the all-cause mortality rate in patients with diabetic nephropathy (DN).
Methods: We analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2007 to 2016. A random split of 7:3 was performed between the training and validation sets.
Background And Aims: To examine the association of serum 25-hydroxyvitamin D [25(OH)D] with all-cause mortality and disease-specific mortality in patients with hypertension.
Methods And Results: This cohort study included US adults in the National Health and Nutrition Examination Survey from 2007 to 2018. All-cause mortality and cause-specific mortality outcomes were determined by association with National Death Index records.
Background: This Bayesian network meta-analysis (NMA) sought to evaluate the efficacy of different endovascular treatments for femoropopliteal artery in-stent restenosis (FP-ISR).
Methods: PubMed, Embase, Cochrane Central Register of Controlled Trials, and Web of science for clinical trials from database inception to March 31, 2023, with no language restrictions to retrieve randomized controlled trials or cohort studies evaluating the impact of any kind of endovascular treatments for FP-ISR. Pair-wise meta-analysis and Bayesian NMA were performed to pool the outcome estimates different endovascular treatments.
Objective: To compare perioperative and long-term safety and effectiveness between conventional carotid endarterectomy (cCEA) and patch carotid endarterectomy (pCEA) under current medical conditions.
Methods: Data on baseline characteristics as well as perioperative and long-term postoperative complications from patients who underwent cCEA or pCEA at the Department of Vascular Surgery, Xuanwu Hospital of Capital Medical University, from 2013 to 2022, were retrospectively collected and analyzed.
Results: A total of 248 CEA patients were included in our study.
Background: The mortality rate among older persons with diabetes has been steadily increasing, resulting in significant health and economic burdens on both society and individuals. The objective of this study is to develop and validate a predictive nomogram for estimating the 5-year all-cause mortality risk in older persons with T2D (T2D).
Methods: We obtained data from the National Health and Nutrition Survey (NHANES).
The assessment of dissolved oxygen (DO) concentration at the sea surface is essential for comprehending the global ocean oxygen cycle and associated environmental and biochemical processes as it serves as the primary site for photosynthesis and sea-air exchange. However, limited comprehensive measurements and imprecise numerical simulations have impeded the study of global sea surface DO and its relationship with environmental challenges. This paper presents a novel spatiotemporal information embedding machine-learning framework that provides explanatory insights into the underlying driving mechanisms.
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