Heart failure medication treatment and prognosis: a retrospective cross-sectional study

ObjectiveHeart failure (HF) is a significant global public health concern and the leading cause of morbidity and mortality worldwide, imposing a substantial economic burden on society. Guideline-directed medical therapy (GDMT) refers to the standardized pharmacological treatment for specific diseases based on recommendations from authoritative clinical guidelines and evidence from large-scale randomized clinical trials. GDMT serves as the cornerstone of drug therapy for heart failure patients. This study describes hospitalized HF patients and focuses on drug prescription and readmission rates.MethodsThis study is a retrospective cross-sectional study with data from HF patients obtained from the Second Affiliated Hospital of Chongqing Medical University between January 2016 and June 2021. Patients were considered to have received GDMT if they were prescribed any guideline-recommended medication. Multilevel logistic regression was used to obtain the relationship between medication and readmission rates. The odds ratios (ORs) and 95% confidence intervals (CIs) have been reported.ResultsIn this study, a total of 5,356 HF patients (51.0% female; average age 77 years) were included. Among these patients, the most commonly used medications were mineralocorticoid receptor antagonists (MRA) (69.3%), Beta-blockers (54.2%), and lipid-lowering agents (46.0%). Currently, GDMT recommendations mainly include five types of drugs: diuretics, angiotensin receptor-neprilysin inhibitors (ARNIs), renin-angiotensin system inhibitors (ACEIs/ARBs), beta-blockers, mineralocorticoid receptor antagonists (MRAs), and sodium-glucose cotransporter-2 inhibitors (SGLT-2i). Among them, the utilization rates of ARNIs, SGLT-2i, triple therapy, and quadruple therapy are relatively low, accounting for 12.7%, 8.1%, 33.2%, and 3.75% respectively. The usage rates of these drugs are gradually increasing, especially after pharmacists participate in clinical decision-making and assist doctors in selecting therapeutic drugs, leading to a significant increase in the utilization rates of guideline-recommended drugs. Additionally, a multivariate logistic regression analysis of all drugs recommended by GDMT showed that ARBs (OR 0.681, CI 0.511–0.908), ARNIs (OR 0.191, CI 0.089–0.406), anticoagulants (OR 0.578, CI 0.403–0.829), tolvaptan (OR 0.340, CI 0.124–0.929), and SGLT-2i (OR 0.238, CI 0.058–0.969) significantly reduced the readmission rate of patients. Further subgroup analysis showed that the efficacy of the drugs varied slightly depending on the type of HF, but was consistent with guideline recommendations and clinical study results.ConclusionIn our hospital, the utilization rate of guideline-recommended drugs is gradually increasing, especially after pharmacists participate in rational drug use in clinical practice, the rate of increase is more significant, which is more in line with GDMT recommendations. Additionally, despite some limitations in our study, most of the guideline-recommended drugs show good therapeutic effects. And, we found that drugs such as SGLT-2i and ivabradine, despite their low usage rates, also demonstrate good therapeutic effects, providing significant implications for clinical decision-making

Evaluating the protective effectiveness and risk factors of ursodeoxycholic acid on COVID-19 among outpatients

Objective: This study aimed to assess the chemopreventive effect of ursodeoxycholic acid (UDCA) against COVID-19 and to analyze infection risk factors, symptoms, and recovery in outpatients with UDCA exposure.Methods: The study enrolled outpatients prescribed UDCA from the Second Affiliated Hospital of Chongqing Medical University, China, between 01 July 2022, and 31 December 2022. Data on demographics, comorbidities, and drug combinations were collected using electronic medical records. COVID-19 infection, symptoms, severity, prognosis, vaccinations, and UDCA administration were surveyed by telephone interviews. UDCA non-users served as controls and were matched in a 1:2 ratio with UDCA users using propensity score matching with the nearest neighbor algorithm. Infection rates, symptomatology, severity, and prognosis were compared between matched and control cohorts, and risk factors and infection and recovery symptoms were analyzed in UDCA-exposed outpatients.Results: UDCA-exposed outpatients (n = 778, 74.8%) and matched UDCA users (n = 95, 74.2%) showed significantly lower SARS-CoV-2 infection rates than control patients (n = 59, 92.2%) (p < 0.05). The matched UDCA group exhibited substantially lower fever, cough, sore throat, and fatigue rates than controls (p < 0.05). Participants with UDCA exposure generally experienced mild symptoms, while those without UDCA had moderate symptoms. The matched UDCA group also had significantly shorter durations of fever and cough (p < 0.05). Risk factors such as age over 60, less than 1 month of UDCA administration, diabetes mellitus, and coronary artery disease significantly increased SARS-CoV-2 infection rates (p < 0.05), while smoking led to a decrease (p < 0.05). Hypertension was associated with a prolonged COVID-19 recovery (p < 0.05), while smoking, vaccination, and fatty liver disease were associated with shorter recovery periods (p < 0.05). The main symptoms in the full UDCA cohort were fever, cough, and sore throat, with fatigue, cough, and hyposthenia being the most persistent.Conclusion: UDCA demonstrated chemopreventive effect against SARS-CoV-2 in outpatients by significantly reducing infection incidence and mitigating COVID-19 symptoms, severity, and recovery duration. Old age, short UDCA course, and comorbidities such as diabetes mellitus and CAD increased infection rates, while hypertension prolonged recovery. Smoking, vaccination, and fatty liver disease reduced infection rates and shortened recovery. UDCA had minimal impact on symptom types. Larger and longer-term clinical studies are needed further to assess UDCA’s effectiveness in COVID-19 prevention or treatment

Modulation of the optical bandgap and photoluminescence quantum yield in pnictogen (Sb3+/Bi3+)-doped organic-inorganic tin(IV) perovskite single crystals and nanocrystals

Water-stable, lead-free zero-dimensional (0D) organic-inorganic hybrid colloidal tin(IV) perovskite, A(2)SnX(6) (A is a monocationic organic ion and X is a halide) nanocrystals (NCs) with high photoluminescence (PL) quantum yield (QY) have rarely been explored. Herein, we report solution-processed colloidal NCs of blue light-emitting T2SnCl6 and orange light-emitting T2Sn1-xSbxCl6 [T+ = tetramethylammonium cation] from their corresponding single crystals (SCs). These colloidal NCs are well-dispersible in nonpolar solvents, thereby maintaining their bright emission. This paves the way for fabricating homogeneous thin films of these NCs. Due to organic cation (T+)-controlled large spin-orbit coupling (SOC), the T2Sn1-xSbxCl6 NCs exhibit bright orange emission with an enhancement in PL QY of 41% compared to their bulk counterpart. Furthermore, we explore T2Sn1-xBixCl6 and T2Sn1-x-yBixSbyCl6 SCs, which show blue and green emission, respectively; the latter is attributed to the newly formed Sb 5p and Sb 5 s orbital-driven band structures confirmed by applying density functional theory (DFT) calculations. The SCs and NCs exhibit excellent stability in water under ambient conditions because of the in-situ generation of a hydrophobic and oxygen-resistant passivating layer of oxychloride in the presence of water. Our findings open a pathway for designing lead-free perovskites materials for thin-film-based optoelectronic devices. (C) 2021 Elsevier Inc. All rights reserved

Enhanced Chinese Domain Named Entity Recognition: An Approach with Lexicon Boundary and Frequency Weight Features

Named entity recognition (NER) plays a crucial role in information extraction but faces challenges in the Chinese context. Especially in Chinese paleontology popular science, NER encounters difficulties, such as low recognition performance for long and nested entities, as well as the complexity of handling mixed Chinese–English texts. This study aims to enhance the performance of NER in this domain. We propose an approach based on the multi-head self-attention mechanism for integrating Chinese lexicon-level features; by integrating Chinese lexicon boundary and domain term frequency weight features, this method enhances the model’s perception of entity boundaries, relative positions, and types. To address training prediction inconsistency, we introduce a novel data augmentation method, generating enhanced data based on the difference set between all and sample entity types. Experiments on four Chinese datasets, namely Resume, Youku, SubDuIE, and our PPOST, show that our approach outperforms baselines, achieving F1-score improvements of 0.03%, 0.16%, 1.27%, and 2.28%, respectively. This research confirms the effectiveness of integrating Chinese lexicon boundary and domain term frequency weight features in NER. Our work provides valuable insights for improving the applicability and performance of NER in other Chinese domain scenarios

Fast and lightweight automatic lithology recognition based on efficient vision transformer network

Traditional methods of lithological classification often rely on the expertise of appraisers and the use of sophisticated measuring instruments. These methods are susceptible to staff experience and are time-consuming. To overcome these limitations, researchers have explored the use of rock images and intelligent algorithms to automatically identify rocks. However, models developed for automatic rock properties identification often require high-performance equipment that cannot be readily deployed on lightweight edge devices. To address this problem, we significantly extend our previous research and propose a method for automatic rock properties identification called SBR-EfficientViT. The method is based on an efficient vision converter and builds on our previous training framework. We also developed a training and application flow framework for the method, which can run with memory requirements of less than 720 MB and graphics memory of 1.6 GB. Furthermore, the proposed SBR-EfficientViT-M1 method achieves an impressive accuracy of 94.75%

Multiphotoluminescence from a Triphenylamine Derivative and Its Application in White Organic Light-Emitting Diodes Based on a Single Emissive Layer

White organic light-emitting diode (WOLED) technology has attracted considerable attention because of its potential use as a next-generation solid-state lighting source. However, most of the reported WOLEDs that employ the combination of multi-emissive materials to generate white emission may suffer from color instability, high material cost, and a complex fabrication procedure which can be diminished by the single-emitter-based WOLED. Herein, a color-tunable material, tris(4-(phenylethynyl)phenyl)amine (TPEPA), is reported, whose photoluminescence (PL) spectrum is altered by adjusting the thermal annealing temperature nearly encompassing the entire visible spectra. Density functional theory calculations and transmission electron microscopy results offer mechanistic understanding of the PL redshift resulting from thermally activated rotation of benzene rings and rotation of 4-(phenylethynyl) phenyl)amine connected to the central nitrogen atom that lead to formation of ordered molecular packing which improves the ??????? stacking degree and increases electronic coupling. Further, by precisely controlling the annealing time and temperature, a white-light OLED is fabricated with the maximum external quantum efficiency of 3.4% with TPEPA as the only emissive molecule. As far as it is known, thus far, this is the best performance achieved for single small organic molecule based WOLED devices

Supplemental Material - Anti-Aging of the Nervous System and Related Neurodegenerative Diseases With Chinese Herbal Medicine

Anti-Aging of the Nervous System and Related Neurodegenerative Diseases With Chinese Herbal Medicine by Xiaohui Du, Nanbin Lou, Sinan Hu, Ruopeng Xiao, Chu Chu, Qiankai Huang, Lin Lu, Shanshan Li, Jing Yang in American Journal of Alzheimer’s Disease & Other Dementias®</p