A hybrid self-supervised model predicting life satisfaction in South Korea.

Objective: Life satisfaction pertains to an individual's subjective evaluation of their life quality, grounded in their personal criteria. It stands as a crucial cognitive aspect of subjective wellbeing, offering a reliable gauge of a person's comprehensive wellbeing status. In this research, our objective is to develop a hybrid self-supervised model tailored for predicting individuals' life satisfaction in South Korea. Methods: We employed the Busan Metropolitan City Social Survey Data in 2021, a comprehensive dataset compiled by the Big Data Statistics Division of Busan Metropolitan City. After preprocessing, our analysis focused on a total of 32,390 individuals with 51 variables. We developed the self-supervised pre-training TabNet model as a key component of this study. In addition, we integrated the proposed model with the Local Interpretable Model-agnostic Explanation (LIME) technique to enhance the ease and intuitiveness of interpreting local model behavior. Results: The performance of our advanced model surpassed conventional tree-based ML models, registering an AUC of 0.7778 for the training set and 0.7757 for the test set. Furthermore, our integrated model simplifies and clarifies the interpretation of local model actions, effectively navigating past the intricate nuances of TabNet's standard explanatory mechanisms. Conclusion: Our proposed model offers a transparent understanding of AI decisions, making it a valuable tool for professionals in the social sciences and psychology, even if they lack expertise in data analytics.

Characteristics of lymph node metastasis and short-term outcome of esophageal squamous-cell carcinoma undergoing minimally invasive esophagectomy: a prospective cross-sectional study (with video).

Introduction: Surgery for esophageal squamous-cell carcinoma (ESCC) presents many potential challenges owing to malignant lymph node metastasis, complex procedures and severe postoperative complications. The appropriate lymphadenectomy for ESCC remains controversial. This study aims to evaluate the characteristics of lymph node metastasis and postoperative complications in patients with ESCC undergoing minimally invasive esophagectomy and extended two-field lymph node dissection. Patients and methods: This prospective, single-center, cross-sectional study was conducted from October 2022 to May 2024. All patients with ESCC who underwent minimally invasive esophagectomy and extended two-field lymph node dissection were selected for this study. Postoperative lymph nodes were divided into upper thoracic, middle thoracic, lower thoracic and abdominal lymph node groups. Results: Seventy-four patients with ESCC, including 49 patients who underwent upfront surgery and 25 patients who received preoperative chemoradiotherapy, were selected. The rate of lymph node metastasis in all patients was 39.2%, with 13.6% of patients having upper thoracic metastasis. The factors affecting the rate of lymph node metastasis included preoperative chemoradiotherapy, tumor stage, poor differentiation, lymphovascular/perineural invasion, and tumor size greater than 2 cm, all of which were significantly different (P<0.05). Common postoperative complications included pneumonia (25.7%), recurrent laryngeal nerve (RLN) palsy (10.8%) and anastomotic leak (4.1%). There were no cases required conversion to open surgery, nor any deaths within 90 days postoperatively. Conclusion: Lymph node metastasis in esophageal squamous-cell carcinoma has a high incidence, occurs in the early stages, and is widely distributed in all regions of the mediastinum and abdomen. Minimally invasive esophagectomy and extended two-field lymph node dissection are feasible and safe, with low complication rates.

Preparation strategies, properties highlights, and emerging applications across environmental, biological, and energy industries of silver-loaded graphitic carbon nitride: A critical review.

In light of escalating environmental pollution and tremendous energy shortage, the development of multifunctional materials with diverse applications across biomedical and energy production platforms has become imperative. Among this domain, nanostructured heterogeneous composites based on semiconductors are exclusively promising owing to their distinct configurations. Notably, graphitic carbon nitride (g-C3N4 (CN)) has drawn substantial interest as a sustainable candidate with surface functionality, electron-rich nature, and interconnected conjugation system along the polymeric matrix. To address the remaining limitations in sub-optimal visible light absorption and rapid charge recombination, the decoration of plasmonic metals, particularly silver (Ag) nanostructures, on bare CN has been reported to induce considerable synergistic promotions. This review highlights the major advancements and challenges in designing silver-loaded graphitic carbon nitride (Ag/CN (ACN)). Fundamentals in typical synthetic strategies, such as hydrothermal, co-precipitation, or chemical reduction, for ACN heterostructures are summarized. The appearance of Ag also influences the inherent properties of CN, as emphasized through alterations in structural as well as electronic behaviors in many studies. We expect that this study can deepen insights into multiple extending applications of ACN regarding environmental, biological, and energy industries, thanks to its favorable well-rounded attributions.

Leveraging explainable machine learning for enhanced management of lake water quality.

Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads, particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic life and public health. Using a large (1800 km2) subtropical lake as an example (Lake Okeechobee, Florida, USA), this study aims to (1) predict key water quality parameters using machine learning (ML) algorithms based on easily measurable variables, (2) identify spatial patterns of these parameters, and (3) determine environmental drivers influencing turbidity levels. The study employs four ML algorithms-Extreme Gradient Boosting (XGB), Light Gradient-Boosting Machine (LGBM), Support Vector Regression (SVR), and Random Forests (RFs)-to predict total phosphorus (TP), total nitrogen (TN), nitrate + nitrite (NOx-N), and turbidity, via station-specific and lake-wide modeling approaches. The station-specific models uncover spatial patterns, while the lake-wide models support operational decision-making. Results indicated that lake stage (water level), water temperature, and, most notably, turbidity were the main nutrient predictors, with XGB demonstrating superior prediction performance. Spatial analysis using K-means clustering identified three distinct lake regions based on nutrient levels and turbidity. Due to its importance, SHapley Additive exPlanations (SHAP) were employed to identify and quantify environmental factors affecting turbidity. Inflows and lake stage were found as primary drivers of turbidity near lake inlets, while wind speed and air temperature affected turbidity in the middle of the lake. This research advances the understanding of lake water quality dynamics, emphasizing the importance of frequent monitoring of turbidity and its environmental drivers for enhanced management and future mitigation efforts.

Design and implementation of a field robot using a parallelogram mechanism.

To meet various industrial requirements such as ease of motion, scalability, and cost efficiency, it is necessary to innovate the design of robotic platforms. In this research, a novel approach, from mechanical design to control implementation, is introduced for launching a robotic platform using a parallelogram mechanism. First, a reverse engineering process is applied, progressing from kinematics to dynamics. Then, several mechanical computations are conducted to ensure the structural stability of the robot framework. Subsequently, the dynamic performance of the system is analyzed, focusing on the driving torque and moments in each link. Additionally, the electrical design and transfer function of each joint are identified to ensure practical execution. To validate the effectiveness and feasibility of the design, both numerical simulations and experimental tests are performed. Theoretical results show the dynamic response of the proposed method, particularly in terms of the driving moments of the robotic joints. In real-world tests, various trajectories, such as different rectangular paths, are demonstrated to showcase the robot's capabilities. From these results, it is clear that the proposed approach is both feasible and applicable in practical scenarios.

The attitude, intention, and related factors of purchasing antibiotics without prescription: a survey in Vietnam.

Background: The abuse of antibiotics is a global problem, and the form of abuse varies among different countries and cultures. The study explored antibiotic self-medication attitudes and intentions to use antibiotics among the public in Can Tho City, Vietnam. Study design: Questionnaire survey on a sample of volunteers. Methods: Between February and August 2023, a paper-based questionnaire survey was conducted among the public in 4 districts of Can Tho City, Vietnam. The data was analyzed with SPSS version 20.0. Descriptive and analytical statistics using multivariate logistic regression analysis were performed to identify the factors associated with antibiotic self-medication. Results: Of the 414 people interviewed, 56% were female, and the majority were aged 30-45 (48.49%). People with a university pro-fessional degree accounted for 39.4%, of whom 10.6% were the medical staff. The overall average score on attitude was 4.43±1.589 (on a 10-point scale), and 85.7% of people had inappropriate attitudes. Average scores of the indicators (a) Positive attitude towards the use of non-prescription antibiotics, (b) Negative attitude towards the use of non-prescription antibiotics, (c) Subjective norms, (d) Perceived behavioral control, and (e) Intention to purchase antibiotics without a prescription were 3.73±0.043, 2.29±0.944, 4.36±1.45, 3.4±1.027, and 3.63±1.145, respectively. The rate of people intending to buy non-prescribed antibiotics was 63.8%. Factors related to people's intention to purchase antibiotics without a prescription included place of residence, education level, occupation, and income. All three factors, attitude, subjective norm, and perceived behavioral control, impacted the intention to buy non-prescription antibiotics, of which the subjective norm factor had the most substantial impact. Conclusions: The rate of people having incorrect attitudes about antibiotics, leading to the intention to buy antibiotics without a prescription, was relatively high. Factors affecting people's intention to purchase non-prescribed antibiotics included factors related to the impact of other people around them and factors originating from themselves.

Clustering for mitigating subject variability in driving fatigue classification using electroencephalography source-space functional connectivity features.

While Electroencephalography (EEG)-based driver fatigue state classification models have demonstrated effectiveness, their real-world application remains uncertain. The substantial variability in EEG signals among individuals poses a challenge in developing a universal model, often necessitating retraining with the introduction of new subjects. However, obtaining sufficient data for retraining, especially fatigue data for new subjects, is impractical in real-world settings. In response to these challenges, this paper introduces a hybrid solution for fatigue detection that combines clustering with classification. Unsupervised clustering groups subjects based on their EEG functional connectivity in an alert state, and classification models are subsequently applied to each cluster for predicting alert and fatigue states. Results indicate that classification on clusters achieves higher accuracy than scenarios without clustering, suggesting successful grouping of subjects with similar functional connectivity characteristics through clustering, thereby enhancing the classification process. Furthermore, the proposed hybrid method ensures a practical and realistic retraining process, improving the adaptability and effectiveness of the fatigue detection system in real-world applications. .

Adult day programs and their effects on individuals with dementia and their caregivers (ADAPT-DemCare): a realist synthesis to develop program theories on the how and why.

BACKGROUND: Adult day programs aim to facilitate aging in place by supporting the health and well-being of persons with dementia and providing respite to their caregivers. However, studies on the effects of day programs are inconclusive, and we especially lack insights into the context conditions and mechanisms of day programs that may produce different outcomes for different groups of persons with dementia and their caregivers. Our objective was to conduct a realist review, synthesizing research on day programs to develop program theories explaining how and why day programs do or do not produce positive or negative outcomes for different groups of persons with dementia, and caregivers. METHODS: We identified 14 literature reviews (including 329 references published between 1975 and 2021) on adult day programs. From this initial pool of studies, we will include those that focused on day program attendees with dementia or meaningful cognitive impairment, and/or their caregivers, and that report how day program contexts (C) and mechanisms (M) bring about outcomes (O) for attendees and caregivers. We will extract CMO statements (i.e., narratives that explain how and why day programs do or do not bring about certain outcomes for whom and under what circumstances). Using additional focused searches, citation mapping, citation tracking, and discussions with our researcher and expert team members, we will identify additional references. CMO statements will be synthesized, transformed into hypotheses, and linked and visualized to form program theories. Using focus groups and the James Lind Alliance Priority Setting Partnership method, we will discuss and prioritize our CMO statements and refine our program theories with 32 experts (older adults, caregivers, Alzheimer societies, caregiver organizations, day program staff and managers, and health system and policy decision makers). DISCUSSION: By identifying essential elements and processes of day programs and related knowledge gaps, this study will generate much-needed knowledge to leverage the full potential of day programs so they can provide appropriate care, preventing premature institutionalization, and unnecessary acute and primary care use. This will ultimately improve the quality of life of persons with dementia and their caregivers, alleviate caregiver burden, and reduce social costs. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42024504030.

Routine intercostal artery reattachment strategy reduces delayed and permanent spinal cord injury after open descending thoracic and thoracoabdominal aortic aneurysm repair.

Objective: During open descending thoracic and thoracoabdominal aortic aneurysm (DTAA/TAAA) repair, we used a routine T8-T12 intercostal artery (ICA) reattachment strategy from July 2004 to June 2009 and after 2017, we used a selective ICA reattachment strategy (reattaching T8-T12 ICAs only when neuromonitor signals were lost) from July 2009 to 2016. This study reviewed our nearly 2-decade experience to assess the impact of 2 ICA reattachment strategies on spinal cord injury (SCI). Methods: All open DTAA/TAAA repairs performed from July 2004 to June 2022 were included, except for cases without intraoperative cerebral spinal fluid drainage. Perioperative data were reviewed. Univariable and multivariable analyses and propensity matching for risk-adjusted effects of 2 strategies for ICA reattachment on SCI were used. Results: In all, 375 patients were operated on with selective strategy and 584 with routine strategy. Age and prevalence of rupture and redo were similar in the 2 groups. The rate of operative mortality and immediate SCI was also similar (selective vs routine: mortality, 12.5% vs 12.3%; immediate SCI, 3.2% vs 2.2%). However, the incidence of delayed and permanent SCI was increased in the selective group (delayed, 10.4% vs 6.9%; permanent, 8.5% vs 5.3%). Multivariable analyses demonstrated selective strategy was a predictor of delayed and permanent SCI, along with TAAA extent II/III, and older age. Conclusions: Two strategies of ICA reattachment did not impact the incidence of immediate SCI, which was infrequent, but the selective strategy was associated with greater rates of delayed permanent SCI. Reattachment of the ICAs within T8-T12 should be performed during open DTAA/TAAA.

Alterations in aortic elasticity indices among type 2 diabetes patients in a low and middle income country using M-mode echocardiography: A cross-sectional comparative study.

BACKGROUND: Diabetes is one of the leading causes of noncommunicable diseases worldwide. It is known to induce cardiovascular remodeling, which can result in a variety of complications, including a considerable increase in aortic stiffness. While studies in Western populations have explored these effects, data on Asians, mainly Vietnamese, are limited. This study aimed to assess aortic elasticity in type 2 diabetes mellitus (T2DM) patients compared to healthy individuals. METHODS: This quantitative, cross-sectional study compared aortic elasticity indices between individuals with T2DM and healthy controls in Vietnam. Aortic elasticity indices were assessed for all participants using M-mode echocardiography. RESULTS: A comparison between the healthy and T2DM groups revealed substantial differences in aortic elasticity indices. The aortic stiffness index (ASI) was significantly greater in the T2DM group than in the control group, with median values of 6.10 (3.64-12.47) and 3.79 (2.40-8.50), respectively (p = 0.003). Aortic strain (AS) was substantially lower in the T2DM group than in the control group, with median values of 8.21% (4.24-13.07) and 10.66% (6.01-18.23), respectively (p = 0.039). Furthermore, the median aortic compliance (AC, 10-2mm/mmHg) and aortic distensibility (AD, 10-3mmHg-1) in individuals with T2DM were 4.07 (2.28-7.44) and 3.08 (1.57-5.26), respectively, lower than those in the control group, with median values of 6.40 (3.08-10.75) and 5.33 (2.80-9.79). A longer diabetes duration was linked to a greater ASI (r = 0.43, p < 0.05), while the AS decreased (r = -0.37, p < 0.05). CONCLUSIONS: Substantial variations in aorta elasticity indices were found in patients with T2DM using M-mode echocardiography. These differences highlight the impact of T2DM on vascular health. More research is needed to investigate the consequences of these discrepancies and their significance for clinical purposes.

Contrasted agronomical and physiological responses of five Coffea arabica genotypes under soil water deficit in field conditions.

Introduction: Breeding programs have developed high-yielding Coffea arabica F1-hybrids as an adaptation against adverse conditions associated with climate change. However, theresponse to drought of coffee F1 hybrids has seldom been assessed. Methods: A trial was established with five C. arabica genotypes (2 pure lines: Catimor and Marsellesa and 3 F1 hybrids: Starmaya, Centroamericano and Mundo Maya) planted under the leguminous tree species Leuceana leucocephala. Coffee growth, yield and physiological responses were assessed under a rain-fed (control: CON) and a rainfall reduction treatment (RR) for 2 years. Results: The RR treatment created a long-term rainfall deficit in a region with suboptimal temperature similar to those predicted by climate change scenarios. Moreover, the RR treatment reduced soil water content by 14% over 2 successive years of production and increased hydric stress of the three F1-hybrids (leaf water potentials averaged -0.8 MPa under RR compared with -0.4 MPa under CON). Under RR, coffee yields were reduced from 16 to 75% compared to CON. Mundo Maya F1 hybrid was the sole high-yielding genotype apable of sustaining its yield under RR conditions. Our results suggested that its significant increase in fine root density (CON = 300 and RR = 910 root.m-2) and its maintenance of photosynthetic rate (2.5 - 3.5 mmol CO2 m-2 s-1) at high evaporative demand might explain why this genotype maintained high yield under RR condition. Discussion: This work highlights a possible drought tolerance mechanism in fruit bearing adult coffee trees where the plant fine root number increases to intake more water in order to preserve turgor and sustainphotosynthesis at high ETo and therefore conserves high yield in dry conditions.

Different forms of fablab organization and their impact on collaboration and innovation.

The aim of this paper is to identify some of the characteristics of innovation and collective work in different fablab organizations. We first define fablabs through a review of literature, situating related questions in the field of ergonomics and focusing our point of view on individual and collective activity. Secondly, we show how the results of our qualitative analyses (performed on data from interviews and observations of fablab managers, users, and projects from 13 fablabs) reveal 3 main types of fablab organization: community-oriented fablabs, academic fablabs and industrial fablabs, in which different activities are carried out. Fablab activity depends on lab users and the type of design projects carried out. The discussion will focus on the fablab organization findings, including the links between design/innovation project work, collective work and evolving rules, and how all of these aspects might direct activity-centered ergonomics research and actions in the future.

Harnessing graph state resources for robust quantum magnetometry under noise.

Precise measurement of magnetic fields is essential for various applications, such as fundamental physics, space exploration, and biophysics. Although recent progress in quantum engineering has assisted in creating advanced quantum magnetometers, there are still ongoing challenges in improving their efficiency and noise resistance. This study focuses on using symmetric graph state resources for quantum magnetometry to enhance measurement precision by analyzing the estimation theory under time-homogeneous and time-inhomogeneous noise models. The results show a significant improvement in estimating both single and multiple Larmor frequencies. In single Larmor frequency estimation, the quantum Fisher information spans a spectrum from the standard quantum limit to the Heisenberg limit within a periodic range of the Larmor frequency, and in the case of multiple Larmor frequencies, it can exceed the standard quantum limit for both noisy cases. This study highlights the potential of graph state-based methods for improving magnetic field measurements under noisy environments.

Challenges in Retrieving Patterns from Generic Data Structures in Clinical Systems - A Technical Case Report.

INTRODUCTION: The secondary use of data in clinical environments offers significant opportunities to enhance medical research and practices. However, extracting data from generic data structures, particularly the Entity-Attribute-Value (EAV) model, remains challenging. This study addresses these challenges by developing a methodological approach to convert EAV-based data into a format more suitable for analysis. BACKGROUND: The EAV model is widely used in clinical information systems due to its adaptability, but it often complicates data retrieval for research purposes due to its vertical data structure and dynamic schema. OBJECTIVE: The objective of this study is to develop a methodological approach to address the handling of these generic data structures, Methods: We introduce a five-step methodological approach: 1) understanding the specific clinical processes to determine data collection points and involved roles; 2) analysing the data source to understand the data structure and metadata; 3) reversing a use-case-specific data structure to map the front-end data input to its storage format; 4) analysing the content to identify medical information and establish connections; and 5) managing schema changes to maintain data integrity. RESULTS: Applying this method to the hospital information system has shown that EAV-based data can be converted into a structured format, suitable for research. This conversion reduced data sparsity and improved the manageability of schema changes without affecting other classes of data. CONCLUSION: The developed approach provides a systematic method for handling complex data relationships and maintaining data integrity in clinical systems using EAV models. This approach facilitates the secondary use of clinical data, enhancing its utility for medical research and practice.

Expanding the CRISPR base editing toolbox in Drosophila melanogaster.

CRISPR base editors can introduce point mutations into DNA precisely, and cytosine base editors (CBEs) catalyze C to T transitions. While CBEs have been thoroughly explored in cell culture and organisms such as mice, little is known about DNA base editing in insects. In this study, we evaluated germline editing rates of three different CBEs expressed under actin (ubiquitous) or nanos (germline) promoters utilizing Drosophila melanogaster. The original Rattus norvegicus-derived cytosine deaminase APOBEC1 (rAPO-1) displayed high base editing rates (~99%) with undetectable indel formation. Additionally, we show that base editors can be used for generating male sterility and female lethality. Overall, this study highlights the importance of promoter choice and sex-specific transmission for efficient base editing in flies while providing new insights for future genetic biocontrol designs in insects.

Role of HLA-B*58:01-restricted CD8+ T cells in HIV-1 subtype AE infection.

HLA-B*58:01 and HLA-B*57 are protective alleles against HIV-1 subtype B or C infection whereas these HLA alleles have not been reported as protective in HIV-1 subtype AE infection. Although HLA-B*58:01-restricted and HLA-B*57-restricted HIV-1-specific CD8+ T cells have been thoroughly analyzed in subtype B or C infection, they have only been partially analyzed in subtype AE infection. We identified six HLA-B*58:01-restricted subtype AE epitopes in Vietnamese individuals infected with subtype AE. HLA-B*58:01-restricted T-cell responses to Gag epitopes, which may control disease progression in HLA-B*58:01+ and HLA-B*57+ individuals infected with subtype B or C, were not protective in subtype AE infection. These findings suggest that the loss of HLA-B*58:01-restricted T cells specific for some Gag epitopes and/or their reduced ability may account for the lack of protective effects conferred by HLA-B*58:01 in subtype AE infection.

May-Thurner syndrome managed with catheter-directed thrombolysis and stent placement: A cases report.

Chronic compression of the left common iliac vein (CIV) by the right common iliac artery (CIA) or May-Thurner syndrome is rare and could be challenging to diagnose. The phenomenon results in chronic left lower extremity vein thrombosis. In this report, we present a 33-year-old female with pain and swelling in her left inner thigh for 2 days. She denied any systemic signs or any remarkable past medical history. Doppler ultrasonography revealed large blood clots extending from the left femoral and great saphenous veins to the upper part of the external iliac vein, causing a nearly complete obstruction. CT venography showed compression of the left CIV near the confluence by the right CIA and the lumbar vertebrae L4. She was managed by catheter-directed thrombolysis with alteplase via a superior vena cava catheter. Subsequently, a left CIV self-expanding stent was successfully placed. Follow-up demonstrated a positive outcome without any complications.

YOLOv7-based automated detection platform for scalp lesions.

Objective: In dermatological research, the focus on scalp and skin health has intensified, particularly regarding prevalent conditions like dandruff and erythema. This study aimed to utilize YOLOv7 model to develop an automated detection web-based system for these specific scalp lesions. Methods: Utilizing a dataset of 2200 clinical images, the model's accuracy and robustness were assessed. The raw images were initially preprocessed by the Roboflow tool. We then trained and evaluated the YOLOv7 model, comparing its performance with several baseline models including YOLOv5, YOLOF, and the single-shot detector. Finally, the proposed model was integrated into a flask API-based web application using the flask-ngrok library. Results: The YOLOv7 demonstrated exceptional performance, attaining a mean average precision of 98.6%, with precision and recall rates of 98.6% and 97.2%, respectively. When benchmarked against baseline models, the YOLOv7 demonstrated enhanced performance metrics both during the training phase and the testing process on unseen data. Conclusions: This study not only validates the potential of YOLOv7 for scalp lesion diagnostic applications but also brings the integration of sophisticated AI models into practical healthcare solutions.

EXploring Patterns of Use and Effects of Adult Day Programs to Improve Trajectories of Continuing Care (EXPEDITE): Protocol for a Retrospective Cohort Study.

BACKGROUND: Adult day programs provide critical supports to older adults and their family or friend caregivers. High-quality care in the community for as long as possible and minimizing facility-based continuing care are key priorities of older adults, their caregivers, and health care systems. While most older adults in need of care live in the community, about 10% of newly admitted care home residents have relatively low care needs that could be met in the community with the right supports. However, research on the effects of day programs is inconsistent. The methodological quality of studies is poor, and we especially lack robust, longitudinal research. OBJECTIVE: Our research objectives are to (1) compare patterns of day program use (including nonuse) by province (Alberta, British Columbia, and Manitoba) and time; (2) compare characteristics of older adults by day program use pattern (including nonuse), province, and time; and (3) assess effects of day programs on attendees, compared with a propensity score-matched cohort of older nonattendees in the community. METHODS: In this population-based retrospective cohort study, we will use clinical and health administrative data of older adults (65+ years of age) who received publicly funded continuing care in the community in the Canadian provinces of Alberta, British Columbia, and Manitoba between January 1, 2012, and December 31, 2024. We will compare patterns of day program use between provinces and assess changes over time. We will then compare characteristics of older adults (eg, age, sex, physical or cognitive disability, area-based deprivation indices, and caregiver availability or distress) by pattern of day program use or nonuse, province, and time. Finally, we will create a propensity score-matched comparison group of older adults in the community, who have not attended a day program. Using time-to-event models and general estimating equations, we will assess whether day program attendees compared with nonattendees enter care homes later; use emergency, acute, or primary care less frequently; experience less cognitive and physical decline; and have better mental health. RESULTS: This will be a 3-year study (July 1, 2024, to June 30, 2027). We received ethics approvals from the relevant ethics boards. Starting on July 1, 2024, we will work with the 3 provincial health systems on data access and linkage, and we expect data analyses to start in early 2025. CONCLUSIONS: This study will generate robust Canadian evidence on the question whether day programs have positive, negative, or no effects on various older adult and caregiver outcomes. This will be a prerequisite to improving the quality of care provided to older adults in day programs, ultimately improving the quality of life of older adults and their caregivers. TRIAL REGISTRATION: ClinicalTrials.gov NCT06440447; https://clinicaltrials.gov/study/NCT06440447. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/60896.

Antimicrobial Resistance Patterns of Pathogens Isolated from Patients with Wound Infection at a Teaching Hospital in Vietnam.

Purpose: At a teaching Hospital in Vietnam, the persistently high incidence of diagnosed wound infection poses ongoing challenges to treatment. This study seeks to explore the causative agents of wound infection and their antimicrobial and multidrug resistance patterns. Methods: A cross-sectional study was conducted at the Department of Microbiology, Military Hospital 103, Vietnam. Data on microorganisms that caused wound infection and their antimicrobial resistance patterns was recorded from hospitalized patients from 2014 to 2021. Using the chi-square test, we analyzed the initial isolation from wound infection specimens collected from individual patients. Results: Over a third (34.9%) of wound infection samples yielded bacterial cultures. Staphylococcus aureus was the most prevalent bacteria, followed by Pseudomonas aeruginosa. Worryingly high resistance rates were observed for several antibiotics, particularly among Gram-negative bacteria. Ampicillin displayed the highest resistance (91.9%), while colistin and ertapenem remained the most effective. In Gram-positive bacteria, glycopeptides like teicoplanin and vancomycin (0% and 3.3% resistance, respectively) were most effective, but their use was limited. Clindamycin and tetracycline showed decreasing effectiveness. Resistance rates differed between surgical and non-surgical wards, highlighting the complex dynamics of antimicrobial resistance within hospitals. Multidrug resistance (MDR) was substantial, with Gram-negative bacteria exhibiting a 63.6% MDR rate. Acinetobacter baumannii showed the highest MDR rate (88.0%). Conclusion: This study investigated wound infection characteristics, antibiotic resistance patterns of common bacteria, and variations by hospital ward. S. aureus was the most prevalent bacteria, and concerning resistance rates were observed, particularly among Gram-negative bacteria. These findings highlight the prevalence of multidrug resistance in wound infections, emphasizing the importance of infection control measures and judicious antibiotic use.