295 research outputs found
Mobile Health for Cardiovascular Disease: The New Frontier for AF Management: Observations from the Huawei Heart Study and mAFA-II Randomised Trial.
Route Selection and Distribution Cost of Express Delivery: An Urban Metro Network Based Study
Route selection and distribution costs of express delivery based on the urban metro network, referred to as metro express delivery (MeD), is addressed in this study. Considering the characteristics of express delivery transportation and the complexity of the urban metro network, three distribution modes of different time periods are proposed and a strict integrated integer linear programming model is developed to minimize total distribution costs. To effectively solve the optimal problem, a standard genetic algorithm was improved and designed. Finally, the Ningbo subway network is used as an example to confirm the practicability and effectiveness of the model and algorithm. The results show that when the distribution number of express delivery packages is 1980, the three different MeD modes can reduce transportation costs by 40.5%, 62.0%, and 59.0%, respectively. The results of the case analysis will help guide express companies to collaborate with the urban metro network and choose the corresponding delivery mode according to the number of express deliveries required
Consumer-Led Screening for Atrial Fibrillation:A Report From the mAFA-II Trial Long-Term Extension Cohort
BACKGROUND: There are limited data on mobile health detection of prevalent atrial fibrillation (AF) and its related risk factors over time. OBJECTIVES: This study aimed to report the trends on prevalent AF detection over time and risk factors, with a consumer-led photoplethysmography screening approach. METHODS: 3,499,461 subjects aged over 18 years, who use smart devices (Huawei Technologies Co.) were enrolled between October 26, 2018, and December 1, 2021. RESULTS: Among 2,852,217 subjects for AF screening, 12,244 subjects (0.43%; 83.2% male, mean age 57 ± 15 years) detected AF episodes. When compared with 2018, the risk (adjusted HRs, 95% CI) for monitored prevalent AF increased significantly for subjects when monitoring started in 2020 (adjusted HR: 1.34; 95% CI: 1.27-1.40; P 93% confirmation of detected AF episodes even for the low-risk general population, highlighting the increased risk for detecting prevalent AF and the need for modification of OSA that increase AF susceptibility. (Mobile Health [mHealth] Technology for Improved Screening, Patient Involvement and Optimizing Integrated Care in Atrial Fibrillation [mAFA (mAF-App) II study]; ChiCTR-OOC-17014138
The Effects of Implementing a Mobile Health-Technology Supported Pathway on Atrial Fibrillation-Related Adverse Events Among Patients With Multimorbidity:The mAFA-II Randomized Clinical Trial
IMPORTANCE: The Mobile Health Technology for Improved Screening and Optimized Integrated Care in Atrial Fibrillation (mAFA-II) trial is a prospective cluster randomized trial that found a significant reduction in the composite clinical outcome of stroke or thromboembolism, all-cause death, and rehospitalization among patients with atrial fibrillation (AF) who used a mobile health (mHealth) technology that implemented the Atrial Fibrillation Better Care (ABC) pathway (ie, A, anticoagulation/avoid stroke; B, better symptom control; and C, cardiovascular disease and comorbidity management) compared with those receiving usual care. Multimorbidity (defined as ≥2 chronic long-term conditions) is common in older patients with AF, but the impact of integrated or holistic care (based on the ABC pathway) on clinical outcomes in this population is uncertain. OBJECTIVE: To evaluate whether implementation of the integrated ABC pathway, supported by mHealth technology, would reduce AF-related adverse events in patients with multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: This prespecified ancillary analysis of data from the extended follow-up of the mAFA II trial was conducted between June 2018 and April 2021. Adult patients with AF were included in the analysis if they had at least 2 comorbidities. Participants were enrolled across 40 centers in China. INTERVENTION: Integrated care supported by mHealth technology (mAFA intervention) vs usual care. MAIN OUTCOMES AND MEASURES: The main outcome was the composite outcome of stroke or thromboembolism, all-cause death, and rehospitalization. Cox proportional hazard modeling was performed for adverse outcomes after adjusting for cluster effect and baseline risk factors. RESULTS: Of 1890 patients, 833 (mean [SD] age, 72.0 [12.0] years; 278 [33.4%] women) with multimorbidity were allocated to the intervention group (ABC pathway), with a mean (SD) follow-up of 419 (257) days, and 1057 patients (mean [SD] age, 72.8 [13.0] years; 443 [41.9%] women) with multimorbidity were allocated to usual care, with a mean (SD) follow-up of 457 (154) days. Compared with usual care, the composite outcome of stroke or thromboembolism, all-cause death, and rehospitalization was significantly reduced in the intervention group (hazard ratio [HR], 0.37; 95% CI, 0.26-0.53; P < .001), as were rehospitalizations alone (HR, 0.42; 95% CI, 0.27-0.64; P < .001). For the C criterion of the ABC pathway, rates of acute coronary syndrome, heart failure, and uncontrolled blood pressure during follow-up were lower in the intervention group than the usual care group (27 patients [3.2%] vs 145 patients [13.7%]; HR, 0.29; 95% CI, 0.19-0.45; P < .001). Subgroup analyses by age, prior stroke, and sex demonstrated consistently lower HRs for the primary composite outcome and rehospitalization for patients with AF allocated to the intervention group compared with patients receiving usual care. CONCLUSIONS AND RELEVANCE: In this study, mHealth technology–based integrated care that facilitated the implementation of the ABC pathway reduced meaningful clinical adverse events in older patients with AF and multimorbidity vs usual care. TRIAL REGISTRATION: WHO International Clinical Trials Registry Platform (ICTRP) Registration number: ChiCTR-OOC-1701413
Cystatin C and risk of new-onset depressive symptoms among individuals with a normal creatinine-based estimated glomerular filtration rate: A prospective cohort study
The association between cystatin C and depressive symptoms in the general population has not been thoroughly elucidated to date. We investigated the association of cystatin C with new-onset depressive symptoms among individuals with normal creatinine-based estimated glomerular filtration rates (eGFR). In the China Health and Retirement Longitudinal Study, 5111 participants without depressive symptoms or renal dysfunction (eGFR \u3c 60 ml/min/1.73
EVE: Efficient zero-shot text-based Video Editing with Depth Map Guidance and Temporal Consistency Constraints
Motivated by the superior performance of image diffusion models, more and
more researchers strive to extend these models to the text-based video editing
task. Nevertheless, current video editing tasks mainly suffer from the dilemma
between the high fine-tuning cost and the limited generation capacity. Compared
with images, we conjecture that videos necessitate more constraints to preserve
the temporal consistency during editing. Towards this end, we propose EVE, a
robust and efficient zero-shot video editing method. Under the guidance of
depth maps and temporal consistency constraints, EVE derives satisfactory video
editing results with an affordable computational and time cost. Moreover,
recognizing the absence of a publicly available video editing dataset for fair
comparisons, we construct a new benchmark ZVE-50 dataset. Through comprehensive
experimentation, we validate that EVE could achieve a satisfactory trade-off
between performance and efficiency. We will release our dataset and codebase to
facilitate future researchers
Fine-tuning vision foundation model for crack segmentation in civil infrastructures
Large-scale foundation models have become the mainstream deep learning
method, while in civil engineering, the scale of AI models is strictly limited.
In this work, a vision foundation model is introduced for crack segmentation.
Two parameter-efficient fine-tuning methods, adapter and low-rank adaptation,
are adopted to fine-tune the foundation model in semantic segmentation: the
Segment Anything Model (SAM). The fine-tuned CrackSAM shows excellent
performance on different scenes and materials. To test the zero-shot
performance of the proposed method, two unique datasets related to road and
exterior wall cracks are collected, annotated and open-sourced, for a total of
810 images. Comparative experiments are conducted with twelve mature semantic
segmentation models. On datasets with artificial noise and previously unseen
datasets, the performance of CrackSAM far exceeds that of all state-of-the-art
models. CrackSAM exhibits remarkable superiority, particularly under
challenging conditions such as dim lighting, shadows, road markings,
construction joints, and other interference factors. These cross-scenario
results demonstrate the outstanding zero-shot capability of foundation models
and provide new ideas for developing vision models in civil engineering
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs
The integration of large language models (LLMs) and search engines represents
a significant evolution in knowledge acquisition methodologies. However,
determining the knowledge that an LLM already possesses and the knowledge that
requires the help of a search engine remains an unresolved issue. Most existing
methods solve this problem through the results of preliminary answers or
reasoning done by the LLM itself, but this incurs excessively high
computational costs. This paper introduces a novel collaborative approach,
namely SlimPLM, that detects missing knowledge in LLMs with a slim proxy model,
to enhance the LLM's knowledge acquisition process. We employ a proxy model
which has far fewer parameters, and take its answers as heuristic answers.
Heuristic answers are then utilized to predict the knowledge required to answer
the user question, as well as the known and unknown knowledge within the LLM.
We only conduct retrieval for the missing knowledge in questions that the LLM
does not know. Extensive experimental results on five datasets with two LLMs
demonstrate a notable improvement in the end-to-end performance of LLMs in
question-answering tasks, achieving or surpassing current state-of-the-art
models with lower LLM inference costs.Comment: Accepted by ACL 2024 main conference. Repo:
https://github.com/plageon/SlimPL
Temporal and bidirectional association between blood pressure variability and arterial stiffness: Cross-lagged cohort study
BACKGROUND: The causal relationship between blood pressure variability (BPV) and arterial stiffness remains debated. OBJECTIVE: This study aimed to explore the temporal and bidirectional associations between long-term BPV and arterial stiffness using a cohort design with multiple surveys. METHODS: Participants from the Beijing Health Management Cohort who underwent health examinations from visit 1 (2010-2011) to visit 5 (2018-2019) were enrolled in this study. Long-term BPV was defined as intraindividual variation using the coefficient of variation (CV) and SD. Arterial stiffness was measured by brachial-ankle pulse wave velocity (baPWV). The bidirectional relationship between BPV and arterial stiffness was explored using cross-lagged analysis and linear regression models, with records before and after visit 3 categorized as phase 1 and phase 2, respectively. RESULTS: Of the 1506 participants, who were a mean of 56.11 (SD 8.57) years old, 1148 (76.2%) were male. The cross-lagged analysis indicated that the standardized coefficients of BPV at phase 1 directing to the baPWV level at phase 2 were statistically significant but not vice-versa. The adjusted regression coefficients of the CV were 4.708 (95% CI 0.946-8.470) for systolic blood pressure, 3.119 (95% 0.166-6.073) for diastolic pressure, and 2.205 (95% CI 0.300-4.110) for pulse pressure. The coefficients of the SD were 4.208 (95% CI 0.177-8.239) for diastolic pressure and 4.247 (95% CI 0.448-8.046) for pulse pressure. The associations were predominant in the subgroup with hypertension, but we did not observe any significant association of baPWV level with subsequent BPV indices. CONCLUSIONS: The findings supported a temporal relationship between long-term BPV and arterial stiffness level, especially among people with hypertension
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