31 research outputs found

    ANALYZE THE TREATMENT REGIMENS AND THROMBOSIS PROPHYLAXIS USED IN CORONARY ARTERY INTERVENTION AT INTERVENTIONAL CARDIOLOGY UNIT IN CAN THO CENTRAL GENERAL HOSPITAL

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    Objective: The study was conducted to analyze the rationality of treatment regimens and thrombosis prophylaxis used in coronary artery intervention to compare to guidelines for treatment according to VNHA and recommendation of ACC/AHA at Interventional cardiology in Can Tho Central General Hospital. Methods: The cross-sectional study was based on the data collected from entire medical records of patients at Interventional cardiology in Can Tho Central General Hospital from August 2017 to February 2018. The rationality of the antithrombotic regimen used at the Hospital is assessed through criteria such as medical combination, dosage, time to take medicine, clinical trials during the treatment. Results: The study found that 95.6% and 90.7% were suitable for medical combination before and after PCI; 100% fit for the use of medicine; and 100% was suitable for antithrombotic agents and clinical trials during treatment time; in terms of dosage, the result showed that entrance and maintenance were 84.9% and 100% for aspirin respectively; 71.7% and 100% for clopidogrel; 100% and 94.7% for ticagrelor; 90.2-92.8% and 98.1% for enoxaparin; especially, heparin-100% anticoagulant was appropriate to recommend. Conclusion: The study showed that treatment regimens and thrombosis prophylaxis in percutaneous coronary intervention at Interventional cardiology in Can Tho Central General Hospital were quite suitable compared to the recommendations of the Heart Association. The results from the study are a scientific basis for the Hospital to maintain or consider adjustments to improve the quality of treatment, ensure the effectiveness and safety of patients

    Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

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    BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

    The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021

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    Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19.Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021 Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo.Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pit-falls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation.Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control

    Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

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    Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

    Addressing climate change with behavioral science: a global intervention tournament in 63 countries

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    Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

    Addressing climate change with behavioral science:A global intervention tournament in 63 countries

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    Internet of Things-Based Intelligent Attendance System: Framework, Practice Implementation, and Application

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    Tracking coronavirus patients and determining their close contacts (as part of COVID-19 mapping) have been huge challenges. In universities, in particular, there are many students and large gatherings who are at a higher risk of obtaining COVID-19. Many smart attendance management systems have been proposed that are based on RFID and fingerprint sensor modules, facial recognition, etc. However, these techniques operate with specific requirements, such as GPUs and large memories/datasets, or by combining recognizance and thermal cameras. To solve these issues and reduce costs, we designed an Internet of Things (IoT)-based intelligent attendance management system. In this paper, we compare the advantages/disadvantages of existing smart attendance management systems. We designed an IoT-based intelligent attendance management system based on the cloud, a web server, Google API, a non-contact body temperature sensor, and the Raspberry Pi 4 module (4G). We conducted a survey at a university and summarized the satisfaction levels of using our system

    Optimal Sliding Mode Control for Tracking Trajectory Problem of Triple Pendubot

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    Triple pendubot – which is advanced model of classical pendubot, is constructed by single input that applied to first link and three link continuous connected. This is a typical nonlinear, unstable and fast-reacting system. With its structure as a SIMO system, it is hard to be controlled by traditional sliding mode controller, especially in the case that set-point changes constantly. This paper proposes a solution mathematical improvement of Lyapunov inequality based on Sliding Mode Algorithm which was inferred in former research. After that, authors use genetic algorithm to find parameters control which are satisfied Lyapunov inequality above. Finally, we use Matlab/Simulink software to simulate system and algorithm. And obtained results are also presented to prove effective proposal
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