31 research outputs found

    What is the Real Cost of Intraoperative Floppy Iris Syndrome in Cataract Surgery?

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    This is a Letter and does not have an abstract. Please download the PDF or view the article in HTML

    Federated Learning for Early Dropout Prediction on Healthy Ageing Applications

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    The provision of social care applications is crucial for elderly people to improve their quality of life and enables operators to provide early interventions. Accurate predictions of user dropouts in healthy ageing applications are essential since they are directly related to individual health statuses. Machine Learning (ML) algorithms have enabled highly accurate predictions, outperforming traditional statistical methods that struggle to cope with individual patterns. However, ML requires a substantial amount of data for training, which is challenging due to the presence of personal identifiable information (PII) and the fragmentation posed by regulations. In this paper, we present a federated machine learning (FML) approach that minimizes privacy concerns and enables distributed training, without transferring individual data. We employ collaborative training by considering individuals and organizations under FML, which models both cross-device and cross-silo learning scenarios. Our approach is evaluated on a real-world dataset with non-independent and identically distributed (non-iid) data among clients, class imbalance and label ambiguity. Our results show that data selection and class imbalance handling techniques significantly improve the predictive accuracy of models trained under FML, demonstrating comparable or superior predictive performance than traditional ML models

    Pneumomediastinum in the COVID-19 era: to drain or not to drain?

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    Pneumomediastinum (PNM) is a rare clinical finding, usually with a benign course, which is managed conservatively in the majority of cases. However, during the COVID-19 pandemic, an increased incidence of PNM has been observed. Several reports of PNM cases in COVID-19 have been reported in the literature and were managed either conservatively or surgically. In this study, we present our institutional experience of COVID-19 associated PNM, propose a management algorithm, and review the current literature. In total, 43 Case Series were identified, including a total of 747 patients, of whom 374/747 (50.1%) were intubated at the time of diagnosis, 168/747 (22.5%) underwent surgical drain insertion at admission, 562/747 (75.2%) received conservative treatment (observation or mechanical ventilation. Inpatient mortality was 51.8% (387/747), while 45.1% of the population recovered and/or was discharged (337/747). In conclusion, with increased incidence of PNM in COVID-19 patients reported in the literature, it is still difficult to assign a true causal relationship between PNM and mortality. We can, however, see that PMN plays an important role in disease prognosis.  Due to increased complexity, high mortality, and associated complications, conservative management may not be sufficient, and a surgical approach is needed

    The MEDEA childhood asthma study design for mitigation of desert dust health effects: implementation of novel methods for assessment of air pollution exposure and lessons learned

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    Background: Desert dust events in Mediterranean countries, originating mostly from the Sahara and Arabian deserts, have been linked to climate change and are associated with significant increase in mortality and hospital admissions from respiratory causes. The MEDEA clinical intervention study in children with asthma is funded by EU LIFE+ program to evaluate the efficacy of recommendations aiming to reduce exposure to desert dust and related health effects. Methods: This paper describes the design, methods, and challenges of the MEDEA childhood asthma study, which is performed in two highly exposed regions of the Eastern Mediterranean: Cyprus and Greece-Crete. Eligible children are recruited using screening surveys performed at primary schools and are randomized to three parallel intervention groups: a) no intervention for desert dust events, b) interventions for outdoor exposure reduction, and c) interventions for both outdoor and indoor exposure reduction. At baseline visits, participants are enrolled on MEDena® Health-Hub, which communicates, alerts and provides exposure reduction recommendations in anticipation of desert dust events. MEDEA employs novel environmental epidemiology and telemedicine methods including wearable GPS, actigraphy, health parameters sensors as well as indoor and outdoor air pollution samplers to assess study participants’ compliance to recommendations, air pollutant exposures in homes and schools, and disease related clinical outcomes. Discussion: The MEDEA study evaluates, for the first time, interventions aiming to reduce desert dust exposure and implement novel telemedicine methods in assessing clinical outcomes and personal compliance to recommendations. In Cyprus and Crete, during the first study period (February–May 2019), a total of 91 children participated in the trial while for the second study period (February–May 2020), another 120 children completed data collection. Recruitment for the third study period (February–May 2021) is underway. In this paper, we also present the unique challenges faced during the implementation of novel methodologies to reduce air pollution exposure in children. Engagement of families of asthmatic children, schools and local communities, is critical. Successful study completion will provide the knowledge for informed decision-making both at national and international level for mitigating the health effects of desert dust events in South-Eastern Europe. Trial registration: ClinicalTrials.gov: NCT03503812, April 20, 2018

    Flying to Quality: Cultural Influences on Online Reviews

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    Customers increasingly consult opinions expressed online before making their final decisions. However, inherent factors such as culture may moderate the criteria and the weights individuals use to form their expectations and evaluations. Therefore, not all opinions expressed online match customers’ personal preferences, neither can firms use this information to deduce general conclusions. Our study explores this issue in the context of airline services using Hofstede’s framework as a theoretical anchor. We gauge the effect of each dimension as well as that of cultural distance between the passenger and the airline on the overall satisfaction with the flight as well as specific service factors. Using topic modeling, we also capture the effect of culture on review text and identify factors that are not captured by conventional rating scales. Our results provide significant insights for airline managers about service factors that affect more passengers from specific cultures leading to higher satisfaction/dissatisfaction

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study