Notes

A cooperative game style using bankruptcy concept regarding water allowance: an incident research within Cina Tarim River Container.
In 2017, ostomy patients gained access to ostomy products in community pharmacies that are fully reimbursed by the Portuguese National Health Service. This impacted the daily lives of people with ostomy and opened a new market of products and services for pharmacies. However, little is known about the sociodemographic and clinical profile of ostomy patients. This study aims to characterize people with ostomy and their caregivers, evaluate access and satisfaction with the pharmacy and explore participants' expectations regarding services and counselling.

This was an observational, cross-sectional, multicentre study involving pharmacy users who acquired ostomy products in Portuguese community pharmacies. Data were collected through a confidential self-report questionnaire between June and August 2019.

Approximately 56% of the participants were ostomy patients, of whom 65.9% were men. KI696 The average age of participating ostomy patients was 65.5 years old (SD = 12.9), and near 80% were retired/pensioners. Careage of ostomy nursing care, highlight the opportunity for an extended role of pharmacists among this group.
The learning environment is one of the most influential factors in training of medical residents. The Dutch Residency Educational Climate Test (D-RECT) is one of the strongest instruments for measuring the learning environment. However, it has not been translated in French. The objective of this study is the psychometric validation of the DRECT French version.

After translation of the D-RECT questionnaire into French, residents of five Moroccan hospitals were invited to complete the questionnaire between July and September 2018. Confirmatory factor analysis was used to evaluate the validity of the construct using the standardized root mean square residual (SRMR), the root mean square error approximation (RMSEA), the Comparative Fit Index (CFI) and the Tucker- Lewis Index (TLI). Reliability analysis was analysed using Internal consistency and Test-retest.

During the study period, 211 residents completed the questionnaire. Confirmatory factor analysis showed an adequate model fit with the following indicators SRMR = 0.058 / RMSEA = 0.07 / CFI = 0.88 / TLI = 0.87. The French translation had a good internal consistency (Cronbach alpha score > 0.7 for all subscales) and a good temporal stability (correlation score between two measurements = 0.89).

This French version has an acceptable validity of the construct, a good internal consistency and good temporal reliability, and may be used to evaluate the learning climate. Additional research is necessary in other French-speaking contexts, in order to confirm these results.
This French version has an acceptable validity of the construct, a good internal consistency and good temporal reliability, and may be used to evaluate the learning climate. Additional research is necessary in other French-speaking contexts, in order to confirm these results.
With cardiovascular disease increasing, substantial research has focused on the development of prediction tools. We compare deep learning and machine learning models to a baseline logistic regression using only 'known' risk factors in predicting incident myocardial infarction (MI) from harmonized EHR data.

Large-scale case-control study with outcome of 6-month incident MI, conducted using the top 800, from an initial 52 k procedures, diagnoses, and medications within the UCHealth system, harmonized to the Observational Medical Outcomes Partnership common data model, performed on 2.27 million patients. We compared several over- and under- sampling techniques to address the imbalance in the dataset. We compared regularized logistics regression, random forest, boosted gradient machines, and shallow and deep neural networks. A baseline model for comparison was a logistic regression using a limited set of 'known' risk factors for MI. Hyper-parameters were identified using 10-fold cross-validation.

Twenty thousand Five hundred and ninety-one patients were diagnosed with MI compared with 2.25 million who did not. A deep neural network with random undersampling provided superior classification compared with other methods. However, the benefit of the deep neural network was only moderate, showing an F1 Score of 0.092 and AUC of 0.835, compared to a logistic regression model using only 'known' risk factors. Calibration for all models was poor despite adequate discrimination, due to overfitting from low frequency of the event of interest.

Our study suggests that DNN may not offer substantial benefit when trained on harmonized data, compared to traditional methods using established risk factors for MI.
Our study suggests that DNN may not offer substantial benefit when trained on harmonized data, compared to traditional methods using established risk factors for MI.
Age-related macular degeneration (AMD) is a chronic eye condition that leads to permanent vision loss in the central visual field. AMD makes reading challenging and inefficient. People with AMD often find it difficult to access, process and understand written patient education materials (PEMs). To promote health literacy, the demands of written PEMs must match the literacy capacities of the target audience. This study aims to evaluate the readability (grade level) and suitability (appropriateness) of online PEMs designed for people with AMD.

Online PEMs were sourced from websites of national organizations providing patient education materials designed for people with AMD. The Flesch-Kincaid Grade Level formula and the Suitability Assessment of Materials instrument were used to assess the readability and suitability of PEMs. Descriptive statistics were used to compare online PEMs by organization based on national guidelines for readability level (≤ sixth grade) and the recommended suitability score (≥ 70%)ealth information must match the reading capacities of the target audience. Heeding to evidence-based guidelines for providing written information to patients with low health literacy and low vision is beneficial for both patients and health care providers. Future research is warranted.
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