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3While delirium is a serious and frequent disorder in intensive care patients, a prediction model is currently not available. We developed and validated a delirium prediction model for adult intensive care patients and determined its additional value compared to the prediction of the caregivers.
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International Innovation is the leading global dissemination resource for the wider scientific, technology and research communities, dedicated to disseminating the latest science, research and technological innovations on a global level. More information and a complimentary subscription offer to the publication can be found at: www.researchmedia.eu
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Machine learning models have proven to be reliable methods in classification tasks. However, little research has been done on classifying dwelling characteristics based on smart meter & weather data before. Gaining insights into dwelling characteristics can be helpful to create/improve the policies for creating new dwellings at NZEB standard. This paper compares the different machine learning algorithms and the methods used to correctly implement the models. These methods include the data pre-processing, model validation and evaluation. Smart meter data was provided by Groene Mient, which was used to train several machine learning algorithms. The models that were generated by the algorithms were compared on their performance. The results showed that Recurrent Neural Network (RNN) 2performed the best with 96% of accuracy. Cross Validation was used to validate the models, where 80% of the data was used for training purposes and 20% was used for testing purposes. Evaluation metrices were used to produce classification reports, which can indicate which of the models work the best for this specific problem. The models were programmed in Python.
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Machine learning models have proven to be reliable methods in classification tasks. However, little research has been conducted on the classification of dwelling characteristics based on smart meter and weather data before. Gaining insights into dwelling characteristics, which comprise of the type of heating system used, the number of inhabitants, and the number of solar panels installed, can be helpful in creating or improving the policies to create new dwellings at nearly zero-energy standard. This paper compares different supervised machine learning algorithms, namely Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Long-short term memory, and methods used to correctly implement these algorithms. These methods include data pre-processing, model validation, and evaluation. Smart meter data, which was used to train several machine learning algorithms, was provided by Groene Mient. The models that were generated by the algorithms were compared on their performance. The results showed that the Long-short term memory performed the best with 96% accuracy. Cross Validation was used to validate the models, where 80% of the data was used for training purposes and 20% was used for testing purposes. Evaluation metrics were used to produce classification reports, which indicates that the Long-short term memory outperforms the compared models on the evaluation metrics for this specific problem.
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Thirty to sixty per cent of older patients experience functional decline after hospitalisation, associated with an increase in dependence, readmission, nursing home placement and mortality. First step in prevention is the identification of patients at risk. The objective of this study is to develop and validate a prediction model to assess the risk of functional decline in older hospitalised patients.
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BACKGROUND: There is no widely used instrument to detect frailty in people with intellectual disabilities (IDs). We aimed to develop and validate a shorter and more practical version of a published frailty index for people with IDs.
METHOD: This study was part of the longitudinal 'Healthy Ageing and Intellectual Disability' study. We included 982 people with IDs aged 50 years and over. The previously developed and validated ID-Frailty Index consisting of 51 deficits was used as the basis for the shortened version, the ID-FI Short Form. Content of the ID-FI Short Form was based on statistics and clinical and practical feasibility. We evaluated the precision and validity of the ID-FI Short Form using the internal consistency, the correlation between the ID-FI Short Form and the original ID-Frailty Index, the agreement in dividing participants in the categories non-frail, pre-frail and frail, and the association with survival.
RESULTS: Seventeen deficits from the original ID-Frailty Index were selected for inclusion in the ID-FI Short Form. All deficits of the ID-FI Short Form are clinically and practically feasible to assess for caregivers and therapists supporting people with ID. We showed acceptable internal consistency with Cronbach's alpha of 0.75. The Pearson correlation between the ID-Frailty Index and the ID-FI Short Form was excellent (r = 0.94, P < 0.001). We observed a good agreement between the full and short forms in dividing the participants in the frailty categories, with a kappa statistic of 0.63. The ID-FI Short Form was associated with survival; with every 1/100 increase on the ID-FI Short Form, the mortality probability increased by 7% (hazard ratio 1.07, P < 0.001).
CONCLUSION: The first validation of the ID-FI Short Form shows it to be a promising, practical tool to assess the frailty status of people with ID.
MULTIFILE
The authors investigate the potential of Mixed Reality (MR) games for team building and assessment. The AMELIO game was designed for a highly immersive MR lab. The game is a multi-player team challenge based on the concept of an escape room, staged in a space colony emergency situation. An explorative empirical pre-post measurement study was carried out to establish whether playing AMELIO influences team cohesiveness. Ten teams of three played AMELIO and filled out pre- and post-game questionnaires with validated measurements of team cohesiveness and mediating factors related to team composition, game experience and team dynamics. The findings show a positive and significant increase in team cohesiveness, with stronger effects for teams with lower pre-game familiarity. In terms of game experience and team dynamics, audio aesthetics and empathy proved to be significant mediating factors. This AIDS game validation and improvement, and understanding and guiding the team building process.
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This study investigates the clinical course of and prognostic factors for quality of life (Short Form 36 items Health survey (SF-36)) and global perceived effect (GPE) in patients treated for chronic nonspecific low back pain at 5 and 12-months follow-up. Data from a prospective cohort (n ¼ 1760) of a rehabilitation center were used, where patients followed a 2-months cognitive behavior treatment. The outcome ‘improvement in quality of life (SF-36)’ was defined as a 10% increase in score on the SF-36 at follow-up compared with baseline. On the GPE scale, patients who indicated to be ‘much improved’ were coded as ‘clinically improved’. Multivariable logistic regression analysis included 23 baseline characteristics. At 5-months follow-up, scores on the SF-36 Mental Component Scale (SF-36; MCS) and the Physical Component Scale (SF-36; PCS) had increased from 46.6 (SD 10.3) to 50.4 (SD 9.8) and from 31.9 (SD 7.1) to 46.6 (SD 10.3), respectively. At 5-months follow-up, 53.0% of the patients reported clinical improvement (GPE) which increased to 60.3% at 12-months follow-up. The 10% improvement in quality of life (SF-36 MCS) at 5-months follow-up was associated with patient characteristics and psychological factors. At 5-months follow-up, the 10% improvement in quality of life (SF-36 PCS) and GPE was associated with patient characteristics, physical examination, work-related factors and psychological factors; for GPE, an association was also found with clinical status. At 12-months follow-up GPE was associated with patient characteristics, clinical status, physical examination and work-related factors. The next phase in this prognostic research is external validation of these results.
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