Prediction of Autonomy Loss in Alzheimer’s Disease
The evolution of functional autonomy loss leads to institutionalization of people affected by Alzheimer’s disease (AD), to an alteration of their quality of life and that of their caregivers. To predict loss of functional autonomy could optimize prevention strategies, aids and cost of care. The aim...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Forecasting |
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| Online Access: | https://www.mdpi.com/2571-9394/4/1/2 |
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| author | Anne-Sophie Nicolas Michel Ducher Laurent Bourguignon Virginie Dauphinot Pierre Krolak-Salmon |
| author_facet | Anne-Sophie Nicolas Michel Ducher Laurent Bourguignon Virginie Dauphinot Pierre Krolak-Salmon |
| author_sort | Anne-Sophie Nicolas |
| collection | DOAJ |
| description | The evolution of functional autonomy loss leads to institutionalization of people affected by Alzheimer’s disease (AD), to an alteration of their quality of life and that of their caregivers. To predict loss of functional autonomy could optimize prevention strategies, aids and cost of care. The aim of this study was to develop and to cross-validate a model to predict loss of functional autonomy as assessed by Instrumental Activities of Daily Living (IADL) score. Outpatients with probable AD and with 2 or more visits to the Clinical and Research Memory Centre of the University Hospital were included. Four Tree-Augmented Naïve bayesian networks (6, 12, 18 and 24 months of follow-up) were built. Variables included in the model were demographic data, IADL score, MMSE score, comorbidities, drug prescription (psychotropics and AD-specific drugs). A 10-fold cross-validation was conducted to evaluate robustness of models. The study initially included 485 patients in the prospective cohort. The best performance after 10-fold cross-validation was obtained with the model able to predict loss of functional autonomy at 18 months (area under the curve of the receiving operator characteristic curve = 0.741, 27% of patients misclassified, positive predictive value = 77% and negative predictive value = 73%). The 13 variables used explain 41.6% of the evolution of functional autonomy at 18 months. A high-performing predictive model of AD evolution of functional autonomy was obtained. An external validation is needed to use the model in clinical routine so as to optimize the patient care. |
| first_indexed | 2024-03-09T19:50:40Z |
| format | Article |
| id | doaj.art-5da2bbe6082c406bb8fe914e3472a44f |
| institution | Directory Open Access Journal |
| issn | 2571-9394 |
| language | English |
| last_indexed | 2024-03-09T19:50:40Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forecasting |
| spelling | doaj.art-5da2bbe6082c406bb8fe914e3472a44f2023-11-24T01:11:37ZengMDPI AGForecasting2571-93942021-12-0141263510.3390/forecast4010002Prediction of Autonomy Loss in Alzheimer’s DiseaseAnne-Sophie Nicolas0Michel Ducher1Laurent Bourguignon2Virginie Dauphinot3Pierre Krolak-Salmon4UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, CNRS, Claude Bernard Lyon 1 University, 43 Bd du 11 Novembre 1918, 69622 Villeurbanne, FranceDepartment of Pharmacy, Groupement Hospitalier de Gériatrie, Hospices Civils de Lyon, 69005 Lyon, FranceUMR 5558, Laboratoire de Biométrie et Biologie Evolutive, CNRS, Claude Bernard Lyon 1 University, 43 Bd du 11 Novembre 1918, 69622 Villeurbanne, FranceFaculté de Médecine Lyon Est, Claude Bernard Lyon 1 University, 8 Avenue Rockefeller, 69008 Lyon, FranceFaculté de Médecine Lyon Est, Claude Bernard Lyon 1 University, 8 Avenue Rockefeller, 69008 Lyon, FranceThe evolution of functional autonomy loss leads to institutionalization of people affected by Alzheimer’s disease (AD), to an alteration of their quality of life and that of their caregivers. To predict loss of functional autonomy could optimize prevention strategies, aids and cost of care. The aim of this study was to develop and to cross-validate a model to predict loss of functional autonomy as assessed by Instrumental Activities of Daily Living (IADL) score. Outpatients with probable AD and with 2 or more visits to the Clinical and Research Memory Centre of the University Hospital were included. Four Tree-Augmented Naïve bayesian networks (6, 12, 18 and 24 months of follow-up) were built. Variables included in the model were demographic data, IADL score, MMSE score, comorbidities, drug prescription (psychotropics and AD-specific drugs). A 10-fold cross-validation was conducted to evaluate robustness of models. The study initially included 485 patients in the prospective cohort. The best performance after 10-fold cross-validation was obtained with the model able to predict loss of functional autonomy at 18 months (area under the curve of the receiving operator characteristic curve = 0.741, 27% of patients misclassified, positive predictive value = 77% and negative predictive value = 73%). The 13 variables used explain 41.6% of the evolution of functional autonomy at 18 months. A high-performing predictive model of AD evolution of functional autonomy was obtained. An external validation is needed to use the model in clinical routine so as to optimize the patient care.https://www.mdpi.com/2571-9394/4/1/2Alzheimer diseaseactivities of daily livingBayes theorem |
| spellingShingle | Anne-Sophie Nicolas Michel Ducher Laurent Bourguignon Virginie Dauphinot Pierre Krolak-Salmon Prediction of Autonomy Loss in Alzheimer’s Disease Forecasting Alzheimer disease activities of daily living Bayes theorem |
| title | Prediction of Autonomy Loss in Alzheimer’s Disease |
| title_full | Prediction of Autonomy Loss in Alzheimer’s Disease |
| title_fullStr | Prediction of Autonomy Loss in Alzheimer’s Disease |
| title_full_unstemmed | Prediction of Autonomy Loss in Alzheimer’s Disease |
| title_short | Prediction of Autonomy Loss in Alzheimer’s Disease |
| title_sort | prediction of autonomy loss in alzheimer s disease |
| topic | Alzheimer disease activities of daily living Bayes theorem |
| url | https://www.mdpi.com/2571-9394/4/1/2 |
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