Risk factors for prediction of delirium at hospital admittance
Corresponding Author
Guillermo Cano-Escalera
Department of Computer Science and Artificial Intelligence, Faculty of Computer Science, University of the Basque Country (UPV/EHU), Spain
Computational Intelligence Group, University of the Basque Country (UPV/EHU), Spain
Correspondence
Guillermo Cano-Escalera, Facultad de Informatica, UPV/EHU, San Sebastian, Spain.
Email: [email protected]
Search for more papers by this authorManuel Graña
Department of Computer Science and Artificial Intelligence, Faculty of Computer Science, University of the Basque Country (UPV/EHU), Spain
Computational Intelligence Group, University of the Basque Country (UPV/EHU), Spain
Search for more papers by this authorJon Irazusta
Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Spain
BioCruces Health Research Institute, Spain
Search for more papers by this authorIdoia Labayen
Institute for Innovation& Sustainable Development in Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
Search for more papers by this authorAriadna Besga
Department of Medicine, Vitoria, BioAraba, Health Research Institute, Hospital Universitario de Araba, Gasteiz, Spain
G10, Biomedical Research Centre in Mental Health Network (CIBERSAM), Madrid, Spain
Search for more papers by this authorCorresponding Author
Guillermo Cano-Escalera
Department of Computer Science and Artificial Intelligence, Faculty of Computer Science, University of the Basque Country (UPV/EHU), Spain
Computational Intelligence Group, University of the Basque Country (UPV/EHU), Spain
Correspondence
Guillermo Cano-Escalera, Facultad de Informatica, UPV/EHU, San Sebastian, Spain.
Email: [email protected]
Search for more papers by this authorManuel Graña
Department of Computer Science and Artificial Intelligence, Faculty of Computer Science, University of the Basque Country (UPV/EHU), Spain
Computational Intelligence Group, University of the Basque Country (UPV/EHU), Spain
Search for more papers by this authorJon Irazusta
Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Spain
BioCruces Health Research Institute, Spain
Search for more papers by this authorIdoia Labayen
Institute for Innovation& Sustainable Development in Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
Search for more papers by this authorAriadna Besga
Department of Medicine, Vitoria, BioAraba, Health Research Institute, Hospital Universitario de Araba, Gasteiz, Spain
G10, Biomedical Research Centre in Mental Health Network (CIBERSAM), Madrid, Spain
Search for more papers by this authorFunding information: Ministerio de Economía y Competitividad; Osasun Saila, Eusko Jaurlaritzako; European Regional development fund
Abstract
Aging population in many developed countries, moves the issue of healthy aging at the forefront of the political, scientific and technological concerns. Delirium is a multifactorial disorder that is highly prevalent in hospitalized elderly people that causes complications in the patient care and increases mortality at the hospital and soon after discharge. Early diagnostics would allow improved treatment and prevention for a syndrome that requires very personalized treatment. This paper deals with machine learning based prediction of delirium at hospital admittance as a computer aided diagnostic tool, as well as with the identification of risk factors by means of the variable importance computed by the classifier model building approaches. We achieve almost 0.80 classification accuracy, which is encourages further exploration of improved classifier models. Exploration of variable importance shows that frailty, dementia and some pharmacological factors are relevant risk factors for delirium at hospital admittance.
CONFLICT OF INTEREST
The authors declare that they have no conflicts of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
REFERENCES
- Aboderin, I. A. G., & Beard, J. R. (2015). Older people's health in sub-saharan africa. The Lancet, 385, e9–e11. https://doi.org/10.1016/S0140-6736(14)61602-0
- Artetxe, A., Ayerdi, B., Graña, M., & Rios, S. (2017). Using anticipative hybrid extreme rotation forest to predict emergency service readmission risk. Journal of Computational Science, 20, 154–161.
- Artetxe, A., Beristain, A., & Graña, M. (2018). Predictive models for hospital readmission risk: A systematic review of methods. Computer Methods and Programs in Biomedicine, 164, 49–64. https://doi.org/10.1016/j.cmpb.2018.06.006
- Artetxe, A., Beristain, A., Graña, M., & Besga, A. (2017). Predicting 30-day emergency readmission risk. In M. Graña, J. M. López-Guede, O. Etxaniz, Á. Herrero, H. Quintián, & E. Corchado (Eds.), International joint conference SOCO'16-CISIS'16-ICEUTE'16 (pp. 3–12). Springer International Publishing.
10.1007/978-3-319-47364-2_1 Google Scholar
- Artetxe, A., Graña, M., Beristain, A., & Ríos, S. (2017). Balanced training of a hybrid ensemble method for imbalanced datasets: A case of emergency department readmission prediction. Neural Computing and Applications, 32(10), 5735–5744.
- Avelino-Silva, T. J., Campora, F., Curiati, J. A. E., & Jacob-Filho, W. (2017). Association between delirium superimposed on dementia and mortality in hospitalized older adults: A prospective cohort study. PLoS Medicine, 14, e1002264.
- Bellelli, G., Moresco, R., Panina-Bordignon, P., Arosio, B., Gelfi, C., Morandi, A., & Cesari, M. (2017). Is delirium the cognitive harbinger of frailty in older adults? A review about the existing evidence. Frontiers in Medicine, 4, 188. https://doi.org/10.3389/fmed.2017.00188
- Besga, A., Ayerdi, B., Alcalde, G., Manzano, A., Lopetegui, P., Graña, M., & González-Pinto, A. (2015). Risk factors for emergency department short time readmission in stratified population. BioMed Research International, 2015, 685067.
- Breiman, L. (2001). Random forest. Machine Learning, 45, 5–32.
- Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40, 373–383. https://doi.org/10.1016/0021-9681(87)90171-8
- Chu, C.-S., Liang, C.-K., Chou, M.-Y., Lin, Y.-T., Hsu, C.-J., Chou, P.-H., & Chu, C.-L. (2016). Short-form mini nutritional assessment as a useful method of predicting the development of postoperative delirium in elderly patients undergoing orthopedic surgery. General Hospital Psychiatry, 38, 15–20.
- Dani, M., Owen, L. H., Jackson, T. A., Rockwood, K., Sampson, E. L., & Davis, D. (2017). Delirium, frailty, and mortality: Interactions in a prospective study of hospitalized older people. The Journals of Gerontology: Series A, 73, 415–418. https://doi.org/10.1093/gerona/glx214
- Diwell, R. A., Davis, D. H., Vickerstaff, V., & Sampson, E. L. (2018). Key components of the delirium syndrome and mortality: Greater impact of acute change and disorganised thinking in a prospective cohort study. BMC Geriatrics, 18, 24.
- Erkinjuntti, T., Sulkava, R., Wikström, J., & Autio, L. (1987). Short portable mental status questionnaire as a screening test for dementia and delirium among the elderly. Journal of the American Geriatrics Society, 35, 412–416. https://doi.org/10.1111/j.1532-5415.1987.tb04662.x
- Feldman, J., Yaretzky, A., Kaizimov, N., Alterman, P., & Vigder, C. (1999). Delirium in an acute geriatric unit: Clinical aspects. Archives of Gerontology and Geriatrics, 28, 37–44.
- Ferrucci, L., Guralnik, J. M., Salive, M. E., Fried, L. P., Bandeen-Roche, K., Brock, D. B., Simonsick, E. M., Corti, M., & Zeger, S. L. (1996). Effect of age and severity of disability on short-term variation in walking speed: The women's health and aging study. Journal of Clinical Epidemiology, 49, 1089–1096. https://doi.org/10.1016/0895-4356(96)00231-4
- Fong, T. G., Davis, D., Growdon, M. E., Albuquerque, A., & Inouye, S. K. (2015). The interface between delirium and dementia in elderly adults. Lancet Neurology, 14, 823–832.
- Fried, L., Tangen, C., Walston, J., Newman, A., Hirsch, C., Gottdiener, J., Seeman, T., Tracy, R., Kop, W., Burke, G., & McBurnie, M. (2001). Frailty in older adults: Evidence for a phenotype. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56, M146–M156.
- Friedman, J. H. (2002). Stochastic gradient boosting: Nonlinear methods and data mining. Computational Statistics & Data Analysis, 38, 367–378. https://doi.org/10.1016/S0167-9473(01)00065-2
- Garmendia, A., Graña, M., Lopez Guede, J., & Rios, S. (2019). Neural and statistical predictors for time to readmission in emergency departments: A case study. Neurocomputing, 354, 3–9.
- Garmendia, A., Graña, M., Lopez-Guede, J. M., & Rios, S. (2017). Predicting patient hospitalization after emergency readmission. Cybernetics and Systems, 48, 182–192. https://doi.org/10.1080/01969722.2016.1276772
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
- Gower, L. E. J., Gatewood, M. O., & Kang, C. S. (2012). Emergency department management of delirium in the elderly. The Western Journal of Emergency Medicine, 13, 194–201.
- Guralnik, J. M., Simonsick, E. M., Ferrucci, L., Glynn, R. J., Berkman, L. F., Blazer, D. G., Scherr, P. A., & Wallace, R. B. (1994). A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. Journal of Gerontology, 49, M85–M94. https://doi.org/10.1093/geronj/49.2.M85
- Haykin, S. (1998). Neural networks: A comprehensive foundation. Prentice-Hall.
- Inouye, S. K., & Charpentier, P. A. (1996). Precipitating factors for delirium in hospitalized elderly persons. Predictive model and interrelationship with baseline vulnerability. JAMA, 275, 852–857.
- Inouye, S. K., Westendorp, R. G. J., & Saczynski, J. S. (2014). Delirium in elderly people. The Lancet, 383, 911–922.
- Johnson, J. R. (2018). Delirium in hospitalized older adults. The New England Journal of Medicine, 378, 96.
- Joosten, E., Demuynck, M., Detroyer, E., & Milisen, K. (2014). Prevalence of frailty and its ability to predict in hospital delirium, falls, and 6-month mortality in hospitalized older patients. BMC Geriatrics, 14(1). https://doi.org/10.1186/1471-2318-14-1
- Jung, P., Pereira, M. A., Hiebert, B., Song, X., Rockwood, K., Tangri, N., & Arora, R. C. (2015). The impact of frailty on postoperative delirium in cardiac surgery patients. The Journal of Thoracic and Cardiovascular Surgery, 149, 869–875.
- Kaiser, M. J., Bauer, J. M., Ramsch, C., Uter, W., Guigoz, Y., Cederholm, T., Thomas, D. R., Anthony, P., Charlton, K. E., Maggio, M., Tsai, A. C., Grathwohl, D., Vellas, B., Sieber, C. C., & MNA-International Group. (2009). Validation of the mini nutritional assessment short-form (mna-sf): A practical tool for identification of nutritional status. The Journal of Nutrition, Health and Aging, 13, 782. https://doi.org/10.1007/s12603-009-0214-7
- Kuhn, M., & Johnson, K. (2013). Applied predictive modeling. Springer.
10.1007/978-1-4614-6849-3 Google Scholar
- Kukreja, D., Günther, U., & Popp, J. (2015). Delirium in the elderly: Current problems with increasing geriatric age. The Indian Journal of Medical Research, 142, 655–662.
- Lipowski, Z. J. (1987). Delirium (acute confusional states). JAMA, 258, 1789–1792.
- Magny, E., Le Petitcorps, H., Pociumban, M., Bouksani-Kacher, Z., Pautas, É., Belmin, J., Bastuji-Garin, S., & Lafuente-Lafuente, C. (2018). Predisposing and precipitating factors for delirium in community-dwelling older adults admitted to hospital with this condition: A prospective case series. PLoS One, 13, e0193034.
- Mahoney, F. I., & Barthel, D. W. (1965). Functional evaluation: The barthel index. Maryland State Medical Journal, 14, 61–65.
- Morandi, A., Davis, D., Fick, D. M., Turco, R., Boustani, M., Lucchi, E., Guerini, F., Morghen, S., Torpilliesi, T., Gentile, S., MacLullich, A. M., Trabucchi, M., & Bellelli, G. (2014). Delirium superimposed on dementia strongly predicts worse outcomes in older rehabilitation inpatients. Journal of the American Medical Directors Association, 15, 349–354.
- Ohl, I. C. B., Chavaglia, S. R. R., Ohl, R. I. B., Lopes, M. C. B. T., Campanharo, C. R. V., Okuno, M. F. P., & Batista, R. E. A. (2019). Evaluation of delirium in aged patients assisted at emergency hospital service. Revista Brasileira de Enfermagem, 72, 153–160.
- Pfeiffer, E. (1975). A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. Journal of the American Geriatrics Society, 23, 433–441.
- Rivière, J., van der Mast, R. C., Vandenberghe, J., & Van Den Eede, F. (2019). Efficacy and tolerability of atypical antipsychotics in the treatment of delirium: A systematic review of the literature. Psychosomatics, 60, 18–26.
- Rodriguez-Mañas, L., & Fried, L. P. (2015). Frailty in the clinical scenario. The Lancet, 385, e7–e9. https://doi.org/10.1016/S0140-6736(14)61595-6
- Setters, B., & Solberg, L. M. (2017). Delirium. Primary Care, 44, 541–559.
- Sourial, N., Bergman, H., Karunananthan, S., Wolfson, C., Payette, H., Gutierrez-Robledo, L. M., Béland, F., Fletcher, J. D., & Guralnik, J. (2013). Implementing frailty into clinical practice: A cautionary tale. The Journals of Gerontology: Series A, 68, 1505–1511. https://doi.org/10.1093/gerona/glt053
- Vaughan, L., Corbin, A., & Goveas, J. (2015). Depression and frailty in later life: A systematic review. Clinical Interventions in Aging, 10, 1947–1958.
- Vellas, B., Guigoz, Y., Garry, P. J., Nourhashemi, F., Bennahum, D., Lauque, S., & Albarede, J. L. (1999). The mini nutritional assessment (mna) and its use in grading the nutritional state of elderly patients. Nutrition, 15, 116–122.
- Verloo, H., Goulet, C., Morin, D., & von Gunten, A. (2016). Association between frailty and delirium in older adult patients discharged from hospital. Clinical Interventions in Aging, 11, 55–63.
- Witten, I. H., Frank, E., & Hall, M. A. (2011). Data mining: Practical machine learning tools and techniques ( 3rd ed.). Morgan Kaufmann Publishers Inc.
