artificial neural network; attrition rate; compliance; lung transplant; multimodal rehabilitation interventions; Leadership and Management; Health Policy; Health Informatics; Health Information Management
Abstract :
[en] [en] BACKGROUND/OBJECTIVES: Despite the effectiveness of exercise and nutritional interventions to improve aerobic capacity and quality of life in lung transplant (LT) recipients, their compliance is low. Strategies to reduce the high attrition rate (participants lost over time) is a major challenge. Artificial neural networks (ANN) may assist in the early identification of patients with high risk of attrition. The main objective of this study is to evaluate the usefulness of ANNs to identify prognostic factors for high attrition rate of a 10-week rehabilitation program after a LT.
METHODS: This prospective observational study included first-time LT recipients over 18 years of age. The main outcome for each patient was the attrition rate, which was estimated by the amount of missing data accumulated during the study. Clinical variables including malnutrition, sarcopenia, and their individual components were assessed at baseline. An ANN and regression analysis were used to identify the factors determining a high attrition rate.
RESULTS: Of the 41 participants, 17 (41.4%) had a high rate of attrition in the rehabilitation program. Only 23 baseline variables had no missing data and were included in the analysis, from which a low age-dependent body mass index (BMI) was the most important conditioning factor for a high attrition rate (p = 7.08 × 10-5), followed by end-stage respiratory disease requiring PT (p = 0.000111), low health-related quality-of-life (HRQoL) (p = 0.0009078), and low handgrip strength (p = 0.023).
CONCLUSIONS: The prevalence of high attrition rate in LT recipients is high. The profile of patients with a high probability of attrition includes those with chronic obstructive pulmonary disease, low BMI and handgrip strength, and reduced HRQoL.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Dávalos-Yerovi, Vanesa ✱; Rehabilitation Research Group, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain ; Physical Medicine and Rehabilitation Department, Hospital Vall d'Hebron, 08035 Barcelona, Spain ; PhD Program in Biomedicine, Department of Experimental and Health Sciences, Universitat Pompeu Fabra-Doctoral School, 08002 Barcelona, Spain
Sánchez-Rodríguez, Dolores ; Rehabilitation Research Group, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain ; Geriatrics Department, Brugmann University Hospital, Université Libre de Bruxelles, 1020 Brussels, Belgium ; Geriatrics Department, Hospital Del Mar, Hospital de L'Esperança, Centre Fòrum, Parc de Salut Mar, 08029 Barcelona, Spain
Gómez-Garrido, Alba ; Physical Medicine and Rehabilitation Department, Hospital Vall d'Hebron, 08035 Barcelona, Spain ; School of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
Launois, Patricia ; Physical Medicine and Rehabilitation Department, Hospital Vall d'Hebron, 08035 Barcelona, Spain ; School of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
Tejero-Sánchez, Marta ; Physical Medicine and Rehabilitation Department, Hospital del Mar, 08003 Barcelona, Spain
Pujol-Blaya, Vicenta ; Physical Medicine and Rehabilitation Department, Hospital Vall d'Hebron, 08035 Barcelona, Spain
Curbelo, Yulibeth G; Physical Medicine and Rehabilitation Department, Hospital del Mar, 08003 Barcelona, Spain
Donohoe, Owen ✱; Université de Liège - ULiège > Fundamental and Applied Research for Animals and Health (FARAH) > FARAH: Santé publique vétérinaire ; Bioscience Research Institute, Technological University of the Shannon, Athlone N37 HD68, Ireland
Marco, Ester ✱; Rehabilitation Research Group, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain ; Physical Medicine and Rehabilitation Department, Hospital del Mar, 08003 Barcelona, Spain ; School of Medicine, Universitat Pompeu Fabra, 08003 Barcelona, Spain
✱ These authors have contributed equally to this work.
Language :
English
Title :
Factors Influencing the Attrition Rate of a 10-Week Multimodal Rehabilitation Program in Patients After Lung Transplant: A Neural Network Analysis.
Publication date :
10 November 2024
Journal title :
Healthcare
eISSN :
2227-9032
Publisher :
Multidisciplinary Digital Publishing Institute (MDPI), Switzerland
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