Evidence map›Paper›PMID 42657900›Full record

ArticleBiometrical journal. Biometrische Zeitschrift2026

Modeling Physical Activity Profiles in COPD Patients: A Basis Expansion Approach to Variable Domain Functional Regression Models.

Pavel Hernández-Amaro, María Durbán, M Carmen Aguilera-Morillo, Cristobal Esteban Gonzalez, Inmaculada Arostegui

Abstract read
In one paragraph

Article in Biometrical journal. Biometrische Zeitschrift, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Pavel Hernández-AmaroUniversidad Carlos III de Madrid, Madrid, Spain.
María DurbánUniversidad Carlos III de Madrid, Madrid, Spain.
M Carmen Aguilera-MorilloUniversitat Politècnica de València, Valencia, Spain.
Cristobal Esteban GonzalezOsakidetza Basque Health Service, Bilbao, Spain.
Inmaculada ArosteguiUniversity of the Basque Country UPV/EHU, Bilbao, Spain.

Funding

Conselleria de Educación, Universidades y Empleo de la Generalitat Valenciana CIAICO/2023/189Spanish Ministry of Science, Innovation and Universities MCIN/AEI/10.13039/501100011033 PID2022-137243OB-I00
6 · The paper itself

Abstract

Physical activity plays an important role in the well-being of patients with Chronic Obstructive Pulmonary Disease (COPD). The telEPOC program, developed at the Galdakao-Usansolo University Hospital (Vizcaya, Spain), provided a telemonitoring data set resulting in a variable domain functional data set. In this sense, the aim is to study the impact of physical activity (measured as daily steps collected in a time interval delimited by the patient's participation in the experiment) on the rate of hospitalizations. To address this challenge, a novel basis expansion approach is proposed to fit a variable-domain functional regression model, which assumes the functional nature of the covariate (daily steps) and incorporates the sample data into the model without alignment. This will enrich the interpretability of the model by incorporating the information provided by the domain through a two-dimensional regression coefficient. In addition, a penalized estimation of the model is proposed in terms of a 2D P-spline penalty, which allows considering different degree of smoothness for each dimension of the functional regression coefficient (anisotropic penalty). The performance of our methodology is also tested and compared with state-of-the-art methods by means of a simulation study. Software for our method can be found in the VDPO R package available in CRAN.

Indexed as

BiometryExerciseModels, StatisticalPulmonary Disease, Chronic ObstructiveHumansRegression AnalysisB‐splinesCOPDmixed modelsvariable domain functional data

Identifiers

PMID42657900
PMCPMC13520829

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.