Exploring flexible polynomial regression as a method to align routine clinical outcomes with daily data capture through remote technologies.
Chronic disease
Clinical outcomes
Missing data
Polynomial regression
Remote patient monitoring
Journal
BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545
Informations de publication
Date de publication:
11 05 2023
11 05 2023
Historique:
received:
30
10
2022
accepted:
06
05
2023
medline:
15
5
2023
pubmed:
12
5
2023
entrez:
11
5
2023
Statut:
epublish
Résumé
Clinical outcomes are normally captured less frequently than data from remote technologies, leaving a disparity in volumes of data from these different sources. To align these data, flexible polynomial regression was investigated to estimate personalised trends for a continuous outcome over time. Using electronic health records, flexible polynomial regression models inclusive of a 1st up to a 4th order were calculated to predict forced expiratory volume in 1 s (FEV There were 8,549 FEV Flexible polynomials can be used to extrapolate clinical outcome measures at frequent time intervals to align with daily data captured through remote technologies.
Sections du résumé
BACKGROUND
Clinical outcomes are normally captured less frequently than data from remote technologies, leaving a disparity in volumes of data from these different sources. To align these data, flexible polynomial regression was investigated to estimate personalised trends for a continuous outcome over time.
METHODS
Using electronic health records, flexible polynomial regression models inclusive of a 1st up to a 4th order were calculated to predict forced expiratory volume in 1 s (FEV
RESULTS
There were 8,549 FEV
CONCLUSION
Flexible polynomials can be used to extrapolate clinical outcome measures at frequent time intervals to align with daily data captured through remote technologies.
Identifiants
pubmed: 37170205
doi: 10.1186/s12874-023-01942-4
pii: 10.1186/s12874-023-01942-4
pmc: PMC10176913
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
114Subventions
Organisme : Department of Health
Pays : United Kingdom
Informations de copyright
© 2023. The Author(s).
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