Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification. / Muse, Victorine P.; Aguayo-Orozco, Alejandro; Balaganeshan, Sedrah B.; Brunak, Søren.

In: Patterns, Vol. 4, No. 8, 100778, 2023.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Muse, VP, Aguayo-Orozco, A, Balaganeshan, SB & Brunak, S 2023, 'Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification', Patterns, vol. 4, no. 8, 100778. https://doi.org/10.1016/j.patter.2023.100778

APA

Muse, V. P., Aguayo-Orozco, A., Balaganeshan, S. B., & Brunak, S. (2023). Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification. Patterns, 4(8), [100778]. https://doi.org/10.1016/j.patter.2023.100778

Vancouver

Muse VP, Aguayo-Orozco A, Balaganeshan SB, Brunak S. Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification. Patterns. 2023;4(8). 100778. https://doi.org/10.1016/j.patter.2023.100778

Author

Muse, Victorine P. ; Aguayo-Orozco, Alejandro ; Balaganeshan, Sedrah B. ; Brunak, Søren. / Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification. In: Patterns. 2023 ; Vol. 4, No. 8.

Bibtex

@article{7dc8edf3f8834600a470399242d09ba2,
title = "Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification",
abstract = "We identified mortality-, age-, and sex-associated differences in relation to reference intervals (RIs) for laboratory tests in population-wide data from nearly 2 million hospital patients in Denmark and comprising more than 300 million measurements. A low-parameter mathematical wave-based modification method was developed to adjust for dietary and environment influences during the year. The resulting mathematical fit allowed for improved association rates between re-classified abnormal laboratory tests, patient diagnoses, and mortality. The study highlights the need for seasonally modified RIs and presents an approach that has the potential to reduce over- and underdiagnosis, affecting both physician-patient interactions and electronic health record research as a whole.",
keywords = "DSML3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems, health data science, hospital laboratory tests, mortality, reference intervals, seasonality",
author = "Muse, {Victorine P.} and Alejandro Aguayo-Orozco and Balaganeshan, {Sedrah B.} and S{\o}ren Brunak",
note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",
year = "2023",
doi = "10.1016/j.patter.2023.100778",
language = "English",
volume = "4",
journal = "Patterns",
issn = "2666-3899",
publisher = "Cell Press",
number = "8",

}

RIS

TY - JOUR

T1 - Population-wide analysis of hospital laboratory tests to assess seasonal variation and temporal reference interval modification

AU - Muse, Victorine P.

AU - Aguayo-Orozco, Alejandro

AU - Balaganeshan, Sedrah B.

AU - Brunak, Søren

N1 - Publisher Copyright: © 2023 The Author(s)

PY - 2023

Y1 - 2023

N2 - We identified mortality-, age-, and sex-associated differences in relation to reference intervals (RIs) for laboratory tests in population-wide data from nearly 2 million hospital patients in Denmark and comprising more than 300 million measurements. A low-parameter mathematical wave-based modification method was developed to adjust for dietary and environment influences during the year. The resulting mathematical fit allowed for improved association rates between re-classified abnormal laboratory tests, patient diagnoses, and mortality. The study highlights the need for seasonally modified RIs and presents an approach that has the potential to reduce over- and underdiagnosis, affecting both physician-patient interactions and electronic health record research as a whole.

AB - We identified mortality-, age-, and sex-associated differences in relation to reference intervals (RIs) for laboratory tests in population-wide data from nearly 2 million hospital patients in Denmark and comprising more than 300 million measurements. A low-parameter mathematical wave-based modification method was developed to adjust for dietary and environment influences during the year. The resulting mathematical fit allowed for improved association rates between re-classified abnormal laboratory tests, patient diagnoses, and mortality. The study highlights the need for seasonally modified RIs and presents an approach that has the potential to reduce over- and underdiagnosis, affecting both physician-patient interactions and electronic health record research as a whole.

KW - DSML3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems

KW - health data science

KW - hospital laboratory tests

KW - mortality

KW - reference intervals

KW - seasonality

U2 - 10.1016/j.patter.2023.100778

DO - 10.1016/j.patter.2023.100778

M3 - Journal article

C2 - 37602220

AN - SCOPUS:85167995684

VL - 4

JO - Patterns

JF - Patterns

SN - 2666-3899

IS - 8

M1 - 100778

ER -

ID: 365554145