Journal article
Diurnal temperature variation and the implications for diagnosis and infectious disease screening: a population-based study
Diagnosis (Berlin, Germany), Vol.11(1), pp.54-62
02/19/2024
DOI: 10.1515/dx-2023-0074
PMCID: PMC11005884
PMID: 37697715
Abstract
Abstract Objectives Fevers have been used as a marker of disease for hundreds of years and are frequently used for disease screening. However, body temperature varies over the course of a day and across individual characteristics; such variation may limit the detection of febrile episodes complicating the diagnostic process. Our objective was to describe individual variation in diurnal temperature patterns during episodes of febrile activity using millions of recorded temperatures and evaluate the probability of recording a fever by sex and for different age groups. Methods We use timestamped deidentified temperature readings from thermometers across the US to construct illness episodes where continuous periods of activity in a single user included a febrile reading. We model the mean temperature recorded and probability of registering a fever across the course of a day using sinusoidal regression models while accounting for user age and sex. We then estimate the probability of recording a fever by time of day for children, working-age adults, and older adults. Results We find wide variation in body temperatures over the course of a day and across individual characteristics. The diurnal temperature pattern differed between men and women, and average temperatures declined for older age groups. The likelihood of detecting a fever varied widely by the time of day and by an individual’s age or sex. Conclusions Time of day and demographics should be considered when using body temperatures for diagnostic or screening purposes. Our results demonstrate the importance of follow-up thermometry readings if infectious diseases are suspected.
Details
- Title: Subtitle
- Diurnal temperature variation and the implications for diagnosis and infectious disease screening: a population-based study
- Creators
- Aaron C. Miller - University of IowaScott H. Koeneman - University of IowaManish Suneja - University of IowaJoseph E. Cavanaugh - University of IowaPhilip M. Polgreen - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Diagnosis (Berlin, Germany), Vol.11(1), pp.54-62
- DOI
- 10.1515/dx-2023-0074
- PMID
- 37697715
- PMCID
- PMC11005884
- NLM abbreviation
- Diagnosis (Berl)
- ISSN
- 2194-8011
- eISSN
- 2194-802X
- Grant note
- DOI: 10.13039/100000133, name: Agency for Healthcare Research and Quality, award: R01HS027375
- Language
- English
- Electronic publication date
- 09/13/2023
- Date published
- 02/19/2024
- Academic Unit
- Statistics and Actuarial Science; Infectious Diseases; Epidemiology; Biostatistics; Injury Prevention Research Center; Nephrology; Internal Medicine
- Record Identifier
- 9984463084602771
Metrics
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