Defining Usual Oral Temperature Ranges in Outpatients Using an Unsupervised Learning Algorithm

Author:

Ley Catherine1,Heath Frederik23,Hastie Trevor45,Gao Zijun46,Protsiv Myroslava17,Parsonnet Julie12

Affiliation:

1. Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California

2. Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California

3. currently with University of California, Irvine, School of Medicine

4. Department of Statistics, School of Humanities and Sciences, Stanford University, Stanford, California

5. Division of Biostatistics, Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California

6. currently with USC Marshall Business School, University of Southern California, Los Angeles

7. currently with Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Solna, Sweden

Abstract

ImportanceAlthough oral temperature is commonly assessed in medical examinations, the range of usual or “normal” temperature is poorly defined.ObjectiveTo determine normal oral temperature ranges by age, sex, height, weight, and time of day.Design, Setting, and ParticipantsThis cross-sectional study used clinical visit information from the divisions of Internal Medicine and Family Medicine in a single large medical care system. All adult outpatient encounters that included temperature measurements from April 28, 2008, through June 4, 2017, were eligible for inclusion. The LIMIT (Laboratory Information Mining for Individualized Thresholds) filtering algorithm was applied to iteratively remove encounters with primary diagnoses overrepresented in the tails of the temperature distribution, leaving only those diagnoses unrelated to temperature. Mixed-effects modeling was applied to the remaining temperature measurements to identify independent factors associated with normal oral temperature and to generate individualized normal temperature ranges. Data were analyzed from July 5, 2017, to June 23, 2023.ExposuresPrimary diagnoses and medications, age, sex, height, weight, time of day, and month, abstracted from each outpatient encounter.Main Outcomes and MeasuresNormal temperature ranges by age, sex, height, weight, and time of day.ResultsOf 618 306 patient encounters, 35.92% were removed by LIMIT because they included diagnoses or medications that fell disproportionately in the tails of the temperature distribution. The encounters removed due to overrepresentation in the upper tail were primarily linked to infectious diseases (76.81% of all removed encounters); type 2 diabetes was the only diagnosis removed for overrepresentation in the lower tail (15.71% of all removed encounters). The 396 195 encounters included in the analysis set consisted of 126 705 patients (57.35% women; mean [SD] age, 52.7 [15.9] years). Prior to running LIMIT, the mean (SD) overall oral temperature was 36.71 °C (0.43 °C); following LIMIT, the mean (SD) temperature was 36.64 °C (0.35 °C). Using mixed-effects modeling, age, sex, height, weight, and time of day accounted for 6.86% (overall) and up to 25.52% (per patient) of the observed variability in temperature. Mean normal oral temperature did not reach 37 °C for any subgroup; the upper 99th percentile ranged from 36.81 °C (a tall man with underweight aged 80 years at 8:00 am) to 37.88 °C (a short woman with obesity aged 20 years at 2:00 pm).Conclusions and RelevanceThe findings of this cross-sectional study suggest that normal oral temperature varies in an expected manner based on sex, age, height, weight, and time of day, allowing individualized normal temperature ranges to be established. The clinical significance of a value outside of the usual range is an area for future study.

Publisher

American Medical Association (AMA)

Subject

Internal Medicine

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1. Aquarium fish and temperature neuropharmacology. Update.;Psychopharmacology & biological narcology;2024-02-02

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