A big data analysis of fever threshold and vital sign characteristics using tympanic temperature in hospitalized patients.

This study aimed to analyze vital sign characteristics of adult patients admitted at the Tertiary Hospital, and to define fever threshold and average body temperature by examining the tympanic temperatures of all patients. Retrospective medical data were extracted from 9195 patients aged > 21 years admitted to a tertiary hospital for elective surgeries between 2016 and 2020. Data regarding the patients' vital signs during their hospital stay, including tympanic body temperature, heart rate, and respiratory rate, were analyzed according to age, sex, and circadian rhythm. A normal-distribution graph was obtained when all the body temperature results were aligned. The average body temperature measured was 36.91 ± 0.45 °C (average ± standard deviation), indicating a potential fever threshold of 37.81 °C. When the participants were divided into age groups, the average temperature, heart rate, and respiratory rate exhibited parabolic trends. Patients in their 60s exhibited the lowest average temperature (36.88 °C), whereas those in their 50s had the lowest average heart rate (75.82/min) and lowest respiratory rate (19.08/min). Heart rate and respiratory rate tended to increase in elderly people older than 81 years. The average body temperature was greater in women than in men (36.94 ± 0.42 °C vs. 36.89 ± 0.47 °C), while the average heart (75.53 ± 10.04/min vs. 77.31 ± 11.52/min) and respiratory rates (19.13 ± 1.39/min vs. 19.29 ± 2.24/min) were lower in women than in men respectively. According to the time of measurement, the average temperature and heart rate appeared to follow a sinusoidal pattern, suggesting that the circadian rhythm was highest at 1 a.m. and lowest at 8 a.m. Tympanic temperature is a convenient measurement method preferred in hospital settings because it is noninvasive and easier to measure compared to other body parts. To develop an improved device and measurement method in the future, it is necessary to analyze tympanic temperature big data and compare it with past vital sign data or biometric information from other body parts.