| Unique ID issued by UMIN | UMIN000061895 |
|---|---|
| Receipt number | R000070822 |
| Scientific Title | Construction of an Input Data Structure for Biothermal Modeling Using Clinical, Exposure, and Environmental Data in Patients with Heatstroke: A Prospective Observational Study |
| Date of disclosure of the study information | 2026/06/13 |
| Last modified on | 2026/06/13 14:49:31 |
A Study to Evaluate Heat Stress Using Clinical, Exposure, and Environmental Data in Patients with Heatstroke
SAFE-HEAT Study
Construction of an Input Data Structure for Biothermal Modeling Using Clinical, Exposure, and Environmental Data in Patients with Heatstroke: A Prospective Observational Study
SAFE-HEAT Study
| Japan |
Heat Stroke
| Emergency medicine |
Others
NO
The objective of this study is to construct an input data structure for connecting real-world clinical data to a biothermal model in adult patients who are transported to or visit the emergency department with heatstroke or heat-related illness.
Clinical, exposure, and environmental information required for biothermal modeling will be extracted from medical records, ambulance records, and public environmental databases corresponding to the time and location of heat exposure. The study will also evaluate the availability of model-input variables, linkage feasibility with environmental data, and the proportion of cases in which model-derived thermophysiological indices can be calculated. Exploratory analyses will assess the relationship between model-derived indices and measured body temperature and clinical course.
Others
To exploratorily evaluate the associations between model-derived thermophysiological indices, including estimated core body temperature, rate of core temperature increase, body heat storage, and sweating burden, and clinical variables such as measured body temperature on arrival, cooling intervention, hospital admission, ICU admission, length of hospital stay, and laboratory data obtained during routine clinical care.
Feasibility of constructing a core clinical, exposure, and environmental dataset required for biothermal model input
Specifically, the study will evaluate the proportion of cases in which information on time and location of heat exposure, exposure duration, activity, clothing, ambient temperature, humidity, wet-bulb globe temperature, wind speed, solar radiation, and other relevant variables can be extracted from medical records, ambulance records, and public environmental databases and integrated into a format suitable for biothermal model input.
Availability rate of each model-input variable
Linkage rate with environmental data based on the time and location of heat exposure
Proportion of cases in which model-derived indices, including estimated core body temperature, rate of core temperature increase, body heat storage, and sweating burden, can be calculated
Difference between model-estimated core body temperature and measured body temperature on arrival
Exploratory associations between model-derived thermophysiological indices and clinical course, including cooling intervention, hospital admission, ICU admission, and length of hospital stay
Exploratory associations between model-derived indices and laboratory data obtained during routine clinical care
Observational
| 18 | years-old | <= |
| 100 | years-old | >= |
Male and Female
Adults aged 18 years or older
Patients transported to or visiting the emergency department of Yamagata University Hospital
Patients diagnosed with heatstroke or heat-related illness
Patients for whom written informed consent is obtained from the patient or a legally acceptable representative
Patients in whom conditions other than heatstroke, such as infection, central nervous system disease, neuroleptic malignant syndrome, or acute drug intoxication, are clearly considered the primary cause of hyperthermia
Patients with insufficient information on the time or location of heat exposure, making acquisition of environmental data difficult
Patients with substantial missing data for key variables required for biothermal model input
Patients or legally acceptable representatives who decline participation or withdraw consent
Patients judged by the principal investigator to be inappropriate for inclusion in the study
50
| 1st name | Ryuto |
| Middle name | |
| Last name | Yokoyama |
Yamagata University
Department of Emergency Medicine, Yamagata University Faculty of Medicine
990-9585
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
0236331122
ryusi0311@gmail.com
| 1st name | RYUTO |
| Middle name | |
| Last name | YOKOYAMA |
Yamagata University Faculty of Medicine
Department of Emergency Medicine, Yamagata University Faculty of Medicine
9909585
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
0236285422
ryusi0311@gmail.com
Yamagata University
Yamagata Univercity
Other
Ethics Review Committee, Faculty of Medicine, Yamagata University
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
0236331122
ryusi0311@gmail.com
NO
| 2026 | Year | 06 | Month | 13 | Day |
Unpublished
Open public recruiting
| 2026 | Year | 06 | Month | 02 | Day |
| 2026 | Year | 06 | Month | 12 | Day |
| 2026 | Year | 06 | Month | 13 | Day |
| 2028 | Year | 12 | Month | 31 | Day |
This is a single-center, prospective, observational study of patients with heatstroke or heat-related illness who are transported to or visit the emergency department of Yamagata University Hospital. No research-specific intervention will be performed. The study will collect clinical information obtained during routine care, ambulance records, and public environmental data corresponding to the time and location of heat exposure.
The main exposure-related variables include time and location of heat exposure, exposure duration, indoor or outdoor setting, activity, clothing, air-conditioning use, fluid intake, ambient temperature, humidity, wet-bulb globe temperature, wind speed, and solar radiation. The main outcomes include feasibility of constructing a model-input dataset, availability rate of each input variable, linkage rate with environmental data, proportion of cases in which model-derived indices can be calculated, and exploratory associations between model-derived thermophysiological indices and clinical course.
Eligible patients who meet the inclusion criteria and do not meet any exclusion criteria will be consecutively enrolled during the study period.
| 2026 | Year | 06 | Month | 13 | Day |
| 2026 | Year | 06 | Month | 13 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000070822