Cargando…
Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan
The objective of the study was to investigate the predictive factors for the hospitalization of patients who presented with mild to moderate heat illness at an emergency department. We conducted a retrospective survey of hospitals with an emergency department in Yamaguchi Prefecture, Japan. The surv...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586706/ https://www.ncbi.nlm.nih.gov/pubmed/26393633 http://dx.doi.org/10.3390/ijerph120911770 |
_version_ | 1782392417486372864 |
---|---|
author | Yamamoto, Takahiro Todani, Masaki Oda, Yasutaka Kaneko, Tadashi Kaneda, Kotaro Fujita, Motoki Miyauchi, Takashi Tsuruta, Ryosuke |
author_facet | Yamamoto, Takahiro Todani, Masaki Oda, Yasutaka Kaneko, Tadashi Kaneda, Kotaro Fujita, Motoki Miyauchi, Takashi Tsuruta, Ryosuke |
author_sort | Yamamoto, Takahiro |
collection | PubMed |
description | The objective of the study was to investigate the predictive factors for the hospitalization of patients who presented with mild to moderate heat illness at an emergency department. We conducted a retrospective survey of hospitals with an emergency department in Yamaguchi Prefecture, Japan. The survey questionnaire entries included patient age, sex, use of an ambulance, vital signs, blood examination conducted at the emergency department, the length of hospitalization, and outcome. We analyzed the predictive factors for hospitalization in patients with heat illness. A total of 127 patients were analyzed. Of these, 49 (37%) were admitted, with 59% discharged on the day following admission. In univariate analysis, the following inpatient characteristics were predictive for hospitalization: old age, low Glasgow Coma Scale score, elevated body temperature, increased serum C-reactive protein, and increased blood urea nitrogen. In logistic regression multivariate analysis, the following were predictive factors for hospitalization: age of ≥ 65 years (odds ratio (OR) 4.91; 95% confidence interval (CI) 1.42–17.00), body temperature (OR 1.97; 95% CI 1.14–3.41), Glasgow Coma Scale (OR 0.40; 95% CI 0.16–0.98), and creatinine (OR 2.92; 95% CI 1.23–6.94). The results suggest that the elderly with hyperthermia, disturbance of consciousness, and elevated serum creatinine have an increased risk for hospitalization with heat illness. |
format | Online Article Text |
id | pubmed-4586706 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-45867062015-10-06 Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan Yamamoto, Takahiro Todani, Masaki Oda, Yasutaka Kaneko, Tadashi Kaneda, Kotaro Fujita, Motoki Miyauchi, Takashi Tsuruta, Ryosuke Int J Environ Res Public Health Article The objective of the study was to investigate the predictive factors for the hospitalization of patients who presented with mild to moderate heat illness at an emergency department. We conducted a retrospective survey of hospitals with an emergency department in Yamaguchi Prefecture, Japan. The survey questionnaire entries included patient age, sex, use of an ambulance, vital signs, blood examination conducted at the emergency department, the length of hospitalization, and outcome. We analyzed the predictive factors for hospitalization in patients with heat illness. A total of 127 patients were analyzed. Of these, 49 (37%) were admitted, with 59% discharged on the day following admission. In univariate analysis, the following inpatient characteristics were predictive for hospitalization: old age, low Glasgow Coma Scale score, elevated body temperature, increased serum C-reactive protein, and increased blood urea nitrogen. In logistic regression multivariate analysis, the following were predictive factors for hospitalization: age of ≥ 65 years (odds ratio (OR) 4.91; 95% confidence interval (CI) 1.42–17.00), body temperature (OR 1.97; 95% CI 1.14–3.41), Glasgow Coma Scale (OR 0.40; 95% CI 0.16–0.98), and creatinine (OR 2.92; 95% CI 1.23–6.94). The results suggest that the elderly with hyperthermia, disturbance of consciousness, and elevated serum creatinine have an increased risk for hospitalization with heat illness. MDPI 2015-09-18 2015-09 /pmc/articles/PMC4586706/ /pubmed/26393633 http://dx.doi.org/10.3390/ijerph120911770 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yamamoto, Takahiro Todani, Masaki Oda, Yasutaka Kaneko, Tadashi Kaneda, Kotaro Fujita, Motoki Miyauchi, Takashi Tsuruta, Ryosuke Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title | Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title_full | Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title_fullStr | Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title_full_unstemmed | Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title_short | Predictive Factors for Hospitalization of Patients with Heat Illness in Yamaguchi, Japan |
title_sort | predictive factors for hospitalization of patients with heat illness in yamaguchi, japan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586706/ https://www.ncbi.nlm.nih.gov/pubmed/26393633 http://dx.doi.org/10.3390/ijerph120911770 |
work_keys_str_mv | AT yamamototakahiro predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT todanimasaki predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT odayasutaka predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT kanekotadashi predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT kanedakotaro predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT fujitamotoki predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT miyauchitakashi predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan AT tsurutaryosuke predictivefactorsforhospitalizationofpatientswithheatillnessinyamaguchijapan |