體表溫度連續監測於提早發現住院高齡者的發燒事件

Detection of Fever Using Continuous Skin Temperature Monitoring in Hospitalized Older Adults

背景：體表溫度連續監測有助於發現住院病人潛在發燒事件。高齡者相較年輕族群體溫顯得較低且變化較小，但目前缺乏連續體表溫度監測於高齡者發燒事件之探討。
目的：了解住院高齡者體表溫度與常規體溫變化趨勢之相關性，比較不同體表溫度測量頻率與住院高齡者發燒事件之相關性，並探討住院高齡者發燒事件之相關因子。
方法：採前瞻性研究法，針對33位疑似或確診感染住院之65歲以上高齡者，2020年3月至11月於台灣南部某醫學中心感染科及內科病房進行收案。以病歷紀錄收集個案基本資料及每班常規測量之耳溫及心率，同時以溫心智慧手環每10秒收集體表溫度，直至個案出院、連續三日無發燒事件發生或停止配戴手環。以描述性統計比較體表溫度與常規耳溫變化，以皮爾森相關分析不同的體表溫度測量頻率與發燒事件之相關性，最後以多元混合效果羅吉斯回歸分析發燒事件之相關因子。
結果：共有720次常規耳溫測量，其中209次（29.0%）為發燒事件，收案期間共23位（69.7%）高齡者出現發燒事件。當住院高齡者發燒時，連續體表溫度變化與常規測量耳溫變化顯著相關（r = .260, p < .001）。體表溫度監測頻率為10秒及1分鐘時，可發現較多的發燒事件。多元混合效果羅吉斯回歸分析結果發現，體表溫度（odds ratio, OR: 1.74, p < .001）與心率（OR: 1.11, p < .001）為預測住院高齡者發燒事件之相關因子。
結論／實務應用：體表溫度連續監測可偵測住院高齡者發燒事件。結合智慧穿戴裝置與雲端服務平台，期可協助臨床護理師即時評估與照護，進而降低工作負荷及提升照護品質。

Background: The continuous monitoring of body surface temperature has been proven to help detect potential fever events in hospitalized patients. However, the efficacy of using body surface temperature to detect fever in older adults remains unclear due to the relatively low and slower-to-change body surface temperature in this population.
Purpose: This study was designed to investigate 1) the relationship between changes in body surface and routine tympanic temperatures, 2) the correlation between body surface temperature measurement frequency and detection of fever, and 3) the factors related to the incidence of fever in hospitalized older adults.
Methods: A prospective study was conducted on 33 hospitalized older adults aged 65 years or older who were suspected to have or diagnosed with an infection in an infectious disease and medical ward at a medical center in southern Taiwan from March to November 2020. Demographic, routine tympanic temperature, and heart rate data were collected by reviewing the participants’medical records. Body surface temperatures were monitored continuously using HEARThermo every 10 seconds until one of the following conditions were met: hospital discharge, no fever for three continuous days, and HEARThermo was removed. Descriptive analysis was used to compare the variations in body surface temperature and routine tympanic temperature measurements. Pearson correlation was used to analyze the correlation between different measurement frequencies and fever events. Finally, mixed effects logistic regression was used to analyze the factors significantly related to fever events.
Results: Seven hundred and twenty routine body temperature measurements were taken, with 209 (29.0%) fever events detected in 23 (69.7%) of the participants. The body surface temperatures were more closely correlated with tympanic temperatures during fever events than non-fever events (r = .260, p < .001). More fever events were detected using body surface temperature monitoring frequencies of every 10 seconds and every 1 minute. After controlling for demographic factors, the results of the mixed effect model indicate that body surface temperature and heart rate are significant factors related to fever events in hospitalized older adults (odds ratio, OR: 1.74, p < .001; OR: 1.11, p < .001).
Conclusions/ Implications for Practice: The continuous monitoring of body surface temperature may improve the detection of fever events in hospitalized older adults. The application of wearable devices and cloud platforms may further facilitate the real-time assessment and care capabilities of nurses, thus reducing their workload and improving care quality.