Background Body temperature control is a frequently used screening test for infectious diseases, such as . We used this procedure to test the body temperature of staff members in a hospital in Tyrol (Austria), where the Covid-19 disease occurred in March 2020. The hospital is located in a mountain area at 995 m above sea level with low outdoor temperatures during early spring season. Under these conditions, we analyzed whether forehead temperature control offers a sufficient screening tool for infectious diseases. Methods Forehead temperature of 101 healthy male and female employees was measured with an infrared thermometer directly after entering the hospital (0 min), followed by further controls after 1 min, 3 min, 5 min and 60 min. We also tracked the outside temperature and the temperature at the entrance hall of the hospital. Results Complete data of body temperature were available for 46 female and 46 male study participants. The average forehead temperature measured directly after entrance to the hospital was the lowest (0 min) 33.17 ± 1.45°C, and increased constantly to 34.90 ± 1.49°C after 1 min, 35.77 ± 1.10°C after 3 min, 36.08 ± 0.79°C after 5 min, and 36.6 ± 0.24°C after 60 min. The outside temperature ranged between -5.5°C and 0°C, the indoor temperature had a constant value of 20.5°C.

Background The activities of daily living (ADL) score is a widely used index to establish the degree of independence from any help in everyday life situations. Measuring ADL accurately is time-consuming and costly. This paper presents a framework to approximate ADL via variables usually collected in comprehensive geriatric assessments. We show that the selected variables serve as good indicators in explaining the physical disabilities of older patients. Methods Our sample included information from a geriatric assessment of 326 patients aged between 64 and 99 years in a hospital in Tyrol, Austria. In addition to ADL, 23 variables reflecting the physical and mental status of these patients were recorded during the assessment. We performed least absolute shrinkage and selection operator (LASSO) to determine which of these variables had the highest impact on explaining ADL. Then, we used receiver operating characteristic (ROC) analysis and logistic regression techniques to validate our model performance. Finally, we calculated cut-off points for each of the selected variables to show the values at which ADL fall below a certain threshold. Results Mobility, urinary incontinence, nutritional status and cognitive function were most closely related to ADL and, therefore, to geriatric patients’ functional limitations. Jointly, the selected variables were able to detect neediness with high accuracy (area under the ROC curve (AUC) = 0.89 and 0.91, respectively). If a patient had a limitation in one of these variables, the probability of everyday life disability increased with a statistically significant factor between 2.4 (nutritional status, 95%-CI 1.5–3.9) and 15.1 (urinary incontinence, 95%-CI 3.6–63.4). Conclusions Our study highlights the most important impairments of everyday life to facilitate more efficient use of clinical resources, which in turn allows for more targeted treatment of geriatric patients. At the patient level, our approach enables early detection of functional limitations and timely indications of a possible need for assistance in everyday life.

Background: The Activities of Daily Living score (ADL) is a widely used index to establish the degree of independence from any help in everyday life situations. Measuring the ADL accurately is time-consuming and costly. This paper presents a framework to approximate the ADL via variables usually collected in standard geriatric assessments. We showed that the selected variables serve as good indicators in explaining the physical disabilities of older and frail patients. Methods: Our sample included information from a geriatric assessment of 326 patients aged between 64 and 99 years in a hospital in Tyrol, Austria. In addition to the ADL, 23 variables reflecting the physical and mental status of these patients were recorded during the assessment. We performed LASSO to determine which of these variables had the highest impact on explaining the ADL. Then, we used ROC analysis and logistic regression techniques to validate our model performance. Finally, we calculated cutoff-points for each of the selected variables, showing at which values the ADL falls below a certain threshold. Results: Mobility, urinary incontinence, nutritional status and cognitive function were closest related to the ADL and, therefore, to a geriatric patient’s functional limitations. Jointly, the selected variables were able to predict neediness with high accuracy (AUC = 0.89 and 0.91, respectively). If a patient had a limitation in one of these variables, the probability of everyday life disability increased with a statistically significant factor between 2.4 (nutritional status, 95%-CI 1.5 – 3.9) and 15.1 (urinary incontinence, 95%-CI 3.6 – 63.4). Conclusions: Our study highlighted the most important impairments of everyday live, facilitating a more efficient use of clinical resources which, in turn, allows for a more targeted treatment of geriatric patients. At the patient level, our approach enables early detection of functional limitations and timely indications of a possible need for assistance in everyday life.