Comparing body temperature measurements using the double sensor method within a wearable device with oral and core body temperature measurements using medical grade thermometers—a short report

Introduction: Body temperature is essential for diagnosing, managing, and following multiple medical conditions. There are several methods and devices to measure body temperature, but most do not allow continuous and prolonged measurement of body temperature. Noninvasive skin temperature sensor combined with a heat flux sensor, also known as the “double sensor” technique, is becoming a valuable and simple method for frequently monitoring body temperature.Methods: Body temperature measurements using the “double sensor” method in a wearable monitoring device were compared with oral and core body temperature measurements using medical grade thermometers, analyzing data from two prospective clinical trials of different clinical scenarios. One study included 45 hospitalized COVID-19 patients in which oral measurements were taken using a hand-held device, and the second included 18 post-cardiac surgery patients in which rectal measurements were taken using a rectal probe.Results: In study 1, Bland-Altman analysis showed a bias of −0.04°C [0.34–(−0.43)°C, 95% LOA] with a correlation of 99.4% (p < 0.001). In study 2, Bland-Altman analysis showed a bias of 0.0°C [0.27–(−0.28)°C, 95% LOA], and the correlation was 99.3% (p < 0.001). In both studies, stratifying patients based on BMI and skin tone showed high accordance in all sub-groups.Discussion: The wearable monitor showed high correlation with oral and core body temperature measurements in different clinical scenarios

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Advanced Hemodynamic Monitoring Allows Recognition of Early Response Patterns to Diuresis in Congestive Heart Failure Patients

There are no clear guidelines for diuretic administration in heart failure (HF), and reliable markers are needed to tailor treatment. Continuous monitoring of multiple advanced physiological parameters during diuresis may allow better differentiation of patients into subgroups according to their responses. In this study, 29 HF patients were monitored during outpatient intravenous diuresis, using a noninvasive wearable multi-parameter monitor. Analysis of changes in these parameters during the course of diuresis aimed to recognize subgroups with different response patterns. Parameters did not change significantly, however, subgroup analysis of the last quartile of treatment showed significant differences in cardiac output, cardiac index, stroke volume, pulse rate, and systemic vascular resistance according to gender, and in systolic blood pressure according to habitus. Changes in the last quartile could be differentiated using k-means, a technique of unsupervised machine learning. Moreover, patients’ responses could be best clustered into four groups. Analysis of baseline parameters showed that two of the clusters differed by baseline parameters, body mass index, and diabetes status. To conclude, we show that physiological changes during diuresis in HF patients can be categorized into subgroups sharing similar response trends, making noninvasive monitoring a potential key to personalized treatment in HF

TRY plant trait database - enhanced coverage and open access

10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18