Monitoring Of Vital Signs Research Articles

Outcomes in patients receiving continuous monitoring of vital signs on general wards: A systematic review and meta-analysis of randomised controlled trials.

The timely identification of deterioration on general wards is crucial to patient care with each hour of delay independently associated with increased risk of death. The introduction of continuous monitoring of patient vital signs on general wards, currently not standard care, may improve patient outcomes. Our aim was to investigate whether patients on general wards receiving continuous vital signs monitoring have better outcomes than patients receiving usual care. Meta-analysis of randomised controlled trials comparing non-critical care patients receiving continuous monitoring of vital signs to usual care. We searched Medline, Embase, and Web of Science, and assessed risk of bias with version 2 of the Cochrane risk-of-bias tool for randomised trials. In addition to measures related to the early detection of deterioration, we planned to present all patient outcomes reported by the clinical trials included. We included seven trials involving 1284 participants. There were no statistically significant differences in the four outcomes pooled. Comparing continuously monitored to normal care, the pooled odds for hospital mortality, major event/complication, and HDU/ICU admission was 0.95 (95% CI 0.59-1.53, p = 0.84; 660 participants, 3 studies), 0.71 (95% CI 0.38-1.31, p = 0.27; 948 participants, 4 studies) and 0.82 (95% CI 0.25-2.67, p = 0.74; 655 participants, 4 studies), respectively. The mean difference for length of stay was 2.12 days lower (95% CI -5.56 to 1.32, p = 0.23; 1034 participants, 6 studies). We found no significant improvements in outcomes for patients continuously monitored compared to usual care. Further research is needed to understand what modalities of continuous monitoring may influence outcomes and investigate the implications of a telepresence service and multi-parameter scoring system. PROSPERO CRD42023458656.

Patients' expectations and experiences with the usage of a self-care application for heart failure: A qualitative interview study.

Heart failure (HF) is a chronic disease characterized by high mortality and healthcare expenditures. Digital health solutions, including mobile health applications (apps), offer opportunities to enhance patients' self-care and quality of life. This qualitative study aimed to explore expectations, experiences, and usage behaviour of HF-patients regarding a self-care app (DoctorME app). Semi-structured interviews were conducted at 2-3 weeks (initial: n = 38), and 4-6 months (post: n = 45) of app use across four European countries. Most patients were male (initial: 84%; post: 78%), aged 60-69 years (initial and post: 29%), with mild HF symptoms. Interviews were transcribed, pseudonymised, and analysed using qualitative content analysis. Five key themes were identified: 1) expectations, 2) perceived usability and benefit, 3) usage behaviour and experiences, 4) self-care, and 5) social influences. Patients expected and valued continuous monitoring of vital signs and weight, early detection of deterioration, and quick feedback. The app was considered user-friendly, with most patients using it as recommended (eight times per month). Those reporting improved self-care attributed it to increased awareness and a sense of security. Patients with established self-care routines did not perceive any additional benefit. Patients' perceptions on the impact of healthcare professionals' and relatives opinions on app use were divided. User-friendliness, continuous monitoring, rapid feedback, and e-learning modules are crucial for integrating self-care apps into daily HF care. While technical reliability and individualisation may enhance long-term use, most HF patients considered the app as a complement to, not a replacement for, professional healthcare guidance.

The burden of treatment of propranolol for infantile hemangiomas: A mixed methods study.

The burden of treatment (BOT) related to propranolol treatment for infantile hemangiomas (IH) has never previously been explored. A modified validated questionnaire, the Treatment Burden Questionnaire, and one-on-one semi-structured interviews were used to assess the BOT for propranolol for IH. Out of 80 caregivers, the overall burden score was very low at 1.2 out of 10; thematic analysis of interviews grouped themes into administration, monitoring, financial, and associated anomalies. The BOT of propranolol for IH is very low but could be reduced further by offering age-based risk stratification related to feeding frequency and risk of hypoglycemia, pragmatic advice around timing of doses before sleep, and reducing frequency of vital sign monitoring.

A Data-Driven Framework for Clinical Decision Support Systems in Positive Airway Pressure and Oxygen Titration

Background: Current obstructive sleep apnea treatment relies on manual PAP titration, but it has limitations. Complex interactions during titration and variations in SpO2 data accuracy pose challenges. Patients with co-occurring chronic hypercapnia may require precise oxygen titration. To address these issues, we propose a Clinical Decision Support System using Markov decision processes. Methods: This study, compliant with data protection laws, focused on adults with OSA-induced hypoxemia utilizing supplemental oxygen and CPAP/BiPAP therapy. PAP titration, conducted over one night, involved vigilant monitoring of vital signs and physiological parameters. Adjustments to CPAP pressure, potential BiLevel transitions, and supplemental oxygen were precisely guided by patient metrics. Markov decision processes outlined three treatment actions for disorder management, incorporating expert medical insights. Results: In our study involving 14 OSA patients (average age: 63 years, 27% females, BMI 41 kg m−2), significant improvements were observed in key health parameters after manual titration. The initial AHI of 61.8 events per hour significantly decreased to an average of 18.0 events per hour after PAP and oxygen titration (p < 0.0001), indicating a substantial reduction in sleep-disordered breathing severity. Concurrently, SpO2 levels increased significantly from an average of 79.7% before titration to 89.1% after titration (p < 0.0003). Pearson correlation coefficients demonstrated aggravation of hypercapnia in 50% of patients (N = 5) with initial pCO2 < 55 mmHg during the increase in CPAP pressure. However, transitioning to BiPAP exhibited a reduction in pCO2 levels, showcasing its efficacy in addressing hypercapnia. Simultaneously, BiPAP therapy correlated with a substantial increase in SpO2, underscoring its positive impact on oxygenation in OSA patients. Markov Decision Process analysis demonstrated realistic patient behavior during stable night conditions, emphasizing minimal apnea and good toleration to high CPAP pressure. Conclusions: The development of a framework for Markov decision processes of PAP and oxygen titration algorithms holds promise for providing algorithms for improving pCO2 and SpO2 values. While challenges remain, including the need for high-quality data, the potential benefits in terms of patient management and care optimization are substantial, and this approach represents an exciting frontier in the realm of telemedicine and respiratory healthcare.

AI algorithm for personalized resource allocation and treatment of hemorrhage casualties

A deep neural network-based artificial intelligence (AI) model was assessed for its utility in predicting vital signs of hemorrhage patients and optimizing the management of fluid resuscitation in mass casualties. With the use of a cardio-respiratory computational model to generate synthetic data of hemorrhage casualties, an application was created where a limited data stream (the initial 10 min of vital-sign monitoring) could be used to predict the outcomes of different fluid resuscitation allocations 60 min into the future. The predicted outcomes were then used to select the optimal resuscitation allocation for various simulated mass-casualty scenarios. This allowed the assessment of the potential benefits of using an allocation method based on personalized predictions of future vital signs versus a static population-based method that only uses currently available vital-sign information. The theoretical benefits of this approach included up to 46% additional casualties restored to healthy vital signs and a 119% increase in fluid-utilization efficiency. Although the study is not immune from limitations associated with synthetic data under specific assumptions, the work demonstrated the potential for incorporating neural network-based AI technologies in hemorrhage detection and treatment. The simulated injury and treatment scenarios used delineated possible benefits and opportunities available for using AI in pre-hospital trauma care. The greatest benefit of this technology lies in its ability to provide personalized interventions that optimize clinical outcomes under resource-limited conditions, such as in civilian or military mass-casualty events, involving moderate and severe hemorrhage.

Through the wall human heart beat detection using single channel CW radar.

Single-channel continuous wave (CW) radar is widely used and has gained popularity due to its simple architecture despite its inability to measure the range and angular location of the target. Its popularity arises in the industry due to the simplicity of the required components, the low demands on the sampling rate, and their low costs. Through-the-wall life signs detection using microwave Doppler Radar is an active area of research and investigation. Most of the work in the literature focused on utilizing multi-channel frequency modulated continuous wave (FMCW), CW, and ultra-wideband (UWB) radar for their capability of range and direction of arrival (DOA) estimation. In this paper, through-the-wall single-subject and two-subject concurrent heart rate detection using single-channel 24-GHz CW radar leveraged with maximal overlap discrete wavelet transform (MODWT) is proposed. Experimental results demonstrated that the repetitive measurement of seven different subjects at a distance of 20cm up to 100cm through two different barriers (wood and brick wall) showed an average accuracy of heart rate extraction of 95.27% for varied distances (20-100cm) in comparison with the Biopac ECG acquisition signal. Additionally, the MODWT method can also isolate the independent heartbeat waveforms from the two subjects' concurrent measurements through the wall. This involved four trials with eight different subjects, achieving an accuracy of 97.04% for a fixed distance of 40cm from the Radar without estimating the angular location of the subjects. Notably, it also superseded the performance of the direct FFT method for the single subject after 40cm distance measurements. The proposed simpler architecture of single-channel CW radar leveraged with MODWT has several potential applications, including post-disaster search and rescue scenarios for finding the trapped, injured people under the debris, emergency evacuation, security, surveillance, and patient vital signs monitoring.

A public dataset of dogs vital signs recorded with ultra wideband radar and reference sensors

Recently, radar sensors have been extensively used for vital sign monitoring in dogs, owing to their noncontact and noninvasive nature. However, a public dataset on dog vital signs has yet to be proposed since capturing data from dogs requires special training and approval. This work presents the first ever ultra wideband radar-based dog vital sign (UWB-DVS) dataset, which was captured in two independent scenarios. In the first scenario, clinical reference sensors are attached to the fainted dogs, and data from UWB radar and reference sensors are captured synchronously. In the second scenario, the dogs can move freely, and video recordings are provided as a reference for movement detection and breathing extraction. For technical validation, a high correlation, above 0.9, is found between the radar and clinical reference sensors for both the heart rate and breathing rate measurements in scenario 1. In scenario 2, the vital signs and movement of the dogs are shown in the form of dashboards, demonstrating the long-term monitoring capability of the radar sensor.

Tetanus Severity Classification in Low-Middle Income Countries through ECG Wearable Sensors and a 1D-Vision Transformer

Tetanus, a life-threatening bacterial infection prevalent in low- and middle-income countries like Vietnam, impacts the nervous system, causing muscle stiffness and spasms. Severe tetanus often involves dysfunction of the autonomic nervous system (ANS). Timely detection and effective ANS dysfunction management require continuous vital sign monitoring, traditionally performed using bedside monitors. However, wearable electrocardiogram (ECG) sensors offer a more cost-effective and user-friendly alternative. While machine learning-based ECG analysis can aid in tetanus severity classification, existing methods are excessively time-consuming. Our previous studies have investigated the improvement of tetanus severity classification using ECG time series imaging. In this study, our aim is to explore an alternative method using ECG data without relying on time series imaging as an input, with the aim of achieving comparable or improved performance. To address this, we propose a novel approach using a 1D-Vision Transformer, a pioneering method for classifying tetanus severity by extracting crucial global information from 1D ECG signals. Compared to 1D-CNN, 2D-CNN, and 2D-CNN + Dual Attention, our model achieves better results, boasting an F1 score of 0.77 ± 0.06, precision of 0.70 ± 0. 09, recall of 0.89 ± 0.13, specificity of 0.78 ± 0.12, accuracy of 0.82 ± 0.06 and AUC of 0.84 ± 0.05.

Executive Summary: Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU.

Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care facilities have implemented systems aimed at detecting and responding to such patients. To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based clinical practice guidelines. We generated actionable questions using the Population, Intervention, Control, and Outcomes format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among "unselected" patients due to the absence of data regarding the benefit and the potential harms of false positive alarms, the risk of alarm fatigue, and cost. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system (GPS). The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023.

Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care hospitals have implemented systems aimed at detecting and responding to such patients. To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines. We generated actionable questions using the Population, Intervention, Control, and Outcomes (PICO) format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation Approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among unselected patients. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system. The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Mapping knowledge landscapes and emerging trends of non-contact vital signs monitoring: A bibliometric and visualization analysis from 2002 to 2023

This study makes a comparative analysis based on knowledge mapping of Chinese and English publications on non-contact vital signs monitoring and provides a reference for future research and development. Publications were retrieved from Web of Science (WoS) and PubMed, China National Knowledge Infrastructure (CNKI), and Wanfang databases from January 1, 2002 to October 31, 2023. Bibliometric analysis was performed using CiteSpace software. Information from 612 English and 543 Chinese original research articles was collected and analyzed. The maximum number of English appeared in 2022 and the maximum number of Chinese articles appeared in 2020, and the number of articles published afterward declined slightly. For the articles published in English, USA and China shared the highest number of publications. Chinese Academy of Sciences was the most published institution. Steffen Leonhardt was the highest-published author. Meanwhile, within the Chinese articles, the most productive province was Beijing. The most productive institution was the Air Force Medical University. The most productive author was Weixue Liu. The research institutions and authors of English and Chinese articles were decentralized. The hotspots of the English articles mainly were “heart rate” and “respiratory rate”, and the Chinese articles focused on “temperature” and “heart rate”. Concluding, the research on non-contact vital signs monitoring is in a booming phase of development at present. Non-contact heart rate monitoring is a popular research direction in English and Chinese research. In the future, research institutions and authors should strengthen their cooperation and communication to promote the development of this research area.

Vital signs estimation in elderly using camera-based photoplethysmography

In the context of Ambient Assisted Living, the demand for healthcare technologies development has been increased in the last two years by the current global health situation. The contagious nature of COVID-19 warrants inevitability to the thought of easing a continuous measurement of vital signs such as Heart Rate, Breath Rate, and SpO2 in a non-invasive manner, contributing of fundamental importance in the assessment of health status especially among frail and/or elderly individuals. A widely diffused method for contactless vital signs monitoring is remote photoplethysmography from facial video streams that, contrary to traditional contact measurement techniques, allows the measurement of vital parameters without the need for wearable sensors (generally considered uncomfortable, especially by the elderly), even with commercial and low-cost digital cameras. This paper proposes the design and implementation of a new pipeline for estimating Heart Rate, Breath Rate, and SpO2 values, and its integration on Raspberry Pi 4 as an elaboration unit. The pipeline provides specific algorithmic blocks to improve vital signs estimation in elderly subjects as it is made more difficult by the skin tone and the presence on the face of wrinkles, folds, and moles. Quantitative evaluations on our dataset containing the acquisition of only elderly older than 65 years of age demonstrate the validity of the proposed pipeline. For validation against the state of the art, tests were also conducted on three standard benchmark datasets containing video with subjects of varying ages. Again, the pipeline proved to be robust concerning the estimation of vital signs considered in the present work.

Three Years of Continuous Vital Signs Monitoring on the General Surgical Ward: Is It Sustainable? A Qualitative Study.

Continuous monitoring of vital signs using a wireless wearable device was implemented in 2018 at a surgical care unit of an academic hospital. This study aimed at gaining insight into nurses' and patients' perspectives regarding the use and innovation of a continuous vital signs monitoring system, three years after its introduction. This qualitative study was performed in a surgical, non-intensive care unit of an academic hospital in 2021. Key-user nurses (nurses with additional training and expertise with the device) and patients were selected for semi-structured interviews, and nurses from the ward were selected for a focus group interview using a topic list. Transcripts of the audio tapes were deductively analysed using four dimensions for adoptions of information and communication technologies (ICT) devices in healthcare. The device provided feelings of safety for nurses and patients. Nurses and patients had a few issues with the device, including the size and the battery life. Nurses gained knowledge and skills in using the system for measurement and interpretations. They perceived the system as a tool to improve the recognition of clinical decline. The use of the system could be further developed regarding the technical device's characteristics, nurses' interpretation of the data and the of type of alarms, the information needs of patients, and clarification of the definition and standardization of continuous monitoring. Three years after the introduction, wireless continuous vital signs monitoring is the new standard of care according to the end-users at the general surgical ward.

Post-hospitalization remote monitoring for patients with heart failure or chronic obstructive pulmonary disease in an accountable care organization

BackgroundPost-hospitalization remote patient monitoring (RPM) has potential to improve health outcomes for high-risk patients with chronic medical conditions. The purpose of this study is to determine the extent to which RPM for patients with congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) is associated with reductions in post-hospitalization mortality, hospital readmission, and ED visits within an Accountable Care Organization (ACO).MethodsNonrandomized prospective study of patients in an ACO offered enrollment in RPM upon hospital discharge between February 2021 and December 2021. RPM comprised of vital sign monitoring equipment (blood pressure monitor, scale, pulse oximeter), tablet device with symptom tracking software and educational material, and nurse-provided oversight and triage. Expected enrollment was for at least 30-days of monitoring, and outcomes were followed for 6 months following enrollment. The co-primary outcomes were (a) the composite of death, hospital admission, or emergency care visit within 180 days of eligibility, and (b) time to occurrence of this composite. Secondary outcomes were each component individually, the composite of death or hospital admission, and outpatient office visits. Adjusted analyses involved doubly robust estimation to address confounding by indication.ResultsOf 361 patients offered remote monitoring (251 with CHF and 110 with COPD), 140 elected to enroll (106 with CHF and 34 with COPD). The median duration of RPM-enrollment was 54 days (IQR 34–85). Neither the 6-month frequency of the co-primary composite outcome (59% vs 66%, FDR p-value = 0.47) nor the time to this composite (median 29 vs 38 days, FDR p-value = 0.60) differed between the groups, but 6-month mortality was lower in the RPM group (6.4% vs 17%, FDR p-value = 0.02). After adjustment for confounders, RPM enrollment was associated with nonsignificantly decreased odds for the composite outcome (adjusted OR [aOR] 0.68, 99% CI 0.25–1.34, FDR p-value 0.30) and lower 6-month mortality (aOR 0.41, 99% CI 0.00–0.86, FDR p-value 0.20).ConclusionsRPM enrollment may be associated with improved health outcomes, including 6-month mortality, for selected patient populations.

Anesthesia Patient Monitoring 2050.

The monitoring of vital signs in patients undergoing anesthesia began with the very first case of anesthesia and has evolved alongside the development of anesthesiology ever since. Patient monitoring started out as a manually performed, intermittent, and qualitative assessment of the patient's general well-being in the operating room. In its evolution, patient monitoring development has responded to the clinical need, for example, when critical incident studies in the 1980s found that many anesthesia adverse events could be prevented by improved monitoring, especially respiratory monitoring. It also facilitated and perhaps even enabled increasingly complex surgeries in increasingly higher-risk patients. For example, it would be very challenging to perform and provide anesthesia care during some of the very complex cardiovascular surgeries that are almost routine today without being able to simultaneously and reliably monitor multiple pressures in a variety of places in the circulatory system. Of course, anesthesia patient monitoring itself is enabled by technological developments in the world outside of the operating room. Throughout its history, anesthesia patient monitoring has taken advantage of advancements in material science (when nonthrombogenic polymers allowed the design of intravascular catheters, for example), in electronics and transducers, in computers, in displays, in information technology, and so forth. Slower product life cycles in medical devices mean that by carefully observing technologies such as consumer electronics, including user interfaces, it is possible to peek ahead and estimate with confidence the foundational technologies that will be used by patient monitors in the near future. Just as the discipline of anesthesiology has, the patient monitoring that accompanies it has come a long way from its beginnings in the mid-19th century. Extrapolating from careful observations of the prevailing trends that have shaped anesthesia patient monitoring historically, patient monitoring in the future will use noncontact technologies, will predict the trajectory of a patient's vital signs, will add regional vital signs to the current systemic ones, and will facilitate directed and supervised anesthesia care over the broader scope that anesthesia will be responsible for.

A comprehensive view of the promotion and prevention of Chronic Non-Communicable Diseases in older adults at the Clemencia Foundation and the Sofia Ratinoff Nursing Home

Health promotion and disease prevention in older adults are essential to improve their quality of life and reduce health care costs in this growing population. A diagnostic study in this area focuses on identifying specific health needs, assessing risk factors, and proposing effective interventions. The objective of this study is to characterize the current state of health promotion and NCD prevention in older adults at the Clemencia Foundation and the Sofia Ratinoff Asylum in the city of Guayaquil. This research is developed by students and teachers of the Emergency Medical career of the Instituto Superior Universitario Espiritu Santo, as part of the project "Promotion and control of NCDs in older adults". The study uses a combination of quantitative and qualitative methods, including surveys, interviews and statistical data analysis. The population studied includes older adults and health professionals from the Clemencia Foundation and the Sofia Ratinoff Asylum, providing a comprehensive view of their health conditions and needs. The results conclude that chronic diseases such as hypertension, diabetes and arthritis are common in older adults, as are respiratory and mental health problems. Risk factors identified include poor dietary habits, lack of physical activity, poor vital sign monitoring, and limited participation of older adults in health promotion programs.

A Combination of Early Enteral Nutrition Support and Nutritional Nursing Interventions Effectively Improves Nutritional Status of Patients with Liver Cirrhosis

This study aimed to examine the clinical impact of early enteral nutrition support combined with nutritional nursing intervention on the bleeding status, nutritional status, and prognosis of patients with liver cirrhosis complicated with upper gastrointestinal bleeding. The patients were divided into two groups: an observation group and a control group. The observation group (n = 50) received early enteral nutrition support, combined with nutritional nursing interventions, while the control group (n = 50) received conventional nursing, including guidance on a healthy diet and vital sign monitoring. We found that body mass index, albumin, and total protein levels were higher among patients in the observation group than among those in the control group. The total effective rate was higher among patients in the observation group than among those in the control group. Patients in the observation group had lower rates of rebleeding frequency, self-rating anxiety and depression scale scores, and complications than those in the control group. Early enteral nutrition support combined with scientific and effective nutritional nursing interventions, can effectively improve the nutritional status of patients with liver cirrhosis complicated with upper gastrointestinal bleeding, thereby preventing complications and facilitating patients’ recovery; this should be widely promoted in clinical practice.

Enhancing well-being in modern education: A comprehensive eHealth proposal for managing stress and anxiety based on machine learning

In the evolving education landscape, institutions are transitioning to a hybrid model encompassing physical and virtual classes. In this scenario, as working hours and exhausting routines increase, individuals accumulate psychological and physical challenges over time. This change requires students and educators to adjust to changes in teaching and learning routines, leading to moments of stress and anxiety. Cultivating self-awareness about unhealthy habits emerges as a pragmatic strategy to address this issue. In this work, a comprehensive eHealth proposal is developed to provide individuals with pertinent health information, assisting educational agents (students and teachers) in identifying and managing these stressful instances during their daily activities. This proposal acquires, processes, and disseminates vital sign data using IoT devices, supported by a Fog Computing architecture for scalability and adaptability. IoT plays a pivotal role in this eHealth proposal, facilitating the seamless collection and transmission of real-time data from various devices. Connected wearables and sensors enable the continuous monitoring of vital signs, enhancing the accuracy and responsiveness of the system. Heart rate data from educational agents were collected for implementation, allowing the evaluation of system performance. Machine learning models were leveraged to discern behavioral profiles and predict possible irregularities in vital signs. The results confirm the system’s ability to perform its intended functions, giving users quick and accurate insights into their evolving behavioral patterns. Integrating these research perspectives underscores the importance of adaptive systems in navigating the challenges of modern education environments. The incorporation of IoT technology not only enhances data collection but also opens avenues for real-time interventions and personalized feedback, ultimately contributing to a more proactive approach in addressing health-related concerns within the educational context.

Surveillance of high-risk early postsurgical patients for real-time detection of complications using wireless monitoring (SHEPHERD study): results of a randomized multicenter stepped wedge cluster trial.

Vital signs measurements on the ward are performed intermittently. This could lead to failure to rapidly detect patients with deteriorating vital signs and worsens long-term outcome. The aim of this study was to test the hypothesis that continuous wireless monitoring of vital signs on the postsurgical ward improves patient outcome. In this prospective, multicenter, stepped-wedge cluster randomized study, patients in the control group received standard monitoring. The intervention group received continuous wireless monitoring of heart rate, respiratory rate and temperature on top of standard care. Automated alerts indicating vital signs deviation from baseline were sent to ward nurses, triggering the calculation of a full early warning score followed. The primary outcome was the occurrence of new disability three months after surgery. The study was terminated early (at 57% inclusion) due to COVID-19 restrictions. Therefore, only descriptive statistics are presented. A total of 747 patients were enrolled in this study and eligible for statistical analyses, 517 patients in the control group and 230 patients in the intervention group, the latter only from one hospital. New disability at three months after surgery occurred in 43.7% in the control group and in 39.1% in the intervention group (absolute difference 4.6%). This is the largest randomized controlled trial investigating continuous wireless monitoring in postoperative patients. While patients in the intervention group seemed to experience less (new) disability than patients in the control group, results remain inconclusive with regard to postoperative patient outcome due to premature study termination. ClinicalTrials.gov, ID: NCT02957825.

Evaluation of the nurse-assisted eHealth intervention ‘eHealth@Hospital-2-Home’ on self-care by patients with heart failure and colorectal cancer post-hospital discharge: protocol for a randomised controlled trial

BackgroundPatients with heart failure (HF) and colorectal cancer (CRC) are prone to comorbidity, a high rate of readmission, and complex healthcare needs. Self-care for people with HF and CRC after hospitalisation can be challenging, and patients may leave the hospital unprepared to self-manage their disease at home. eHealth solutions may be a beneficial tool to engage patients in self-care.MethodsA randomised controlled trial with an embedded evaluation of intervention engagement and cost-effectiveness will be conducted to investigate the effect of eHealth intervention after hospital discharge on the self-efficacy of self-care. Eligible patients with HF or CRC will be recruited before discharge from two Norwegian university hospitals. The intervention group will use a nurse-assisted intervention—eHealth@Hospital-2-Home—for six weeks. The intervention includes remote monitoring of vital signs; patients’ self-reports of symptoms, health and well-being; secure messaging between patients and hospital-based nurse navigators; and access to specific HF and CRC health-related information. The control group will receive routine care. Data collection will take place before the intervention (baseline), at the end of the intervention (Post-1), and at six months (Post-2). The primary outcome will be self-efficacy in self-care. The secondary outcomes will include measures of burden of treatment, health-related quality of life and 30- and 90-day readmissions. Sub-study analyses are planned in the HF patient population with primary outcomes of self-care behaviour and secondary outcomes of medication adherence, and readmission at 30 days, 90 days and 6 months. Patients’ and nurse navigators’ engagement and experiences with the eHealth intervention and cost-effectiveness will be investigated. Data will be analysed according to intention-to-treat principles. Qualitative data will be analysed using thematic analysis.DiscussionThis protocol will examine the effects of the eHealth@ Hospital-2-Home intervention on self-care in two prevalent patient groups, HF and CRC. It will allow the exploration of a generic framework for an eHealth intervention after hospital discharge, which could be adapted to other patient groups, upscaled, and implemented into clinical practice.Trial registrationClinical trials.gov (ID 301472).