Escala de alerta precoce na identificação de pacientes com risco de deterioração clínica / Early warning scale for identifying patients at risk of clinical deterioration / Escala de alerta temprana en la identificación de pacientes con riesgo de deterioro clínico

Objetivo: avaliar pontuação da National Early Warning Score (NEWS) em relação ao tipo de desfecho e perfil dos pacientes da enfermaria clínica médica de um hospital em Teresina, Piauí, Brasil. Método: estudo quantitativo realizado num hospital público, em Teresina, com 150 prontuários de pacientes internados no setor clínica médica de fevereiro de 2022 a dezembro de 2022, a partir de registros demográficos, clínicos e valores da escala na admissão e desfecho. Resultados: houve associação dos valores da escala com a faixa etária (p=0,029), tempo de internação (p=0,023) e tipo de desfecho (p < 0,001). Alto risco clínico prevaleceu entre pacientes do sexo masculino (13%), na faixa etária de 60 a 94 anos (13%), com permanência de 21 a 57 dias (19,2%) e óbito como desfecho (100%). Conclusão: implementação da referida escala evidenciou ser fundamental para prever agravos clínicos e melhorar qualidade da assistência.

Objective: to evaluate the National Early Warning Score (NEWS) in relation to the type of outcome and profile of patients in the medical clinical ward of a hospital in Teresina, Piauí, Brazil. Method: a quantitative study conducted in a public hospital in Teresina, with 150 medical records of patients admitted to the medical clinic sector from February 2022 to December 2022, based on demographic and clinical records and scale values at admission and outcome. Results: there was an association between the scale values and the age group (p=0.029), length of stay (p=0.023) and type of outcome (p < 0.001). High clinical risk prevailed among male patients (13%), aged between 60 and 94 years (13%), with a stay of 21 to 57 days (19.2%), and death as an outcome (100%). Conclusion: implementation of the aforementioned scale proved to be fundamental for predicting clinical problems and improving care quality.

Objetivo: evaluar el puntaje de la National Early Warning Score (NEWS) con respecto al tipo de desenlace y el perfil de los pacientes de la enfermería clínica médica de un hospital en Teresina, Piauí, Brasil. Método: estudio cuantitativo realizado en un hospital público en Teresina, con 150 historiales médicos de pacientes internados en el sector de clínica médica desde febrero de 2022 hasta diciembre de 2022, a partir de registros demográficos, clínicos y valores de la escala en la admisión y desenlace. Resultados: hubo asociación de los valores de la escala con la edad (p=0,029), tiempo de internación (p=0,023) y tipo de desenlace (p < 0,001). El alto riesgo clínico prevaleció entre los pacientes del sexo masculino (13%), en la franja de edad entre 60 y 94 años (13%), con una estancia de 21 a 57 días (19,2%) y fallecimiento como desenlace (100%). Conclusión: la implementación de dicha escala demostró ser fundamental para prever agravios clínicos y mejorar la calidad de la asistencia.

Effect of music-based interventions on anxiety and stress-related vital signs in patients undergoing cardiac catheterization: A systematic review and meta-analysis.

OBJECTIVES: This work aimed to evaluate the effect of music-based intervention (MBI) on anxiety and stress-related vital signs (heart rate, respiratory rate and blood pressure) in patients undergoing cardiac catheterization. DESIGN: A systematic review and meta-analysis. METHODS: This systematic review and meta-analysis was conducted according to PRISMA guidelines. PubMed, Cochrane Library, Embase and CINAHL were systematically searched from inception to October 31, 2023. Two authors independently searched electronic databases, selected literature, extracted data and assessed the risk of bias according to the eligibility criteria. The Review Manager software (RevMan version 5.4.1) was used to perform meta-analysis. RESULTS: Eleven randomized controlled trials (RCTs) with adult patients (n = 1204) (passive music therapy, 8 studies; passive music listening, 3 studies) were enrolled and brought into qualitative assessment. Nine of these RCTs (n = 868) were taken into quantitative analysis. Meta-analysis using the random-effects model revealed that the difference in the pre-post anxiety level in the music group was significantly greater than that in the control group. However, meta-analysis results for heart rate, respiratory rate, systolic blood pressure and diastolic blood pressure did not show significant differences. CONCLUSION: The findings suggested that MBI had a significant effect on reducing anxiety in patients undergoing cardiac catheterization. However, the limited quantity and quality of included studies highlight the need for additional research to comprehensively analyze the influence of MBI on anxiety reduction in this patient population.

Feasibility study of the use of a wearable vital sign patch in an intensive care unit setting.

Multiple studies and review papers have concluded that early warning systems have a positive effect on clinical outcomes, patient safety and clinical performances. Despite the substantial evidence affirming the efficacy of EWS applications, persistent barriers hinder their seamless integration into clinical practice. Notably, EWS, such as the National Early Warning Score, simplify multifaceted clinical conditions into singular numerical indices, thereby risking the oversight of critical clinical indicators and nuanced fluctuations in patients' health status. Furthermore, the optimal deployment of EWS within clinical contexts remains elusive. Manual assessment of EWS parameters exacts a significant temporal toll on healthcare personnel. Addressing these impediments necessitates innovative approaches. In this regard, wearable medical technologies emerge as promising solutions capable of continual monitoring of hospitalized patients' vital signs. To overcome the barriers of the use of early warning scores, wearable medical technology has the potential to continuously monitor vital signs of hospitalised patients. However, a fundamental inquiry arises regarding the comparability of their reliability to the current used golden standards. This inquiry underscores the imperative for rigorous evaluation and validation of wearable medical technologies to ascertain their efficacy in augmenting extant clinical practices. This prospective, single-center study aimed to evaluate the accuracy of heart rate and respiratory rate measurements obtained from the Vivalink Cardiac patch in comparison to the ECG-based monitoring system utilized at AZ Maria Middelares Hospital in Ghent. Specifically, the study focused on assessing the concordance between the data obtained from the Vivalink Cardiac patch and the established ECG-based monitoring system among a cohort of ten post-surgical intensive care unit (ICU) patients. Of these patients, five were undergoing mechanical ventilation post-surgery, while the remaining five were not. The study proceeded by initially comparing the data recorded by the Vivalink Cardiac patch with that of the ECG-based monitoring system. Subsequently, the data obtained from both the Vivalink Cardiac patch and the ECG-based monitoring system were juxtaposed with the information derived from the ventilation machine, thereby providing a comprehensive analysis of the patch's performance in monitoring vital signs within the ICU setting. For heart rate, the Vivalink Cardiac patch was on average within a 5% error range of the ECG-based monitoring system during 85.11±10.81% of the measured time. For respiratory rate this was during 40.55±17.28% of the measured time. Spearman's correlation coefficient showed a very high correlation of ρ = 0.9 8 for heart rate and a moderate correlation of ρ = 0.66 for respiratory rate. In comparison with the ventilated respiratory rate (ventilation machine) the Vivalink and ECG-based monitoring system both had a moderate correlation of ρ = 0.68 . A very high correlation was found between the heart rate measured by the Vivalink Cardiac patch and that of the ECG-based monitoring system of the hospital. Concerning respiratory rate the correlation between the data from the Vivalink Cardiac patch, the ECG-based monitoring system and the ventilation machine was found to be moderate.

Accuracy of Patient-Collected Vital Signs.

Introduction: Telehealth has emerged as an important clinical setting for managing acute respiratory tract infections (ARIs), potentially reducing emergency department and urgent care overcrowding, and reducing nosocomial transmission. Many current algorithms for ARI management incorporate information on patient vital signs. However, the accuracy of vital signs collected by patients using readily available home devices and techniques has not been studied. Methods: A cross-sectional sample of patients seen for urgent conditions at a hospital emergency and urgent care center were given instructions and low-cost, readily available devices to collect their vital signs. A trained research coordinator collected a parallel set of vital signs using standard hospital equipment, serving as the gold standard. We analyzed the performance of patient-collected vital signs compared with vital signs collected by a trained research coordinator. Results: A total of 300 patients completed the study. Patient-collected vital signs were highly specific for traditional levels of abnormalities (HR >100 beats per min, RR >24 breaths per min, temperature >100.4 degrees Fahrenheit, oxygen saturation <94 percent); however, sensitivity was poor for elevated heart rate by pulse estimation (25%) and elevated respiratory rate (60%). Heart rate and oxygen saturation by pulse oximeter and oral temperature had higher sensitivity. Conclusions: Vital signs measured and provided by patients are not uniformly accurate, particularly when using manual techniques rather than automated devices. Telehealth algorithms that rely on these values could provide incorrect triage and management advice.

DiffPhys: Enhancing Signal-to-Noise Ratio in Remote Photoplethysmography Signal Using a Diffusion Model Approach.

Remote photoplethysmography (rPPG) is an emerging non-contact method for monitoring cardiovascular health based on facial videos. The quality of the captured videos largely determines the efficacy of rPPG in this application. Traditional rPPG techniques, while effective for heart rate (HR) estimation, often produce signals with an inadequate signal-to-noise ratio (SNR) for reliable vital sign measurement due to artifacts like head motion and measurement noise. Another pivotal factor is the overlooking of the inherent properties of signals generated by rPPG (rPPG-signals). To address these limitations, we introduce DiffPhys, a novel deep generative model particularly designed to enhance the SNR of rPPG-signals. DiffPhys leverages the conditional diffusion model to learn the distribution of rPPG-signals and uses a refined reverse process to generate rPPG-signals with a higher SNR. Experimental results demonstrate that DiffPhys elevates the SNR of rPPG-signals across within-database and cross-database scenarios, facilitating the extraction of cardiovascular metrics such as HR and HRV with greater precision. This enhancement allows for more accurate monitoring of health conditions in non-clinical settings.

Postoperative Recovery in the Youngest: Beyond Technology.

BACKGROUND: Measuring and interpreting vital signs in pediatric patients recovering from anaesthesia, particularly those up to 36 months old, is challenging. Nurses' decision-making regarding the level of monitoring must balance patient safety with individualized care. This study aimed to explore the perceptions of critical care nurses and registered nurse anesthetists regarding their experiences and actions when making decisions about vital sign monitoring for children in post-anesthesia care units (PACUs). METHODS: A qualitative study utilizing the critical incident technique was conducted. Interviews were performed with a purposeful sample of 17 critical care nurses and registered nurse anaesthetists from two hospitals. RESULTS: Nurses reported that the rationale for decisions concerning the need for vital sign monitoring in children was both adequate and inadequate. Actions were taken to adjust the monitoring of vital signs, optimizing conditions for assessment and ensuring the child's safe recovery. CONCLUSIONS: The complexity of accurately monitoring children makes it challenging for nurses in the PACU to adhere to guidelines. Evidence-based care and safety are compromised when technology has limitations and is not adapted for paediatric use, leading to a greater reliance on experience and clinical assessment. This reliance on experience is crucial for reliable assessment but also entails accepting greater risks.

Contactless and Calibration-Free Blood Pressure and Pulse Rate Monitor for Screening and Monitoring of Hypertension: Cross-Sectional Validation Study.

BACKGROUND: The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors. OBJECTIVE: This study aims to investigate the accuracy of a contactless BP monitor software app for classifying the full range of clinically relevant BPs as hypertensive or nonhypertensive and to evaluate its accuracy for measuring the pulse rate (PR) and BP of people with BPs relevant to stage-1 hypertension. METHODS: The software app, known commercially as Lifelight, was investigated following the data collection and data analysis methodology outlined in International Organization for Standardization (ISO) 81060-2:2018/AMD 1:2020 "Non-invasive Sphygmomanometers-Part 2: Clinical investigation of automated measurement type." This validation study was conducted by the independent laboratory Element Materials Technology Boulder (formerly Clinimark). The study generated data from 85 people aged 18-85 years with a wide-ranging distribution of BPs specified in ISO 81060-2:2018/AMD 1:2020. At least 20% were required to have Fitzpatrick scale skin tones of 5 or 6 (ie, dark skin tones). The accuracy of the app's BP measurements was assessed by comparing its BP measurements with measurements made by dual-observer manual auscultation using the same-arm sequential method specified in ISO 81060-2:2018/AMD 1:2020. The accuracy of the app's PR measurements was assessed by comparing its measurements with concurrent electroencephalography-derived heart rate values. RESULTS: The app measured PR with an accuracy root-mean-square of 1.3 beats per minute and mean absolute error of 1.1 (SD 0.8) beats per minute. The sensitivity and specificity with which it determined that BPs exceeded the in-clinic systolic threshold for hypertension diagnosis were 70.1% and 71.7%, respectively. These rates are consistent with those reported for conventional BP monitors in a literature review by The National Institute for Health and Care Excellence. The app's mean error for measuring BP in the range of normotension and stage-1 hypertension (ie, 65/85, 76% of participants) was 6.5 (SD 12.9) mm Hg for systolic BP and 0.4 (SD 10.6) mm Hg for diastolic BP. Mean absolute error was 11.3 (SD 10.0) mm Hg and 8.6 (SD 6.8) mm Hg, respectively. CONCLUSIONS: A calibration-free, software-only medical device was independently tested against ISO 81060-2:2018/AMD 1:2020. The safety and performance demonstrated in this study suggest that this technique could be a potential solution for rapid and scalable screening and management of hypertension.

A novel health monitoring system for vital signs using IoT.

The current research looked at how to use the Internet of Things (IoT) to create a vital sign health monitoring system. Eight indications are employed to get critical patient information. Therefore, the number of nodes of the IoT embedded in the human body is 8, which have been worked on in different places of the body. Among the 8 nodes, node number 1 is located in the center of the grid (the center of the human body). The number of rounds is 9000 and the nodes are adopted with the initial energy of the nodes of 0.5 J and the radio range of 10 m. MATLAB software was used to simulate the WBAN network, which consists of IoT sensors embedded in the human body. The eight-item health assessment tool takes the following into account: pulse rate, blood pressure (mm Hg), serum cholesterol (mg/dl), temperature (°C), exercise-induced angina, and exercise-induced ST-wave depression, major blood vessels are counted using a medical procedure called endoscopy that involves examining the alveoli, which are small air sacs in the lungs where gas exchange occurs. We compared the number of major vessels at rest with the maximal heart rate during activity. The sensors were responsible for sending this data to the health center (base station). The data collected from the installation of these 8 sensors on 303 patients were collected and evaluated by machine learning method using MLP neural network method. Finally, it can be claimed that the present study has provided an automated method of determining the health of people using the IoT in a way that provides a state of health with an accuracy of over 99% and can be used in medical centers.

Reliable Contactless Monitoring of Heart Rate, Breathing Rate, and Breathing Disturbance During Sleep in Aging: Digital Health Technology Evaluation Study.

BACKGROUND: Longitudinal monitoring of vital signs provides a method for identifying changes to general health in an individual, particularly in older adults. The nocturnal sleep period provides a convenient opportunity to assess vital signs. Contactless technologies that can be embedded into the bedroom environment are unintrusive and burdenless and have the potential to enable seamless monitoring of vital signs. To realize this potential, these technologies need to be evaluated against gold standard measures and in relevant populations. OBJECTIVE: We aimed to evaluate the accuracy of heart rate and breathing rate measurements of 3 contactless technologies (2 undermattress trackers, Withings Sleep Analyzer [WSA] and Emfit QS [Emfit]; and a bedside radar, Somnofy) in a sleep laboratory environment and assess their potential to capture vital signs in a real-world setting. METHODS: Data were collected from 35 community-dwelling older adults aged between 65 and 83 (mean 70.8, SD 4.9) years (men: n=21, 60%) during a 1-night clinical polysomnography (PSG) test in a sleep laboratory, preceded by 7 to 14 days of data collection at home. Several of the participants (20/35, 57%) had health conditions, including type 2 diabetes, hypertension, obesity, and arthritis, and 49% (17) had moderate to severe sleep apnea, while 29% (n=10) had periodic leg movement disorder. The undermattress trackers provided estimates of both heart rate and breathing rate, while the bedside radar provided only the breathing rate. The accuracy of the heart rate and breathing rate estimated by the devices was compared with PSG electrocardiogram-derived heart rate (beats per minute) and respiratory inductance plethysmography thorax-derived breathing rate (cycles per minute), respectively. We also evaluated breathing disturbance indexes of snoring and the apnea-hypopnea index, available from the WSA. RESULTS: All 3 contactless technologies provided acceptable accuracy in estimating heart rate (mean absolute error <2.12 beats per minute and mean absolute percentage error <5%) and breathing rate (mean absolute error ≤1.6 cycles per minute and mean absolute percentage error <12%) at 1-minute resolution. All 3 contactless technologies were able to capture changes in heart rate and breathing rate across the sleep period. The WSA snoring and breathing disturbance estimates were also accurate compared with PSG estimates (WSA snore: r2=0.76; P<.001; WSA apnea-hypopnea index: r2=0.59; P<.001). CONCLUSIONS: Contactless technologies offer an unintrusive alternative to conventional wearable technologies for reliable monitoring of heart rate, breathing rate, and sleep apnea in community-dwelling older adults at scale. They enable the assessment of night-to-night variation in these vital signs, which may allow the identification of acute changes in health, and longitudinal monitoring, which may provide insight into health trajectories. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3390/clockssleep6010010.

A Retrospective Observational Study of Continuous Wireless Vital Sign Monitoring via a Medical Grade Wearable Device on Hospitalized Floor Patients.

Background: Continuous vital sign monitoring via wearable technology, combined with algorithm-based notifications, has been utilized for early detection of patient deterioration. In this retrospective observational study, we summarize a large-scale implementation of a continuous monitoring system in medical-surgical units of two hospitals over the course of fifteen (15) months. Methods: An FDA-cleared wireless monitoring device (BioButton®, BioIntelliSense Inc., Golden, CO, USA), was placed on each patient upon admission. The wearable device measures heart rate and respiratory rate at rest, skin temperature, and patient activity levels. High-frequency data (up to 1440 measurements per day) are transmitted to display in exception management software (BioDashboard™, version 2.9, BioIntelliSense Inc.). Algorithmic and rules-based notifications are triggered based on clinical and statistical trending criteria. We present (i) agreement of device readings with bedside charted measurements, (ii) the frequency of notifications, (iii) the occurrence of notifications prior to clinical deterioration events, and (iv) impact on clinical management, including early data on length of stay (LOS). Results: In total, 11,977 patient encounters were monitored at two sites. Bias ±95% limits of agreement were 1.8 ± 12.5 for HR and 0.4 ± 8.0 for RR. The rates of notifications were 0.97 and 0.65 per patient-day at Sites 1 and 2, respectively. Among clinical deteriorations, 73% (66%) had at least one notification within 24 h prior at Site 1 (Site 2). At Site 1, there were 114 cases for which a notification led to a new or changed physician's order. LOS in the first unit monitored by the system exhibited a decreasing trend from 3.07 days to 2.75 days over 12 months. Conclusions: Wearable continuous vital sign monitoring with the BioIntelliSense BioButton® system enables early detection of clinical deterioration.

Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor.

BACKGROUND AND OBJECTIVE: Continuous prediction of late-onset sepsis (LOS) could be helpful for improving clinical outcomes in neonatal intensive care units (NICU). This study aimed to develop an artificial intelligence (AI) model for assisting the bedside clinicians in successfully identifying infants at risk for LOS using non-invasive vital signs monitoring. METHODS: In a retrospective study from the NICU of the Máxima Medical Center in Veldhoven, the Netherlands, a total of 492 preterm infants less than 32 weeks gestation were included between July 2016 and December 2018. Data on heart rate (HR), respiratory rate (RR), and oxygen saturation (SpO2) at 1 Hz were extracted from the patient monitor. We developed multiple AI models using 102 extracted features or raw time series to provide hourly LOS risk prediction. Shapley values were used to explain the model. For the best performing model, the effect of different vital signs and also the input type of signals on model performance was tested. To further assess the performance of applying the best performing model in a real-world clinical setting, we performed a simulation using four different alarm policies on continuous real-time predictions starting from three days after birth. RESULTS: A total of 51 LOS patients and 68 controls were finally included according to the patient inclusion and exclusion criteria. When tested by seven-fold cross-validations, the mean (standard deviation) area under the receiver operating characteristic curve (AUC) six hours before CRASH was 0.875 (0.072) for the best performing model, compared to the other six models with AUC ranging from 0.782 (0.089) to 0.846 (0.083). The best performing model performed only slightly worse than the model learning from raw physiological waveforms (0.886 [0.068]), successfully detecting 96.1 % of LOS patients before CRASH. When setting the expected alarm window to 24 h and using a multi-threshold alarm policy, the sensitivity metric was 71.6 %, while the positive predictive value was 9.9 %, resulting in an average of 1.15 alarms per day per patient. CONCLUSIONS: The proposed AI model, which learns from routinely collected vital signs, has the potential to assist clinicians in the early detection of LOS. Combined with interpretability and clinical alarm management, this model could be better translated into medical practice for future clinical implementation.

Smart Medical Evacuation Support System for the Military.

Medical support in crisis situations is a major challenge. Efficient implementation of the medical evacuation process especially in operations with limited human resources that may occur during armed conflicts can limit the loss of these resources. Proper evacuation of wounded soldiers from the battlefield can increase the chances of their survival and rapid return to further military operations. This paper presents the technical details of the decision support system for medical evacuation to support this process. The basis for the functioning of this system is the continuous measurement of vital signs of soldiers via a specialized measurement module with a set of medical sensors. Vital signs values are then transmitted via the communication module to the analysis and inference module, which automatically determines the color of medical triage and the soldier's chance of survival. This paper presents the results of tests of our system to validate it, which were carried out using test vectors of soldiers' vital signs, as well as the results of the system's performance on a group of volunteers who performed typical activities of tactical operations. The results of this study showed the usefulness of the developed system for supporting military medical services in military operations.

Exercise Is a Vital Sign.

Description In this review, we argue that exercise (physical activity) be monitored as a vital sign since no other basic sign or symptom provides as much information about a patient's health status. The influence of regular exercise on patient health is indisputable, with strong evidence to show the power of exercise to mitigate chronic disease and improve overall health. Several simple tools, such as Physical Activity as a Vital Sign and Exercise as a Vital Sign are available to assess patient physical activity. When properly applied, there is evidence to support the efficacy of these tools, but there are barriers that prevent broad inclusion in primary care, among which are time and provider knowledge. In our review, we also discussed the value of physician-led lifestyle discussions with patients and found they view these discussions favorably. There is also evidence that physicians who exercise are more likely to have these lifestyle discussions with their patients, but the proportion of physicians who exercise regularly is fairly low. We believe physicians' awareness of their patients' sedentary lifestyles should prompt a prescription to increase physical activity, but additional in-clinic support and community resources need to be in place for patients to get a regular dose.

Atrial Septal Defect secundum with inferior floppy rim in the elderly: surgical closure or transcatheter closure? A case report.

Atrial Septal Defect closure in childhood and early adulthood has a good prognosis, but in older individuals the risk-benefit ratio is not as straightforward. We report a 57-year-old man who was easily fatigued when exercising. The cardiac examination revealed a wide and fixed splitting of S2, a pulmonary ejection systolic murmur grade III/VI, and increased jugular venous pressure. The transesophageal echocardiography showed Atrial Septal Defect secundum with a diameter of 20 mm, L-to-R shunt, and 5 mm, a thin and floppy inferior rim. The patient underwent surgical Atrial Septal Defect closure. The deficient posteroinferior rim occurs only in 3.3% of patients with secundum Atrial Septal Defect. This condition will enhance the likelihood of occluder dislodgement in the transcatheter closure approach. We learn from this case that surgical Atrial Septal Defect closure may be an option for elderly patients if there is an inadequate, thin, and floppy inferior rim or no comorbidities.

Health in a Virtual Environment (HIVE): A Novel Continuous Remote Monitoring Service for Inpatient Management.

The aim of this study was to describe the implementation of a novel 50-bed continuous remote monitoring service for high-risk acute inpatients treated in non-critical wards, known as Health in a Virtual Environment (HIVE). We report the initial results, presenting the number and type of patients connected to the service, and assess key outcomes from this cohort. This was a prospective, observational study of characteristics and outcomes of patients connected to the HIVE continuous monitoring service at a major tertiary hospital and a smaller public hospital in Western Australia between January 2021 and June 2023. In the first two and a half years following implementation, 7541 patients were connected to HIVE for a total of 331,118 h. Overall, these patients had a median length of stay of 5 days (IQR 2, 10), 11.0% (n = 833) had an intensive care unit admission, 22.4% (n = 1691) had an all-cause emergency readmission within 28 days from hospital discharge, and 2.2% (n = 167) died in hospital. Conclusions: Our initial results show promise, demonstrating that this innovative approach to inpatient care can be successfully implemented to monitor high-risk patients in medical and surgical wards. Future studies will investigate the effectiveness of the program by comparing patients receiving HIVE supported care to comparable patients receiving routine care.

Millimeter-Wave Radar-Based Identity Recognition Algorithm Built on Multimodal Fusion.

Millimeter-wave radar-based identification technology has a wide range of applications in persistent identity verification, covering areas such as security production, healthcare, and personalized smart consumption systems. It has received extensive attention from the academic community due to its advantages of being non-invasive, environmentally insensitive and privacy-preserving. Existing identification algorithms mainly rely on a single signal, such as breathing or heartbeat. The reliability and accuracy of these algorithms are limited due to the high similarity of breathing patterns and the low signal-to-noise ratio of heartbeat signals. To address the above issues, this paper proposes an algorithm for multimodal fusion for identity recognition. This algorithm extracts and fuses features derived from phase signals, respiratory signals, and heartbeat signals for identity recognition purposes. The spatial features of signals with different modes are first extracted by the residual network (ResNet), after which these features are fused with a spatial-channel attention fusion module. On this basis, the temporal features are further extracted with a time series-based self-attention mechanism. Finally, the feature vectors of the user's vital sign modality are obtained to perform identity recognition. This method makes full use of the correlation and complementarity between different modal signals to improve the accuracy and reliability of identification. Simulation experiments show that the algorithm identity recognition proposed in this paper achieves an accuracy of 94.26% on a 20-subject self-test dataset, which is much higher than that of the traditional algorithm, which is about 85%.

Vital Signs as Predictors of Oxygen Requirements in COVID-19 Outpatients: The Development of a Streamlined Risk Score.

BACKGROUND: With COVID-19 becoming a common disease, primary care facilities such as clinics are required to efficiently triage patients at high risk of severe illness within the constraints of limited medical resources. However, existing COVID-19 severity risk scores require detailed medical history assessments, such as evaluating the severity of pneumonia via chest CT and accounting for past and comorbid conditions. Therefore, they may not be suitable for practical use in clinical settings with limited medical resources, including personnel and equipment. PURPOSE:  The goal is to identify key variables that predict the need for oxygen therapy in COVID-19 patients and develop a simplified clinical risk score based solely on vital signs to predict oxygen requirements. PATIENTS AND METHODS: A retrospective observational study of 584 outpatients with COVID-19 confirmed by polymerase chain reaction test visited Sasebo Chuo Hospital between April 28, 2022, and August 18, 2022. Analyses were conducted after adjustment for background factors of age and sex with propensity score matching. We used the Fisher test for nominal variables and the Kruskal-Wallis test for continuous variables. RESULTS: After adjusting for age and sex, several factors significantly correlated with the need for oxygen within seven days including body temperature (p < 0.001), respiratory rate (p = 0.007), SpO2 (p < 0.001), and the detection of pneumonia on CT scans (p = 0.032). The area under the receiver-operating characteristic curve for the risk score based on these vital signs and CT was 0.947 (95% confidence interval: 0.911-0.982). The risk score based solely on vital signs was 0.937 (0.900-0.974), demonstrating the ability to predict oxygen administration with no significant differences. CONCLUSIONS: Body temperature, advanced age, increased respiratory rate, decreased SpO2, and the presence of pneumonia on CT scans were significant predictors of oxygen need within seven days among the study participants. The risk score, based solely on vital signs, effectively and simply assesses the likelihood of requiring oxygen therapy within seven days with high accuracy. The risk score, which utilizes only age and vital signs and does not require a detailed patient history or CT scans, could streamline hospital referral processes for admissions.

Evaluating Sleep Challenges in Hospitalized Youth.

OBJECTIVE: To characterize sleep quality and sleep disruptions among youth hospitalized outside of the intensive care unit (ICU). PATIENTS AND METHODS: Participants were eligible for the survey-based study if they were 8-17 years old, English-speaking, hospitalized for ≥3 days outside of the ICU, and developmentally able to understand surveys. Survey administration included a sleep diary, the Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD), and a study-specific Inpatient Sleep Disruptors Questionnaire. The chart review provided additional clinical information. Descriptive and comparative statistics were performed to assess the association between overnight clinical monitoring and daytime sleepiness. RESULTS: Forty-five participants (mean age 13.4 years, 60% female), recruited between May and December 2022, were included in the study. Mean total sleep time (8.2 ± 1.7 hours) and ESS-CHAD score (8.6 ± 4.3) were normal with 79% reporting fair to good sleep the previous night. Participants rated alarms on equipment, vital signs, and noise as most disruptive to sleep. Participants with vital signs every four hours showed higher levels of daytime sleepiness compared with participants with vitals measured every shift (9.3 vs. 6.3; p=0.04). CONCLUSIONS: Most participants reported normal sleep, although there was wide variability with a portion with impaired sleep quality and elevated daytime sleepiness. Alarms on equipment, vital signs, and noise were most disruptive, and increased vital sign frequency was also associated with increased daytime sleepiness. In clinically stable pediatric patients, a reduction in vital sign monitoring overnight may be an important change to improve patient sleep.

Effects of the thoracic block technique on vital signs, blood gases, and lung compliance in children with atelectasis.

Objectives: This study was aimed at examining the effects of the thoracic block technique on vital signs, arterial blood gases, and lung compliance in children with unilateral atelectasis receiving mechanical ventilation. Methods: Forty-four boys and girls with unilateral atelectasis and receiving mechanical ventilation, ranging in age from 4 months to 4 years, were recruited from the Abo El-Reesh Hospital intensive care unit at Cairo University. They were assigned to control and study groups: group A included 22 children receiving chest physical therapy, and group B included 22 children receiving the same chest physical therapy program as well as the thoracic block technique. Electrocardiography, mechanical ventilation, and blood gas analysis were conducted to assess the respiratory and heart rates, dynamic compliance, and arterial blood gases, respectively. Results: Respiratory rate and heart rate were significantly lower in the study group than the control group (p = 0.03). PaO2 and SaO2 increased in both groups, and the increase was more significant (p = 0.01 and 0.001, respectively) in group B than group A. A significant decrease in PaCO2 was observed in both groups, and the decrease was more significant in group B than group A (p = 0.02). A significant increase in dynamic lung compliance was observed in both groups, and the increase was more significant in group B than group A (p = 0.01). Conclusions: Applying the thoracic block technique rather than chest physical therapy techniques alone in children with atelectasis receiving mechanical ventilation may lead to improvements in arterial blood gases and dynamic lung compliance, and has no negative effects on heart rate and respiratory rate.