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.

A Novel Protocol for the Early Detection of COVID-19 at a Skilled Nursing Facility.

Accurate measurement of vital signs are important at skilled nursing facilities (SNF). Recent technological advancements now enable automated vital sign measurements. This overcomes the limitations of traditional manual vital sign measurement, which is time-consuming and error-prone. We present a novel case where continuous vital sign measurement was used to detect meaningful vital sign changes that led to early detection of a COVID-19 outbreak at a SNF. Residents were continuously monitored for changes to baseline respiratory rate and heart rate and with a Probability of Change (POC). Variations in baseline respiratory rate and heart rate occurred in 66% and 42%, respectively, of COVID-19 positive individuals; 83% of participants had statistically significant variations in either vital sign. Clinical investigations are typically triggered by vital signs outside normal ranges. We present a novel methodology to detect subtle vital sign changes that can lead to earlier diagnosis, treatment, and recovery from infections, like COVID-19.

Influence of exercise using the Valsalva maneuver on vital signs in young adults.

[Purpose] To examine the influence of exercise using the Valsalva maneuver on vital signs. [Participants and Methods] Twenty-five healthy university students participated in the study. All participants were instructed to perform the squat under two loading intensities, that is, with barbell weights of 40% and 80% of body weight, under two conditions: no breath-holding (Control group) and breath-holding (Valsalva group). Blood pressure, pulse pressure, lactic acid level, and Borg scale scores were measured before and after each exercise session. [Results] Systolic blood pressure, mean blood pressure, and pulse pressure increased in the 80% Control, 40% Valsalva, and 80% Valsalva groups. [Conclusion] The use of the Valsalva maneuver could influence the vital signs of young, healthy participants.

Can I Discharge This Adult Patient with Abnormal Vital Signs From the Emergency Department?

BACKGROUND: Vital signs are an essential component of the emergency department (ED) assessment. Vital sign abnormalities are associated with adverse events in the ED setting and may indicate a risk of poor outcomes after ED discharge. CLINICAL QUESTION: What is the risk of adverse events among adult patients with abnormal vital signs at the time of ED discharge? EVIDENCE REVIEW: Studies retrieved included 6 retrospective studies with adult patients discharged from the ED. These studies evaluated adverse outcomes in adult patients discharged from the ED with abnormal vital signs. Hypotension at discharge was associated with the highest odds of adverse events after discharge. Tachycardia was also a key predictor of adverse events after discharge and may be easily missed by ED clinicians. CONCLUSION: Based on the available evidence, the specific vital sign abnormality and the number of total abnormalities influence the risk of adverse outcomes after discharge. Vital sign abnormalities at the time of discharge also increase the risk of ED revisit. The most common abnormal vital sign at the time of discharge is tachycardia.

The non-haemorrhagic vagal response to trauma: a review of hypotensive and bradycardic responses to injury in the absence of bleeding.

PURPOSE: Trauma has the potential to cause haemorrhage, tissue damage, pain, visceral manipulation and psychological distress. Each of these consequences of trauma can cause changes in autonomic outflow, which dictates a patient's vital signs. Patients who are hypotensive and bradycardic due to a vagally mediated parasympathetic response to pain, psychological distress and visceral manipulation may be confused with those who exhibit bradycardia and hypotension following significant blood volume loss. METHODS: This review summarises literature that describes specific stimuli, patterns of injury and patient characteristics that are associated with a non-haemorrhagic vagal response to trauma. RESULTS: Twenty-six records described predominantly parasympathetic responses to trauma (both blunt and penetrating) and surgery ("iatrogenic trauma"). Such a non-haemorrhagic vagal response occurs following a wide variety of injury patterns. Patient age and sex are poor predictors of the likelihood of a non-haemorrhagic vagal response. The development and resolution of a non-haemorrhagic vagal response occurs over a heterogenous time period. It is unclear whether speed of onset and resolution is linked to the pattern of injury or other factors causing a predominantly parasympathetic response following non-haemorrhagic trauma. CONCLUSION: The pattern of injury, patient demographic and speed of onset / resolution associated with the non-haemorrhagic vagal response to trauma may is heterogenous. It is therefore challenging to clinically distinguish between the hypotensive bradycardia due to hypovolaemia secondary to haemorrhage, or a parasympathetic response to trauma in the absence of bleeding.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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%.

Safety and efficacy of motor imagery-based physical activity in high-risk pregnancy: A randomized controlled study.

OBJECTIVE: This study aimed to investigate the acute effects of motor imagery-based physical activity on maternal well-being, maternal blood pressure, heart rate, oxygen saturation, fetal heart rate, and uterine contractions in women with high-risk pregnancies. METHODS: This randomized controlled trial was conducted in Izmir Tepecik Education and Research Hospital from August 2023 to January 2024. Seventy-six women with high-risk pregnancies were randomized into two groups: a motor imagery group (n = 38, diaphragmatic-breathing exercise and motor imagery-based physical activity) and a control group (n = 38, diaphragmatic-breathing exercise). Maternal well-being was determined using the Numerical Rating Scale-11. Digital sphygmomanometry was used to measure maternal heart rate and blood pressure, pulse oximetry for oxygen saturation, and cardiotocography for fetal heart rate and uterine contractions. Assessments were performed pre-intervention, mid-intervention, and post-intervention. RESULTS: There were no significant differences in baseline characteristics between groups (P > 0.05). There was a significant main effect of time in terms of maternal well-being and maternal heart rate (P = 0.001 and P = 0.015). In addition, there was a significant main effect of the group on oxygen saturation (P = 0.025). The overall group-by-time interaction was significant for maternal well-beingm with an effect size of 0.05 (P = 0.041). CONCLUSION: The combination of diaphragmatic-breathing exercises and a motor imagery-based physical activity program in women with high-risk pregnancies was determined to have no adverse effects on the fetus, did not induce uterine contractions, and resulted in a significant improvement in maternal well-being and oxygen saturation. Thus, imagery-based physical activity can be used in high-risk pregnancies where physical activity and exercise are not recommended.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Clinical Factors Associated with Outcomes in People with Moderate-Severe Traumatic Brain Injury.

The aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) is to design a data dictionary to inform data collection and facilitate prediction of outcomes for moderate-severe traumatic brain injury (TBI) across Australia. The process has engaged diverse stakeholders across six areas: social, health, clinical, biological, acute interventions, and long-term outcomes. Here, we report the results of the clinical review. Standardized searches were implemented across databases to April 2022. English-language reports of studies evaluating an association between a clinical factor and any clinical outcome in at least 100 patients with moderate-severe TBI were included. Abstracts, and full-text records, were independently screened by at least two reviewers in Covidence. The findings were assessed through a consensus process to determine inclusion in the AUS-TBI data resource. The searches retrieved 22,441 records, of which 1137 were screened at full text and 313 papers were included. The clinical outcomes identified were predominantly measures of survival and disability. The clinical predictors most frequently associated with these outcomes were the Glasgow Coma Scale, pupil reactivity, and blood pressure measures. Following discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous studies evaluating associations between clinical factors and outcomes in patients with moderate-severe TBI. A small number of factors were reported consistently, however, how and when these factors were assessed varied. The findings of this review and the subsequent consensus process have informed the development of an evidence-informed data dictionary for moderate-severe TBI in Australia.

Injury severity bias in missing prehospital vital signs: Prevalence and implications for trauma registries.

BACKGROUND: Vital signs are important factors in assessing injury severity and guiding trauma resuscitation, especially among severely injured patients. Despite this, physiological data are frequently missing from trauma registries. This study aimed to evaluate the extent of missing prehospital data in a hospital-based trauma registry and to assess the associations between prehospital physiological data completeness and indicators of injury severity. METHODS: A retrospective review was conducted on all adult trauma patients brought directly to a level 1 trauma center in Toronto, Ontario by paramedics from January 1, 2015, to December 31, 2019. The proportion of missing data was evaluated for each variable and patterns of missingness were assessed. To investigate the associations between prehospital data completeness and injury severity factors, descriptive and unadjusted logistic regression analyses were performed. RESULTS: A total of 3,528 patients were included. We considered prehospital data missing if any of heart rate, systolic blood pressure, respiratory rate or oxygen saturation were incomplete. Each individual variable was missing from the registry in approximately 20 % of patients, with oxygen saturation missing most frequently (n = 831; 23.6 %). Over 25 % (n = 909) of patients were missing at least one prehospital vital sign, of which 69.1 % (n = 628) were missing all four of these variables. Patients with incomplete data were more severely injured, had higher mortality, and more frequently received lifesaving interventions such as blood transfusion and intubation. Patients were most likely to have missing prehospital physiological data if they died in the trauma bay (unadjusted OR: 9.79; 95 % CI: 6.35-15.10), did not survive to discharge (unadjusted OR: 3.55; 95 % CI: 2.76-4.55), or had a prehospital GCS less than 9 (OR: 3.24; 95 % CI: 2.59-4.06). CONCLUSION: In this single center trauma registry, key prehospital variables were frequently missing, particularly among more severely injured patients. Patients with missing data had higher mortality, more severe injury characteristics and received more life-saving interventions in the trauma bay, suggesting an injury severity bias in prehospital vital sign missingness. To ensure the validity of research based on trauma registry data, patterns of missingness must be carefully considered to ensure missing data is appropriately addressed.