Interpretation of continuously measured vital signs data of COVID-19 patients by nurses and physicians at the general ward: A mixed methods study.

BACKGROUND: Continuous monitoring of vital signs is introduced at general hospital wards to detect patient deterioration. Interpretation and response currently rely on experience and expert opinion. This study aims to determine whether consensus exist among hospital professionals regarding the interpretation of vital signs of COVID-19 patients. In addition, we assessed the ability to recognise respiratory insufficiency and evaluated the interpretation process. METHODS: We performed a mixed methods study including 24 hospital professionals (6 nurses, 6 junior physicians, 6 internal medicine specialists, 6 ICU nurses). Each participant was presented with 20 cases of COVID-19 patients, including 4 or 8 hours of continuously measured vital signs data. Participants estimated the patient's situation ('improving', 'stable', or 'deteriorating') and the possibility of developing respiratory insufficiency. Subsequently, a semi-structured interview was held focussing on the interpretation process. Consensus was assessed using Krippendorff's alpha. For the estimation of respiratory insufficiency, we calculated the mean positive/negative predictive value. Interviews were analysed using inductive thematic analysis. RESULTS: We found no consensus regarding the patient's situation (α 0.41, 95%CI 0.29-0.52). The mean positive predictive value for respiratory insufficiency was high (0.91, 95%CI 0.86-0.97), but the negative predictive value was 0.66 (95%CI 0.44-0.88). In the interviews, two themes regarding the interpretation process emerged. "Interpretation of deviations" included the strategies participants use to determine stability, focused on finding deviations in data. "Inability to see the patient" entailed the need of hospital professionals to perform a patient evaluation when estimating a patient's situation. CONCLUSION: The interpretation of continuously measured vital signs by hospital professionals, and recognition of respiratory insufficiency using these data, is variable, which might be the result of different interpretation strategies, uncertainty regarding deviations, and not being able to see the patient. Protocols and training could help to uniform interpretation, but decision support systems might be necessary to find signs of deterioration that might otherwise go unnoticed.

VitalSeer: The development of a contactless sensing technology based on a user-centric data-driven clinical approach.

The COVID-19 pandemic presented challenges to the healthcare system while catalyzing the adoption of virtual care. The need for remote assessment and real-time monitoring of physiological vital signs has driven towards a need for virtual care solutions. This paper presents the outcome of a multidisciplinary collaboration to ensure clinical usability of a remote contactless sensing technology, VitalSeer, and to help close gaps between emerging technologies and clinical practice. The paper describes the user-centric data-driven clinical approach to address the needs as identified by clinical experts through the iterative and agile development cycle. It highlights findings from preliminary studies to validate proof-of-concept VitalSeer's adoptability, accessibility and usability. The studies on volunteers demonstrated the accuracy of VitalSeer's heart rate model at a low MAE of 0.74 (bpm) and a RMSE of 1.2 bpm, below the threshold of clinical grade contact-based sensors. The paper concludes with a discussion on the technology implications in emergency medicine and community care.

Accuracy of Self-Injection Locking Radar System for Vital Signs Detection During the COVID-19 Pandemic at a Hospital in Taiwan: Measuring Vital Signs Accurately with SIL Radar for Hospital Healthcare.

BACKGROUND Self-injection locking (SIL) radar uses continuous-wave radar and an injection-locked oscillator-based frequency discriminator that receives and demodulates radar signals remotely to monitor vital signs. This study aimed to compare SIL radar with traditional electrocardiogram (ECG) measurements to monitor respiratory rate (RR) and heartbeat rate (HR) during the COVID-19 pandemic at a single hospital in Taiwan. MATERIAL AND METHODS We recruited 31 hospital staff members (16 males and 15 females) for respiratory rates (RR) and heartbeat rates (HR) detection. Data acquisition with the SIL radar and traditional ECG was performed simultaneously, and the accuracy of the measurements was evaluated using Bland-Altman analysis. RESULTS To analyze the results, participates were divided into 2 groups (individual subject and multiple subjects) by gender (male and female), or 4 groups (underweight, normal weight, overweight, and obesity) by body mass index (BMI). The results were analyzed using mean bias errors (MBE) and limits of agreement (LOA) with a 95% confidence interval. Bland-Altman plots were utilized to illustrate the difference between the SIL radar and ECG monitor. In all BMI groups, results of RR were more accurate than HR, with a smaller MBE. Furthermore, RR and HR measurements of the male groups were more accurate than those of the female groups. CONCLUSIONS We demonstrated that non-contact SIL radar could be used to accurately measure HR and RR for hospital healthcare during the COVID-19 pandemic.

Continuous monitoring is superior to manual measurements in detecting vital sign deviations in patients with COVID-19.

BACKGROUND: Patients admitted to the emergency care setting with COVID-19-infection can suffer from sudden clinical deterioration, but the extent of deviating vital signs in this group is still unclear. Wireless technology monitors patient vital signs continuously and might detect deviations earlier than intermittent measurements. The aim of this study was to determine frequency and duration of vital sign deviations using continuous monitoring compared to manual measurements. A secondary analysis was to compare deviations in patients admitted to ICU or having fatal outcome vs. those that were not. METHODS: Two wireless sensors continuously monitored (CM) respiratory rate (RR), heart rate (HR), and peripheral arterial oxygen saturation (SpO2 ). Frequency and duration of vital sign deviations were compared with point measurements performed by clinical staff according to regional guidelines, the National Early Warning Score (NEWS). RESULTS: SpO2 < 92% for more than 60 min was detected in 92% of the patients with CM vs. 40% with NEWS (p < .00001). RR > 24 breaths per minute for more than 5 min were detected in 70% with CM vs. 33% using NEWS (p = .0001). HR ≥ 111 for more than 60 min was seen in 51% with CM and 22% with NEWS (p = .0002). Patients admitted to ICU or having fatal outcome had longer durations of RR > 24 brpm (p = .01), RR > 21 brpm (p = .01), SpO2 < 80% (p = .01), and SpO2 < 85% (p = .02) compared to patients that were not. CONCLUSION: Episodes of desaturation and tachypnea in hospitalized patients with COVID-19 infection are common and often not detected by routine measurements.

Association between a Frailty Index from Common Laboratory Values and Vital Signs (FI-LAB) and Hospital and Post-Hospital Outcomes in Veterans with COVID-19 Infection.

OBJECTIVES: Determine the association of higher FI-LAB scores, derived from common laboratory values and vital signs, with hospital and post-hospital outcomes in Veterans hospitalized with COVID-19 infection. DESIGN, SETTING, AND PARTICIPANTS: A retrospective, multicenter, cohort study of 7 Veterans Health Administration (VHA) medical centers in Florida and Puerto Rico. Patients aged 18 years and older hospitalized with COVID-19 and followed for up to 1 year post discharge or until death. Clinical Frailty Measure: FI-LAB. MAIN OUTCOMES AND MEASURES: Hospital and post-hospital outcomes. RESULTS: Of the 671 eligible patients, 615 (91.5%) patients were included (mean [SD] age, 66.1 [14.8] years; 577 men [93.8%]; median stay, 8 days [IQR:3-15]. There were sixty-one in-hospital deaths. Veterans in the moderate and high FI-LAB groups had a higher proportion of inpatient mortality (13.3% and 20.6%, respectively) than the low group (4.1%), p <0.001. Moderate and high FI-LAB scores were associated with greater inpatient mortality when compared to the low group, OR:3.22 (95%CI:1.59-6.54), p=.001 and 6.05 (95%CI:2.48-14.74), p<0.001, respectively. Compared with low FI-LAB scores, moderate and high scores were also associated with prolonged length of stay, intensive care unit (ICU) admission, and transfer. CONCLUSIONS AND RELEVANCE: In this study of patients admitted to 7 VHA Hospitals during the first surge of the pandemic, higher FI-LAB scores were associated with higher in-hospital mortality and other in-hospital outcomes; FI-LAB can serve as a validated, rapid, feasible, and objective frailty tool in hospitalized adults with COVID-19 that can aid clinical care.

Cardiorespiratory fitness as a vital sign of CVD risk in the COVID-19 era.

The severe health consequences of the corona virus disease 2019 (COVID-19) pandemic have been exacerbated by the prevalence of cardiovascular disease (CVD) risk factors, such as physical inactivity, obesity, hypertension, and diabetes. Further, policy decisions during the pandemic augmented unhealthy lifestyle behaviors and health inequalities, likely increasing the global disease burden. Cardiorespiratory fitness (CRF) is a well-established biomarker associated with CVD risk. Emerging data demonstrate that high CRF offers some protection against severe outcomes from COVID-19 infection, highlighting the importance of CRF for population health and the potential for limiting the severity of future pandemics. CRF is best assessed by cardiopulmonary exercise testing (CPET), which will be an important tool for understanding the prolonged pathophysiology of COVID-19, the emergence of long-COVID, and the lasting effects of COVID-19 on CVD risk. Utilization of CRF and CPET within clinical settings should become commonplace because of lessons learned from the COVID-19 pandemic.

A Feasibility Study of Remote Non-Contact Vital Signs (NCVS) Monitoring in a Clinic Using a Novel Sensor Realized by Software-Defined Radio (SDR).

The COVID-19 outbreak has caused panic around the world as it is highly infectious and has caused about 5 million deaths globally. A robust wireless non-contact vital signs (NCVS) sensor system that can continuously monitor the respiration rate (RR) and heart rate (HR) of patients clinically and remotely with high accuracy can be very attractive to healthcare workers (HCWs), as such a system can not only avoid HCWs' close contact with people with COVID-19 to reduce the infection rate, but also be used on patients quarantined at home for telemedicine and wireless acute-care. Therefore, we developed a custom Doppler-based NCVS radar sensor system operating at 2.4 GHz using a software-defined radio (SDR) technology, and the novel biosensor system has achieved impressive real-time RR/HR monitoring accuracies within approximately 0.5/3 breath/beat per minute (BPM) on student volunteers tested in our engineering labs. To further test the sensor system's feasibility for clinical use, we applied and obtained an Internal Review Board (IRB) approval from Texas Tech University Health Sciences Center (TTUHSC) and have used this NCVS monitoring system in a doctor's clinic at TTUHSC; following testing on 20 actual patients for a small-scale clinical trial, we have found that the system was still able to achieve good NCVS monitoring accuracies within ~0.5/10 BPM across 20 patients of various weight, height and age. These results suggest our custom-designed NCVS monitoring system may be feasible for future clinical use to help combatting COVID-19 and other infectious diseases.

Detecting Patient Deterioration Early Using Continuous Heart rate and Respiratory rate Measurements in Hospitalized COVID-19 Patients.

BACKGROUND: Presenting symptoms of COVID-19 patients are unusual compared with many other illnesses. Blood pressure, heart rate, and respiratory rate may stay within acceptable ranges as the disease progresses. Consequently, intermittent monitoring does not detect deterioration as it is happening. We investigated whether continuously monitoring heart rate and respiratory rate enables earlier detection of deterioration compared with intermittent monitoring, or introduces any risks. METHODS: When available, patients admitted to a COVID-19 ward received a wireless wearable sensor which continuously measured heart rate and respiratory rate. Two intensive care unit (ICU) physicians independently assessed sensor data, indicating when an intervention might be necessary (alarms). A third ICU physician independently extracted clinical events from the electronic medical record (EMR events). The primary outcome was the number of true alarms. Secondary outcomes included the time difference between true alarms and EMR events, interrater agreement for the alarms, and severity of EMR events that were not detected. RESULTS: In clinical practice, 48 (EMR) events occurred. None of the 4 ICU admissions were detected with the sensor. Of the 62 sensor events, 13 were true alarms (also EMR events). Of these, two were related to rapid response team calls. The true alarms were detected 39 min (SD = 113) before EMR events, on average. Interrater agreement was 10%. Severity of the 38 non-detected events was similar to the severity of 10 detected events. CONCLUSION: Continuously monitoring heart rate and respiratory rate does not reliably detect deterioration in COVID-19 patients when assessed by ICU physicians.

ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units.

With advances in the Internet of Things, patients in intensive care units are constantly monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face monitoring has been required for the safety of patients and medical staff. A control center monitors the vital signs of patients in ICUs. However, some medical devices, such as ventilators and infusion pumps, operate in a standalone fashion without communication capabilities, requiring medical staff to check them manually. One promising solution is to use a robotic system with a camera. We propose a real-time optical digit recognition embedded system called ROMI. ROMI is a mobile robot that monitors patients by recognizing digits displayed on LCD screens of medical devices in real time. ROMI consists of three main functions for recognizing digits: digit localization, digit classification, and digit annotation. We developed ROMI by using Matlab Simulink, and the maximum digit recognition performance was 0.989 mAP on alexnet. The developed system was deployed on NVIDIA GPU embedded platforms: Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. We also created a benchmark by evaluating the runtime performance by considering ten pre-trained CNN models and three NVIDIA GPU platforms. We expect that ROMI will support medical staff with non-face-to-face monitoring in ICUs, enabling more effective and prompt patient care.

Readmission Risk after COVID-19 Hospitalization: A Moderation Analysis by Vital Signs.

OBJECTIVE: Readmission to the hospital after hospitalization with coronavirus disease 2019 (COVID-19) is associated with significant morbidity and mortality. Hospital clinicians may identify the presence of a patient's comorbid conditions, overall severity of illness, and clinical status at discharge as risk factors for readmission. Objective data are lacking to support reliance on these factors for discharge decision making. The objective of our study was to examine risk factors for readmission to the hospital after COVID-19 hospitalization and the impact of vital sign abnormalities, within 24 hours of discharge, on readmission rates. METHODS: In total, 2557 COVID-19-related hospital admissions within the Lifespan Health System, a large multicenter health system (Rhode Island), of 2230 unique patients aged 18 years and older, occurring from April 1, 2020 to December 31, 2020 were analyzed. Risk factors associated with readmission within 30 days were identified and analyzed using Cox regression. A moderation analysis by vital signs at discharge on the risk of readmission was performed. RESULTS: Clinical factors associated with readmissions included existing cardiovascular conditions (risk ratio 2.32, 95% confidence interval [CI] 1.10-4.90) and pulmonary disease (risk ratio 3.25, 95% CI 1.62-6.52). The absence of abnormal vital signs within 24 hours of discharge was associated with decreased 30-day readmission rates (risk ratio 0.70, 95% CI 0.52-0.94). Elevated C-reactive protein and d-dimer values and in-hospital complications including stroke, myocardial infarction, acute renal failure, and gastrointestinal bleeding were not associated with an increased risk of readmission. In moderation analysis, the presence of normal vital signs within 24 hours of discharge was associated with decreased readmission risk in patients who had primary risk factors for readmission including pulmonary disease (risk ratio 0.80, 95% CI 0.65-0.99), psychiatric disorders, and substance use (risk ratio 0.70, 95% CI 0.52-0.94). CONCLUSIONS: Comorbid conditions, including pulmonary and cardiovascular disease, are associated with readmission risk after COVID-19 hospitalization. The normalization of vital signs within 24 hours of discharge during COVID-19 hospitalization may be an indicator of readiness for discharge and may mitigate some readmission risk conferred by comorbid conditions.

Safety during interhospital helicopter transfer of ventilated COVID-19 patients. No clinical relevant changes in vital signs including non-invasive cardiac output.

BACKGROUND: During the COVID-19 pandemic in The Netherlands, critically ill ventilated COVID-19 patients were transferred not only between hospitals by ambulance but also by the Helicopter Emergency Medical Service (HEMS). To date, little is known about the physiological impact of helicopter transport on critically ill patients and COVID-19 patients in particular. This study was conducted to explore the impact of inter-hospital helicopter transfer on vital signs of mechanically ventilated patients with severe COVID-19, with special focus on take-off, midflight, and landing. METHODS: All ventilated critically ill COVID-19 patients who were transported between April 2020 and June 2021 by the Dutch 'Lifeliner 5' HEMS team and who were fully monitored, including noninvasive cardiac output, were included in this study. Three 10-min timeframes (take-off, midflight and landing) were defined for analysis. Continuous data on the vital parameters heart rate, peripheral oxygen saturation, arterial blood pressure, end-tidal CO2 and noninvasive cardiac output using electrical cardiometry were collected and stored at 1-min intervals. Data were analyzed for differences over time within the timeframes using one-way analysis of variance. Significant differences were checked for clinical relevance. RESULTS: Ninety-eight patients were included in the analysis. During take-off, an increase was noticed in cardiac output (from 6.7 to 8.2 L min-1; P < 0.0001), which was determined by a decrease in systemic vascular resistance (from 1071 to 739 dyne·s·cm-5, P < 0.0001) accompanied by an increase in stroke volume (from 88.8 to 113.7 mL, P < 0.0001). Other parameters were unchanged during take-off and mid-flight. During landing, cardiac output and stroke volume slightly decreased (from 8.0 to 6.8 L min-1, P < 0.0001 and from 110.1 to 84.4 mL, P < 0.0001, respectively), and total systemic vascular resistance increased (P < 0.0001). Though statistically significant, the found changes were small and not clinically relevant to the medical status of the patients as judged by the attending physicians. CONCLUSIONS: Interhospital helicopter transfer of ventilated intensive care patients with COVID-19 can be performed safely and does not result in clinically relevant changes in vital signs.

A Non-Contact Detection Method for Multi-Person Vital Signs Based on IR-UWB Radar.

With the vigorous development of ubiquitous sensing technology, an increasing number of scholars pay attention to non-contact vital signs (e.g., Respiration Rate (RR) and Heart Rate (HR)) detection for physical health. Since Impulse Radio Ultra-Wide Band (IR-UWB) technology has good characteristics, such as non-invasive, high penetration, accurate ranging, low power, and low cost, it makes the technology more suitable for non-contact vital signs detection. Therefore, a non-contact multi-human vital signs detection method based on IR-UWB radar is proposed in this paper. By using this technique, the realm of multi-target detection is opened up to even more targets for subjects than the more conventional single target. We used an optimized algorithm CIR-SS based on the channel impulse response (CIR) smoothing spline method to solve the problem that existing algorithms cannot effectively separate and extract respiratory and heartbeat signals. Also in our study, the effectiveness of the algorithm was analyzed using the Bland-Altman consistency analysis statistical method with the algorithm's respiratory and heart rate estimation errors of 5.14% and 4.87%, respectively, indicating a high accuracy and precision. The experimental results showed that our proposed method provides a highly accurate, easy-to-implement, and highly robust solution in the field of non-contact multi-person vital signs detection.

Wearable Technologies for Pediatric Patients with Surgical Infections-More than Counting Steps?

Reliable vital sign assessments are crucial for the management of patients with infectious diseases. Wearable devices enable easy and comfortable continuous monitoring across settings, especially in pediatric patients, but information about their performance in acutely unwell children is scarce. Vital signs were continuously measured with a multi-sensor wearable device (Everion®, Biofourmis, Zurich, Switzerland) in 21 pediatric patients during their hospitalization for appendicitis, osteomyelitis, or septic arthritis to describe acceptance and feasibility and to compare validity and reliability with conventional measurements. Using a wearable device was highly accepted and feasible for health-care workers, parents, and children. There were substantial data gaps in continuous monitoring up to 24 h. The wearable device measured heart rate and oxygen saturation reliably (mean difference, 2.5 bpm and 0.4% SpO2) but underestimated body temperature by 1.7 °C. Data availability was suboptimal during the study period, but a good relationship was determined between wearable device and conventional measurements for heart rate and oxygen saturation. Acceptance and feasibility were high in all study groups. We recommend that wearable devices designed for medical use in children be validated in the targeted population to assure future high-quality continuous vital sign assessments in an easy and non-burdening way.

Respinos: A Portable Device for Remote Vital Signs Monitoring of COVID-19 Patients.

The rapidly increasing number of COVID-19 patients has posed a massive burden on many healthcare systems worldwide. Moreover, the limited availability of diagnostic and treatment equipment makes it difficult to treat patients in the hospital. To reduce the burden and maintain the quality of care, asymptomatic patients or patients with mild symptoms are advised to self-isolate at home. However, self-isolated patients need to be continuously monitored as their health can turn into critical condition within a short time. Therefore, a portable device that can remotely monitor the condition and progression of the health of these patients is urgently needed. Here we present a portable device, called Respinos, that can monitor multiparameter vital signs including respiratory rate, heart rate, body temperature, and SpO2. It can also operate as a spirometer that measures forced vital capacity (FVC), forced expiratory volume (FEV), FEV in the first second (FEV1), and peak expiratory flow Rate (PEFR) parameters which are useful for detecting pulmonary diseases. The spirometer is designed in the form of a tube that can be ergonomically inflated by the patient, and is equipped with an accurate and disposable turbine based air flow sensor to evaluate the patient's respiratory condition. Respinos uses rechargeable batteries and wirelessly connects to a mobile application whereby the patient's condition can be monitored in real-time and consulted with doctors via chat. Extensive comparison against medical-grade reference devices showed good performance of Respinos. Overall results demonstrate the potential of Respinos for remote patient monitoring during and post pandemic.

Using a graph-based image segmentation algorithm for remote vital sign estimation and monitoring.

Reliable and contactless measurements of vital signs, such as respiration and heart rate, are still unmet needs in clinical and home settings. Mm-wave radar and video-based technologies are promising, but currently, the signal processing-based vital sign extraction methods are prone to body motion disruptions or illumination variations in the surrounding environment. Here we propose an image segmentation-based method to extract vital signs from the recorded video and mm-wave radar signals. The proposed method analyses time-frequency spectrograms obtained from Short-Time Fourier Transform rather than individual time-domain signals. This leads to much-improved robustness and accuracy of the heart rate and respiration rate extraction over existing methods. The experiments were conducted under pre- and post-exercise conditions and were repeated on multiple individuals. The results are evaluated by using four metrics against the gold standard contact-based measurements. Significant improvements were observed in terms of precision, accuracy, and stability. The performance was reflected by achieving an averaged Pearson correlation coefficient (PCC) of 93.8% on multiple subjects. We believe that the proposed estimation method will help address the needs for the increasingly popular remote cardiovascular sensing and diagnosing posed by Covid-19.