Vital Sign Parameters Research Articles

Efficacy of Nusinersen Treatment in Type 1, 2, and 3 Spinal Muscular Atrophy: Real-World Data from a Single-Center Study.

Spinal muscular atrophy (SMA) is an inherited neuromuscular disease characterized by progressive muscle weakness and atrophy due to the absence of the survival motor neuron 1 (SMN1) gene. SMA is classified into types 0 through 4 based on the age of symptom onset and the severity of motor function decline. Recent advances in SMA treatment, including nusinersen, onasemnogene abeparvovec, and risdiplam, have significantly improved the prognosis of SMA patients. This study evaluated the safety and efficacy of nusinersen in pediatric patients with SMA types 1, 2, and 3 in a real-world clinical setting. This prospective observational single-center study assessed the treatment effects of nusinersen in 23 pediatric patients with genetically confirmed SMA over a 22-month observation period. All the participants received intrathecal loading doses of 12 mg of nusinersen on days 1, 14, 28, and 63, followed by maintenance doses every four months. Functional assessments were conducted using the CHOP-INTEND scale. Data were collected during routine patient visits, including clinical laboratory tests and vital sign parameters, and adverse events were recorded. The inclusion criteria were defined by the national reimbursement program for nusinersen treatment in Poland. Initially, 37 patients ranging from 1 month old to 18 years old were included, but 23 were ultimately observed due to changes in treatment regimens or assessment scales. The patients showed significantly improved CHOP-INTEND scores over the 22-month period. At 6 months, the average increase was 4.2 points, continuing to 17.8 points at 22 months. By the end of the study, 100% of patients showed either stabilization or improvement, with significant clinical improvements observed in several patients. Nusinersen was generally well-tolerated, with post-lumbar puncture headache and lower back pain being the most common adverse events. Nusinersen treatment significantly enhances motor function in pediatric patients with SMA types 1, 2, and 3. This study demonstrates the importance of early and sustained treatment, with most patients showing the continuous improvement or stabilization of motor function. These findings support the use of nusinersen as an effective therapy for SMA; however, further research is needed to understand the long-term outcomes and optimize treatment strategies.

Evaluation of the effectiveness of a segmented alternating shift pattern based on wearable vital signs monitoring devices during COVID-19: a cross-sectional study

AimTo explore the feasibility and effectiveness of an alternating shift pattern in two-hour segments in the state of emergency management of public health events.MethodsA cross-sectional research design was conducted in our study. The nursing staff working in the admission ward of suspected or confirmed patients with COVID-19 in December 2022 were selected as subjects by the whole-group sampling method. We adopted a shift pattern of alternating shifts every two-hour in the isolation wards. The vital signs parameters were captured by uniformly wearing the multi-signs sensing devices, and the questionnaires collected the symptoms.ResultsSixty-seven female participants, with a mean age of 33.09 ± 5.96 years, were included in this study. Measurements of body temperature (T), blood oxygen saturation (SpO2), respiratory rate (RR), and heart rate (HR) while wearing personal protective equipment (PPE) all remained within normal limits. None of the nurses reported sweating, dizziness, blurred vision, palpitations, or dyspnea. Statistical analysis showed significant differences between the critical care group and the non-critical care group in terms of age (P = 0.041), working duration (P = 0.036), and the total number of entries into isolation areas for nursing care (rounds) (P = 0.007). However, there were no statistically significant differences in vital signs based on age, work duration, or body mass index (BMI). The data indicated a notable increase in body temperature compared to other vital sign parameters with increasing work time while wearing PPE. Body temperature approached the upper limit when working close to 2 h long.ConclusionsThe alternating shift pattern in two-hour segments can effectively maintain the physical well-being of nurses wearing PPE without increasing the burden on nursing staff or the wastage of protective materials. This approach is recommended for addressing similar public health events in the future.

A Context Awareness System for Clinical Environments

This study addresses the complex management of patient-related information in hospitals and clinical settings. This information includes treatments, medications, vital signs, patient locations, and data exchange between healthcare professionals. The lack of effective synchronization between these elements often delays timely care. This study proposes an architecture based on a semantic representation model that articulates the various components of a hospital environment. This model supports decision-making in healthcare by facilitating inferences from the environment. The semantic model serves as a basis for executing predefined rules that trigger actions through a reasoner, resulting in notifications, such as administering medications or responding to abnormal vital signs. The model integrates supervised learning to improve the accuracy of alerts. The experiment focused on monitoring vital sign parameters, such as Spo2, body temperature, and heart rate. The combination of semantic representation modeling and machine learning algorithms demonstrates a robust approach for improving the efficiency and accuracy of healthcare alerts in clinical settings.

IoT-Based Heartbeat Rate-Monitoring Device Powered by Harvested Kinetic Energy.

Remote patient-monitoring systems are helpful since they can provide timely and effective healthcare facilities. Such online telemedicine is usually achieved with the help of sophisticated and advanced wearable sensor technologies. The modern type of wearable connected devices enable the monitoring of vital sign parameters such as: heart rate variability (HRV) also known as electrocardiogram (ECG), blood pressure (BLP), Respiratory rate and body temperature, blood pressure (BLP), respiratory rate, and body temperature. The ubiquitous problem of wearable devices is their power demand for signal transmission; such devices require frequent battery charging, which causes serious limitations to the continuous monitoring of vital data. To overcome this, the current study provides a primary report on collecting kinetic energy from daily human activities for monitoring vital human signs. The harvested energy is used to sustain the battery autonomy of wearable devices, which allows for a longer monitoring time of vital data. This study proposes a novel type of stress- or exercise-monitoring ECG device based on a microcontroller (PIC18F4550) and a Wi-Fi device (ESP8266), which is cost-effective and enables real-time monitoring of heart rate in the cloud during normal daily activities. In order to achieve both portability and maximum power, the harvester has a small structure and low friction. Neodymium magnets were chosen for their high magnetic strength, versatility, and compact size. Due to the non-linear magnetic force interaction of the magnets, the non-linear part of the dynamic equation has an inverse quadratic form. Electromechanical damping is considered in this study, and the quadratic non-linearity is approximated using MacLaurin expansion, which enables us to find the law of motion for general case studies using classical methods for dynamic equations and the suitable parameters for the harvester. The oscillations are enabled by applying an initial force, and there is a loss of energy due to the electromechanical damping. A typical numerical application is computed with Matlab 2015 software, and an ODE45 solver is used to verify the accuracy of the method.

A Phase 1, Randomized, Double-Blind, Placebo-Controlled, Single Ascending Dose Study to Evaluate the Pharmacokinetics, Immunogenicity, Safety, and Tolerability After Subcutaneous Administration of Tozorakimab in Healthy Chinese Participants.

Tozorakimab is a high-affinity human immunoglobulin G1 monoclonal antibody that neutralizes interleukin (IL)-33, an IL-1 family cytokine. This phase 1, single-center, randomized, double-blind, placebo-controlled, single ascending dose study (NCT05070312) evaluated tozorakimab in a healthy Chinese population. Outcomes included the characterization of the pharmacokinetic (PK) profile and immunogenicity of tozorakimab. Safety outcomes included treatment-emergent adverse events (TEAEs) and clinical laboratory, electrocardiogram, and vital sign parameters. Healthy, non-smoking, male, and female Chinese participants aged 18-45 years with a body mass index 19-24kg/m2 were enrolled. In total, 36 participants across 2 cohorts of 18 participants were randomized 2:1 to receive a single subcutaneous dose of tozorakimab (300mg [2mL] or 600mg [4mL]) or matching placebo (2 or 4mL). Tozorakimab showed dose-dependent serum PK concentrations with an approximate monophasic distribution in serum over time and a maximum observed peak concentration of 20.1 and 33.7μg/mL in the 300- and 600-mg cohorts, respectively. No treatment-emergent anti-drug antibodies for tozorakimab were observed in any of the participants. There were no clinically relevant trends in the occurrence of TEAEs across the treatment groups. There were no clinically relevant trends over time in clinical laboratory (hematology, clinical chemistry, and urinalysis), electrocardiogram, or vital sign parameters in any treatment group. Overall, tozorakimab demonstrated dose-dependent systemic exposure in healthy Chinese participants and was well tolerated, with no safety concerns identified in this study.

Feasibility, functionality, and user experience with wearable technologies for acute exacerbation monitoring in patients with severe COPD

Background: The increasing interest in remote patient monitoring technologies in patients with chronic obstructive pulmonary disease (COPD) requires a phased and stepwise investigative approach, which includes high-risk clinical subgroups who stand to benefit most from such innovations.Methods: Patients aged > 40 with spirometry-confirmed COPD presenting with a current acute exacerbation (ECOPD) were recruited from a tertiary centre Day Hospital in this prespecified feasibility study. Heart rate, respiratory rate, oxygen saturation, skin temperature, and daily activity and overnight sleep quality parameters were collected remotely by a wearable biometric wristband and ring for 21 consecutive days. “Total ambulatory wear time” and “percent of useable data” for eligible vital sign parameters were calculated. Correlation and agreement between cardiorespiratory vital sign data were performed using Spearman’s correlation rho and the Bland-Altman test, respectively. User experience was measured with end-of-study System Usability Scale (SUS) questionnaires.Results: Nine participants (mean age 66.8 ± 8.4 years, 22% female, mean FEV1 1.4L (34.1% predicted), with “severe” (56%) or “very severe” (44%) COPD) experiencing a current ECOPD were included. Wear time was 94% (wristband) and 88.2% (ring) of the total ambulatory study period. Wristband-obtained data (every 1 min, artefact-free) revealed 99.2% and 98.6% of all heart rate and temperature data, respectively, was useable, whereas only 17.6% of all respiratory rate data was useable. Ring-obtained data (every 5 min, “average” and “good” quality) revealed 84.5% of all heart rate data was useable. Cross-sectional analyses with nurse-obtained vital signs revealed correlation coefficients of 0.56 (p = 0.11) and 0.81 (p = 0.0086) for wristband-obtained and ring-obtained heart rate, respectively, and only 0.15 (p = 0.74) for wristband-obtained respiratory rate, without evidence of systematic/proportional bias. Longitudinal heart rate and respiratory rate inter-device analyses demonstrated correlations of 0.86 (p < 0.001) and 0.65 (p < 0.001), respectively. Finally, end-of-study SUS scores were 86.4/100 (wristband) and 89.2/100 (ring).Conclusion: Older adults with severe/very severe COPD experiencing a current ECOPD were capable of autonomous physiological data collection/upload/transmission from their home environment over several weeks using sophisticated wearable biometric technology, with favourable user experiences. Cross-sectional and longitudinal comparative results call into question the paradigm of single sets of infrequent/interval vital sign checks as the current “gold-standard” in frontline clinical practice.

Importance of specific vital signs in nurses' recognition and response to deteriorating patients: A scoping review.

To explore the published research related to nurses' documentation and use of vital signs in recognising and responding to deteriorating patients. Scoping review of international, peer-reviewed research studies. Cumulative Index to Nursing and Allied Health Literature Complete, Medline Complete, American Psychological Association PsycInfo and Excerpta Medica were searched on 25 July 2023. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Of 3880 potentially eligible publications, 32 were included. There were 26 studies of nurses' vital sign documentation: 21 adults and five paediatric. The most and least frequently documented vital signs were blood pressure and respiratory rate respectively. Seven studies focused on vital signs and rapid response activation or afferent limb failure. Five studies of vital signs used to trigger the rapid response system showed heart rate was the most frequent and respiratory rate and conscious state were the least frequent. Heart rate was least likely and oxygen saturation was most likely to be associated with afferent limb failure (n = 4 studies). Despite high reliance on using vital signs to recognise clinical deterioration and activate a response to deteriorating patients in hospital settings, nurses' documentation of vital signs and use of vital signs to activate rapid response systems is poorly understood. There were 21studies of nurses' vital sign documentation in adult patients and five studies related to children. A deeper understanding of nurses' decisions to assess (or not assess) specific vital signs, analysis of the value or importance nurses place (or not) on specific vital sign parameters is warranted. The influence of patient characteristics (such as age) or the clinical practice setting, and the impact of nurses' workflows of vital sign assessment warrants further investigation. No Patient or Public Contribution.

Dystocia due to Breech presentation with cranio -skeletal malformations in a crossbred cow

A third calving full term pregnant Jersey cross bred cattle was presented to Veterinary Poly Clinic with the history of calving difficulty. All the vital sign parameters of the Dam were within the normal limits. The animal is on sternal recumbency. Upon vaginal examination, it was found that the cervix was fully dilated. Additionally, a breech presentation was observed. Detailed vaginal examination and manipulations the calf was brought to extended position of hind legs. Then by careful assistance hind limb was dragged outside then the calf's hip and thigh region were locked at the pelvic brim of the dam, making delivery difficult. Despite ample lubrication, a bulldog calf with cranio-skeletal malformations was delivered. These malformations are attributed to hereditary causes, primarily driven by recessive autosomal genes. The communication highlights the importance of understanding genetic predispositions and conducting thorough examinations during pregnancy to detect such anomalies early. It also emphasizes the need for careful breeding practices to minimize the risk of inherited disorders in livestock populations.

Dexmedetomidine at Home for Intractable Dystonia and Insomnia in Children With Special Needs: A Case Series.

We know that syndromic conditions and severe chronic diseases can be associated with symptoms that may interfere with sleep, significantly impacting the life quality of children and caregivers. Drugs commonly used in treating insomnia, such as melatonin, benzodiazepines, niaprazine, and antihistamines, are often either ineffective or associated with adverse effects, requiring new therapeutic perspectives. Dexmedetomidine is a selective alpha-2 agonist with hypnotic and anxiolytic effects, which, by stimulating alpha-2 adrenergic receptors in the locus coeruleus, induces sleep comparable to stages 2-3 of the non-REM phase without substantially affecting the respiratory drive during sedation. Its use has already been extensively described in pediatric intensive care or procedural sedation literature. In 2018, the Italian Medicines Agency (Agenzia Italiana Del Farmaco AIFA) authorized the off-label use of dexmedetomidine outside of intensive care in Children undergoing palliative treatment to control distressing symptoms related to pathology and refractory sleep disorders, and the literature reported cases of children who received dexmedetomidine at home. Our study aims to describe the home use of dexmedetomidine in children with insomnia or intractable dystonic states. We conducted a retrospective analysis through a questionnaire addressed to 12 Italian pediatric palliative care centers regarding the home use of dexmedetomidine in sleep disorders and intractable dystonic states. We collected a case series of 9 children treated with dexmedetomidine at home, 8 via intranasal and 1 via intravenous route. All children received the first drug administration in the hospital or hospice during a dedicated admission, under close monitoring of vital signs parameters for 72 hours (3 days, range 2-7 days). After discharge, the potential side effects of the drug were explained to the patient's families, and, once informed consent was obtained, the home administration of dexmedetomidine continued, with follow-up by the palliative care team. At home, dexmedetomidine was administered for 3000 days (minimum 1 month, maximum 36 months). The first patient was treated for 1095 days, from 2019 to 2021 (discontinued due to underlying condition-related death). All patients observed a persistent benefit from the treatment on symptoms, and none of them discontinued dexmedetomidine administration due to drug-related adverse effects or perceived lack of therapeutic efficacy. Therefore, its use at home may represent a promising therapeutic approach for intractable sleep disorders or dystonic states in pediatric palliative care children. Further studies are needed to confirm our results.

Advancing Chronic Respiratory Disease Care with Real-Time Vital Sign Prediction

Cardiovascular and chronic respiratory diseases, being pervasive in nature, pose formidable challenges to the overall well-being of the global populace. With an alarming annual mortality rate of approximately 19 million individuals across the globe, these diseases have emerged as significant public health concerns warranting immediate attention and comprehensive understanding. The mitigation of this elevated mortality rate can be achieved through the application of cutting-edge technological innovations within the realm of medical science, which possess the capacity to enable the perpetual surveillance of various physiological indicators, including but not limited to blood pressure, cholesterol levels, and blood glucose concentrations. The forward-thinking implications of these pivotal physiological or vital sign parameters not only facilitate prompt intervention from medical professionals and carers, but also empower patients to effectively navigate their health status through the receipt of pertinent periodic notifications and guidance from healthcare practitioners. In this research endeavour, we present a novel framework that leverages the power of machine learning algorithms to forecast and categorise forthcoming values of pertinent physiological indicators in the context of cardiovascular and chronic respiratory ailments. Drawing upon prognostications of prospective values, the envisaged framework possesses the capacity to effectively categorise the health condition of individuals, thereby alerting both caretakers and medical professionals. In the present study, a machine-learning-driven prediction and classification framework has been employed, wherein a genuine dataset comprising vital signs has been utilised. In order to anticipate the forthcoming 1-3 minutes of vital sign values, a series of regression techniques, namely linear regression and polynomial regression of degrees 2, 3, and 4, have been subjected to rigorous examination and evaluation. In the realm of caregiving, a concise 60-second prognostication is employed to enable the expeditious provision of emergency medical aid. Additionally, a more comprehensive 3-minute prognostication of vital signs is utilised for the same purpose. The patient's overall health is evaluated based on the anticipated vital signs values through the utilisation of three machine learning classifiers, namely Support Vector Machine (SVM), Decision Tree and Random Forest. The findings of our study indicate that the implementation of a Decision Tree algorithm exhibits a high level of accuracy in accurately categorising a patient's health status by leveraging anomalous values of vital signs. This approach demonstrates its potential in facilitating prompt and effective medical interventions, thereby enhancing the overall quality of care provided to patients.

Certificateless Anonymous Signcryption Scheme With Provable Security in the Standard Model Suitable for Healthcare Wireless Sensor Networks

In healthcare wireless sensor networks(HWSNs), wireless sensors are placed on the patient, which collect the patient’s vital signs parameters and various environmental information, and send these data to the doctor, so that the doctor is able to perform real-time remote monitoring for the patient. The patient’s vital signs parameters contain a lot of private information. It is very likely to cause the leakage of patient’s private information if these parameters are transmitted through the public channel. In addition, many patients don’t want doctors to know their true identity. We designed a certificateless anonymous signcryption (CL-ASC) scheme for HWSNs in this paper. It encrypts the patient’s vital signs parameters, authenticates the legitimacy of the sensor, and realizes the anonymity of the sensor. We then showed the security proofs of new scheme in the standard model. Finally, we compared the performance of the six schemes. Since only three pairing operations are used, the new scheme enjoys higher computation efficiency and is suitable for HWSNs.

ECG and NIBP Simulators in One Device Display on TFT Nextion

Accurate monitoring of NIBP (Non-Invasive Blood Pressure) parameters using vital sign monitors is crucial for patient care. Therefore, calibration of vital sign monitors is essential to ensure their safety and reliability. The purpose of this study is a vital sign simulator was developed, integrating ECG and NIBP parameters with a TFT Nextion display, to calibrate ECG and NIBP readings on vital sign monitors. The system utilized the Arduino Mega 2560 as the central controller and the MPX5050GP sensor for NIBP measurement and motor pump control. The NIBP parameters were measured at two settings: 60/30 and 80/50. The results showed a maximum systolic error of 3.5% and a diastolic error of 5.6% for the NIBP setting of 80/50. The largest standard deviation value of 2.05 was observed at the NIBP setting of 60/30. The highest uncertainty value of 0.5 was also found in the NIBP 60/30 setting. The obtained data indicated stable module readings within the acceptable threshold for vital sign monitor calibration. The developed vital sign simulator offers a reliable means of calibrating NIBP parameters, enabling accurate blood pressure measurements. Further research and refinement can be conducted to enhance the system's precision and expand its capabilities for calibration of additional vital sign parameters. By ensuring accurate calibration, healthcare professionals can rely on vital sign monitors for effective patient monitoring and diagnosis.

Contactless methods to acquire heart and respiratory signals—A review

<p align="justify">The vital sign is the most important parameter for the internal health status of any subject in time. Every person is witnessed of COVID-19 global pandemic viruses. The world population has faced this problem globally. Collecting the infected person’s sample data in a contact-based approach may lead to the spreading of the disease. On the other hand, if we use a non-contact-based approach for the collection, it is somehow far better and breaks the chain of virus spreading. This radar-based technique is preferred in non-contact vital sign detection so that any person gets to their health status prior and according to that doctor can diagnose the proper treatment. The radar-based signal is targeted to the subject’s chest. Due to the chest wall displacement main vital sign parameters of the heart and respiration of the individual’s health are being captured. These captured signals are called vital signs, with this it is very helpful that the pre-diagnosis and treatment can be recommended by doctors or health service providers. Some patients due to their movement may be older or children for a long-time use skin irritation or allergy type of problems may face. On the other hand, some patients may be COVID-19 infected disease and burn patients. Hence, it is not possible to connect as both cases are unexpected for the required purpose. For constant and continuous measurement, existing contact-based methods are not fruitful hence non-contact-based approach is adopted. Non-contact-based vital sign detection is preferably due to several problems occurring. This paper presents a state-of-the-art review of recent monitoring methods and techniques for health monitoring in medical fields of operations. These methods and techniques are used as a tool to acquire, visualize and analyze the sampled data collected in any environment either indoor or outdoor.</p>

The use of whole-body trauma CT should be based on mechanism of injury: A risk analysis of 3920 patients at a tertiary trauma centre

BackgroundMechanism of injury (MOI) plays a significant role in a decision to perform whole-body computed tomography (CT) imaging for trauma patients. Various mechanisms have unique patterns of injury and therefore form an important variable in decision making. MethodsRetrospective cohort study including all patients >18 years old who received a whole-body CT scan between 1 January 2019 and 19 February 2020. The outcomes were divided into CT ‘positive’ if any internal injuries were detected and CT ‘negative’ if no internal injuries were detected. The MOI, vital sign parameters, and other relevant clinical examination findings at presentation were recorded. Results3920 patients met the inclusion criteria, of which 1591 (40.6%) had a positive CT. The most common MOI was fall from standing height (FFSH), accounting for 23.0%, followed by motor vehicle accident (MVA), accounting for 22.4%. Covariates significantly associated with a positive CT included age, MVA >60 km/h, motor bike, bicycle, or pedestrian accident >30 km/h, prolonged extrication >30 min, fall from height above standing, penetrating chest or abdominal injury, as well as hypotension, neurological deficit, or hypoxia on arrival. FFSH was shown to reduce the risk of a positive CT overall, however, sub-analysis of FFSH in patients >65 years showed a significant association with a positive CT (OR 2.34, p < 0.001) compared to <65 years. ConclusionsPre-arrival information including MOI and vital signs have significant impact on identifying subsequent injuries with CT imaging. In high energy trauma, we should consider the need for whole-body CT based on MOI alone regardless of the clinical examination findings. However, for low-energy trauma, including FFSH, in the absence of clinical examination findings which support an internal injury, a screening whole-body CT is unlikely to yield a positive result, particularly in the age group <65yo.

Early Postoperative Vital Signs Predict Subsequent 90-Day Mortality After Pancreaticoduodenectomy

BackgroundWhile complication rates after pancreaticoduodenectomy (PD) have improved in recent decades, surgical-related death remains a possibility. Postoperative vital signs offer an untapped opportunity to identify predictors of 90-day mortality. MethodsWe performed a retrospective chart review interrogating postoperative day (POD 0–7) vital sign measurements from patients undergoing a PD at Thomas Jefferson University Hospital, Philadelphia, PA (2009–2014). Five specific vital signs were examined as predictors of mortality: temperature, heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure. Statistical analyses and logic algorithms were employed to rank vital sign parameters, with cut-points, to identify those associated with the highest risk of mortality and the most clinical relevance. ResultsIn our cohort, 11/750 patients (1.5%) died within 30 days of surgery, and 21/750 patients (2.8%) died within 90 days of surgery. Vital sign perturbations associated with the highest risk of mortality included mean SBP < 95 mmHg on POD 7 (odds ratio 51.46) and the mean temperature < 96.9℉ on POD 3 (odds ratio 22.63) with specificities exceeding 99%. The most clinically relevant predictor (i.e., a higher sensitivity) was DBP < 60.5 mmHg on POD 7 (odds ratio 12.45, sensitivity of 75%). These predictors remained statistically significant in a multivariable model. ConclusionsVital signs can be more effectively utilized to predict 90-day mortality after pancreaticoduodenectomy. Values beyond an informative threshold can potentially identify patients for more intensive monitoring with a goal of rescuing patients and preventing death.

Early prediction of delirium upon intensive care unit admission: Model development, validation, and deployment

Study objectiveTo develop, validate, and deploy models for predicting delirium in critically ill adult patients as early as upon intensive care unit (ICU) admission. DesignRetrospective cohort study. SettingSingle university teaching hospital in Taipei, Taiwan. Patients6238 critically ill patients from August 2020 to August 2021. MeasurementsData were extracted, pre-processed, and split into training and testing datasets based on the time period. Eligible variables included demographic characteristics, Glasgow Coma Scale, vital signs parameters, treatments, and laboratory data. The predicted outcome was delirium, defined as any positive result (a score ≥ 4) of the Intensive Care Delirium Screening Checklist that was assessed by primary care nurses in each 8-h shift within 48 h after ICU admission. We trained models to predict delirium upon ICU admission (ADM) and at 24 h (24H) after ICU admission by using logistic regression (LR), gradient boosted trees (GBT), and deep learning (DL) algorithms and compared the models' performance. Main resultsEight features were extracted from the eligible features to train the ADM models, including age, body mass index, medical history of dementia, postoperative intensive monitoring, elective surgery, pre-ICU hospital stays, and GCS score and initial respiratory rate upon ICU admission. In the ADM testing dataset, the incidence of ICU delirium occurred within 24 h and 48 h was 32.9% and 36.2%, respectively. The area under the receiver operating characteristic curve (AUROC) (0.858, 95% CI 0.835–0.879) and area under the precision-recall curve (AUPRC) (0.814, 95% CI 0.780–0.844) for the ADM GBT model were the highest. The Brier scores of the ADM LR, GBT, and DL models were 0.149, 0.140, and 0.145, respectively. The AUROC (0.931, 95% CI 0.911–0.949) was the highest for the 24H DL model and the AUPRC (0.842, 95% CI 0.792–0.886) was the highest for the 24H LR model. ConclusionOur early prediction models based on data obtained upon ICU admission could achieve good performance in predicting delirium occurred within 48 h after ICU admission. Our 24-h models can improve delirium prediction for patients discharged >1 day after ICU admission.

Use of Evidence-Based Vital Signs in Pediatric Early Warning Score to Predict Clinical Deterioration on Acute Care Units.

The pediatric early warning score (PEWS) is a tool used to predict clinical deterioration. Referenced vital sign parameters are based on expert opinion but heart rate and respiratory rate percentiles in hospitalized children have been published. This retrospective case-control study of unplanned intensive care unit (ICU) transfers compares evidence-based vital signs (EBVS) effect on PEWS sensitivity and specificity, determines the impact of age categories on PEWS deterioration prediction, and evaluates whether EBVS PEWS is associated with need for invasive ICU supports. EBVS PEWS improved sensitivity (43%-71% vs 30%-63%) for unplanned transfers with slightly decreased specificity (88%-98% vs 93%-99%). Logistic regression analysis and odds ratios (ORs) demonstrated EBVS PEWS was associated with increased risk for ICU-specific supports (OR = 1.16, 95% confidence interval [CI] = 1.0-1.34, P = .0498). Evidence-based vital signs can improve PEWS sensitivity to identify unplanned ICU transfers and identify patients requiring ICU-specific interventions.

Vitality surveillance at distance using thin-film tandem-like narrowband near-infrared photodiodes with light-enhanced responsivity

Remote measurement of vital sign parameters like heartbeat and respiration rate represents a compelling challenge in monitoring an individual's health in a noninvasive way. This could be achieved by large field-of-view, easy-to-integrate unobtrusive sensors, such as large-area thin-film photodiodes. At long distances, however, discriminating weak light signals from background disturbance demands superior near-infrared (NIR) sensitivity and optical noise tolerance. Here, we report an inherently narrowband solution-processed, thin-film photodiode with ultrahigh and controllable NIR responsivity based on a tandem-like perovskite-organic architecture. The device has low dark currents (<10-6 mA cm-2), linear dynamic range >150 dB, and operational stability over time (>8hours). With a narrowband quantum efficiency that can exceed 200% at 850 nm and intrinsic filtering of other wavelengths to limit optical noise, the device exhibits higher tolerance to background light than optically filtered silicon-based sensors. We demonstrate its potential in remote monitoring by measuring the heart rate and respiration rate from distances up to 130 cm in reflection.

Analysis of Signal Processing Methods to Reject the DC Offset Contribution of Static Reflectors in FMCW Radar-Based Vital Signs Monitoring

Frequency-modulated continuous wave (FMCW) radars are currently being investigated for remote vital signs monitoring (measure of respiration and heart rates) as an innovative wireless solution for healthcare and ambient assisted living. However, static reflectors (furniture, objects, stationary body parts, etc.) within the range or range angular bin where the subject is present contribute in the Doppler signal to a direct current (DC) offset. The latter is added to the person's information, containing also a useful DC component, causing signal distortion and hence reducing the accuracy in measuring the vital sign parameters. Removing the sole contribution of the unwanted DC offset is fundamental to perform proper phase demodulation, so that accurate vital signs monitoring can be achieved. In this work, we analyzed different DC offset calibration methods to determine which one achieves the highest accuracy in measuring the physiological parameters as the transmitting frequency varies. More precisely, by using two FMCW radars, operating below 10 GHz and at millimeter wave (mmWave), we applied four DC offset calibration methods to the baseband radar signals originated by the cardiopulmonary activities. We experimentally determined the accuracy of the methods by measuring the respiration and the heart rates of different subjects in an office setting. It was found that the linear demodulation outperforms the other methods if operating below 10 GHz while the geometric fitting provides the best results at mmWave.

Long-Term Oxygen Therapy in Patients with Pulmonary Artery Hypertension

Introduction: Dyspnea associated with pulmonary arterial hypertension (PAH) requires supplemental oxygen to maintain oxygen saturation. Many researches related to oxygen therapy in chronic obstructive pulmonary disease and cor pulmonale are available, but the effect of long-term oxygen therapy (LTOT) has not been explored in PAH patients. Aim: This study aimed to determine the effect of LTOT in patients diagnosed with PAH. Methodology: All adult patients with PAH, primary or secondary to respiratory disease who require LTOT, were included in the study. The following parameters were collected: age, gender, severity of PAH based on echocardiogram, body mass index, comorbidities, type of oxygen therapy device, amount and duration of oxygen usage, mortality, frequency of readmission, oxygenation, and vital sign parameters. Results: This was a retrospective study which included 332 participants diagnosed to have PAH after detailed echocardiogram assessment. Out of these, 32 participants were prescribed LTOT at the time of discharge. At the time of discharge, there was a significant improvement in all the vital signs and oxygenation variables. The increase in oxygenation, hemoglobin, and reduced respiratory rate after LTOT was statistically significant (P