Continuous Monitoring Of Vital Signs Research Articles

Abstract 4144517: Feasibility of Deep Sedation for Catheter Ablation of Atrial Fibrillation Using Pulsed Field Ablation

Introduction: General anesthesia is commonly utilized during catheter ablation of atrial fibrillation (AF) in the United States, providing patient immobility and permitting esophageal temperature management for radiofrequency ablation. Pulsed field ablation (PFA) is associated with shorter procedure time, less risk of esophageal injury, and less dependence on catheter stability compared with radiofrequency ablation. There are limited data available on performing the procedure with deep sedation as an alternative to general anesthesia with endotracheal intubation. Methods: Consecutive patients who underwent catheter ablation of AF at Endeavor Health (Chicago, IL) using pulsed field ablation (Farapulse, Boston Scientific, Marlborough, MA or PulseSelect, Medtronic, Minneapolis, MN) and deep sedation between March and May 2024 were retrospectively included in this study. Deep sedation (monitored anesthesia care) was administered by a certified registered nurse anesthetist and attending anesthesiologist, consisting of bolus and infusion dosing of propofol, dexmedetomidine, fentanyl, and midazolam at the discretion of the practitioner with continuous monitoring of vital signs and end-tidal CO2. The primary endpoint was the rate of airway complications or requirement for conversion to general anesthesia. Secondary endpoints were the rate of acute procedural success (all pulmonary veins isolated), total time in the EP lab, procedure time (from lidocaine to removal of sheaths), and non-procedure time (difference between total time in lab and procedure time). Results: A total of 40 patients (mean age 70.4 ± 13.6 years, BMI 30.2 ± 7.4, 60% females) were included in the analysis. There were no instances of airway complications or conversion from deep sedation to general anesthesia. There was a 100% rate of acute isolation of pulmonary veins. The average total time in the lab was 156.6 ± 41.5 minutes; consisting of a mean procedure time of 107.1 ± 39.7 minutes and non-procedure time 49.5 ± 10.3 minutes. Conclusions: In this initial experience at a single center, deep sedation (monitored anesthesia care) for PFA was associated with no instances of airway complications. The findings may not apply to patients with moderate or severe obstructive sleep apnea or other pulmonary diseases. Although patients generally were amnestic to the procedure, larger studies incorporating patient-reported outcomes are needed, as well as data regarding long-term clinical outcomes and cost.

Compact Vital-Sensing Band with Uninterrupted Power Supply for Core Body Temperature and Pulse Rate Monitoring.

Although wearable devices for continuous monitoring of vital signs have undergone significant advancements, their need for frequent recharging precludes continuous operation, potentially leading to adverse outcomes being overlooked. Additionally, the scattered locations of the sensors hamper wearability. Herein, we present a compact vital-sensing band with uninterrupted power supply designed for continuous monitoring of core body temperature (CBT) and pulse rate. The band─which comprises two sensors, a power source (i.e., a flexible thermoelectric generator (TEG) and a battery), and a flexible circuit─is worn on the forearm. The CBT is calculated by measuring the skin temperature and heat flux, while a triboelectric nanogenerator-based self-powered pressure sensor is utilized for pulse rate monitoring. The TEG is a flexible unit that converts body heat into electricity, accumulating a total energy of 314 mJ (100%). Out of this total energy, only 43.2 mJ (7.2%) is utilized for CBT measurements, while the remaining 270.80 mJ (92.8%) is stored in the battery. This enables reliable and continuous operation of the vital-sensing band, highlighting its potential for use in healthcare applications.

ML-powered Internet of Medical Things (MLIoMT) Structure for Heart Disease Prediction

Background ML-powered Internet of Medical Things (MLIoMT) is a burgeoning framework poised to transform healthcare, particularly in the timely identification of heart disease. Objectives This article proposes an innovative MLIoMT structure aimed at leveraging machine learning (ML) algorithms for heart disease detection. Materials and Methods Through the integration of wearable sensors, mobile applications, cloud computing, and advanced ML techniques, MLIoMT enables continuous monitoring of vital signs and cardiac health indicators in real time. By analyzing this data stream, abnormalities indicative of heart disease can be detected early, facilitating timely intervention and personalized healthcare recommendations. The MLIoMT framework employs diverse ML methods, such as deep learning and ensemble techniques to enhance the accuracy and reliability of heart disease prediction models. Results The proposed structure holds promise for revolutionizing preventive healthcare, enabling proactive management of cardiac health, and ultimately reducing the burden of heart disease. Results in terms of accuracy, precision, recall and F1 score show that the proposed system has better performance and efficiency. Conclusion Overall, MLIoMT represents a significant advancement in healthcare technology, with the potential to improve patient outcomes and enhance overall quality of life.

A Cloud Infrastructure for Health Monitoring in Emergency Response Scenarios.

Wearable devices have a significant impact on society, and recent advancements in modern sensor technologies are opening up new possibilities for healthcare applications. Continuous vital sign monitoring using Internet of Things solutions can be a crucial tool for emergency management, reducing risks in rescue operations and ensuring the safety of workers. The massive amounts of data, high network traffic, and computational demands of a typical monitoring application can be challenging to manage with traditional infrastructure. Cloud computing provides a solution with its built-in resilience and elasticity capabilities. This study presents a Cloud-based monitoring architecture for remote vital sign tracking of paramedics and medical workers through the use of a mobile wearable device. The system monitors vital signs such as electrocardiograms and breathing patterns during work sessions, and it is able to manage real-time alarm events to a personnel management center. In this study, 900 paramedics and emergency workers were monitored using wearable devices over a period of 12 months. Data from these devices were collected, processed via Cloud infrastructure, and analyzed to assess the system's reliability and scalability. The results showed a significant improvement in worker safety and operational efficiency. This study demonstrates the potential of Cloud-based systems and Internet of Things devices in enhancing emergency response efforts.

DEVELOPMENT OF INNOVATIVE MEDICAL DEVICES IN NEONATOLOGY: LITERATURE REVIEW

The aim of this study is to review the development of medical devices in neonatology, exploring technological advances, identifying innovations and challenges, and proposing recommendations for future research. The methodology involved a narrative review of the literature, searching databases such as PubMed, EBSCO, Cochrane, and IEEE Xplore, focusing on studies from the last ten years on medical devices for neonatology. The results highlight that technologies such as artificial intelligence and machine learning have improved the monitoring and prognosis of neonatal conditions, allowing for more precise and personalized interventions. 3D printing emerges as a promising tool for creating personalized medical devices, meeting the specific needs of each patient. Wearable devices for continuous monitoring of vital signs and advanced enteral and parenteral feeding devices have demonstrated a positive impact on neonatal health. Mechanical ventilators with gentler and smarter modes have reduced serious complications, and catheters with antimicrobial coatings have helped to reduce the incidence of neonatal sepsis. The conclusions indicate that technological innovations are fundamental to improving neonatal care. The integration of artificial intelligence, 3D printing and continuous monitoring has the potential to transform neonatology, improving clinical outcomes and the quality of life of newborns. However, challenges such as the variability of neonatal pathologies, cost and accessibility of devices and the need for adequate training of health professionals need to be addressed. Investment in continuous research, clinical validation and interdisciplinary training is recommended to ensure the effective adoption of these innovative technologies in daily clinical practices.

Time to detection of serious adverse events by continuous vital sign monitoring versus clinical practice.

Continuous vital sign monitoring detects far more severe vital sign deviations (SVDs) than intermittent clinical rounds, and deviations are to some extent related to subsequent serious adverse events (SAEs). Early detection of SAEs is pivotal to allow for effective interventions but the time relationship between detection of SAEs by continuous vital sign monitoring versus clinical practice is not well-described at the general ward. To quantify the time difference between detection of SAEs by continuous vital sign monitoring and clinical suspicion of deterioration (CSD) in major abdominal surgery patients. Five hundred and five patients had their vital signs continuously monitored in combination with usual clinical practice consisting of National Early Warning Score assessments at least every 8'th hour, assessments during rounds, and other kinds of staff-patient interactions. The primary outcome was the time difference between the first chart note of CSD versus the first SVD, detected by continuous vital sign monitoring, in patients with a subsequent confirmed SAE during or up to 48 h after end of continuous vital sign monitoring. Out of the 505 continuously monitored patients, 142 patients had a combination of both postoperative SAE, CSD and SVD, and thus were included in the primary analysis. The median time from the first SVD to SAE was 42.8 h (interquartile range 19.8-72.1 h) compared to 13 minutes (interquartile range - 4.8 to 3.5 h) for CSD with a median difference of 48.1 h (95% confidence interval 43.0-54.8 h), p-value < .001. Continuous vital sign monitoring detects signs of oncoming SAEs in the form of SVD hours before CSD, potentially allowing for earlier and more effective treatments to reduce the extent of SAEs.

Recent Advances in the Wearable Devices for Monitoring and Management of Heart Failure.

Heart failure (HF) is an acute and degenerative condition with high morbidity and mortality rates. Early diagnosis and treatment of HF can significantly enhance patient outcomes through admission and readmission reduction and improve quality of life. Being a progressive condition, the continuous monitoring of vital signs and symptoms of HF patients to identify any deterioration and to customize treatment regimens can be beneficial to the management of this disease. Recent breakthroughs in wearable technology have revolutionized the landscape of HF management. Despite the potential benefits, the integration of wearable devices into HF management requires careful consideration of technical, clinical, and ethical challenges, such as performance, regulatory requirements and data privacy. This review summarizes the current evidence on the role of wearable devices in heart failure monitoring and management, and discusses the challenges and opportunities in the field.

Comparing peripheral limb and forehead vital sign monitoring in newborn infants at birth.

To study the feasibility of measuring heart rate (HR) and oxygen saturation (SpO2) on the forehead, during newborn transition at birth, and to compare these measurements with those obtained from the wrist. Vital signs were measured and compared between forehead-mounted reflectance (remittance) photoplethysmography sensor (fhPPG) and a wrist-mounted pulse oximeter sensor (wrPO), from 20 enrolled term newborns born via elective caesarean section, during the first 10 min of life. From the datasets available (n = 13), the median (IQR) sensor placement times for fhPPG, ECG and wrPO were 129 (70) s, 143 (68) s, and 159 (76) s, respectively, with data recorded for up to 10 min after birth. The success rate (percentage of total possible HR values reported once sited) of fhPPG (median = 100%) was higher compared to wrPO (median = 69%) during the first 6 min of life (P < 0.005). Both devices exhibited good HR agreement with ECG, achieving >95% agreement by 3 (fhPPG) and 4 (wrPO) min. SpO2 for fhPPG correlated with wrPO (r = 0.88), but there were significant differences in SpO2 between the two devices between 3 and 8 min (P < 0.005), with less variance observed with fhPPG SpO2. In the period of newborn transition at birth in healthy term infants, forehead measurement of vital signs was feasible and exhibited greater HR accuracy and higher estimated SpO2 values compared to wrist-sited pulse oximetry. Further investigation of forehead monitoring based on the potential benefits over peripheral monitoring is warranted. This study demonstrates the feasibility of continuously monitoring heart rate and oxygen saturation from an infant's forehead in the delivery room immediately after birth. Significantly higher SpO2 measurements were observed from the forehead than the wrist during the transition from foetal to newborn life. Continuous monitoring of vital signs from the forehead could become a valuable tool to improve the delivery of optimal care provided for newborns at birth.

Discrepancies between Promised and Actual AI Capabilities in the Continuous Vital Sign Monitoring of In-Hospital Patients: A Review of the Current Evidence.

Continuous vital sign monitoring (CVSM) with wireless sensors in general hospital wards can enhance patient care. An artificial intelligence (AI) layer is crucial to allow sensor data to be managed by clinical staff without over alerting from the sensors. With the aim of summarizing peer-reviewed evidence for AI support in CVSM sensors, we searched PubMed and Embase for studies on adult patients monitored with CVSM sensors in general wards. Peer-reviewed evidence and white papers on the official websites of CVSM solutions were also included. AI classification was based on standard definitions of simple AI, as systems with no memory or learning capabilities, and advanced AI, as systems with the ability to learn from past data to make decisions. Only studies evaluating CVSM algorithms for improving or predicting clinical outcomes (e.g., adverse events, intensive care unit admission, mortality) or optimizing alarm thresholds were included. We assessed the promised level of AI for each CVSM solution based on statements from the official product websites. In total, 467 studies were assessed; 113 were retrieved for full-text review, and 26 studies on four different CVSM solutions were included. Advanced AI levels were indicated on the websites of all four CVSM solutions. Five studies assessed algorithms with potential for applications as advanced AI algorithms in two of the CVSM solutions (50%), while 21 studies assessed algorithms with potential as simple AI in all four CVSM solutions (100%). Evidence on algorithms for advanced AI in CVSM is limited, revealing a discrepancy between promised AI levels and current algorithm capabilities.

Feasibility of Monitoring Heart and Respiratory Rates Using Nonwearable Devices and Consistency of the Measured Parameters: Pilot Feasibility Study.

As Japan is the world's fastest-aging society with a declining population, it is challenging to secure human resources for care providers. Therefore, the Japanese government is promoting digital transformation and the use of nursing care equipment, including nonwearable devices that monitor heart and respiratory rates. However, the feasibility of monitoring heart and respiratory rates with nonwearable devices and the consistency of the rates measured have not been reported. In this study, we focused on a sheet-type nonwearable device (Safety Sheep Sensor) introduced in many nursing homes. We evaluated the feasibility of monitoring heart rate (HR) and respiratory rate (RR) continuously using nonwearable devices and the consistency of the HR and RR measured. A sheet-type nonwearable device that measured HR and RR every minute through body vibrations was placed under the mattress of each participant. The participants in study 1 were healthy individuals aged 20-60 years (n=21), while those in study 2 were older adults living in multidwelling houses and required nursing care (n=20). The HR was measured using standard methods by the nurse and using the wearable device (Silmee Bar-type Lite sensor), and RR was measured by the nurse. The primary outcome was the mean difference in HR and RR between nonwearable devices and standard methods. The mean difference in HR was -0.32 (SD 3.12) in study 1 and 0.04 (SD: 3.98) in study 2; both the differences were within the predefined accepted discrepancies (<5 beats/min). The mean difference in RR was -0.98 (SD 3.01) in study 1 and -0.49 (SD 2.40) in study 2; both the differences were within the predefined accepted discrepancies (3 breaths/min). HR and RR measurements obtained using the nonwearable devices and the standard method were similar. Continuous monitoring of vital signs using nonwearable devices can aid in the early detection of abnormal conditions in older people.

Wearable network for multilevel physical fatigue prediction in manufacturing workers.

Manufacturing workers face prolonged strenuous physical activities, impacting both financial aspects and their health due to work-related fatigue. Continuously monitoring physical fatigue and providing meaningful feedback is crucial to mitigating human and monetary losses in manufacturing workplaces. This study introduces a novel application of multimodal wearable sensors and machine learning techniques to quantify physical fatigue and tackle the challenges of real-time monitoring on the factory floor. Unlike past studies that view fatigue as a dichotomous variable, our central formulation revolves around the ability to predict multilevel fatigue, providing a more nuanced understanding of the subject's physical state. Our multimodal sensing framework is designed for continuous monitoring of vital signs, including heart rate, heart rate variability, skin temperature, and more, as well as locomotive signs by employing inertial motion units strategically placed at six locations on the upper body. This comprehensive sensor placement allows us to capture detailed data from both the torso and arms, surpassing the capabilities of single-point data collection methods. We developed an innovative asymmetric loss function for our machine learning model, which enhances prediction accuracy for numerical fatigue levels and supports real-time inference. We collected data on 43 subjects following an authentic manufacturing protocol and logged their self-reported fatigue. Based on the analysis, we provide insights into our multilevel fatigue monitoring system and discuss results from an in-the-wild evaluation of actual operators on the factory floor. This study demonstrates our system's practical applicability and contributes a valuable open-access database for future research.

Design and Development of an IoT-Based Embedded System for Continuous Monitoring of Vital Signs

Design and Development of an IoT-Based Embedded System for Continuous Monitoring of Vital Signs

Penetrating Barriers: Noncontact Measurement of Vital Bio Signs Using Radio Frequency Technology.

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient's physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject's condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient's physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health.

Sedative effects of propofol and risk factors for excessive sedation in the endoscopic treatment of biliary and pancreatic diseases.

The safety and effectiveness of propofol in more complex endoscopic procedures, such as endoscopic retrograde cholangiopancreatography, remain unknown. Thus, we aimed to evaluate propofol sedation during endoscopic cholangiopancreatography, ultrasound-guided intervention, and gastroduodenal stenting and examine risk factors for excessive sedation. We retrospectively analyzed data from 870 patients who underwent endoscopic treatment with propofol sedation for biliary and pancreatic disease between October 2020 and September 2021. Sedation included propofol and fentanyl, with continuous monitoring of vital signs and the bispectral index. The assessed risk factors included age, complications, body mass index, treatment duration, and specialty. Distal bile duct treatment (n = 367), hilar bile duct treatment (n = 197), post-small-intestinal reconstruction treatment (n = 75), endoscopic ultrasound-guided intervention (n = 140), and gastrointestinal obstruction treatment (n = 91) were performed. The rates of excessive sedation, hypoxemia, and hypotension were 7.8%, 6.0%, and 1.8%, respectively. Post-small-intestinal reconstruction treatment had the highest incidence rate of excessive sedation (16%), whereas endoscopic ultrasound-guided intervention had the lowest incidence rate (4.3%). Multivariate analysis revealed significant associations between excessive sedation and comorbid sleep apnea, obesity, and prolonged procedural time. Obesity, sleep apnea syndrome, and prolonged procedure time are risk factors for excessive sedation related to propofol use. Thus, sedation techniques should be tailored for these patients.

Early detection of deteriorating patients in general wards through continuous contactless vital signs monitoring.

To assess the efficacy of continuous contactless vital signs monitoring with an automated Early Warning System (EWS) in detecting clinical deterioration among patients in general wards. A prospective observational cohort study was conducted in the medical unit of a tertiary care hospital in India, involving 706 patients over 84,448 monitoring hours. The study used a contactless ballistocardiography system (Dozee system) to continuously monitor heart rate, respiratory rate, and blood pressure. The study assessed total, mean, and median alerts at 24, 48, 72, 96, 120 h, and length of stay (LOS) before patient deterioration or discharge. It analyzed alert sensitivity and specificity, average time from initial alert to deterioration, and healthcare practitioners (HCP) activity. Study was registered with the Clinical Trials Registry-India CTRI/2022/10/046404. Out of 706 patients, 33 (5%) experienced clinical deterioration, while 673 (95%) did not. The deterioration group consistently had a higher number of alerts compared to those who were discharged normally, across all time-points. On average, the time between the initial alert and clinical deterioration was 16 h within the last 24 h preceding the event. The sensitivity of the Dozee-EWS varied between 67% and 94%. HCP spend 10% of their time on vital signs check and documentation. This study suggests that utilizing contactless continuous vital signs monitoring with Dozee-EWS in general ward holds promise for enhancing the early detection of clinical deterioration. Further research is essential to evaluate the effectiveness across a wider range of clinical settings.

Embedding Ethics in the Implementation of a Vital Sign Monitoring Technology.

The implementation of wireless continuous vital sign monitoring (CVSM) technologies changes daily care practices of healthcare professionals, which gives rise to unknown new roles and responsibilities. In this paper we present a study on how we combine the disciplines of medical informatics and ethics in the implementation of the Philips Healthdot, a smart patch for remote CVSM. The aim of this study is to investigate experiences and perspectives on the support levels and roles and responsibilities associated with the integration of smart patches, by conducting interviews with nurses. This interdisciplinary study gives insights into the technological, organizational, and ethical concerns surrounding the implementation of CVSM in healthcare. The findings and analytical approach may provide valuable insights for researching the appropriate implementation of digital health technologies.

Quality of Electrocardiography Recorded with Consumer Smart Shirts.

Smart wearables support continuous monitoring of vital signs for early detection of deteriorating health. However, the devices and sensors require sufficient quality to produce meaningful signals, in particular, if data is acquired in motion. In this study, we equipped 48 subjects with smart shirts recording one-lead electrocardiography (ECG), thoracic and abdominal respiratory inductance plethysmography, and three-axis acceleration. For 10 min each, the subjects sit, stand, walk, and run, with a resting period of 5 min in between each activity. We preprocessed the electrocardiogram and applied a signal quality index. We analyzed the signal quality index grouped by the activity and participants. For sitting, standing, walking, and running, the ECG signals provide acceptable quality over 73.20 %, 91.85 %, 12.26 %, and 13.14 % of the recording time. In conclusion, smart wearables may be useful for continuous health monitoring of people with a sedentary lifestyle, but rather not for sportive activities.

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

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

Continuous early warning score calculations can facilitate the evaluation of the condition of patients developing anastomotic leak or infection after esophageal and pancreatic resection; a cohort study

BackgroundEarly diagnosis of anastomotic leak is challenging due to its heterogeneous clinical presentation. Continuous vital sign monitoring compared to periodic monitoring has potential to expedite anastomotic leak diagnosis. The aim is to assess this potential after esophageal and pancreatic cancer resection. MethodsIn this data modelling cohort study vital signs were continuously monitored and periodically recorded according to EWS protocol. We retrospectively calculated EWSs every one minute using continuous vital sign data. The percentage of patients having an EWS-alarm in 24 hours preceding an anastomotic leak, the elapsed time between the first alarm and diagnosis were compared between regular periodic nurse EWSs and the continuously calculated EWSs. These data were also compared to those of patients with other infectious complications and controls without complications. ResultsOne hundred ninety patients were included, twenty-six with an anastomotic leak (14%), thirty-six with an infectious complication (19%) and one hundred twenty-eight controls (67%). The time between the first continuous EWS-alarm and anastomotic leak was 23 hours [IQR 19-24] compared to 3hrs [IQR 2-13] with periodic alarms. Sixty-two percent of leak patients had at least one continuous alarm in the 24 hours before the event, compared to 15% for periodic EWS (p<.001). More patients with infections had a continuous alarm compared to anastomotic leak patients (86% vs. 62%, p=.026). Postoperative alarms in both groups were more frequent compared to controls. ConclusionAfter esophageal and pancreatic resections, continuous monitoring alarms earlier and more frequently than periodic monitoring before anastomotic leak diagnosis. However, combination with several other diagnostic modalities seems required for the definite diagnosis.

INTENSIVE TREATMENT OF SEPTIC SHOCK IN PEDIATRIC PRACTICE

In pediatric practice, septic shock (SS) is a serious, urgent condition with a high incidence and increased risk of death. Intensive therapy in this condition is based on provision of volume-expansion fluid management, prescription of antibiotic medications, and vasopressor support. Urgent care for children is provided in an intensive care unit and includes mandatory determination of the aetiology of SS (by inoculation of blood samples for sterility), provision of venous access and continuous monitoring of vital signs with measurement of lactate levels. The intensity of respiratory support changes according to the following stepwise logic: oxygen therapy – non-invasive ventilation – mechanical ventilation. When providing fluid management to a patient with SS, preference is given to crystalloid solutions. Antibacterial therapy is devised empirically and must be administered within the first hour of ICU admission. If fluid management proves insufficient to ensure stable hemodynamic parameters, vasopressor support is provided by administering inotropic agents, vasodilators and inodilators (norepinephrine, epinephrine, dopamine and dobutamine). Evidence on the effectiveness of corticosteroids in children and adolescents with SS is lacking. Knowledge of the latest algorithms of intensive treatment of SS in pediatric practice will enhance the quality of care and improve the therapeutic prognosis in this category of patients.