Continuous monitoring of vital signs with the Everion biosensor on the surgical ward: a clinical validation study

Background: ICU is the costly part of the hospital that has functional approach for patients who have reversible conditions so it needs mechanical ventilation and other special services. Some patients are not really in need of special care only the continuous monitoring of vital signs needs of the public sector. Patients with good condition or End-Stage were not candidate to admitting in ICU. The aim of this study was to evaluate indications of admitting patients in internal ICU and the rate of mortality in Emam Khomeini hospital in 2013.Methods: The study was conducted retrospectively evaluated the records of patients hospitalized in ICU and disease prognosis and treatment of disease and APACHE2 criteria was analyses.Results: The mean age of patients in the study was 61.05±19.81. Of 118 patients, 70 (59.3%) survived and 48 (40.7%) patients died. APACHE2 mean in the study was 21.46±7.5. GCS average was 9.83±4.27. There was correlation between mortality of patients and type of disease. In this study in APACHE2 score between 25-29 and >35 in mortality rate we are higher than standard average and in 10-14 and 20-24 we are lower than standard average.Conclusions: This study shows that GCS is not a good measure for the evaluation of patients hospitalized in internal ICU. In the present study, patients with higher APACHE2 score of 35 died. That show hospitalization that patient in ICU has no difference in the prognosis of them. As regards mortality rate in ICU patients in this study has no significant difference with predicted APACHE values, indications of ICU admition in Emam Khomeini hospital observed exactly.

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Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review

Journal of Medical Internet Research ◽

10.2196/18636 ◽

2020 ◽

Vol 22 (6) ◽

pp. e18636 ◽

Cited By ~ 4

Author(s):

Jobbe P L Leenen ◽

Crista Leerentveld ◽

Joris D van Dijk ◽

Henderik L van Westreenen ◽

Lisette Schoonhoven ◽

...

Keyword(s):

Systematic Review ◽

Health Care ◽

Clinical Outcomes ◽

Health Care Professionals ◽

Continuous Monitoring ◽

Vital Signs ◽

Current Evidence ◽

Cochrane Central Register ◽

Wireless Devices

Background Continuous monitoring of vital signs by using wearable wireless devices may allow for timely detection of clinical deterioration in patients in general wards in comparison to detection by standard intermittent vital signs measurements. A large number of studies on many different wearable devices have been reported in recent years, but a systematic review is not yet available to date. Objective The aim of this study was to provide a systematic review for health care professionals regarding the current evidence about the validation, feasibility, clinical outcomes, and costs of wearable wireless devices for continuous monitoring of vital signs. Methods A systematic and comprehensive search was performed using PubMed/MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 2009 to September 2019 for studies that evaluated wearable wireless devices for continuous monitoring of vital signs in adults. Outcomes were structured by validation, feasibility, clinical outcomes, and costs. Risk of bias was determined by using the Mixed Methods Appraisal Tool, quality assessment of diagnostic accuracy studies 2nd edition, or quality of health economic studies tool. Results In this review, 27 studies evaluating 13 different wearable wireless devices were included. These studies predominantly evaluated the validation or the feasibility outcomes of these devices. Only a few studies reported the clinical outcomes with these devices and they did not report a significantly better clinical outcome than the standard tools used for measuring vital signs. Cost outcomes were not reported in any study. The quality of the included studies was predominantly rated as low or moderate. Conclusions Wearable wireless continuous monitoring devices are mostly still in the clinical validation and feasibility testing phases. To date, there are no high quality large well-controlled studies of wearable wireless devices available that show a significant clinical benefit or cost-effectiveness. Such studies are needed to help health care professionals and administrators in their decision making regarding implementation of these devices on a large scale in clinical practice or in-home monitoring.

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Continuous monitoring of cerebrovascular autoregulation: a validation study

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp.72.5.583 ◽

2002 ◽

Vol 72 (5) ◽

pp. 583-586 ◽

Cited By ~ 82

Author(s):

E W Lang

Keyword(s):

Validation Study ◽

Continuous Monitoring ◽

Cerebrovascular Autoregulation

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406 Clinical Validation of AI Scoring in Adult and Pediatric Clinical PSG Samples Compared to Prospective, Double-Blind Scoring Panel

SLEEP ◽

10.1093/sleep/zsab072.405 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A161-A161

Author(s):

Chris Fernandez ◽

Sam Rusk ◽

Nick Glattard ◽

Yoav Nygate ◽

Fred Turkington ◽

...

Keyword(s):

Validation Study ◽

Periodic Breathing ◽

Sleep Stages ◽

Clinical Validation ◽

Double Blind ◽

Adult Age ◽

Public Data ◽

Patient Reported ◽

Funding Opportunities ◽

Sensitivity Specificity

Abstract Introduction Despite an appreciable rise in sleep wellness and sleep medicine A.I. research publications, public data corpuses, institutional support, and health A.I. research funding opportunities, the availability of controlled-retrospective, hybrid-retrospective-prospective, and prospective-RCT quality clinical validation study evidence is limited with respect to their potential clinical impact. Furthermore, only a few practical examples of A.I. technologies are validated, in use today clinically, and widely adopted, to assist in sleep diagnoses and treatment. In this study, we contribute to this growing body of clinical A.I. validation evidence and experimental design methodologies with an interoperable A.I. scoring engine in Adult and Pediatric populations. Methods Stratified random sampling with proportionate allocation was applied to a database of N>10,000 retrospective diagnostic clinical polysomnography (PSG), selected by evidence grading standards, with controls applied for OSA severity, diagnoses; sleep, psychiatric, neurologic, neurodevelopmental, cardiac, pulmonary, metabolic disorders, medications; benzodiazepines, antidepressants, stimulants, opiates, sleep aids, demographic groups of interest; sex, adult age, pediatric age, BMI, weight, height, and patient-reported sleepiness, to establish representative N=100 Adult and N=100 Pediatric samples. Double Blinded scoring was prospectively collected for each sample by 3 experienced RPSGT certified sleep technologists randomized from a pool of 9 scorers. Sensitivity (PA), Specificity (NA), Accuracy (OA), Kappa (K), and 95% Bootstrap CI’s are presented for sleep stages, OSA/CSA, hypopnea 3%/4%, arousals, limb movements, Cheyenne-Stokes respiration, periodic breathing, atrial fibrillation, and other events, and normative, mild, moderate, and severe OSA categories for global-AHI and REM-AHI. Results for Sleep Staging and OSA Severity Diagnostic Accuracy are summarized. Results A.I. scoring performance meet but in most cases exceeded initial clinical validation study (N=72 Adults, 2017) PA, NA, OA, K point-estimates and confidence-interval results for the 26 event types and 8 AHI-categories evaluated. The Adult sample showed 87%/94% Sensitivity/Specificity across all stages (Wake/N1/N2/N3/REM) and 94%/96% Sensitivity/Specificity for AHI>=15. The Pediatric sample showed 87%/93% Sensitivity/Specificity staging, 89%/98% Sensitivity/Specificity AHI>=15. Observed Accuracy was >90% for Adults and Pediatrics all 26 events and 7 AHI-categories analyzed, except REM-AHI>=5 (85%/82% Adults/Pediatrics). Conclusion We provide clinical validation evidence that demonstrates interoperable A.I. scoring performance in representative Adult and Pediatric patient clinical PSG samples when compared to prospective, double-blind scoring panel. Support (if any):

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Intelligent Bed Sheet Detects Respiratory Patterns

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931218621271 ◽

2018 ◽

Vol 62 (1) ◽

pp. 1177-1181 ◽

Cited By ~ 1

Author(s):

Laura Nicholson ◽

Olivia Lin ◽

Edward Shim

Keyword(s):

Continuous Monitoring ◽

Resource Constraints ◽

New Technology ◽

Vital Signs ◽

The Body ◽

Second Phase ◽

Age In Place ◽

Sensor Validation ◽

Health Canada ◽

Respiratory Conditions

A new technology using an intelligent bed sheet made of fabric sensors is described as a novel advancement that supports wireless and continuous monitoring of vital signs without requiring wire attachments to the body. The intelligent bed sheet developed by Studio 1 Labs Inc. (Studio 1 Labs), can be used to support three distinct groups: i) healthcare institutions with human resource constraints, ii) caregivers who provide care for seniors, infants and children at home, and iii) independent seniors who prefer to age in place. This article describes two complementary research phases using the intelligent bed sheet to detect heart rate, respiratory rate, and respiratory effort. The first phase explores sensor validation from the intelligent bed sheet with preset respiratory conditions from high technology mannequins. The second phase involves a use case with healthy young adults comparing between physiological signals from the bed sheet with standard nursing protocols of manual counts and a pulse oximeter approved by Health Canada.

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Review: Continuous Monitoring to Detect Failure to Rescue in Adult Postoperative Inpatients

Biomedical Instrumentation & Technology ◽

10.2345/0899-8205-52.4.281 ◽

2018 ◽

Vol 52 (4) ◽

pp. 281-287 ◽

Cited By ~ 1

Author(s):

Sue Carol Verrillo ◽

Bradford D. Winters

Keyword(s):

Vital Sign ◽

Sleep Disordered Breathing ◽

Continuous Monitoring ◽

Vital Signs ◽

Clinical Deterioration ◽

Failure To Rescue ◽

Contributing Factors ◽

Unexpected Death ◽

Practice Model ◽

Preventable Complication

Abstract Failure to rescue, or the unexpected death of a patient due to a preventable complication, is a nationally documented problem with numerous and multifaceted contributing factors. These factors include the frequency and method of collecting vital sign data, response to abnormal vital signs, and delays in the escalation of care for general ward patients who are showing signs of clinical deterioration. Patients' clinical deterioration can be complicated by concurrent secondary factors, including opioid abuse/dependence, being uninsured, or having sleep-disordered breathing. Using the Johns Hopkins Nursing Evidence-Based Practice Model, this integrative review synthesizes 43 research and nonresearch sources of evidence. Published between 2001 and 2017, these sources of evidence focus on failure to rescue, the multifaceted contributing factors to failure to rescue, and how continuous vital sign monitoring could ameliorate failure to rescue and its causes. Recommendations from the sources of evidence have been divided into system, structural, or technological categories.

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