scholarly journals Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients

2020 ◽  
Vol 132 (3) ◽  
pp. 424-439 ◽  
Author(s):  
Martine J. M. Breteler ◽  
Eline J. KleinJan ◽  
Daan A. J. Dohmen ◽  
Luke P. H. Leenen ◽  
Richard van Hillegersberg ◽  
...  
Keyword(s):  
High Risk ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Surgical Patients ◽  
Major Surgery ◽  
Data Loss ◽  
Limits Of Agreement ◽  
Correct Treatment ◽  
Patient Deterioration ◽  
Vital Signs Monitoring

Abstract Background Vital signs are usually recorded once every 8 h in patients at the hospital ward. Early signs of deterioration may therefore be missed. Wireless sensors have been developed that may capture patient deterioration earlier. The objective of this study was to determine whether two wearable patch sensors (SensiumVitals [Sensium Healthcare Ltd., United Kingdom] and HealthPatch [VitalConnect, USA]), a bed-based system (EarlySense [EarlySense Ltd., Israel]), and a patient-worn monitor (Masimo Radius-7 [Masimo Corporation, USA]) can reliably measure heart rate (HR) and respiratory rate (RR) continuously in patients recovering from major surgery. Methods In an observational method comparison study, HR and RR of high-risk surgical patients admitted to a step-down unit were simultaneously recorded with the devices under test and compared with an intensive care unit–grade monitoring system (XPREZZON [Spacelabs Healthcare, USA]) until transition to the ward. Outcome measures were 95% limits of agreement and bias. Clarke Error Grid analysis was performed to assess the ability to assist with correct treatment decisions. In addition, data loss and duration of data gaps were analyzed. Results Twenty-five high-risk surgical patients were included. More than 700 h of data were available for analysis. For HR, bias and limits of agreement were 1.0 (–6.3, 8.4), 1.3 (–0.5, 3.3), –1.4 (–5.1, 2.3), and –0.4 (–4.0, 3.1) for SensiumVitals, HealthPatch, EarlySense, and Masimo, respectively. For RR, these values were –0.8 (–7.4, 5.6), 0.4 (–3.9, 4.7), and 0.2 (–4.7, 4.4) respectively. HealthPatch overestimated RR, with a bias of 4.4 (limits: –4.4 to 13.3) breaths/minute. Data loss from wireless transmission varied from 13% (83 of 633 h) to 34% (122 of 360 h) for RR and 6% (47 of 727 h) to 27% (182 of 664 h) for HR. Conclusions All sensors were highly accurate for HR. For RR, the EarlySense, SensiumVitals sensor, and Masimo Radius-7 were reasonably accurate for RR. The accuracy for RR of the HealthPatch sensor was outside acceptable limits. Trend monitoring with wearable sensors could be valuable to timely detect patient deterioration. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

scholarly journals Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e020162 ◽  
Author(s):  
Martine J M Breteler ◽  
Erik Huizinga ◽  
Kim van Loon ◽  
Luke P H Leenen ◽  
Daan A J Dohmen ◽  
...  
Keyword(s):  
Heart Rate ◽  
High Risk ◽  
Outcome Measures ◽  
Vital Signs ◽  
Wireless Sensor ◽  
Surgical Patients ◽  
Data Loss ◽  
Limits Of Agreement ◽  
Patient Deterioration ◽  
Step Down

Background and objectivesIntermittent vital signs measurements are the current standard on hospital wards, typically recorded once every 8 hours. Early signs of deterioration may therefore be missed. Recent innovations have resulted in ‘wearable’ sensors, which may capture patient deterioration at an earlier stage. The objective of this study was to determine whether a wireless ‘patch’ sensor is able to reliably measure respiratory and heart rate continuously in high-risk surgical patients. The secondary objective was to explore the potential of the wireless sensor to serve as a safety monitor.DesignIn an observational methods comparisons study, patients were measured with both the wireless sensor and bedside routine standard for at least 24 hours.SettingUniversity teaching hospital, single centre.ParticipantsTwenty-five postoperative surgical patients admitted to a step-down unit.Outcome measuresPrimary outcome measures were limits of agreement and bias of heart rate and respiratory rate. Secondary outcome measures were sensor reliability, defined as time until first occurrence of data loss.Results1568 hours of vital signs data were analysed. Bias and 95% limits of agreement for heart rate were −1.1 (−8.8 to 6.5) beats per minute. For respiration rate, bias was −2.3 breaths per minute with wide limits of agreement (−15.8 to 11.2 breaths per minute). Median filtering over a 15 min period improved limits of agreement of both respiration and heart rate. 63% of the measurements were performed without data loss greater than 2 min. Overall data loss was limited (6% of time).ConclusionsThe wireless sensor is capable of accurately measuring heart rate, but accuracy for respiratory rate was outside acceptable limits. Remote monitoring has the potential to contribute to early recognition of physiological decline in high-risk patients. Future studies should focus on the ability to detect patient deterioration on low care environments and at home after discharge.

scholarly journals Reliability of a wearable wireless patch for continuous remote monitoring of vital signs in patients recovering from major surgery: a clinical validation study from the TRaCINg trial

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e031150 ◽  
Author(s):  
Candice Downey ◽  
Shu Ng ◽  
David Jayne ◽  
David Wong
Keyword(s):  
Monitoring System ◽  
Vital Sign ◽  
Vital Signs ◽  
University Hospital ◽  
Secondary Outcome ◽  
Major Surgery ◽  
Limits Of Agreement ◽  
Temperature Bias ◽  
Vital Signs Monitoring ◽  
Recorded Data

ObjectiveTo validate whether a wearable remote vital signs monitor could accurately measure heart rate (HR), respiratory rate (RR) and temperature in a postsurgical patient population at high risk of complications.DesignManually recorded vital signs data were paired with vital signs data derived from the remote monitor set in patients participating in the Trial of Remote versus Continuous INtermittent monitoring (TRaCINg) study: a trial of continuous remote vital signs monitoring.SettingSt James’s University Hospital, UK.Participants51 patients who had undergone major elective general surgery.InterventionsThe intervention was the SensiumVitals monitoring system. This is a wireless patch worn on the patient’s chest that measures HR, RR and temperature continuously. The reference standard was nurse-measured manually recorded vital signs.Primary and secondary outcome measuresThe primary outcomes were the 95% limits of agreement between manually recorded and wearable patch vital sign recordings of HR, RR and temperature. The secondary outcomes were the percentage completeness of vital sign patch data for each vital sign.Results1135 nurse observations were available for analysis. There was no clinically meaningful bias in HR (1.85 bpm), but precision was poor (95% limits of agreement −23.92 to 20.22 bpm). Agreement was poor for RR (bias 2.93 breaths per minute, 95% limits of agreement −8.19 to 14.05 breaths per minute) and temperature (bias 0.82°C, 95% limits of agreement −1.13°C to 2.78°C). Vital sign patch data completeness was 72.8% for temperature, 59.2% for HR and 34.1% for RR. Distributions of RR in manually recorded measurements were clinically implausible.ConclusionsThe continuous monitoring system did not reliably provide HR consistent with nurse measurements. The accuracy of RR and temperature was outside of acceptable limits. Limitations of the system could potentially be overcome through better signal processing. While acknowledging the time pressures placed on nursing staff, inaccuracies in the manually recorded data present an opportunity to increase awareness about the importance of manual observations, particularly with regard to methods of manual HR and RR measurements.

Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

2021 ◽  
Author(s):  
Yu Gu ◽  
Xiang Zhang ◽  
Huan Yan ◽  
Zhi Liu ◽  
Fuji Ren
Keyword(s):  
Real Time ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Implementation Process ◽  
Sleep Monitoring ◽  
Daily Lives ◽  
Vital Signs Monitoring ◽  
Quality Sleep ◽  
Enhancement Method ◽  
Positioning Algorithm

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.

scholarly journals Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

2021 ◽  
Author(s):  
Yu Gu ◽  
Xiang Zhang ◽  
Huan Yan ◽  
Zhi Liu ◽  
Fuji Ren
Keyword(s):  
Real Time ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Implementation Process ◽  
Sleep Monitoring ◽  
Daily Lives ◽  
Vital Signs Monitoring ◽  
Quality Sleep ◽  
Enhancement Method ◽  
Positioning Algorithm

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.

scholarly journals Current concepts of perioperative monitoring in high-risk surgical patients: a review

2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Paolo Aseni ◽  
Stefano Orsenigo ◽  
Enrico Storti ◽  
Marco Pulici ◽  
Sergio Arlati
Keyword(s):  
High Risk ◽  
Clinical Evaluation ◽  
Hemodynamic Monitoring ◽  
Perioperative Complications ◽  
Surgical Patients ◽  
Major Surgery ◽  
Main Task ◽  
Evaluation Tool ◽  
Non Invasive ◽  
Number Of Patients

Abstract A substantial number of patients are at high-risk of intra- or post-operative complications or both. Most perioperative deaths are represented by patients who present insufficient physiological reserve to meet the demands of major surgery. Recognition and management of critical high-risk surgical patients require dedicated and effective teams, capable of preventing, recognize, start treatment with adequate support in time to refer patients to the satisfactory ICU level provision. The main task for health-care planners and managers is to identify and reduce this severe risk and to encourage patient’s safety practices. Inadequate tissue perfusion and decreased cellular oxygenation due to hypovolemia, heart dysfunction, reduced cardiovascular reserve, and concomitant diseases are the most common causes of perioperative complications. Hemodynamic, respiratory and careful sequential monitoring have become essential aspects of the clinical practice both for surgeons and intensivists. New monitoring techniques have changed significantly over the past few years and are now able to rapidly identify shock states earlier, define the etiology, and monitor the response to different therapies. Many of these techniques are now minimally invasive or non-invasive. Advanced hemodynamic and respiratory monitoring combines invasive, non-invasive monitoring skills. Non-invasive ultrasound has emerged during the last years as an essential operative and perioperative evaluation tool, and its use is now rapidly growing. Perioperative management guided by appropriate sequential clinical evaluation combined with respiratory and hemodynamic monitoring is an established tool to help clinicians to identify those patients at higher risk in the attempt to reduce the complications rate and potentially improve patient outcomes. This review aims to provide an update of currently available standard concepts and evolving technologies of the various respiratory and hemodynamic monitoring systems for the high-risk surgical patients, highlighting their potential usefulness when integrated with careful clinical evaluation.

scholarly journals Referral of Surgical Patients to an Anaesthetic Clinic: A Decision-making Analysis

1994 ◽  
Vol 22 (5) ◽  
pp. 562-567 ◽  
Author(s):  
A. Lee ◽  
M. E. Lum ◽  
K. M. Hillman ◽  
A. Bauman
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
High Risk ◽  
Surgical Patients ◽  
Major Surgery ◽  
Relative Importance ◽  
Medical Problems ◽  
Effective Utilization ◽  
Professional Groups ◽  
History Of

Effective utilization of an anaesthetic clinic depends on appropriate referral of high-risk surgical patients. The decision-making behaviour of anaesthetists and nurses was examined to identify factors that influence the referral of patients to an outpatient anaesthetic clinic. Eleven consultant anaesthetists, seven anaesthetic trainees and sixteen nurses working in anaesthetic areas estimated the likelihood that they would refer patients for each of the 30 scenarios presented. The relative importance of each factor influencing the decision to refer as determined by the 34 participants were: type of procedure (22%), co-morbidities (18%), fitness (13%), history of anaesthetic problems (12%), medications (11%), age (10%), obesity (8%) and anxiety (6%). Indicative risk factors identified were aged 65 years or over, unable to climb more than two flights of stairs, presence of significant medical problems, gross obesity, history of anaesthetic problems, taking regular medications, scheduled for major surgery and expressed anxiety about the anaesthetic. There were large variations in the decision-making behaviour among health professional groups.

scholarly journals Patient perspectives of wearable sensors: a mixed methods evaluation (Preprint)

2020 ◽  
Author(s):  
Meera Joshi ◽  
Stephanie Archer ◽  
Abigail Morbi ◽  
Sonal Arora ◽  
Richard Kwasnicki ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Surgical Patients ◽  
Sensor Technology ◽  
Patient Questionnaire ◽  
Continuous Variables ◽  
Wearable Sensor ◽  
Structured Interviews ◽  
Patient Deterioration ◽  
Mixed Methods Evaluation ◽  
Interview Studies

BACKGROUND Continuous vital sign monitoring using wearable sensors may enable earlier detection of patient deterioration and sepsis. OBJECTIVE To explore patient experiences of wearable sensor technology and continuous monitoring through questionnaire and interview studies. METHODS All patients recruited for a wearable sensor study were asked to complete a study questionnaire. Patients were asked 9 questions with answers on Likert scale and scores were treated as continuous variables. A subgroup of surgical patients wearing the wearable sensor were invited to take part in semi-structured interviews. All interview data was analysed using thematic analysis. RESULTS A total of 453 patients completed the patient questionnaire (90.6% response rate). A high proportion of patients agreed the wearable sensor was comfortable to wear (n=427, 85.4%), they would wear the patch again when in hospital (n=429, 85.8%) and they would wear the wearable patch at home (n=398, 79.6%). Twelve surgical patients consented to interviews. Five main themes of interest to patients emerged from the interviews; 1) Centralised monitoring 2) enhanced feelings of patient safety, 3) impact on nursing staff 4) comfort & usability and 5) the future and views on technology. CONCLUSIONS Overall, the feedback from patients using wearable monitoring was strongly positive with relatively few concerns raised. Patients feel wearable sensors improve their sense of safety, may relieve pressure on healthcare staff and are a welcome part of future healthcare

Risk of Recurrence of Venous Thromboembolism After Major Surgery for Cancer,

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3342-3342
Author(s):  
Aurelien Delluc ◽  
Patrice Crenn ◽  
Emmanuelle Le Moigne ◽  
Francis Couturaud ◽  
Gregoire Le Gal ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
High Risk ◽  
Cancer Patients ◽  
Conflicts Of Interest ◽  
Lower Limbs ◽  
Surgical Patients ◽  
Cancer Site ◽  
Major Surgery ◽  
Cumulative Probability ◽  
Risk Of Recurrence

Abstract Abstract 3342 Background: In patients with venous thromboembolism (VTE) provoked by major surgery, the risk of recurrence is low during and after the anticoagulation period. Conversely, cancer patients with VTE have a very high risk of VTE recurrence even under anticoagulant therapy. Some cancer patients develop VTE within three months following surgical treatment of their malignancy. It is unknown whether these patients have a low risk of recurrence of VTE, or if they have the high risk of recurrence associated with cancer. Methods: We analyzed data of a single center cohort study conducted at the Brest University Hospital, France. All consecutive cancer patients with pulmonary embolism and/or deep vein thrombosis of the lower limbs diagnosed between January 2000 and July 2009 in our center were followed-up for VTE recurrence. Patients were classified as “surgical” patients if they had major surgery for cancer in the three months before VTE. Probabilities of recurrence of VTE in surgical patients and in non-surgical patients were estimated according to Kaplan-Meier method and were compared by log-rank test. Hazard Ratios (HR) for VTE recurrence and 95% confidence intervals (CI) were obtained using Cox proportional hazard regression models with adjustments on age, sex, past history of VTE, cancer site, and metastases. Results: We followed 220 cancer patients with symptomatic VTE (mean age 69.9 ± 11.0 years, male sex n=127 (57.7%)). Of these patients, 42 (19.1%) had major surgery for cancer three months before the index VTE and 178 (80.9%) were non-surgical cancer patients. Surgical patients were more often men (30/42 (71.4%) vs. 97/178 (54.5%), p=0.05) and had less metastases at baseline (7/42 (16.7%) vs. 61/178 (34.3%), p=0.03) than non-surgical patients. Mean age was not different between surgical and non-surgical patients (70.1±10.5 vs. 69.8±11.2, p=0.90). Most surgical patients discontinued anticoagulation after six months of treatment, whereas non-surgical patients were receiving long term anticoagulation. At two years, 29 patients had a recurrence of VTE (2/44 surgical patients and 27/180 non-surgical patients). The cumulative probability of recurrence of VTE was lower in surgical patients than in non-surgical patients (2.8% (95% CI −2.5 to 8.1) vs. 11.3% (95% CI 5.8 to 16.8) at 6 months (p=0.14), 3.0% (95% CI −2.3 to 8.3) vs. 16.2% (95% CI 9.3 to 23.1) at 1 year (p=0.06), and 9.3% (95% CI −4.0 to 22.6) vs. 27.5% (95% CI 18. To 36.9) at 2 years (p=0.04)). At two years, the adjusted hazard ratio for recurrence of VTE was 0.20 (95% CI 0.05 to 0.91) in surgical patients compared with non-surgical cancer patients. There was a trend for a lower cumulative probability of death in surgical patients than in non-surgical patients after two years of follow-up (40.2% (95% CI 23.0 to 57.4) vs. 57.7% (95% CI 49.5 to 65.9), p=0.06). Conclusion: In this study, patients with cancer who develop VTE after major cancer surgery had a lower risk of recurrence of VTE than non-surgical cancer patients. Disclosures: No relevant conflicts of interest to declare.

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