2017 Scientific Session of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) Houston, Texas, USA, 22–25 March 2017

doi:10.1007/s00464-017-5445-9

Cited by 4 publications

(2 citation statements)

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“…A total of 10 distinct smart shirts were utilized, with Hexoskin being the most prevalent. These studies used the data collected by smart shirts for various purposes, such as quantifying stress through heart rate variability (HRV) data in medical personnel and identifying early physiological markers that preceded self-injurious behavior in individuals with intellectual disabilities [35,82,96]. More observational research such as these is required to explore the implementation of smart shirts in live settings and make practical use of the data collected through its processing and analysis.…”

Section: Principal Findingsmentioning

confidence: 99%

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

Khundaqji

Hing

Furness

et al. 2020

JMIR Mhealth Uhealth

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Background The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings. Objective This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures. Methods A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported. Results Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5%), followed by validation (29/101, 28.7%), observational studies (21/101, 20.8%), and reviews (1/101, 0.1%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients. Conclusions Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.

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Section: Principal Findingsmentioning

confidence: 99%

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

Khundaqji

Hing

Furness

et al. 2020

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

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“…In previous studies, we examined how manometry influenced surgical decisions. We found that the manometry results changed the planned operation at least 50.9% of the time [ 6 ]. Therefore, this current study aimed to identify which factors seen on a typical HRM exam influenced the final decision at the GE junction.…”

mentioning

confidence: 99%

Components of high-resolution manometry that change surgical decisions

et al. 2023

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Background High-resolution manometry (HRM) is vital in evaluating patients for surgery at the gastroesophageal (GE) junction. Previously, we reported manometry alters surgery choices at the GE junction over 50% of the time, and its components, i.e., abnormal motility and distal contractile integral (DCI), are vital in decision-making. This single-institution retrospective study examines how HRM characteristics, reported with the Chicago classification, can alter the intended surgical plans for foregut surgery. Methods We collected data on pre-operative symptoms for patients undergoing HRM studies from 2012 to 2016, i.e., Upper GI X-rays, 48-h pH studies, DeMeester scores, upper endoscopy, and biopsy reports. HRM results were further categorized via Chicago classification (i.e., normal or abnormal motility). The DCI was determined; Patients not seen by a surgeon were excluded. Then a single surgeon, blinded to patient identity and HRM results, determined the planned procedure. The reviewer was then exposed to the HRM results; procedural plans were revised if needed. HRM results were then evaluated to determine which factors most influenced the surgical decisions. Results 298 HRM studies were initially identified; 114 met search criteria. Overall, HRM altered the planned procedure in 50.9% of cases (n = 58), with abnormal motility in 54.4% (62/114) cases. Abnormal motility findings corresponded to 70.6% (41/58) of the patients in which HRM changed the surgery decision. A DCI of < 1000 was identified in only 31.6% (36/114) of all patients, but 39.7% (23/58) of cases where the surgical decision was altered. A DCI of > 5000 was identified in only 10.5% (12/114) of all patients but 10.3% (6/58) of cases with altered surgical decisions. A DCI < 1000 and abnormal motility were generally associated with a partial fundoplication. Conclusions This study demonstrates the impact of identifying abnormal motility via the Chicago classification and factors like DCI on surgical choice at the GE junction.

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