A new possibility to assess the perioperative walking capacity using a global positioning system in neurosurgical spine patients: a feasibility study

Spine patient care with wearable medical technology: state-of-the-art, opportunities, and challenges: a systematic review

BACKGROUND CONTEXT

Healthcare reforms that demand quantitative outcomes and technical innovations have emphasized the use of Disability and Functional Outcome Measurements (DFOMs) to spinal conditions and interventions. Virtual healthcare has become increasingly important following the COVID-19 pandemic and wearable medical devices have proven to be a useful adjunct. Thus, given the advancement of wearable technology, broad adoption of commercial devices (ie, smartwatches, phone applications, and wearable monitors) by the general public, and the growing demand from consumers to take control of their health, the medical industry is now primed to formally incorporate evidence-based wearable device-mediated telehealth into standards of care.

PURPOSE

To (1) identify all wearable devices in the peer-reviewed literature that were used to assess DFOMs in Spine, (2) analyze clinical studies implementing such devices in spine care, and (3) provide clinical commentary on how such devices might be integrated into standards of care.

STUDY DESIGN/SETTING

A systematic review.

METHODS

A comprehensive systematic review was conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) across the following databases: PubMed; MEDLINE; EMBASE (Elsevier); and Scopus. Articles related to wearables systems in spine healthcare were selected. Extracted data was collected as per a predetermined checklist including wearable device type, study design, and clinical indices studied.

RESULTS

Of the 2,646 publications that were initially screened, 55 were extensively analyzed and selected for retrieval. Ultimately 39 publications were identified as being suitable for inclusion based on the relevance of their content to the core objectives of this systematic review. The most relevant studies were included, with a focus on wearables technologies that can be used in patients' home environments.

CONCLUSIONS

Wearable technologies mentioned in this paper have the potential to revolutionize spine healthcare through their ability to collect data continuously and in any environment. In this paper, the vast majority of wearable spine devices rely exclusively on accelerometers. Thus, these metrics provide information about general health rather than specific impairments caused by spinal conditions. As wearable technology becomes more prevalent in orthopedics, healthcare costs may be reduced and patient outcomes will improve. A combination of DFOMs gathered using a wearable device in conjunction with patient-reported outcomes and radiographic measurements will provide a comprehensive evaluation of a spine patient's health and assist the physician with patient-specific treatment decision-making. Establishing these ubiquitous diagnostic capabilities will allow improvement in patient monitoring and help us learn about postoperative recovery and the impact of our interventions.

Mobile health technology for remote home monitoring after surgery: a meta-analysis

BACKGROUND

Mobile health (mHealth) technology has been proposed as a method of improving post-discharge surveillance. Little is known about how mHealth has been used to track patients after surgery and whether its use is associated with differences in postoperative recovery.

METHODS

Three databases (PubMed, MEDLINE and the Cochrane Central Registry of Controlled Trials) were searched to identify studies published between January 1999 and February 2021. Mobile health was defined as any smartphone or tablet computer capable of electronically capturing health-related patient information and transmitting these data to the clinical team. Comparable outcomes were pooled via meta-analysis with additional studies compiled via narrative review. The quality of each study was assessed based on Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria.

RESULTS

Forty-five articles met inclusion criteria. While the majority of devices were designed to capture general health information, others were specifically adapted to the expected outcomes or potential complications of the index procedure. Exposure to mHealth was associated with fewer emergency department visits (odds ratio 0.42, 95 per cent c.i. 0.23 to 0.79) and readmissions (odds ratio 0.47, 95 per cent c.i. 0.29 to 0.77) as well as accelerated improvements in quality of life after surgery. There were limited data on other postoperative outcomes.

CONCLUSION

Remote home monitoring via mHealth is feasible, adaptable, and may even promote more effective postoperative care. Given the rapid expansion of mHealth, physicians and policymakers need to understand these technologies better so that they can be integrated into high-quality clinical care.

The use of smartphone-derived location data to evaluate participation following critical illness: A pilot observational cohort study

BACKGROUND

Disability is common following critical illness, impacting the quality of life of survivors, and is difficult to measure. 'Participation' can be quantified as involvement in life outside of their home requiring movement from their home to other locations. Participation restriction is a key element of disability, and following critical illness, participation may be diminished. It may be possible to quantify this change using pre-existing smartphone data.

OBJECTIVES

The feasibility of extracting location data from smartphones of survivors of intensive care unit (ICU) admission and assessing participation, using location-based outcomes, during recovery from critical illness was evaluated.

METHODS

Fifty consecutively admitted, consenting adult survivors of non-elective admission to ICU of greater than 48-h duration were recruited to a prospective observational cohort study where they were followed up at 3 and 6 months following discharge. The feasibility of extracting location data from survivors' smartphones and creating location-derived outcomes assessing participation was investigated over three 28-d study periods: pre-ICU admission and at 3 and 6 months following discharge. The following were calculated: time spent at home; the number of destinations visited; linear distance travelled; and two 'activity spaces', a minimum convex polygon and standard deviation ellipse.

RESULTS

Results are median [interquartile range] or n (%). The number of successful extractions was 9/50 (18%), 12/39 (31%), and 13/33 (39%); the percentage of time spent at home was 61 [56-68]%, 77 [66-87]%, and 67 [58-77]% (P = 0.16); the number of destinations visited was 34 [18-64], 38 [22-63], and 65 [46-88] (P = 0.02); linear distance travelled was 367 [56-788], 251 [114-323], and 747 [326-933] km over 28 d (P = 0.02), pre-ICU admission and at 3 and 6 months following ICU discharge, respectively. Activity spaces were successfully created.

CONCLUSION

Limited smartphone ownership, missing data, and time-consuming data extraction limit current implementation of mass extraction of location data from patients' smartphones to aid prognostication or measure outcomes. The number of journeys taken and the linear distance travelled increased between 3 and 6 months, suggesting participation may improve over time.

Normative data of a smartphone app-based 6-minute walking test, test-retest reliability, and content validity with patient-reported outcome measures

OBJECTIVE

The 6-minute walking test (6WT) is used to determine restrictions in a subject's 6-minute walking distance (6WD) due to lumbar degenerative disc disease. To facilitate simple and convenient patient self-measurement, a free and reliable smartphone app using Global Positioning System coordinates was previously designed. The authors aimed to determine normative values for app-based 6WD measurements.

METHODS

The maximum 6WD was determined three times using app-based measurement in a sample of 330 volunteers without previous spine surgery or current spine-related disability, recruited at 8 centers in 5 countries (mean subject age 44.2 years, range 16-91 years; 48.5% male; mean BMI 24.6 kg/m2, range 16.3-40.2 kg/m2; 67.9% working; 14.2% smokers). Subjects provided basic demographic information, including comorbidities and patient-reported outcome measures (PROMs): visual analog scale (VAS) for both low-back and lower-extremity pain, Core Outcome Measures Index (COMI), Zurich Claudication Questionnaire (ZCQ), and subjective walking distance and duration. The authors determined the test-retest reliability across three measurements (intraclass correlation coefficient [ICC], standard error of measurement [SEM], and mean 6WD [95% CI]) stratified for age and sex, and content validity (linear regression coefficients) between 6WD and PROMs.

RESULTS

The ICC for repeated app-based 6WD measurements was 0.89 (95% CI 0.87-0.91, p < 0.001) and the SEM was 34 meters. The overall mean 6WD was 585.9 meters (95% CI 574.7-597.0 meters), with significant differences across age categories (p < 0.001). The 6WD was on average about 32 meters less in females (570.5 vs 602.2 meters, p = 0.005). There were linear correlations between average 6WD and VAS back pain, VAS leg pain, COMI Back and COMI subscores of pain intensity and disability, ZCQ symptom severity, ZCQ physical function, and ZCQ pain and neuroischemic symptoms subscores, as well as with subjective walking distance and duration, indicating that subjects with higher pain, higher disability, and lower subjective walking capacity had significantly lower 6WD (all p < 0.001).

CONCLUSIONS

This study provides normative data for app-based 6WD measurements in a multicenter sample from 8 institutions and 5 countries. These values can now be used as reference to compare 6WT results and quantify objective functional impairment in patients with degenerative diseases of the spine using z-scores. The authors found a good to excellent test-retest reliability of the 6WT app, a low area of uncertainty, and high content validity of the average 6WD with commonly used PROMs.

Objective measures of functional impairment for degenerative diseases of the lumbar spine: a systematic review of the literature

BACKGROUND CONTEXT

The accurate determination of a patient's functional status is necessary for therapeutic decision-making and to critically appraise treatment efficacy. Current subjective patient-reported outcome measure (PROM)-based assessments have limitations and can be complimented by objective measures of function.

PURPOSE

To systematically review the literature and provide an overview on the available objective measures of function for patients with degenerative diseases of the lumbar spine.

STUDY DESIGN/SETTING

Systematic review of the literature.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Two reviewers independently searched the PubMed, Web of Science, EMBASE, and SCOPUS databases for permutations of the words "objective," "assessment," "function," "lumbar," and "spine" including articles on human subjects with degenerative diseases of the lumbar spine that reported on objective measures of function, published until September 2018. Risk of bias was not assessed. No funding was received. The authors report no conflicts of interest.

RESULTS

Of 2,389 identified articles, 82 were included in the final analysis. There was a significant increase of 0.12 per year in the number of publications dealing with objective measures of function since 1989 (95% CI 0.08-0.16, p<.001). Some publications studied multiple diagnoses and objective measures. The United States was the leading nation in terms of scientific output for objective outcome measures (n=21; 25.6%), followed by Switzerland (n=17; 20.7%), Canada, Germany, and the United Kingdom (each n=6; 7.3%). Our search revealed 21 different types of objective measures, predominantly applied to patients with lumbar spinal stenosis (n=67 publications; 81.7%), chronic/unspecific low back pain (n=28; 34.2%) and lumbar disc herniation (n=22; 26.8%). The Timed-Up-and-Go test was the most frequently applied measure (n=26 publications; 31.7%; cumulative number of reported subjects: 5,181), followed by the Motorized Treadmill Test (n=25 publications; 30.5%, 1,499 subjects) and with each n=9 publications (11.0%) the Five-Repetition Sit-To-Stand test (955 subjects), as well as accelerometry analyses (336 subjects). The reliability and validity of many of the less-applied objective measures was uncertain. There was profound heterogeneity in their application and interpretation of results.

CONCLUSIONS

Clinical studies on patients with lumbar degenerative diseases increasingly employ objective measures of function, which offer high potential for improving the quality of outcome measurement in patient-care and research. This review provides an overview on available options. Our findings call for an agreement and standardization in terms of test selection, conduction and analysis to facilitate comparison of results across cohorts.

PROSPERO REGISTRATION NUMBER

CRD42019122622.

Wide Disagreement Between Alternative Assessments of Premorbid Physical Activity: Subjective Patient and Surrogate Reports and Objective Smartphone Data

OBJECTIVES

Surrogate-decision maker and patient self-reported estimates of the distances walked prior to acute illness are subjective and may be imprecise. It may be possible to extract objective data from a patient's smartphone, specifically, step and global position system data, to quantify physical activity. The objectives were to 1) assess the agreement between surrogate-decision maker and patient self-reported estimates of distance and time walked prior to resting and daily step-count and 2) determine the feasibility of extracting premorbid physical activity (step and global position system) data from critically ill patients.

DESIGN

Prospective cohort study.

SETTING

Quaternary ICU.

PATIENTS

Fifty consecutively admitted adult patients who owned a smartphone, who were ambulatory at baseline, and who remained in ICU for more than 48 hours participated.

MEASURMENTS AND MAIN RESULTS

There was no agreement between patients and surrogates for all premorbid walking metrics (mean bias 108% [99% lower to 8,700% higher], 83% [97% to 2,100%], and 71% [96% to 1,080%], for distance, time, and steps, respectively). Step and/or global position system data were successfully extracted from 24 of 50 phones (48%; 95% CI, 35-62%). Surrogate-decision makers, but not patient self-reported, estimates of steps taken per day correlated with smartphone data (surrogates: n = 13, ρ = 0.56, p < 0.05; patients: n = 13, ρ = 0.30, p = 0.317).

CONCLUSION

There was a lack of agreement between surrogate-decision maker and patient self-reported subjective estimates of distance walked. Obtaining premorbid physical activity data from the current-generation smartphones was feasible in approximately 50% of patients.

Blind RSSD-Based Indoor Localization with Confidence Calibration and Energy Control

Indoor localization based on wireless sensor networks (WSNs) is an important field of research with numerous applications, such as elderly care, miner security, and smart buildings. In this paper, we present a localization method based on the received signal strength difference (RSSD) to determine a target on a map with unknown transmission information. To increase the accuracy of localization, we propose a confidence value for each anchor node to indicate its credibility for participating in the estimation. An automatic calibration device is designed to help acquire the values. The acceleration sensor and unscented Kalman filter (UKF) are also introduced to reduce the influence of measuring noise in the application. Energy control is another key point in WSN systems and may prolong the lifetime of the system. Thus, a quadtree structure is constructed to describe the region correlation between neighboring areas, and the unnecessary anchor nodes can be detected and set to sleep to save energy. The localization system is implemented on real-time Texas Instruments CC2430 and CC2431 embedded platforms, and the experimental results indicate that these mechanisms achieve a high accuracy and low energy cost.