Literature DB >> 34450590

Smartphone GPS signatures of patients undergoing spine surgery correlate with mobility and current gold standard outcome measures.

Alessandro Boaro1,2, Jeffrey Leung1, Harrison T Reeder3, Francesca Siddi1, Elisabetta Mezzalira1, Gang Liu3, Rania A Mekary1,4, Yi Lu5, Michael W Groff5, Jukka-Pekka Onnela3, Timothy R Smith1,5.   

Abstract

OBJECTIVE: Patient-reported outcome measures (PROMs) are currently the gold standard to evaluate patient physical performance and ability to recover after spine surgery. However, PROMs have significant limitations due to the qualitative and subjective nature of the information reported as well as the impossibility of using this method in a continuous manner. The smartphone global positioning system (GPS) can be used to provide continuous, quantitative, and objective information on patient mobility. The aim of this study was to use daily mobility features derived from the smartphone GPS to characterize the perioperative period of patients undergoing spine surgery and to compare these objective measurements to PROMs, the current gold standard.
METHODS: Eight daily mobility features were derived from smartphone GPS data in a population of 39 patients undergoing spine surgery for a period of 2 months starting 3weeks before surgery. In parallel, three different PROMs for pain (visual analog scale [VAS]), disability (Oswestry Disability Index [ODI]) and functional status (Patient-Reported Outcomes Measurement Information System [PROMIS]) were serially measured. Segmented linear regression analysis was used to assess trends before and after surgery. The Student paired t-test was used to compare pre- and postoperative PROM scores. Pearson's correlation was calculated between the daily average of each GPS-based mobility feature and the daily average of each PROM score during the recovery period.
RESULTS: Smartphone GPS features provided data documenting a reduction in mobility during the immediate postoperative period, followed by a progressive and steady increase with a return to baseline mobility values 1 month after surgery. PROMs measuring pain, physical performance, and disability were significantly different 1 month after surgery compared to the 2 immediate preoperative weeks. The GPS-based features presented moderate to strong linear correlation with pain VAS and PROMIS physical score during the recovery period (Pearson r > 0.7), whereas the ODI and PROMIS mental scores presented a weak correlation (Pearson r approximately 0.4).
CONCLUSIONS: Smartphone-derived GPS features were shown to accurately characterize perioperative mobility trends in patients undergoing surgery for spine-related diseases. Features related to time (rather than distance) were better at describing patient physical and performance status. Smartphone GPS has the potential to be used for the development of accurate, noninvasive and personalized tools for patient mobility monitoring after surgery.

Entities:  

Keywords:  GPS; PROMs; digital phenotyping; smartphone; spine surgery

Mesh:

Year:  2021        PMID: 34450590      PMCID: PMC9012532          DOI: 10.3171/2021.2.SPINE202181

Source DB:  PubMed          Journal:  J Neurosurg Spine        ISSN: 1547-5646


  28 in total

1.  Reliability and validity of gait analysis by android-based smartphone.

Authors:  Shu Nishiguchi; Minoru Yamada; Koutatsu Nagai; Shuhei Mori; Yuu Kajiwara; Takuya Sonoda; Kazuya Yoshimura; Hiroyuki Yoshitomi; Hiromu Ito; Kazuya Okamoto; Tatsuaki Ito; Shinyo Muto; Tatsuya Ishihara; Tomoki Aoyama
Journal:  Telemed J E Health       Date:  2012-03-08       Impact factor: 3.536

2.  Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health.

Authors:  Jukka-Pekka Onnela; Scott L Rauch
Journal:  Neuropsychopharmacology       Date:  2016-01-28       Impact factor: 7.853

3.  Surgical or nonoperative treatment for lumbar spinal stenosis? A randomized controlled trial.

Authors:  Antti Malmivaara; Pär Slätis; Markku Heliövaara; Päivi Sainio; Heikki Kinnunen; Jyrki Kankare; Nina Dalin-Hirvonen; Seppo Seitsalo; Arto Herno; Pirkko Kortekangas; Timo Niinimäki; Hannu Rönty; Kaj Tallroth; Veli Turunen; Paul Knekt; Tommi Härkänen; Heikki Hurri
Journal:  Spine (Phila Pa 1976)       Date:  2007-01-01       Impact factor: 3.468

Review 4.  Evaluating the correlation and responsiveness of patient-reported pain with function and quality-of-life outcomes after spine surgery.

Authors:  John DeVine; Daniel C Norvell; Erika Ecker; Daryl R Fourney; Alex Vaccaro; Jeff Wang; Gunnar Andersson
Journal:  Spine (Phila Pa 1976)       Date:  2011-10-01       Impact factor: 3.468

5.  A Smartphone Application Suite for Assessing Mobility.

Authors:  Priyanka Madhushri; Armen A Dzhagaryan; Emil Jovanov; Aleksandar Milenkovic
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

6.  The Rise of Wearable Technology in Health Care.

Authors:  Thomas M Krummel
Journal:  JAMA Netw Open       Date:  2019-02-01

Review 7.  Do we have the right PROMs for measuring outcomes in lumbar spinal surgery?

Authors:  O M Stokes; A A Cole; L M Breakwell; A J Lloyd; C M Leonard; M Grevitt
Journal:  Eur Spine J       Date:  2017-01-09       Impact factor: 3.134

8.  Relapse prediction in schizophrenia through digital phenotyping: a pilot study.

Authors:  Ian Barnett; John Torous; Patrick Staples; Luis Sandoval; Matcheri Keshavan; Jukka-Pekka Onnela
Journal:  Neuropsychopharmacology       Date:  2018-02-22       Impact factor: 7.853

9.  Digital Phenotyping in Patients with Spine Disease: A Novel Approach to Quantifying Mobility and Quality of Life.

Authors:  David J Cote; Ian Barnett; Jukka-Pekka Onnela; Timothy R Smith
Journal:  World Neurosurg       Date:  2019-02-22       Impact factor: 2.104

10.  Reconsidering the minimally important difference: evidence of instability over time and across groups.

Authors:  Carolyn E Schwartz; Jie Zhang; Bruce D Rapkin; Joel A Finkelstein
Journal:  Spine J       Date:  2018-09-21       Impact factor: 4.166

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