Evidence map›Paper›PMID 38221955›Full record

ReviewWorld neurosurgery: X2024

Smartphone-based activity tracking for spine patients: Current technology and future opportunities.

Adam Leibold, Daniyal Mansoor Ali, James Harrop, Ashwini Sharan, Alexander R Vaccaro, Ahilan Sivaganesan

Abstract readReview
In one paragraph

Review in World neurosurgery: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Patient-reported outcome measures in lumbar disc herniation: a scoping review.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Adam LeiboldDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
Daniyal Mansoor AliDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
James HarropDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
Ashwini SharanDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
Alexander R VaccaroDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
Ahilan SivaganesanDepartment of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Activity trackers and wearables allow accurate determination of physical activity, basic vital parameters, and tracking of complex medical conditions. This review attempts to provide a roadmap for the development of these applications, outlining the basic tools available, how they can be combined, and what currently exists in the marketplace for spine patients. Various types of sensors currently exist to measure distinct aspects of user movement. These include the accelerometer, gyroscope, magnetometer, barometer, global positioning system (GPS), Bluetooth and Wi-Fi, and microphone. Integration of data from these sensors allows detailed tracking of location and vectors of motion, resulting in accurate mobility assessments. These assessments can have great value for a variety of healthcare specialties, but perhaps none more so than spine surgery. Patient-reported outcomes (PROMs) are subject to bias and are difficult to track frequently - a problem that is ripe for disruption with the continued development of mobility technology. Currently, multiple mobile applications exist as an extension of clinical care. These include Manage My Surgery (MMS), SOVINITY-e-Healthcare Services, eHealth System, Beiwe Smartphone Application, QS Access, 6WT, and the TUG app. These applications utilize sensor data to assess patient activity at baseline and postoperatively. The results are evaluated in conjunction with PROMs. However, these applications have not yet exploited the full potential of available sensors. There is a need to develop smartphone applications that can accurately track the functional status and activity of spine patients, allowing a more quantitative assessment of outcomes, in contrast to legacy PROMs.

Indexed as

Mobile applicationsPatient-reported outcome measures (PROMs)Smartphone-based activity trackingSmartphone sensorsSpine surgery

Identifiers

PMID38221955
PMCPMC10787294

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.