Evidence map›Paper›PMID 35441110›Full record

ArticleJournal of spine surgery (Hong Kong)2022

Two-year continuous data capture using a wearable sensor to remotely monitor the surgical spine patient: a case report.

R Dineth Fonseka, Pragadesh Natarajan, Monish M Maharaj, Kaitlin Rooke, Ralph J Mobbs

Abstract readCase Reports
In one paragraph

Article in Journal of spine surgery (Hong Kong), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

5 authors.

R Dineth FonsekaFaculty of Medicine, University of New South Wales, Sydney, Australia.
Pragadesh NatarajanFaculty of Medicine, University of New South Wales, Sydney, Australia.
Monish M MaharajFaculty of Medicine, University of New South Wales, Sydney, Australia.
Kaitlin RookeNeuroSpine Surgery Research Group (NSURG), Sydney, Australia.
Ralph J MobbsFaculty of Medicine, University of New South Wales, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report the case of a 46-year-old male with long-standing low back pain who presented with a deterioration of symptoms characterised by back and right leg pain corresponding to the L4 and L5 dermatomes. An MRI scan revealed severe central and lateral recess stenosis at L4/5 secondary to a large central disc protrusion. We remotely monitored activity and general health metrics over a time-period exceeding two years. This is the first study to monitor these metrics remotely and continuously in the surgical spine patient. Over this time, he received several interventions including a spinal cord stimulator implant, and an L4/5 microdiscectomy. We tracked his fluctuating health status using the Oura Ring [objectively measuring metrics including step count, sleep patterns, heart rate (HR), heart-rate variability (HRV), and respiratory rate (RR)] and with daily self-reported scores on the Visual Analogue Scale. The Oura Ring is a convenient and lightweight wearable device that is worn on any finger. Taken together, metrics provided a comprehensive picture of deterioration and recovery, paralleling key events in the patient's history. The use of wearable devices is feasible in enabling long-term remote continuous monitoring. This may assist surgeons and rehabilitation providers in identifying early deterioration and monitoring the post-intervention course of recovery.

Indexed as

case reportdigital healthDisc herniationremote monitoringwearable sensor

Identifiers

PMID35441110
PMCPMC8990385

What OpenQuestion holds

Textmetadata
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.