Evidence map›Paper›PMID 28720144›Full record

ArticleJournal of neuroengineering and rehabilitation2017

Identifying predictors for postoperative clinical outcome in lumbar spinal stenosis patients using smart-shoe technology.

Sunghoon I Lee, Andrew Campion, Alex Huang, Eunjeong Park, Jordan H Garst, Nima Jahanforouz, Marie Espinal, Tiffany Siero, Sophie Pollack, Marwa Afridi and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. The past, present, and future of remote patient monitoring in spine care: an overview.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 · 2021
    Review
  8. 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

14 authors.

Sunghoon I LeeCollege of Information and Computer Science, UMass Amherst, Amherst, USA.
Andrew CampionNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Alex HuangNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Eunjeong ParkCardiovascular Research Institute, Yonsei University College of Medicine, Los Angeles, USA.
Jordan H GarstNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Nima JahanforouzNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Marie EspinalNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Tiffany SieroNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Sophie PollackNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Marwa AfridiNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Meelod DaneshvarNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Saif GhiasNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA.
Majid SarrafzadehComputer Science Department, UCLA, Los Angeles, USA.
Daniel C LuNeuroplasticity and Repair Laboratory, UCLA, Los Angeles, USA. dclu@mednet.ucla.edu.

Funding

UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
NCATS NIH HHS UL1 TR000124
6 · The paper itself

Abstract

backgroundApproximately 33% of the patients with lumbar spinal stenosis (LSS) who undergo surgery are not satisfied with their postoperative clinical outcomes. Therefore, identifying predictors for postoperative outcome and groups of patients who will benefit from the surgical intervention is of significant clinical benefit. However, many of the studied predictors to date suffer from subjective recall bias, lack fine digital measures, and yield poor correlation to outcomes.

methodsThis study utilized smart-shoes to capture gait parameters extracted preoperatively during a 10 m self-paced walking test, which was hypothesized to provide objective, digital measurements regarding the level of gait impairment caused by LSS symptoms, with the goal of predicting postoperative outcomes in a cohort of LSS patients who received lumbar decompression and/or fusion surgery. The Oswestry Disability Index (ODI) and predominant pain level measured via the Visual Analogue Scale (VAS) were used as the postoperative clinical outcome variables.

resultsThe gait parameters extracted from the smart-shoes made statistically significant predictions of the postoperative improvement in ODI (RMSE =0.13, r=0.93, and p<3.92×10

conclusionsThe reported results herein support the hypothesis that the measurement of gait characteristics by our smart-shoe system can provide accurate predictions of the surgical outcomes, assisting clinicians in identifying which LSS patient population can benefit from the surgical intervention and optimize treatment strategies.

Indexed as

ShoesAdultAgedBiomechanical PhenomenaCohort StudiesDecompression, SurgicalDisability EvaluationFemaleGaitHumansLumbar VertebraeMaleMiddle AgedPain MeasurementPilot ProjectsPostoperative PainLumbar spinal stenosisOswestry disability indexPredictionPredominant painSmart shoesWalking test

Identifiers

PMID28720144
PMCPMC5516369

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.