Evidence map›Paper›PMID 34621568›Full record

ArticleSurgical neurology international2021

Age, body mass index, and osteoporosis are more predictive than imaging for adjacent-segment reoperation after lumbar fusion.

Nii-Kwanchie Ankrah, Ilyas M Eli, Subu N Magge, Robert G Whitmore, Andrew Y Yew

Open access · hybridAbstract read
In one paragraph

Article in Surgical neurology international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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 at 1 institution in 1 country.

Nii-Kwanchie AnkrahDepartment of Neurosurgery, Lahey Clinic, Burlington, Massachusetts, United States.
Ilyas M EliDepartment of Neurosurgery, University of Utah, Clinical Neurosciences Center, Salt Lake City, Utah, United States.
Subu N MaggeDepartment of Neurosurgery, Lahey Clinic, Burlington, Massachusetts, United States.
Robert G WhitmoreDepartment of Neurosurgery, Lahey Clinic, Burlington, Massachusetts, United States.
Andrew Y YewDepartment of Neurosurgery, Lahey Clinic, Burlington, Massachusetts, United States.
Lahey Hospital and Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdjacent-segment disease (ASD) is a well-described long-term complication after lumbar fusion. There is a lack of consensus about the risk factors for development of ASD, but identifying them could improve surgical outcomes. Our goal was to analyze the effect of patient characteristics and radiographic parameters on the development of symptomatic ASD requiring revision surgery after posterior lumbar fusion.

methodsIn this retrospective cohort study, we identified patients who underwent lumbar fusion surgery and revision surgery from May 2012 to November 2018 using an institutional lumbar fusion registry. Patients having both pre- and post-operative upright radiographs were included in the study. Revision surgeries for which the index operation was performed at an outside hospital were excluded from analysis. Univariate analysis was conducted on candidate variables, and variables with

resultsOf the 106 patients identified, 21 required reoperation (29 months average follow-up). Age >65 years (OR 4.14, 95% CI 1.46-11.76,

conclusionAge >65, BMI >34, and osteoporosis were independent predictors of adjacent-segment reoperation after lumbar spinal fusion.

Indexed as

Adjacent segment diseaseFusionImagingLumbar lordosisReoperationSpine

Identifiers

PMID34621568
PMCPMC8492407
OpenAlexW3197720367

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.