Evidence map›Paper›PMID 42080986›Full record

ReviewOrthopadie (Heidelberg, Germany)2026

[AI-based surgical planning of adult spinal deformities : Analysis of an AI-based tool for correction planning and execution employing patient-specific contoured rods].

Patrick Strube, Alexander Hölzl, Anna-Maria Vogel, Georg Matziolis, Chris Lindemann

Abstract readEnglish AbstractReview
In one paragraph

Review in Orthopadie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Patrick StrubeOrthopädie, Campus Waldkliniken Eisenberg, Universitätsklinikum Jena/Friedrich Schiller Universität Jena, 07607, Eisenberg, Deutschland. p.strube@waldkliniken-eisenberg.de.
Alexander HölzlOrthopädie, Campus Waldkliniken Eisenberg, Universitätsklinikum Jena/Friedrich Schiller Universität Jena, 07607, Eisenberg, Deutschland.
Anna-Maria VogelOrthopädie, Campus Waldkliniken Eisenberg, Universitätsklinikum Jena/Friedrich Schiller Universität Jena, 07607, Eisenberg, Deutschland.
Georg MatziolisOrthopädie, Campus Waldkliniken Eisenberg, Universitätsklinikum Jena/Friedrich Schiller Universität Jena, 07607, Eisenberg, Deutschland.
Chris LindemannOrthopädie, Campus Waldkliniken Eisenberg, Universitätsklinikum Jena/Friedrich Schiller Universität Jena, 07607, Eisenberg, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimal alignment correction can potentially lower the high complication rates of adult scoliosis surgeries. AI tools can help make the analysis and planning process easier as well as improve the surgical realization via patient-specific rod manufacturing.

objectivesInvestigation of an AI-based tool regarding this. MATERIALS AND

methodsAnalysis of the first 10 AI-tool used-cases of adult scoliosis in our department regarding outcome and limitations.

resultsThe method allows time-sparing analysis and significant improvement of the spine profile. Limitations result from unimplemented parameters in the model and from arbitrary bias caused by the planner, which influence the surgical success rate of adult scoliosis.

conclusionsThe presented AI-tool represents a practicable and easy to use method for restoring the balance of patients. Extension of the model could potentially lower complication rates in the future.

Indexed as

Artificial IntelligenceScoliosisSpinal FusionSurgery, Computer-AssistedAdultHumansIntelligent SystemsOsteotomyPatient Care PlanningArtificial intelligenceOsteotomyPlanning technicScoliosisSpine

Identifiers

PMID42080986
PMCPMC13230238

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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.