Evidence map›Paper›PMID 39276221›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2024

Puberty changes the natural history of idiopathic scoliosis: three prediction models for future radiographic curve severity from 1563 consecutive patients.

Stefano Negrini, Maryna Yaskina, Sabrina Donzelli, Alberto Negrini, Giulia Rebagliati, Claudio Cordani, Fabio Zaina, Eric C Parent

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Article in 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, 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
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1 · What the graph read from it

What it found

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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

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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.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Stefano NegriniDepartment of Biomedical, Surgical and Dental Sciences, University "La Statale", Milan, Italy. Stefano.negrini@unimi.it.ORCID 0000-0002-1878-2747
Maryna YaskinaWomen and Children's Health Research Institute, University of Alberta, Edmonton, Canada.
Sabrina DonzelliUtrecht University Medical Center UMC Otropedic Department Utrecht, Utrecht, Netherlands.
Alberto NegriniISICO (Italian Scientific Spine Institute), Milan, Italy.
Giulia RebagliatiISICO (Italian Scientific Spine Institute), Milan, Italy.
Claudio CordaniIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Fabio ZainaISICO (Italian Scientific Spine Institute), Milan, Italy.
Eric C ParentDepartment of Physical Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUnderstanding idiopathic scoliosis (IS) natural history during growth is essential for shared decision-making between patients and physicians. We developed a retrospective model with the largest available sample in the literature and we aimed to investigate if using three peri-pubertal growth periods provides better prediction than a unique model.

methodsSecondary analysis of a previous study on IS natural history data from radiographs before and at the first consult. Three groups: BEFORE (age 6-10), AT (age 11-Risser 2) and AFTER (from Risser 3) the pubertal growth spurt. Available predictors: Cobb angle, curve type, sex, observation time, and Risser score. We used linear mixed-effects models to predict future Cobb angles in each group. We internally validated prediction accuracy with over 100 patients per group (3 to 5-fold cross-validation).

resultsWe included 1563 participants (275 BEFORE, 316 AFTER, 782 females and 190 males AT). Curves increased over time mostly in AT, importantly in BEFORE, but also in AFTER. All models performed better than the general one. In BEFORE, 74.2% of the predictions were within ± 5

conclusionIS curve severities increase differently during growth with puberty stages. Model accuracy increases when tailored by growth spurt periods. Our models may help patients and clinicians share decisions, identify the risk of progression and inform treatment planning.

Indexed as

PubertyScoliosisAdolescentChildFemaleHumansMaleRadiographyRetrospective StudiesSeverity of Illness IndexNatural historyPrognosisPubertyScoliosis

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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.