Evidence map›Paper›PMID 31236658›Full record

Observational studyEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2019

Accurate prediction of spontaneous lumbar curve correction following posterior selective thoracic fusion in adolescent idiopathic scoliosis using logistic regression models and clinical rationale.

H Koller, W Hitzl, M C Marks, P O Newton

Abstract readMulticenter StudyObservational Study
PubMed Publisher
In one paragraph

Observational study 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, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  4. Implementation of artificial intelligence (AI) in ASD treatment.North American Spine Society journal · 2025
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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

4 authors.

H KollerDepartment of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany. koller-spine@gmx.de.
W HitzlResearch Office, Biostatistics, Paracelsus Medical University, Salzburg, Austria.
M C MarksSetting Scoliosis Straight, Harms Study Group, San Diego, USA.
P O NewtonDepartment of Orthopedic Surgery, Rady Children's Hospital San Diego, University of California San Diego, San Diego, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccurate prediction of spontaneous lumbar curve correction (SLCC) after selective thoracic fusion (STF) remains difficult. This study sought to improve prediction accuracy of SLCC. The hypothesis was preoperative and intraoperative variables could predict SLCC < 20°.

methodsA multicenter observational prospective analysis was conducted to determine predictors of SLCC in AIS patients that had posterior STF. Curve types included major thoracic curves (Lenke 1, 3-4).The primary outcome variable was to establish prediction models, and a postoperative lumbar curve (LC) ≤ 20° was defined as the target variable. Multivariate logistic regression models were established to study the relationship between selected variables and a LC ≤ 20° versus a LC > 20° at ≥ 2-year follow-up. Single and dual thresholds models in perspective of clinical rationales were applied to find models with the highest positive/negative predictive values (PPV/NPV). The secondary outcome measure was SRS scores at ≥ 2-year follow-up.

results410 patients were included. At ≥ 2-year follow-up 282 patients had LC ≤ 20°. These patients had better SRS-22 scores than those with LC > 20° (P = 0.02). The postoperative LC and LC ≤ 20° were predicted by preoperative LC and LC-bending Cobb angle (P < 0.01, r = 0.4-0.6). Logistic regression models could be established to identify patients at risk for failing the target LC ≤ 20°.For preoperative LC and LC-bending, the prediction model achieved a NPV/PPV of 80%/72%. If the postoperative main thoracic curve is combined with the preoperative LC and a gray area for difficult decisions was allowed, model accuracy could even be improved (NPV/PPV = 96%/81%).

conclusionAn accurate prediction model for postoperative SLCC was established based on a large analysis of prospective STF cases. These models can support prediction and understanding of postoperative SLCC aiding in surgical decision making when contemplating a selective thoracic fusion. These slides can be retrieved under Electronic Supplementary Material.

Indexed as

Clinical Decision RulesSpinal FusionAdolescentChildFemaleFollow-Up StudiesHumansLogistic ModelsLumbar VertebraeMalePredictive Value of TestsProspective StudiesRadiographyScoliosisThoracic VertebraeTreatment OutcomeLumbar curvePredictionScoliosisSelective thoracic fusionSurgery

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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.