ArticleSpine deformity2024
Which sagittal plane assessment method is most predictive of complications after adult spinal deformity surgery?
Article in Spine deformity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning-based prediction of proximal junctional pathology after adult spinal deformity surgery: a systematic review and diagnostic test accuracy meta-analysis.Acta neurochirurgica · 2026Pooled it
- Machine learning clustering reveals risk factors of mechanical complications requiring revision in adult spinal deformity surgery: a 2-year follow-up study.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 · 2026Article
- Impact of lumbar pedicle subtraction osteotomy (PSO) level on global alignment and proportion (GAP) score in revision adult iatrogenic flatback spinal deformities.Spine deformity · 2025Article
- Alignment Goals in Adult Spinal Deformity Surgery.Global spine journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
purposeDifferent methods of sagittal alignment assessment compete for predicting adverse events after adult spinal deformity (ASD) surgery. We wanted to study which method provides greater benefit.
methodsRetrospective study of 391 patients operated for ASD, with > 6 instrumented levels, fused to the pelvis, and 2 years of follow-up. Three alignment methods were analyzed 6-week postoperatively: (1) Roussouly mismatch; (2) GAP score/GAP categories; (3) T4-L1-Hip axis. Binary logistic regression generated models that best predict the following adverse events: mechanical complications (MC): in general and isolated (PJK, PJF, rod breakage); reinterventions (in general and after MC); and readmissions. ROC/AUC analysis was also implemented. In a second regression round, we added different variables that were selected on univariate analysis-demographic, surgical, and radiographic-to complete the models.
resultsThe best predictor parameters in most models were T4-L1PA mismatch and GAP score; we could not prove a predictive ability of the Roussouly mismatch. The T4-L1PA mismatch best predicted general MC, PJK, PJK + PJF, and readmission, while the GAP score best predicted PJF and reinterventions (for MC and for any complication). However, the variance explained by these models was limited (Nagelkerke's R2 = 0.031-0.113), with odds ratios ranging from 1.070 to 1.456. ROC curves plotted an AUC between 0.57 and 0.70. Introducing additional variables (demographic, surgical, and radiographic) improved prediction in all the models (Nagelkerke's R2 = 0.082-0.329) and allowed predicting rod breakage.
conclusionThe T4-L1-Hip axis and GAP score show potential in predicting adverse events, surpassing the Roussouly method. Despite partial efficacy in complication anticipation, recognizing postoperative sagittal alignment as a key modifiable risk factor, the crucial need arises to integrate diverse variables, both modifiable and non-modifiable, for enhanced predictive accuracy. LEVEL OF EVIDENCE: Level IV.
Indexed as
Identifiers
38607513What OpenQuestion holds
Registered trials
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.