Predictors of pelvic tilt normalization: a multicenter study on the impact of regional and lower-extremity compensation on pelvic alignment after complex adult spinal deformity surgery
Notice bibliographique
Résumé
OBJECTIVE: The objective was to determine the degree of regional decompensation to pelvic tilt (PT) normalization after complex adult spinal deformity (ASD) surgery. METHODS: Operative ASD patients with 1 year of PT measurements were included. Patients with normalized PT at baseline were excluded. Predicted PT was compared to actual PT, tested for change from baseline, and then compared against age-adjusted, Scoliosis Research Society-Schwab, and global alignment and proportion (GAP) scores. Lower-extremity (LE) parameters included the cranial-hip-sacrum angle, cranial-knee-sacrum angle, and cranial-ankle-sacrum angle. LE compensation was set as the 1-year upper tertile compared with intraoperative baseline. Univariate analyses were used to compare normalized and nonnormalized data against alignment outcomes. Multivariable logistic regression analyses were used to develop a model consisting of significant predictors for normalization related to regional compensation. RESULTS: In total, 156 patients met the inclusion criteria (mean ± SD age 64.6 ± 9.1 years, BMI 27.9 ± 5.6 kg/m2, Charlson Comorbidity Index 1.9 ± 1.6). Patients with normalized PT were more likely to have overcorrected pelvic incidence minus lumbar lordosis and sagittal vertical axis at 6 weeks (p < 0.05). GAP score at 6 weeks was greater for patients with nonnormalized PT (0.6 vs 1.3, p = 0.08). At baseline, 58.5% of patients had compensation in the thoracic and cervical regions. Postoperatively, compensation was maintained by 42% with no change after matching in age-adjusted or GAP score. The patients with nonnormalized PT had increased rates of thoracic and cervical compensation (p < 0.05). Compensation in thoracic kyphosis differed between patients with normalized PT at 6 weeks and those with normalized PT at 1 year (69% vs 35%, p < 0.05). Those who compensated had increased rates of implant complications by 1 year (OR [95% CI] 2.08 [1.32-6.56], p < 0.05). Cervical compensation was maintained at 6 weeks and 1 year (56% vs 43%, p = 0.12), with no difference in implant complications (OR 1.31 [95% CI -2.34 to 1.03], p = 0.09). For the lower extremities at baseline, 61% were compensating. Matching age-adjusted alignment did not eliminate compensation at any joint (all p > 0.05). Patients with nonnormalized PT had higher rates of LE compensation across joints (all p < 0.01). Overall, patients with normalized PT at 1 year had the greatest odds of resolving LE compensation (OR 9.6, p < 0.001). Patients with normalized PT at 1 year had lower rates of implant failure (8.9% vs 19.5%, p < 0.05), rod breakage (1.3% vs 13.8%, p < 0.05), and pseudarthrosis (0% vs 4.6%, p < 0.05) compared with patients with nonnormalized PT. The complication rate was significantly lower for patients with normalized PT at 1 year (56.7% vs 66.1%, p = 0.02), despite comparable health-related quality of life scores. CONCLUSIONS: Patients with PT normalization had greater rates of resolution in thoracic and LE compensation, leading to lower rates of complications by 1 year. Thus, consideration of both the lower extremities and thoracic regions in surgical planning is vital to preventing adverse outcomes and maintaining pelvic alignment.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».