A Case-Controlled Study Evaluating the Effect of Cone Beam CT (O-Arm) Imaging and Navigation on Pedicle Screw Placement in Adult Spinal Surgery
Notice bibliographique
Résumé
Introduction Intraoperative CT and navigation systems (NAV) may provide an opportunity to improve precision and accuracy of pedicle screw placement, and in so doing, improve patient outcomes. Our study aimed to examine the efficacy and safety of NAV for pedicle screw placement in elective and emergent adult spinal surgery cases. We currently use this technology for surgery in all primary diagnoses of the adult spine including trauma, degenerative, deformity, revision surgery, and tumor. We sought to examine the efficacy and safety of NAV for pedicle screw placement in this broad range of surgical spinal cases. Materials and Methods All patients who underwent pedicle screw fixation with O-arm imaging and StealthStation navigation between January 2008 and December 2012 were analyzed. Patients were matched with historic case controls (non-NAV). Diagnosis, number, timing, and degree of screw malposition were recorded. Any screw with pedicle breach greater than 0 mm was recorded as misplaced. All patients had a minimum follow-up of 1 year. Quantitative statistical analysis compared screw placement between NAV and non-NAV cases. Results A total of 253 patients met the inclusion criteria by primary diagnosis in the NAV group. Diagnosis categories were not significantly different between groups (trauma 20%, oncology 12%, inflammatory arthropathy 2%, scoliotic deformity 23%, spondylolisthesis 25%, degenerative 13%, and miscellaneous other diagnoses 5%, p = 0.269). Mean number of screws placed was 11.4 in the NAV group and 10.8 in the non-NAV group ( p = 0.299) with misplaced screws in 78 patients (31%) in the NAV group and 105 (42.2%) in the non-NAV group ( p < 0.009). Intraoperative screw revision rates were equivalent between groups (21 in the NAV group and 20 in the non-NAV group, p = 1); however, the number of screws revised during the same admission was significantly different (2 in the NAV group and 9 in the non-NAV group, p < 0.004). Likewise, late postoperative surgical revision rates were significantly different with six patients requiring readmission for screw revision within 1 year in the non-NAV group compared with none in the NAV cohort ( p < 0.008). All categories of primary diagnosis demonstrated reduction ( p < 0.05) in the rate of screw malposition. Screw revision rates for individual diagnoses, however, intraoperatively or early postoperatively were not different between groups with the exception of major adult deformity ( p < 0.002). Thoracic trauma pedicle screws ( p < 0.005) and pedicle screws for deformity ( p < 0.001) were most likely to be malpositioned. Traumatic cervical screws were most likely to require subsequent admission and screw revision. Rates of adverse events were not significantly different between groups. Reoperation for instrumentation failure was significantly different (0 cases in the NAV group and 7 in the non-NAV cohort, p < 0.008). Conclusion Intraoperative 3D imaging with navigation provides an equally safe and more accurate and precise tool for pedicle screw placement than traditional techniques in adult spine surgery. Our data demonstrated a difference in the need for revision screw placement, particularly noted for deformity procedures. Considering the serious consequences of deviant screw position, the use of this technology provides a promising tool to increase patient safety and accuracy for hardware placement.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».