Comparing risk stratification indices in predicting perioperative adverse events following posterior atlantoaxial and occipitocervical fusion

Le résumé fourni par la source

OBJECTIVE: Craniocervical instability often requires surgical stabilization through atlantoaxial fusion (AAF) or occipitocervical fusion (OCF), procedures commonly performed in older adults and/or patients with poor functional status and multiple comorbidities. Despite the high-risk nature of this patient population, there are limited data on perioperative risk stratification. Thus, authors of this study aim to assess the ability of an 11-item modified frailty index (mFI-11) and the Charlson Comorbidity Index (CCI) to predict adverse events (AEs) following AAF and OCF. METHODS: Adult patients without prior surgery who underwent AAF or OCF between 2009 and 2023 were eligible for inclusion in this retrospective study. The perioperative AEs analyzed were major complications, nonhome discharge, and prolonged length of stay (LOS). Univariable and multivariable logistic regression analyses, as well as receiver operating characteristic curve analysis, were used to determine which index best predicted these AEs. RESULTS: Among the 219 patients included in this study, most of whom were female (60.7%), the median age was 71.5 years, and 45.2% of patients were 60-69 years old. The median LOS was 6 days, with 27.4% of patients staying ≥ 10 days. Major complications occurred in 16.9% of patients, and 37.4% of the patients were not discharged to home. The median mFI-11 was 1, and the most frequent score was 1 (32.4% of patients). The median CCI was 4, and the most frequent score was ≥ 5 (38.4% of patients). In the multivariable analysis, neither risk index was independently associated with a major complication or prolonged LOS; however, the mFI-11 score was associated with increased odds of predicting a nonhome discharge (OR 1.8, p = 0.003). ROC curve analysis revealed that both the mFI-11 and CCI showed modest but similar discriminative ability in predicting major complications (area under the curve [AUC] 0.633 vs 0.636, respectively). For nonhome discharge, the mFI-11 had slightly stronger discriminative ability (AUC 0.645 vs 0.602, respectively). Neither index had strong discriminative ability in predicting prolonged LOS (AUC 0.576 vs 0.597, respectively). CONCLUSIONS: The mFI-11 demonstrated a slight advantage over the CCI in identifying AEs according to ROC analysis, yet neither index independently predicted major complications or prolonged LOS in the multivariable analysis. However, a higher mFI-11 score was associated with increased odds of predicting a nonhome discharge. While the mFI-11 may offer slightly greater clinical utility in predicting AEs following AAF and/or OCF, neither index alone is sufficient to determine surgical candidacy.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.