DOI: 10.1097/nor.0000000000001225 ISSN: 0744-6020
Frailty Index and Prognostic Nutritional Index Jointly Predict Hip Fracture Prognosis in Older Adults
ChuanQiang Dai, YouShu Zhang, GuiFang Wu, Yao Zhang, Yao Dong
Objective:
To evaluate the combined predictive value of the frailty index (FI) and prognostic nutritional index (PNI) for prognosis in elderly hip fracture patients.
Methods:
Clinical data from 110 elderly hip fracture patients were prospectively analyzed with 1-year postoperative follow-up. Patients were stratified into survival (
n
= 76) and non-survival (
n
= 34) groups based on outcomes. Collected parameters included demographic characteristics, fracture patterns, treatment modalities, and laboratory indices. Receiver operating characteristic curve analysis assessed the predictive efficacy of FI and PNI individually and combined. Optimal cutoff values were determined for patient stratification. Kaplan–Meier analysis evaluated 1-year survival rates, while Cox proportional hazards modeling identified prognostic factors.
Results:
Significant intergroup differences (
P
< .05) were observed for body mass index, intraoperative transfusion rates, American Society of Anesthesiologists classification, frailty prevalence, FI values, lymphocyte counts, albumin levels, and C-reactive protein (CRP). The nonsurvival group demonstrated significantly lower PNI (
P
< .05). Receiver operating characteristic analysis yielded area under the curve values of 0.713 (FI), 0.782 (PNI), and 0.816 (combined). Patients with high FI/low PNI showed the poorest 1-year survival. Multivariate analysis identified decreased lymphocyte counts and PNI, along with elevated CRP and FI, as independent risk factors for adverse outcomes (
P
< .05).
Conclusion:
The FI–PNI combination provides superior prognostic accuracy for elderly hip fracture patients, reflecting comprehensive pathophysiological changes. Key independent risk factors include lymphopenia, hypoalbuminemia, elevated CRP, and increased FI. Routine frailty and nutritional assessments should guide personalized care plans to optimize outcomes.