Abstract
BACKGROUND AND OBJECTIVES:
Adult spinal deformity (ASD) surgery is associated with high rates of mechanical complications, including rod fracture, pseudarthrosis, and implant failure. Although frailty has emerged as a superior predictor of adverse outcomes compared with chronological age or comorbidity burden alone, its specific relationship with long-term mechanical complications remains incompletely characterized. This study evaluated whether preoperative frailty independently predicts the development of mechanical complications after ASD surgery.
METHODS:
This retrospective cohort study included consecutive patients who underwent long-segment ASD corrective surgery with minimum 24-month radiographic follow-up. Frailty was assessed using the 5-item modified Frailty Index (mFI-5). The primary outcome was the occurrence of mechanical complications (rod fracture, pseudarthrosis, or implant loosening). Secondary outcomes included medical complications, estimated blood loss, and hospital length of stay. Multivariable logistic regression was performed to determine the independent association between frailty and mechanical complications.
RESULTS:
A total of 185 patients were included, of whom 55 were frail (mFI-5 ≥3) and 130 were nonfrail (mFI-5 <3). Frail patients had significantly higher rates of overall hardware failure (50.9% vs 33.1%, P = .034), rod fracture (32.7% vs 16.2%, P = .020), and pseudarthrosis (41.8% vs 23.8%, P = .023). On multivariable logistic regression adjusting for age and body mass index, frailty remained an independent predictor of overall hardware failure (odds ratio 2.97, 95% CI, 1.47-6.00, P = .002), as well as rod fracture and pseudarthrosis. Frailty was not associated with medical complications, estimated blood loss, or hospital length of stay.
CONCLUSION:
Preoperative frailty is independently associated with mid- to long-term mechanical complications after ASD surgery. Routine incorporation of mFI-5 assessment into preoperative evaluation, combined with targeted bone-health optimization and frailty-adapted construct planning, may improve risk stratification and construct durability. Prospective multicenter studies are needed to validate whether multimodal interventions can reduce mechanical failure rates in frail patients.
KEY WORDS: Adult spinal deformity, Frailty, Mechanical complications, Modified Frailty Index, Pseudarthrosis, Rod fracture, Surgical outcomes
ABBREVIATIONS:
- ASD
adult spinal deformity
- EBL
estimated blood loss
- mFI-5
5-item modified Frailty Index.
Adult spinal deformity (ASD) is a common and disabling condition in the aging population, characterized by progressive coronal and sagittal malalignment that results in pain, functional limitation, and reduced health-related quality of life.1 With advances in surgical techniques and perioperative care, the number of corrective ASD procedures has increased substantially over the past 2 decades.2 Despite these improvements, these operations remain technically demanding and are associated with significant risk.3 Reported complication rates range from 34% to 70%, with reoperation rates of approximately 20% to 25% at 2-year follow-up.4
Mechanical complications—including rod fracture, pseudarthrosis, and implant loosening—represent a particularly important subset of adverse outcomes.5 These complications often occur in a delayed fashion (typically 6-24 months postoperatively), frequently lead to loss of sagittal correction, and are a leading cause of revision surgery.5 Reported rates of rod fracture after long-segment constructs range from 7% to 33%, whereas pseudarthrosis occurs in approximately 10% to 30% of patients, depending on surgical and patient-related factors.6
Traditional risk stratification in ASD surgery has relied on variables, such as chronological age, body mass index (BMI), and individual comorbidities.7 Although informative, these measures do not fully capture a patient's overall physiological reserve. Frailty is a multidimensional syndrome of decreased physiological reserve and increased vulnerability to stressors that has evolved as a response to the limitations of traditional risk scores.7 In spine surgery—particularly in complex ASD procedures—the 5-item modified Frailty Index (mFI-5) has emerged as a practical and objective tool that provides a more complete assessment of physiological vulnerability than age or comorbidity burden alone.8
Previous studies have demonstrated that frail patients undergoing ASD surgery experience higher rates of major complications, longer hospital stays, nonhome discharge, readmission, and reoperation compared with nonfrail patients.9 Frailty has also been associated with proximal junctional failure and wound-related complications and has been shown to outperform age and comorbidity burden in multivariable analyses.10 However, most existing studies have focused on short-term or composite outcomes, with fewer specifically evaluating the relationship between frailty and mid- to long-term mechanical complications such as rod fracture, pseudarthrosis, and implant failure.7
The aim of this study was to evaluate whether preoperative frailty, defined by mFI-5 score ≥3, independently predicts the development of mechanical complications after ASD surgery.
METHODS
Study Design and Patient Selection
This was a retrospective cohort study of patients who underwent surgical treatment of ASD with fusion ≥5 levels. Consecutive adult patients (age ≥18 years) who underwent posterior spinal instrumentation and fusion for ASD between 2016 and 2024 were included. ASD was defined by the following criteria: coronal Cobb angle ≥30°, C7 sagittal vertical axis ≥4 cm, coronal vertical axis ≥3 cm, pelvic tilt ≥25°, or thoracic kyphosis ≥60°. Patients with less than 24 months of clinical and radiographic follow-up or incomplete medical records were excluded. A total of 185 patients met the inclusion criteria and were included in the final analysis.
Ethical Statement
The study protocol was reviewed and approved by the Institutional Review Board (No. Pro00023643). Given the retrospective nature of the study and the use of deidentified patient data, the requirement for informed patient consent was waived by the Institutional Review Board.
Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Frailty Assessment
Preoperative frailty was evaluated using the mFI-5. Patients were classified as frail if their mFI-5 score was ≥3 and as nonfrail if their mFI-5 score was <3.9
Data Collection and Outcome Measures
Demographic data (age, sex, and BMI), comorbidities, surgical history, and perioperative variables were collected from electronic medical records.
The primary outcomes were mechanical complications, including any hardware failure, rod fracture, screw fracture, screw pullout, and pseudarthrosis. Medical complications included wound infection, deep vein thrombosis (DVT), pulmonary embolism, pneumonia, and sepsis. Secondary perioperative outcomes included estimated blood loss (EBL) and length of hospital stay.
Mechanical complications were diagnosed based on clinical presentation and confirmed with plain radiographs and computed tomography scans during the follow-up period.
Statistical Analysis
Continuous data are presented as mean ± SD and were compared between the frail and nonfrail groups using the Mann-Whitney U test. Categorical variables are presented as number (percentage) and were compared using the Fisher exact test. Univariate logistic regression was first performed to assess the association between frailty and individual complications. Multivariate logistic regression models were then constructed to evaluate whether frailty was an independent predictor of mechanical complications after adjusting for age and BMI. Odds ratios (OR) with 95% CI are reported. A P-value of <.05 was considered statistically significant. All statistical analyses were performed using SPSS version 28.0 (IBM Corp.).
RESULTS
Among 185 patients included in the study, 55 (29.7%) met criteria for frailty (mFI-5 ≥3), whereas 130 (70.3%) were classified as nonfrail. Baseline demographic and clinical characteristics are presented in Table 1. Frail patients were significantly older than nonfrail patients (66.3 ± 9.4 vs 63.1 ± 8.2 years, P = .011) and demonstrated a higher prevalence of comorbid conditions. Postoperative mechanical outcomes differed significantly according to frailty status. Frail patients (mFI-5 ≥3, n = 55) demonstrated significantly higher rates of mechanical complications compared with nonfrail patients (mFI-5 <3, n = 130). Specifically, frail patients had higher rates of rod fracture (32.7% vs 16.2%, P = .020), pseudarthrosis (41.8% vs 23.8%, P = .023), and overall hardware failure (50.9% vs 33.1%, P = .034). No significant differences were observed for screw fracture (3.6% vs 2.3%, P = .635) or screw pullout (23.6% vs 18.5%, P = .546).
TABLE 1.
Baseline Demographics and Clinical Characteristics by Frailty Group
| Variable | Overall (n = 185) | Nonfrail (n = 130) | Frail (n = 55) | P |
|---|---|---|---|---|
| Demographics | ||||
| Age (y) | 64.1 ± 8.7 | 63.1 ± 8.2 | 66.3 ± 9.4 | .011 |
| Male sex, n (%) | 101 (54.6) | 71 (54.6) | 30 (54.5) | 1.000 |
| BMI (kg/m2) | 29.9 ± 5.4 | 29.5 ± 5.5 | 31.0 ± 5.2 | .057 |
| Comorbidities | ||||
| Diabetes mellitus, n (%) | 39 (21.1) | 15 (11.5) | 24 (43.6) | <.001 |
| COPD, n (%) | 22 (11.9) | 5 (3.8) | 17 (30.9) | <.001 |
| CHF, n (%) | 6 (3.2) | 1 (0.8) | 5 (9.1) | .009 |
| History of MI, n (%) | 5 (2.7) | 0 (0.0) | 5 (9.1) | .002 |
| Surgical history | ||||
| Prior back surgery, n (%) | 116 (62.7) | 80 (61.5) | 36 (65.5) | .736 |
| Prior fusion, n (%) | 87 (47.0) | 61 (46.9) | 26 (47.3) | 1.000 |
| Perioperative | ||||
| Estimated blood loss (mL) | 840.7 ± 705.9 | 824.7 ± 687.1 | 878.8 ± 754.2 | .697 |
| Length of stay (d) | 9.3 ± 4.7 | 9.1 ± 4.4 | 9.7 ± 5.2 | .422 |
BMI, body mass index; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disorder; MI, myocardial infarction.
Values are mean ± SD or n (%). P values from the Mann-Whitney U test (continuous) or Fisher exact test (categorical). P values indicate statistical significance (P < .05).
Regarding medical complications, no statistically significant differences were observed between frail and nonfrail patients. Rates of wound infection (5.5% vs 7.7%, P = .758), DVT (10.9% vs 9.2%, P = .787), pulmonary embolism (0.0% vs 0.8%, P = 1.000), pneumonia (3.6% vs 0.8%, P = .211), and overall medical complications (20.0% vs 16.9%, P = .772) were comparable. No cases of sepsis were reported in either group.
Secondary outcomes, including EBL (878.8 ± 754.2 vs 824.7 ± 687.1 mL, P = .697) and length of hospital stay (9.7 ± 5.2 vs 9.1 ± 4.4 days, P = .422), were similar between groups (Table 2).
TABLE 2.
Complication Rates by Frailty Group
| Variable | Overall (n = 185) | Nonfrail (n = 130) | Frail (n = 55) | P |
|---|---|---|---|---|
| Mechanical complications | ||||
| Any hardware failure, n (%) | 71 (38.4) | 43 (33.1) | 28 (50.9) | .034 |
| Rod fracture, n (%) | 39 (21.1) | 21 (16.2) | 18 (32.7) | .020 |
| Screw fracture, n (%) | 5 (2.7) | 3 (2.3) | 2 (3.6) | .635 |
| Screw pullout, n (%) | 37 (20.0) | 24 (18.5) | 13 (23.6) | .546 |
| Pseudarthrosis, n (%) | 54 (29.2) | 31 (23.8) | 23 (41.8) | .023 |
| Medical complications | ||||
| Any medical complication, n (%) | 33 (17.8) | 22 (16.9) | 11 (20.0) | .772 |
| Wound infection, n (%) | 13 (7.0) | 10 (7.7) | 3 (5.5) | .758 |
| DVT, n (%) | 18 (9.7) | 12 (9.2) | 6 (10.9) | .787 |
| Pulmonary embolism, n (%) | 1 (0.5) | 1 (0.8) | 0 (0.0) | 1.000 |
| Pneumonia, n (%) | 3 (1.6) | 1 (0.8) | 2 (3.6) | .211 |
| Secondary outcomes (mean ± SD) | ||||
| Total EBL (mL) | 840.7 ± 705.9 | 824.7 ± 687.1 | 878.8 ± 754.2 | .697 |
| LOS (d) | 9.3 ± 4.7 | 9.1 ± 4.4 | 9.7 ± 5.2 | .422 |
DVT, deep vein thrombosis; EBL, estimated blood loss; LOS, length of hospital stay.
Values are presented as number (percentage). P-values were calculated using the Fisher exact test. P-values indicate statistical significance (P < .05).
On univariate analysis, frailty was significantly associated with any hardware failure (OR, 2.10, 95% CI, 1.10-3.99, P = .031), rod fracture (OR, 2.53, 95% CI, 1.21-5.25, P = .017), and pseudarthrosis (OR, 2.30, 95% CI, 1.17-4.49, P = .021). Frailty was not significantly associated with any medical complication (OR, 1.23, 95% CI, 0.55-2.74, P = .676) or DVT (OR, 1.20, 95% CI, 0.43-3.39, P = .787) (Table 3).
TABLE 3.
Univariate ORs for Frailty (5-Item Modified Frailty Index ≥3) and Postoperative Complications
| Complication | OR | 95% CI | P |
|---|---|---|---|
| Any hardware failure | 2.10 | 1.10-3.99 | .031 |
| Rod fracture | 2.53 | 1.21-5.25 | .017 |
| Screw fracture | 1.60 | 0.26-9.84 | .635 |
| Screw pullout | 1.37 | 0.64-2.93 | .546 |
| Pseudarthrosis | 2.30 | 1.17-4.49 | .021 |
| Any medical complication | 1.23 | 0.55-2.74 | .676 |
| Wound infection | 0.69 | 0.18-2.62 | .758 |
| DVT | 1.20 | 0.43-3.39 | .787 |
DVT, deep vein thrombosis; OR, odds ratio.
P values from the Fisher exact test. P values indicate statistical significance (P < .05).
On multivariable logistic regression, frailty (mFI-5 ≥3) was an independent predictor of any hardware failure after adjusting for age and BMI (OR, 2.97, 95% CI, 1.47-6.00, P = .002). Frailty also independently predicted rod fracture (OR, 2.98, 95% CI, 1.39-6.39, P = .005) and pseudarthrosis (OR, 2.47, 95% CI, 1.24-4.92, P = .010), but not screw pullout (OR, 1.52, 95% CI, 0.69-3.31, P = .297) (Table 4).
TABLE 4.
Multivariate Logistic Regression Analysis of Predictors of Mechanical Complications
| Variable | OR | 95% CI | P | R2 |
|---|---|---|---|---|
| Any hardware failure (n = 185, e = 71) | 0.079 | |||
| Frailty (mFI ≥3) | 2.97 | 1.47-6.00 | .002 | |
| Age (y) | 0.95 | 0.91-0.99 | .010 | |
| BMI (kg/m2) | 0.91 | 0.86-0.97 | .005 | |
| Rod fracture (n = 185, e = 39) | 0.056 | |||
| Frailty (mFI ≥3) | 2.98 | 1.39-6.39 | .005 | |
| Age (y) | 0.96 | 0.92-1.00 | .034 | |
| Pseudarthrosis (n = 185, e = 54) | 0.032 | |||
| Frailty (mFI ≥3) | 2.47 | 1.24-4.92 | .010 | |
| Age (y) | 0.98 | 0.94-1.02 | .253 | |
| Screw pullout (n = 185, e = 37) | 0.016 | |||
| Frailty (mFI ≥3) | 1.52 | 0.69-3.31 | .297 | |
| Age (y) | 0.97 | 0.93-1.01 | .121 | |
BMI, body mass index; mFI, modified Frailty Index; OR, odds ratio; R2, Nagelkerke pseudo R-squared.
P values indicate statistical significance (P < .05).
Given the baseline differences in comorbidities between frail and nonfrail patients, univariate and multivariate logistic regression analyses were performed to identify independent predictors of any hardware failure. Additional factors associated with increased risk included hypertension requiring medication (OR, 2.07; 95% CI, 1.10-3.88; P = .023), peripheral vascular disease or rest pain (OR, 2.68; 95% CI, 1.19-6.01; P = .017), and impaired sensorium (OR, 2.26; 95% CI, 1.14-4.48; P = .019) (Table 5).
TABLE 5.
Univariate Logistic Regression Analysis of Individual Risk Factors for Any Hardware Failure
| Variable | OR | 95% CI | P |
|---|---|---|---|
| Comorbidities | |||
| Diabetes mellitus | 1.72 | 0.84-3.51 | .137 |
| COPD | 1.13 | 0.46-2.79 | .795 |
| CHF | 0.80 | 0.14-4.47 | .797 |
| History of MI | 2.47 | 0.40-15.16 | .329 |
| Nonindependent functional status | 0.81 | 0.37-1.80 | .609 |
| PCI/cardiac surgery/angina | 1.68 | 0.80-3.53 | .171 |
| HTN on medication | 2.07 | 1.10-3.88 | .023 |
| PVD or rest pain | 2.68 | 1.19-6.01 | .017 |
| Impaired sensorium | 2.26 | 1.14-4.48 | .019 |
| TIA/CVA without deficit | 0.87 | 0.43-1.72 | .680 |
| CVA with deficit | 3.34 | 0.60-18.75 | .170 |
| Surgical history | |||
| Prior back surgery | 0.78 | 0.43-1.44 | .431 |
| Prior fusion | 0.73 | 0.40-1.33 | .305 |
CVA, cerebrovascular accident; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disorder; HTN, hypertension; MI, myocardial infarction; OR, odds ratio; PCI, percutaneous coronary intervention; PVD, peripheral vascular disease; TIA, transient ischemic attack.
Variables with P < .05 on univariate analysis were entered into the multivariate model (Table 6).
Multivariate model was constructed to account for potential confounding by comorbidities. The model incorporating individual comorbidities, hypertension requiring medication (OR, 2.09; 95% CI, 1.07-4.08; P = .030), and peripheral vascular disease/rest pain (OR, 2.47; 95% CI, 1.05-5.79; P = .037) remained independent predictors of hardware failure.
These findings indicate that the association between frailty and hardware failure remained significant after adjustment for age and BMI, whereas model incorporating individual comorbidities identified additional independent predictors (Table 6).
TABLE 6.
Multivariate Logistic Regression Models for Any Hardware Failure
| Variable | OR | 95% CI | P | R2 |
|---|---|---|---|---|
| Individual comorbidities (n = 185, events = 71) | ||||
| HTN on medication | 2.09 | 1.07-4.08 | .030 | 0.082 |
| PVD or rest pain | 2.47 | 1.05-5.79 | .037 | |
| Impaired sensorium | 1.76 | 0.86-3.59 | .121 | |
HTN, hypertension; OR, odds ratio; PVD, peripheral vascular disease; R2, Nagelkerke pseudo R-squared.
Model A includes individual comorbidities significant on univariate analysis.
Age-stratified subgroup analyses were performed to evaluate whether the effect of frailty varied across age groups. The association between frailty and hardware failure was most pronounced among patients aged 65 years or older, where frail patients had significantly higher odds of hardware failure compared with nonfrail patients (OR, 2.86; 95% CI, 1.20-6.86; P = .027). No significant association was observed in patients aged younger than 65 years, although trends toward increased risk were observed. The association between frailty and pseudarthrosis was particularly evident among patients aged 65 years or older (OR, 3.60; 95% CI, 1.41-9.16; P = .009), suggesting that the impact of frailty on delayed mechanical complications may be amplified in older patients (Table 7).
TABLE 7.
Subgroup Analysis of Frailty and Hardware Failure
| Age group | n | Frail (%) | Nonfrail (%) | OR | 95% CI | P |
|---|---|---|---|---|---|---|
| Effect of frailty on any hardware failure by age group | ||||||
| <55 | 21 | 3/5 (60.0) | 9/16 (56.2) | 1.17 | 0.15-9.01 | 1.000 |
| 55-65 | 71 | 6/15 (40.0) | 17/56 (30.4) | 1.53 | 0.47-4.98 | .541 |
| ≥65 | 93 | 19/35 (54.3) | 17/58 (29.3) | 2.86 | 1.20-6.86 | .027 |
| Effect of frailty on rod fracture by age group | ||||||
| <55 | 21 | 3/5 (60.0) | 5/16 (31.2) | 3.30 | 0.41-26.37 | .325 |
| 55-65 | 71 | 4/15 (26.7) | 7/56 (12.5) | 2.55 | 0.63-10.24 | .228 |
| ≥65 | 93 | 11/35 (31.4) | 9/58 (15.5) | 2.50 | 0.91-6.83 | .116 |
| Effect of frailty on pseudarthrosis by age group | ||||||
| <55 | 21 | 2/5 (40.0) | 6/16 (37.5) | 1.11 | 0.14-8.68 | 1.000 |
| 55-65 | 71 | 5/15 (33.3) | 14/56 (25.0) | 1.50 | 0.44-5.14 | .525 |
| ≥65 | 93 | 16/35 (45.7) | 11/58 (19.0) | 3.60 | 1.41-9.16 | .009 |
OR, odds ratio.
DISCUSSION
In this retrospective cohort study of 185 patients undergoing long-segment ASD surgery, preoperative frailty was independently associated with significantly higher rates of mechanical complications and overall hardware failure, even after adjustment for age and BMI. Frail patients experienced markedly elevated risks of rod fracture (32.7% vs 16.2%) and pseudarthrosis (41.8% vs 23.8%), resulting in an overall hardware failure rate of 50.9% compared with 33.1% in nonfrail patients. Yet, they showed no increase in medical complications or perioperative parameters, such as EBL or hospital length of stay. This differential impact—where frailty predominantly manifests as delayed structural and mechanical failure rather than acute systemic events—represents the central and most clinically relevant finding of this study. It suggests that frailty exerts its strongest influence on mid- to long-term construct durability and biologic healing, rather than on immediate postoperative resilience, and underscores the importance of distinguishing between these 2 distinct domains of surgical risk in ASD patients.
Several mechanisms likely underlie frailty's selective effect on mechanical complications. Frail individuals commonly exhibit sarcopenia, reduced bone mineral density, impaired osteoblast function, and chronic low-grade inflammation, all of which compromise fusion biology and weaken the bone-implant interface.11 These deficits predispose to pseudarthrosis and screw-related failures, while diminished paraspinal muscle support increases cyclic loading on instrumentation, promoting rod fracture in long-segment constructs.12 Recent evidence has also demonstrated that preoperative sarcopenia and paraspinal myosteatosis, particularly at the upper instrumented vertebra, are independent predictors of proximal junctional kyphosis after long-segment spinal fusion for ASD.13 The simultaneous elevation of multiple mechanical failure modes (rod fracture, pseudarthrosis, and overall hardware failure) observed in frail patients in this cohort supports the notion that frailty impairs both biologic and biomechanical aspects of spinal reconstruction. Unlike chronological age or isolated comorbidities, the mFI-5 captures this cumulative physiological vulnerability in a manner that directly correlates with the structural demands of complex ASD correction.7
In striking contrast, frailty was not associated with medical complications in this series. Contemporary perioperative management protocols—including optimized fluid management, infection prevention bundles, and thromboprophylaxis—appear effective at mitigating short-term physiological stresses, even in physiologically vulnerable patients.14 However, these same interventions do little to address the persistent impairments in tissue regeneration, bone quality, and muscle function that drive delayed structural complications typically occurring between 6 and 24 months after surgery.15 This dissociation between preserved short-term medical safety and compromised long-term construct durability is an important observation that distinguishes this study from many previous reports that have primarily examined composite or early complications.16 It highlights a critical gap in current risk-stratification paradigms for ASD surgery, where frailty's long-term effects may be underappreciated if only short-term outcomes are considered.17
These findings align with and extend the existing literature on frailty in ASD surgery.16 Systematic reviews and large cohort studies have consistently demonstrated that frail patients experience higher overall complication rates, readmissions, and reoperations, with frailty indices often outperforming chronological age or comorbidity burden as predictors.10 More recent work has begun to link frailty specifically to mechanical complications and proximal junctional failure; however, few studies have isolated the delayed structural consequences or explicitly contrasted them with medical events.18 By focusing on a minimum 24-month radiographic follow-up and specific mechanical end points (rod fracture, pseudarthrosis, and hardware failure), the current analysis highlights frailty's role as a key determinant of construct longevity beyond the perioperative period and adds granularity to the growing body of evidence, supporting frailty as a superior risk-stratification tool in complex spine surgery.
From a clinical perspective, these results strongly support routine preoperative mFI-5 assessment in ASD surgical planning.9 Early identification of frail patients enables improved risk stratification, more informed shared decision making, and tailored strategies—including pharmacological and nutritional bone-health optimization, structured prehabilitation programs to combat sarcopenia, and frailty-adapted construct modifications such as multirod constructs or enhanced pelvic fixation—to enhance long-term durability.8 Implementing such frailty-specific pathways could meaningfully reduce revision rates and improve patient-reported outcomes in this high-risk population. Prospective multicenter trials are warranted to determine whether these targeted interventions can translate into lower mechanical failure rates.
Limitations
This study has limitations inherent to its retrospective, single-center design, including potential selection bias and unmeasured confounding. Although multivariable models adjusted for age and BMI, other important risk factors for mechanical complications—such as bone mineral density/osteoporosis, smoking status, osteotomy type and grade, use of pelvic fixation, exact construct length, and specific implant characteristics—could not be included. Some of these variables may be partially captured within the mFI-5 itself, but residual confounding cannot be excluded. Strengths of the study include the relatively large cohort size, standardized frailty threshold, consistent minimum 24-month radiographic follow-up, and focused evaluation of mid- to long-term mechanical outcomes rather than composite endpoints.
In summary, preoperative frailty is a robust independent predictor of delayed mechanical complications after ASD surgery. By emphasizing frailty's disproportionate effect on structural healing and construct durability rather than short-term medical events, this study provides a more nuanced framework for preoperative counseling, surgical decision making, and future research in this challenging patient population.
CONCLUSION
In conclusion, preoperative frailty is a robust independent predictor of mechanical complications after ASD surgery. These results reinforce frailty assessment as an essential component of preoperative risk stratification and highlight the need for frailty-specific optimization protocols and surgical techniques in this vulnerable population. Prospective, multicenter trials are warranted to validate these observations and evaluate whether targeted interventions can meaningfully reduce mechanical failure rates in frail patients undergoing ASD correction.
Acknowledgments
The authors would like to acknowledge all clinical staff and research personnel involved in the care and follow-up of patients included in this study. Author contributions: Atef F. Hulliel: Conceptualization, study design, data analysis, statistical interpretation, manuscript drafting, and critical revision of the manuscript. Dana Saleh: Data collection, literature review, manuscript preparation, and critical revision of the manuscript. Ahmad Zayd Alkadri: Data collection, manuscript preparation, literature review, and critical revision of the manuscript. Vito Evola: manuscript preparation, critical revision of the manuscript. Mohsen Rostami, Patrick Kim: Data interpretation and critical revision of the manuscript. Puya Alikhani: Supervision, study guidance, and critical revision of the manuscript. All authors reviewed and approved the final version of the manuscript.
Contributor Information
Dana Saleh, Email: danasaleh@usf.edu.
Ahmad Zayd Alkadri, Email: azalkadri@usf.edu.
Vito Evola, Email: ve159@mynsu.nova.edu.
Mohsen Rostami, Email: mohsenrostami@usf.edu.
Patrick Kim, Email: pkim@usf.edu.
Puya Alikhani, Email: palikhan@usf.edu.
Funding
This study did not receive any funding or financial support.
Disclosures
The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.