A Simpler, Modified Frailty Index Weighted by Complication Occurrence Correlates to Pain and Disability for Adult Spinal Deformity Patients

INTRODUCTION

Frailty, or vulnerability to adverse health outcomes, is gaining recognition as a key consideration in preoperative risk stratification and patient counseling. To quantify frailty, some clinicians have adopted a “deficit accumulation”–based approach, developing frailty indices that tally combinations of disabilities, comorbidities, and social situations associated with physiologic decline.^1,2 These frailty screening tools are validated in a number of patient populations and have been used in the adult spinal deformity (ASD) literature to identify patients at risk for adverse outcomes following deformity-corrective surgery.^3–5

Although there is no established consensus for detecting frailty in ASD patients, one of the most commonly cited ASD-specific frailty assessment tools is the 2017 Miller et al⁶ ASD frailty index (ASD-FI). Developed in a prospectively collected population of 450 ASD patients, the ASD-FI includes 40 distinct health deficits assessing physical disability, medical comorbidities, activities of daily living, mood, and cognition. A patient's ASD-FI score is generated by calculating the mean of expressed deficits, yielding a score from 0 to 1, with higher values indicating greater frailty. The ASD-FI has been externally validated in multiple databases, and it has been shown to correlate with length of hospital stay, incidence of proximal junctional kyphosis, risk of major complication, and risk of reoperation.^6–8

Despite the ASD-FI's validity as a risk assessment tool, its calculation requires a complete set of 40 variables, making it cumbersome to use in a clinical setting. Additionally, more than half of the 40 health deficits included in the ASD-FI stem from patient-reported outcome measures—some of which are not always available in a patient's chart or medical record. To address these problems, this study aims to crease a simpler, modified ASD frailty index (mASD-FI) that relies less on patient-reported outcomes. Instead of simply calculating the mean of all expressed frailty index health deficits, this study weights the component deficits by their overall contribution to the risk of adverse outcomes.

MATERIALS AND METHODS

RESULTS

DISCUSSION

During the last several decades, advances in technology and surgical techniques have allowed surgeons to treat ASD patients with increasingly complex pathologies and comorbidity profiles.^13,14 Given the increasing heterogeneity of patients undergoing ASD-corrective surgery, many studies in the ASD literature emphasize the importance of preoperative risk stratification, or the identification of patients likely to benefit from surgical treatment and patients likely to experience a complication.^15–17 Within this body of research, a number of studies have demonstrated the importance of frailty in the preoperative risk stratification process.^4,18 To quantify the frailty status of patients undergoing ASD-corrective surgery, Miller et al developed the ASD-FI, a frailty assessment tool that has since been validated in multiple databases as a predictor of longer hospital stay, complication risk, and risk of reoperation.^6–8 Despite its validity as a risk stratification tool, the ASD-FI may be impractical to use outside of a research setting because its calculation requires a complete set of 40 variables—some of which rely on multiple HRQL questionnaires not readily available in a patient's medical record. This study proposes a clinically practical, shorter, modified ASD frailty index.

Our results showed that together, 8 health deficits were responsible for 85.0% of the variation in ASD-FI score (Table 2). Because these 8 factors were able to predict a significant proportion of the variation in ASD-FI score, they were ultimately included in our final mASD-FI. Aside from the considerably shorter list of factors needed to calculate mASD-FI score, the mASD-FI constitutes an appreciable deviation from the Miller et al ASD-FI in that its component factors are weighted by their relationship to the incidence of medical complications. Regression coefficient–based weighting of comorbidity scores is common in the risk index literature.^19–21 Compared with other methodologies, the regression coefficient–based weighting of risk scores has demonstrated superior performance in predicting outcomes.¹¹ In weighting the component factors of our frailty index by their relationship to medical complications, we aim to make the mASD-FI more clinically relevant for risk stratification than existing, unweighted frailty indices.

Additionally, whereas calculating the Miller et al ASD-FI requires data from at least 4 separate HRQL questionnaires (SF-36v2, LSDI, SRS-22r, and ODI), calculating mASD-FI score only relies on data from a single questionnaire, the SF-36v2. Multiple studies in the spine literature highlight the administrative burden of HRQL assessments, and longer series of survey questions have been correlated with lower completion rates and lower overall quality of life.^22–24 Compared with the ASD-FI, the mASD-FI offers a lower administrative burden, making its calculation more practical in a clinical setting.

Although the mASD-FI requires fewer variables to calculate than previously published frailty indices, our results suggest that the shortened, 8-factor index is still sufficiently broad to capture a wide range of frailty states. Of a possible 21 points, patient mASD-FI scores in our population spanned from 0 to 18, with 70% of patients presenting as NF, 12% as frail, and 18% as SF. Although the Miller et al ASD-FI publication reports a slightly smaller proportion of “not frail” patients in their operative ASD population (41% NF, 35% frail, 24% SF), this discrepancy may be explained by the fact that our patient population included both operative and nonoperative ASD patients. Although there are few studies in the ASD literature investigating differences in frailty between operative and nonoperative patients, nonoperative ASD patients have been shown to be less comorbid, with significantly lower rates of depression and severe baseline malalignment.²⁵

Importantly, our results showed that increasing frailty status, as assessed by the mASD-FI, was associated with higher levels of baseline low back pain and disability, as assessed by both ODI and SRS-22r scores. This finding further suggests that the mASD-FI may serve as a valuable assessment of baseline physiologic decline and vulnerability; however, future studies should investigate the relationship between mASD-FI score and surgical outcomes.

Although weighting mASD-FI variables by their relationship to the incidence of medical complications pegs the frailty index directly to clinical outcomes, this should not lead one to conclude that the factors comprising the mASD-FI are directly related to risk of adverse events. Instead, these factors may be mediating variables that reflect the presence (or absence) of more severe conditions, which in turn may increase the likelihood of an adverse event—this is a key limitation in the interpretation of our frailty index. Our analysis is also limited by small sample size, which reduces the statistical power of our findings. Lastly, although developing the mASD-FI in a population of both operative and nonoperative ASD patients lends our index greater generalizability, additional research is necessary to fully validate the index's utility as a risk stratification tool.

CONCLUSION

This study modifies an existing ASD frailty index and proposes a weighted, shorter mASD-FI. The mASD-FI relies less on patient-reported variables, and it weights component factors by their contribution to adverse outcomes. Because increasing mASD-FI score is associated with inferior clinical measures of pain and disability, the mASD-FI may serve as a valuable tool for preoperative risk assessment.