KEY POINTS Multiple frailty screening tools have been used for neurosurgical patients, each with advantages and disadvantages. Frailty is associated with worse postoperative outcomes including complications, length of stay, and mortality after both spinal and intracranial neurosurgery. Some neurosurgical procedures (eg, spine deformity surgery) may improve frailty postoperatively. Further research is required to understand how outcomes for frail patients undergoing neurosurgery can be improved.

The world is experiencing an aging population. Currently, there are over 703 million people worldwide aged over 65 years of age, projected to reach 1.5 billion by 2050.1 Advances in anesthetic and surgical techniques have allowed elderly and potentially frail patients to undergo neurosurgical procedures that might otherwise have been too risky. As a result, neuroanesthesiologists are increasingly likely to encounter frail patients in their daily practice and need to understand the impact of frailty on postoperative outcomes to offer optimal clinical care to this complex surgical population.2

Frailty is a complex and multidimensional concept first defined by Fried et al3 in 2001 as an age-related syndrome of physiological decline. Frailty is a marker of fragility and is characterized by diminished physiological reserve and vulnerability to adverse health outcomes in general. For the frail patient, even a minor change in health status, let alone a major neurosurgical procedure, may result in an inability to return to their prestress or presurgery baseline function. Therefore, a frail elderly person with exhausted physiological and neurological reserve is much more likely to have debilitating effects after surgery, with a reduced probability of recovering their independence (Fig. 1).

FIGURE 1: Simplified trajectory of recovery for frail and non-frail patients after surgical procedures. Frail patients (red line) have greater disability at baseline than non-frail patients (blue line), and a greater risk of experiencing complications and increases in disability in the first 3 months after surgery. However, after 12 months, the majority of patients with frailty experience improvement in disability from baseline status (red dotted line), unlike non-frail patients. Importantly, a minority of frail patients experienced a progressive increase in disability over the year after surgery (red dashed line). Adapted and modified from the results of McIsaac et al, 2020.4 Adaptations are themselves works protected by copyright. So in order to publish this adaptation, authorization must be obtained both from the owner of the copyright in the original work and from the owner of the copyright in the translation or adaptation.

This review summarizes the tools available to measure frailty in the neurosurgical population and the prevalence of frailty in both spine and intracranial surgical cohorts. Current evidence on the relationship of frailty with postoperative outcomes, and interventions to improve outcomes, will also be discussed. Finally, areas to focus future research are outlined.

MEASUREMENT OF FRAILTY IN NEUROSURGICAL PATIENTS

Despite its widely accepted definition, frailty is measured and screened using a variety of measurement tools in both clinical practice and research. The 2 main models of frailty are the deficit accumulation and phenotypic approaches. The deficit accumulation approach postulates that health deficits accumulate as people age and that greater deficits confer greater risk.5 Therefore, frailty results from the accumulation of these deficits and may be disproportionate to age. In contrast, the frailty phenotype proposes that comorbidity is an etiological risk factor for frailty, and disability results from frailty, although frailty is not synonymous with either of these.3 This distinct clinical frailty syndrome, which has been validated to predict patient outcomes, includes weakness, slowness, low levels of physical activity, exhaustion, and weight loss.3

Frailty measurement tools, including those with specific application to neurosurgical populations, are summarized in Table 1. Each tool has distinct advantages and disadvantages, and not all have been specifically validated for use in neurosurgical populations. The modified Frailty Index (mFI)7 and the 5-factor mFI (mFI-5)8 are simplified versions of the Frailty Index (FI) commonly used in administrative or large databases, similar to the Risk Analysis Index.9 The Clinical Frailty Scale6 has been recommended for surgical populations given its ease of use, practical nature, and excellent predictive ability.12 Frailty tools that have been validated for specific spine pathologies include the “Adult Spinal Deformity FI”11 and the “Metastatic Spinal Tumor FI.”10 In contrast, no specific validated frailty tools for surgical patients with intracranial pathology were identified in the current literature.

TABLE 1 - The Advantages and Disadvantages of the Most Common Frailty Measurement Tools, Including Those With Specific Application to Neurosurgical Populations Frailty tool Description Advantages Disadvantages General assessment tools  Clinical Frailty Scale (CFS)6 Categorizes an individual using descriptors and pictograms to assess the level of vulnerability, with a range from 1 (very fit) to 9 (terminally ill) • Good predictive capacity for adverse health effects and postoperative outcomes
• Useful screening tool
• Quick and easy to use • Subjective
• Oversimplifies diagnostic process leading clinicians to disregard the need for comprehensive geriatric assessment
• Not multidimensional
• Less useful when assessing patients with advanced dementia  CSHA Frailty Index (FI)5 A deficit accumulation model, including 70 items, derived from the CSHA. Sum number of positive outcomes and divide by 70. A score >0.21 indicates frailty • Strong predictive validity
• Can be generated by any health care data
• Expressed as a continuous scale
• Both self-reported and measured items • Time-consuming
• Not practical for a clinical environment  Frailty phenotype3 Five functional measures—unintentional weight loss, self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity.
• Frailty defined by 3/5 criteria • Validated from the cardiovascular health study and for surgical populations
• Closely related to sarcopenia, immune dysfunction, and adverse health outcomes
• Less time-consuming than FI • Only limited items were evaluated so not a comprehensive assessment
• Difficult to work out causal relationships between the risk domains
• Still labor-intensive  NSQIP 11-point Modified Frailty Index (mFI)7 Maps some of the FI criteria to the NSQIP database to create an 11-point mFI • Uses factors that are easily available in the clinical setting
• Convenient and simpler than the original FI
• A practical approach to measuring frailty in other national databases • Contains variables that are no longer reported in the NSQIP database (as of 2012)
• Possible that erroneous inferences could be made that cannot be supported by existing data
• Not created using a validated method  NSQIP 5-point Modified Frailty Index (mFI)8 As of 2012, the NSQIP no longer reports many of the comorbidities used to calculate the mFI. The 5i-mFI was created based on the remaining mFI variables available in the NSQIP database • Contains elements available in the medical record and large administrative databases
• Good correlation between 5 and 11-point mFI across surgical subspecialties, including neurosurgery • Based on the remaining mFI variables in the NSQIP database, rather than any clinical or scientific evidence of the variables' strength in representing true frailty
• Largely consists of comorbid conditions rather than true phenotypic frailty  Risk Analysis Index (RAI)9 14-item instrument that can be calculated prospectively (RAI-C), using a clinical questionnaire, or retrospectively (RAI-A), using variables from the surgical quality improvement databases (Veterans Affairs or NSQIP) • Predictive ability on a par with other tools
• RAI-C could be a rapid, cost-effective way to preoperatively screen entire elective surgery populations
• More effective than previously used frailty tools for patients for brain tumor surgery • RAI-C uses clinical judgment and may be subject to bias
• Needs further validation in non-veteran community populations Neurosurgery-specific assessment tools  Metastatic Spinal Tumor Frailty Index (MSTFI)10 Includes 7 comorbid conditions (anemia, chronic lung disease, coagulopathy, electrolyte abnormality, pulmonary and circulation disorders, renal failure, and malnutrition), and 2 additional variables (nature of admission and surgical approach) • May specifically predict the risk of major in-hospital complications and mortality in patients having surgery for spinal metastases
• Uses data available in national databases
• Spine-specific • The 2 additional variables could make it more of a risk prediction score than a measure of frailty specifically
• Largely consists of comorbid conditions rather than true phenotypic frailty
• External validation revealed low model discrimination—might not yet be generalizable  Adult Spinal Deformity Frailty Index (ASD-FI)11 An accumulating deficits model using 40 binary variables. The mean score of all deficits was calculated, resulting in a FI ranging from 0 to 1. Scores of 0.3-0.5 considered frail; >0.5 severely frail • Created using a validated method
• Strong correlation to other frailty measures
• Spine-specific • Impractical
• Clinical applicability limited as requires documentation of 40 variables
• Not weighted by variable

ASD indicates adult spinal deformity; CSHA, Canadian Study of Health and Ageing; FI, Frailty Index; 5i-mFI, 5-item modified Frailty Index; mFI, modified Frailty Index; MST, metastatic spinal tumor; NSQIP, National Surgical Quality Improvement Program; RAI, Risk Analysis Index; RAI-A, Administrative Risk Analysis Index; RAI-C, Clinical Risk Analysis Index.

PREVALENCE OF FRAILTY IN NEUROSURGICAL POPULATIONS

Many neurosurgical pathologies are seen more frequently in older patients, bringing associated frailty to elderly surgical populations. Examples include benign and malignant intracranial neoplasms, falls causing head injury and intracranial bleeding, spinal fractures secondary to reduced bone density, and degenerative spine disease.13 Frailty is increasing in the overall surgical population, with a 30% prevalence in nononcologic surgery in older adults and higher in patients with cancer.14

Frailty prevalence varies depending on the neurosurgical population surveyed, likely due to the use of different frailty assessment tools, as well as population differences, including age distribution. In a recent systematic review, 20% to 40% of metastatic spinal tumor patients, 12% to 56% of adult spine deformity patients, and 10% to 83% of degenerative spine disease patients were frail.15 In patients with brain tumors, the prevalence of frailty also varied widely, with a 5% to 15% prevalence in patients over 65 years of age,16 and up to 57% in patients over 80 years of age.17 In another systematic review, frailty also varied by tumor subtype; the lowest prevalence was observed in pituitary tumor resection (1.5%), rising to 8.2% for other intracranial tumors excluding pituitary, and to as high as 55% for intracranial meningiomas.18 Finally, a recent systematic review found that ~30% of patients with aneurysmal subarachnoid hemorrhage (SAH) were frail.19

RELATIONSHIP BETWEEN FRAILTY AND POSTOPERATIVE OUTCOMES

The importance of understanding the relationship between frailty and postoperative outcomes has been a focus in the recent literature. Previous studies have consistently shown that frailty in patients undergoing intracranial neurosurgery and spine surgery is associated with poor outcomes,15,18 including higher mortality, complication and reoperation rates, longer hospital length of stay, non–home discharge disposition, readmission rates, and overall costs. Interestingly, one study highlighted a significantly increased risk of acute short-term postoperative complications in frail geriatric patients undergoing cranial surgery for primary central nervous system neoplasm, but no difference in long-term complications at readmission time points.20

Using a variety of definitions, frailty has been correlated with clinically important outcomes (mortality, survival, complications, length of stay, costs, discharge disposition, and readmission) after intracranial surgery, with mFI-5 being the most commonly used measurement tool.18 Other syntheses of the literature have attempted to examine the effects of frailty based on different tumor subtypes, given that each has a unique trajectory and prognosis. In a recent systematic review, the relationship between frailty and outcomes differed between brain tumor subtypes in subtle ways, highlighting that analyzing all tumor types together may underestimate the prognostic value of frailty.21

Glioblastoma

In the aforementioned systematic review, Qureshi et al21 identified 16 recent studies focused on glioblastoma and reported significant relationships between frailty and overall survival, extended hospital lengths of stay, postoperative complications, and extra-familial aid postdischarge. Some authors have argued that elderly patients with significant comorbidity may be less likely to tolerate surgery or adjuvant chemotherapy, and may also be less likely to be offered aggressive treatment, both of which may contribute to worse prognoses for this demographic.22 A recent study suggested that frailty should not hinder offering treatment as elderly patients with low Karnofsky Performance Status scores (a percentage-based score classifying patients as to their level of functional impairment) can still show significant improvement postoperatively.23 However, the lack of validated frailty tools together with the highly progressive nature of malignant brain tumors makes the role of using frailty to guide care in this population unclear at this time.

Intracranial Meningioma

Studies have indicated that higher mFI scores are independently associated with overall postoperative morbidity and mortality in patients with meningioma.21 Kuwabara et al24 found that an mFI-5 score of 2 or more predicted poor outcomes in older patients better than chronological age.24 Another study in patients who underwent skull base meningioma resection found similar perioperative complications in older compared with younger patients, though worse baseline functional status was predictive of complications.25 Among all intracranial tumor types, frailty is an important risk factor for poor outcomes and frailty assessment should be part of the preoperative evaluation.

Chronic Subdural Hemorrhage

Frailty predicts worse outcomes for patients undergoing surgical drainage of chronic subdural hemorrhage, including higher major complication rates, non–home discharge, and 30-day mortality.26,27 In terms of choice of frailty assessment tools, the Clinical Frailty Scale may be a superior predictor of worse functional outcomes after chronic subdural hemorrhage than the mFI.28 In contrast, the initial Glasgow Coma Scale score was a better predictor of mortality and discharge disposition than age or frailty in patients with acute subdural hematoma in one study.29 Due to the preliminary nature of these analyses, the prognostic value of frailty indices requires further validation in this patient population.

Cerebral Aneurysm

Frailty has been shown to be similarly predictive of worse outcomes after intracranial aneurysm surgery. A simplified measure of frailty (eg, mFI-5) was an independent predictor of in-hospital complications after surgery for unruptured cerebral aneurysms and was a more useful predictor of postoperative outcome in younger patients (<75 y of age) compared with chronological age.24 In another retrospective study of patients with angiogram-negative SAH, frailty was a better predictor of mortality and discharge to home compared with both the Hunt-Hess and Fisher scores.30 However, frailty did not predict mortality after aneurysmal SAH.19 Frailty may, therefore, have a role in some aspects of prognostication in these populations, although prospective validation is needed and represents a key challenge for surgical decision-making.31

Spine Surgery

As with intracranial procedures, frailty has consistently been shown to predict adverse events, discharge destination, and mortality in spine surgery patients using a variety of assessment tools.15,32 Using the mFI-11, frailty was a more robust indicator of outcomes after spine surgery than age alone.33,34 Although frailty predicted perioperative adverse events, the mFI did not predict patient-reported outcomes at 3 and 12 months after spine surgery, with most patients achieving a clinically meaningful improvement regardless of frailty status.35

INTERVENTIONS TO IMPROVE OUTCOMES FOR FRAIL NEUROSURGICAL PATIENTS

Several methods and interventions have been described to improve outcomes for frail patients.

Frailty Screening and Bundled Care Pathways

Frailty represents a potentially modifiable characteristic in the neurosurgical population with significant implications for clinical decision-making, risk stratification, and improving value-based care. Frailty screening may guide appropriate patient selection, escalation in postoperative monitoring, and multidisciplinary engagement. In a broad surgical population, a frailty screening initiative implemented as part of a pragmatic quality improvement program demonstrated mortality reduction across all patient groups, with greater benefit in those with higher levels of frailty, possibly due to greater multidisciplinary involvement and surveillance.36 Similarly, Schmidt et al2 proposed the implementation of a specific neurosurgical comprehensive pathway for the care of the frail patient, with the aim of maintaining independence and preventing frailty-associated disability. In a recent retrospective analysis, a standardized protocol for complex spine surgery was associated with reduced length of hospital stay and intensive care utilization but not complications, although this study was not specific to frail patients.37 While promising, such pathways require further refinement and prospective validation for frail patients with spine and intracranial pathologies.

Prehabilitation

Prehabilitation interventions to increase physiological reserve and functional capacity may improve outcomes in frail patients; however, there is currently a lack of sufficient evidence to understand the optimal structure and delivery of such programs.38 Whether prehabilitation improves outcomes in neurosurgical patients specifically is unknown, with sparse literature available on this topic. In other surgical populations, 2 randomized controlled trials in elective colorectal39 and cancer surgery40 did not demonstrate improved postoperative outcomes with prehabilitation, possibly due to suboptimal adherence to prehabilitation protocols.

Role of Surgery to Improve Frailty

There is increasing evidence that frailty may improve after some surgical interventions, particularly if the patient’s functional impairment is related to a reversible neurological pathology (Fig. 1). This concept is supported by an observational study comparing the trajectory of operative and nonoperative approaches in patients with adult spinal deformity.41 In that study, frailty scores improved in those undergoing surgery despite having greater deformity than those who did not undergo surgery and who were more likely to develop severe frailty. In another study, although frail patients undergoing surgery for degenerative spine disease were more likely to experience short-term adverse events, these patients achieved similar long-term improvements in patient-reported outcomes and quality of life.35 Finally, a large prospective longitudinal study on recovery after elective noncardiac surgery found that although frail patients experienced early increases in disability and complications they ultimately observed greater reductions in disability than non-frail patients regardless of the frailty assessment tool used Fig. 1.4

UNANSWERED QUESTIONS/FUTURE RESEARCH

The literature examining frailty in neurosurgical patients has grown rapidly in recent years, but several areas of focus are needed going forward. Although frailty is now established as a key risk factor for poor outcomes, a range of frailty measurement tools have been used. Rigorous, prospective studies are required to validate either existing or neurosurgery-specific frailty measurement tools, including in both spine and intracranial surgery patients. Another key area of needed research is to establish evidence-based interventions to improve outcomes for frail patients, which will likely be multidimensional in nature (Fig. 2). Such interventions will likely focus on standardized frailty screening, multidisciplinary involvement, evidence-based care pathways, prehabilitation, and rehabilitation, and enhanced postoperative surveillance programs. Furthermore, the optimal patient selection, including frailty thresholds, for inclusion in such pathways remains unknown.

FIGURE 2:

Potential components of a multidimensional approach to improving outcomes for frail patients undergoing neurosurgical procedures upon which to focus future research.

CONCLUSION

As the neurosurgical population ages, frailty is an increasingly important factor in patient selection, perioperative risk stratification, and optimization to reduce complications. Frailty is measured using the phenotypic or deficit accumulation models, with simplified models such as the Clinical Frailty Scale or mFI commonly used in studies in neurosurgical patients. Increasing frailty consistently predicts worse patient outcomes across a range of neurosurgical procedures, including early complications, disability, non–home discharge, and mortality. Evidence for interventions to improve outcomes for frail patients is limited in the neurosurgical population, although bundled care pathways, exercise programs, and multidisciplinary involvement show promise. Surgery itself may be an intervention to improve frailty in selected patients, and future research should focus on identifying effective interventions to improve both short-term complications and long-term outcomes.

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