Sage Journals: Discover world-class research

Abstract

Study Design

Multicenter comparative cohort.

Objective

Studies have shown markedly higher rates of complications and all-cause mortality following surgery for adult cervical deformity (ACD) compared with adult thoracolumbar deformity (ATLD), though the reasons for these differences remain unclear. Our objectives were to compare baseline frailty, disability, and comorbidities between ACD and complex ATLD patients undergoing surgery.

Methods

Two multicenter prospective adult spinal deformity registries were queried, one ATLD and one ACD. Baseline clinical and frailty measures were compared between the cohorts.

Results

616 patients were identified (107 ACD and 509 ATLD). These groups had similar mean age (64.6 vs 60.8 years, respectively, P = .07). ACD patients were less likely to be women (51.9% vs 69.5%, P < .001) and had greater Charlson Comorbidity Index (1.5 vs .9, P < .001) and ASA grade (2.7 vs 2.4, P < .001). ACD patients had worse VR-12 Physical Component Score (PCS, 25.7 vs 29.9, P < .001) and PROMIS Physical Function Score (33.3 vs 35.3, P = .031). All frailty measures were significantly worse for ACD patients, including hand dynamometer (44.6 vs 55.6 lbs, P < .001), CSHA Clinical Frailty Score (CFS, 4.0 vs 3.2, P < .001), and Edmonton Frailty Scale (EFS, 5.15 vs 3.21, P < .001). Greater proportions of ACD patients were frail (22.9% vs 5.7%) or vulnerable (15.6% vs 10.9%) based on EFS (P < .001).

Conclusions

Compared with ATLD patients, ACD patients had worse baseline characteristics on all measures assessed (comorbidities/disability/frailty). These differences may help account for greater risk of complications and all-cause mortality previously observed in ACD patients and facilitate strategies for better preoperative optimization.

Keywords

adult spinal deformity cervical spinal deformity comorbidities disability frailty thoracolumbar spinal deformity

Introduction

Spinal deformity includes a broad range of conditions that can involve all regions of the spine and can impact individuals across all ages. Deformities of the adult thoracolumbar spine have been well studied over the past several decades.^1,2 These deformities are most commonly degenerative in nature, but may also result from untreated or residual deformities present in childhood or adolescence, arise from iatrogenic conditions, develop due to underlying neuromuscular or connective tissue disorders, or result from traumatic or neoplastic processes. Classification systems^3-7 and strategies for treatment^8-12 of adult thoracolumbar deformities (ATLD) have been proposed, and multiple studies of disease impact,^13,14 treatment outcomes,^15-21 and complications associated with surgical correction^20,22-27 have been reported.

In contrast to ATLD, study of adult cervical deformity (ACD) has been far more limited.²⁸ Early reports of ACD surgery were primarily small case series of the most severe deformities, treated with what was considered high-risk procedures, and often associated with high rates of severe complications.^29-31 With more recent advances in anesthesia, critical care, and surgical techniques, and perhaps spurred by progress in the care of ATLD deformity, there has been renewed interest in the study and treatment of ACD. These advances have included proposal of an ACD classification system,³² description of surgical techniques,^33,34 and studies focused on disease impact,³⁵ treatment outcomes,^36-38 and operative complications.^36,37,39

As study of ACD has progressed, it has become clear that operative treatment of ACD is associated with markedly higher rates of complications and all-cause mortality than operative treatment of ATLD. For example, all-cause mortality within 1-year of surgery to treat ACD has been reported to be 9-fold higher than for ATLD surgery (9.2% vs 1.0%, respectively).^27,40 Although the explanation for these differences is often based on a perceived worse health state of ACD patients, this has not been previously demonstrated. Our objectives were to compare baseline measures of frailty, disability, and comorbidities between ACD and complex ATLD patients undergoing surgery based on 2 large prospectively-collected, multicenter cohorts, one focused on ACD and the other focused on complex ATLD.

Methods

Study Design and Patient Populations

This study is a retrospective review of patients drawn from 2 multicenter, prospective cohort studies, one focused on ACD and the other on ATLD, conducted to assess the outcome of adult spinal deformity among those who underwent surgical treatment at 13 centers across the United States.

The ACD study is registered through ClinicalTrials.gov (NCT01588054). All study participants signed informed consent, and the study received institutional review board approval at all participating sites. Eligible patients were at least 18 years of age and had a diagnosis of cervical deformity with plan for operative treatment. ACD was defined based on meeting at least one of the following radiographic/alignment criteria: (1) C2-C7 sagittal kyphosis (Cobb >15°, (2) T1-slope (T1S) minus cervical lordosis (CL) ≥ 35°, (3) segmental cervical kyphosis >10° between any 2 vertebra between C2 and T1 or >15° across any 3 vertebra between C2 and T1, (4) cervical scoliosis >10° with Cobb angle end vertebra within the cervical spine, (5) C2-C7 sagittal vertical axis (SVA) >4 cm, or (6) McGregor’s slope >20° or chin brow vertical angle (CBVA) > 25°. Exclusion criteria included active spinal infection or neoplasm, deformity due to acute trauma, prisoners, and pregnancy or immediate plans to get pregnant.

The complex ATLD study is registered through ClinicalTrials.gov (NCT04194138). All study participants signed informed consent, and the study received institutional review board approval at all participating sites. Eligible patients were at least 18 years of age and had a diagnosis of adult congenital, degenerative, idiopathic, or iatrogenic thoracolumbar spinal deformity with plan for operative treatment. In addition, for this study of complex thoracolumbar deformities, patients were required to meet any of the following criteria: (1) radiographic criteria (PI-LL ≥25°, TPA ≥30°, SVA >15 cm, thoracic scoliosis ≥70°, thoracolumbar/lumbar scoliosis ≥50°, or global coronal alignment >7 cm); (2) procedural criteria (posterior spinal fusion >12 levels, 3-column osteotomy (3-CO), or anterior-column reconstruction (ACR); or (3) geriatric criteria (age >65 years and minimum 7 levels of spinal instrumentation during surgery). Exclusion criteria included active spinal infection or neoplasm, deformity due to acute trauma, neuromuscular conditions, syndromic scoliosis, inflammatory arthritis/autoimmune diseases, prisoners, and pregnancy or immediate plans to get pregnant.

Data Collection

At preoperative baseline and at postoperative follow-up visits, demographic, clinical, radiographic, and functional frailty data were collected using standardized forms. The present study focuses on preoperative baseline assessments. Demographic and clinical data included patient age, sex, body mass index (BMI), Charlson Comorbidity Index (CCI), and American Society of Anesthesiologists (ASA) grade. Patient-reported outcomes measures included the Veterans RAND 12-item health survey (VR-12) with summary physical and mental component scores (PCS and MCS, respectively) and the Patient-Reported Outcomes Measurement Information System (PROMIS).

Assessments of patient frailty included the Edmonton Frail Scale (EFS),⁴¹ the Canadian Study of Health and Aging (CSHA) Clinical Frailty Scale (CFS),⁴² and hand grip strength. The EFS was developed as a practical tool to assess frailty in both the inpatient and outpatient settings. The EFS assesses 9 domains: cognition, general health status, functional independence, social support, medication use, nutrition, mood, continence, and functional performance. For the EFS, functional performance is assessed based on the time required to rise from a seated position in a chair, walk 3 meters, and return to and sit in the chair. An overall EFS score is tabulated with 0-5 reflecting “not frail”, 6-7 reflecting “vulnerable”, and scores of >7 reflecting progressively increasing decreases of frailty. The CFS is a judgement-based tool to screen for and broadly stratify varying degrees of frailty that was developed through the CSHA. The CFS score ranges from 1 (very fit) to 9 (terminally ill), with intermediate scores of 2 (well), 3 (managing well), 4 (vulnerable), 5 (mildly frail), 6 (moderately frail), 7 (severely frails), and 8 very severely frail). A hand grip dynamometer was used to assess hand grip strength. In the seated position with the elbow flexed at 90° and the hand in line with the wrist and forearm, the patient was asked to squeeze the dynamometer as hard as possible, first using the left hand, then using the right hand. The higher value (left or right) was recorded as the grip strength.

Full-length standing anteroposterior and lateral radiographs were obtained at the time of enrollment. Radiographs were analyzed at a central site using validated software (Spineview, ENSAM Laboratory of Biomechanics, Paris, France).⁴³ Standard techniques were used to assess C2-C7 lordosis, T1 slope, C2-C7 sagittal vertical axis (SVA), T4-T12 thoracic kyphosis (TK), C2-S1 SVA, C7-S1 SVA, pelvic incidence to lumbar lordosis mismatch (PI-LL), T1-pelvic angle, and pelvic tilt (PT).

Data Assessment and Statistical Analysis

Statistical analysis was performed using IBM SPSS (version 28.0). Descriptive statistics were reported using means and standard deviations (SD) for continuous variables and frequencies with percentages for categorical variables. Categorical variables were compared using the Pearson’s chi-squared test. Continuous data were assessed for normality using the Shapiro-Wilk test. Statistical comparisons of continuous data were performed using either Student’s t test for data with normal distribution or the Mann-Whitney U test for data without normal distribution. Factors that independently distinguished between ACD and ATLD patients were assessed with multivariate logistic regression analysis using the factors with a P ≤ .1 on univariate comparisons between the 2 patient groups. Correlations between VR-12 PCS and frailty measures were assessed using the Pearson correlation coefficient. All tests were two-tailed, with a significance level of P-value <.05.

Results

Patient Population

A total of 616 patients were assessed, including 107 ACD and 509 ATLD patients. Baseline descriptive parameters for the 107 ACD patients are summarized in Table 1. ACD patients had a mean age of 64.6 years (SD = 12.3), a mean BMI of 28.6 (“overweight”), and approximately one-half (51.0%) were women. A history of cervical fusion and thoracolumbar fusion was reported in 39.3% and 34.6% of ACD patients, respectively. The most common diagnoses among ACD patients were degenerative cervical kyphosis (72.0%), dropped head syndrome (17.8%), iatrogenic cervical kyphosis (17.8%), and cervical kyphosis associated with ankylosing spondylitis (4.7%).

Table 1.

Baseline Demographics, Diagnosis, Radiographic Parameters, and History of Previous Surgery for 107 Adult Cervical Deformity Patients.^a

	Mean (SD) (Range)	Number (%)
Age (years)	64.6 (12.3) (30; 87)
Women		55 (51.9)
Body mass index	28.6 (5.9) (17.5; 43.1)
Charlson comorbidity index, mean (SD)	1.5 (1.9)
ASA grade, mean (SD)	2.7 (.5)
Previous cervical fusion
Yes		42 (39.3)
No		65 (60.7)
Previous thoracolumbar fusion
Yes		37 (34.6)
No		70 (65.4)
Diagnosis
Degenerative CK		77 (72.0)
Dropped head syndrome		19 (17.8)
Iatrogenic CK		19 (17.8)
AS-associated CK		5 (4.7)
RA-associated CK		2 (1.9)
Congenital CK		1 (.9)
Congenital scoliosis		1 (.9)
Radiographic measures
C2-C7 lordosis (°)	−9.7 (25.5) (−88.1; 59.8)
T1 slope (°)	39.7 (23.2) (2.0; 104.2)
T1 slope minus C2-C7 lordosis (°)	47.6 (21.5) (8.7; 112.2)
C2-C7 SVA (mm)	49.8 (19.1) (5.0; 85.5)
Cervical coronal cobb angle (°)^b	6.2 (4.7) (1.1; 23.6)
Upper thoracic coronal cobb angle (°)^c	15.3 (10.4) (5.6; 39.6)
Thoracic kyphosis (T4-T12) (°)	−46.5 (20.3) (−102.4; −2.8)
C2-S1 SVA (mm)	65.5 (66.2) (−42.7; 257.0)
C7-S1 SVA (mm)	24.1 (62.7) (−113.1; 270.0)
T1-pelvic-angle (°)	18.1 (9.6) (1.4; 45.4)
Pelvic tilt (°)	22.8 (9.2) (−.1; 45.4)

^aCK = cervical kyphosis; RA = rheumatoid arthritis; AS = ankylosing spondylitis; SVA = sagittal vertical axis.

^b56 patients had measurable cervical scoliosis; absolute value.

^c15 patients had measurable upper thoracic scoliosis; absolute value.

Baseline descriptive parameters for the 509 ATLD patients are summarized in Table 2. ATLD patients had a mean age of 60.8 years (SD = 15.6), a mean BMI of 27.1 (“overweight”), and the majority (69.5%) were women. A history of cervical fusion and thoracolumbar fusion was reported in 14.5% and 43.4% of ATLD patients, respectively. Measurable thoracolumbar scoliosis was present in 341 (67.0%) of patients and the mean coronal Cobb angle in these patients was 37.8° (SD = 23.4°).

Table 2.

Baseline Demographics, Radiographic Parameters, and History of Previous Surgery for 509 Adult Thoracolumbar Deformity Patients.^a

	Mean (SD)	Number (%)
Age (years)	60.8 (15.6) (18; 88)
Women	354 (69.5)
Body mass index	27.1 (5.5) (15.8; 44.1)
Charlson comorbidity index	.9 (1.5)
ASA grade	2.4 (.6)
Previous cervical fusion
Yes		74 (14.5)
No		435 (85.5)
Previous thoracolumbar fusion
Yes		221 (43.4)
No		288 (56.6)
Radiographic measures
C2-C7 lordosis (°)	10.4 (16.4) (−32.2; 64.4)
T1 slope (°)	32.7 (15.1; −4.3; 83.5)
T1 slope minus C2-C7 lordosis (°)	21.9 (12.6) (−13.2; 82.3)
C2-C7 SVA (mm)	28.1 (14.8) (−10.3; 74.7)
TL coronal cobb angle, max (°)^b	37.8 (23.4) (5.2; 106.0)
Thoracic kyphosis (T4-T12) (°)	−37.3 (22.4) (−123.4; 31.7)
C2-S1 SVA (mm)	89.1 (73.7) (−47.8; 332.5)
C7-S1 SVA (mm)	67.5 (68.3) (−57.8; 351.6)
PI-LL mismatch	16.5 (23.2; −62.4; 86.9)
T1-pelvic-angle (°)	24.4 (13.8) (−25.6; 83.3)
Pelvic tilt (°)	24.8 (11.4; −20.3; 66.5)

^aSVA = sagittal vertical axis; TL = thoracolumbar; PI = pelvic incidence; LL = lumbar lordosis.

^b341 patients had measurable thoracolumbar scoliosis; absolute value.

Comparisons of Clinical Parameters and Patient-Reported Outcomes Measures Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Baseline demographics and clinical parameters are summarized and compared between ACD and ATLD patients in Table 3. There was no significant difference in mean age between ACD and ATLD patients (64.6 and 60.8 years, respectively; P = .070). A significantly greater proportion of ATLD patients were women (69.5%) compared with ACD patients (51.9%; P < .001). Health status was significantly worse for ACD patients compared with ATLD patients based on both the CCI (1.9 vs 1.5, P < .001) and the ASA grade (2.7 vs 2.4, P < .001). ACD patients had significantly worse physical health based on the VR12-PCS (25.7 vs 29.9, P < .001) and significantly worse health status across multiple PROMIS domains, including Pain Interference, Physical Function, Social Satisfaction (discretionary social activities), and Social Satisfaction Role (all P ≤ .031, Table 3).

Table 3.

Comparison of Baseline Demographics, Comorbidities, Disability, and Frailty Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients.^a

Statistically significant p values are shown in bold.

^aTL = thoracolumbar, SD = standard deviation, BMI = body mass index, ASA = American Society of Anesthesiologists, VR = Veterans RAND, PROMIS = Patient-Reported Outcomes Measurement System, DSA = discretionary social activities, CSHA = Canadian Study of Health and Aging; for differences with statistically significant differences, gray-highlighted boxes reflect the more negatively impacted group.

^bMann-Whitney U Test.

^cPearson’s chi-squared test.

^dStudent’s t test.

^eTime to walk 3 M starting from and returning to a seated position in a chair.

Comparisons of Frailty Measures Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Baseline measures of frailty are summarized and compared between ACD and ATLD patients in Table 3. Grip strength, as assessed by a dynamometer, was significantly lower for ACD patients (44.6 lbs vs 55.6 lbs, P < .001). The mean CFS score for ACD patients was 4.0 (SD = 1.6), which corresponds to “vulnerable” and was 3.2 (SD = 1.4) for ATLD patients, which corresponds to “managing well” (P < .001). The overall EFS score was significantly worse for ACD compared with ATLD patients (5.15 vs 3.21, P < .001). For the majority of the individual frailty domains within the EFS, ACD patients score significantly worse than ATLD patients, including General Health Status I and II, Functional Independence, Med Use I and II, Mood, and Functional Performance (Table 3). Compared with ATLD patients, a significantly greater proportion of ACD patients were categorized as vulnerable (15.6% vs 10.9%) or frail (22.9% vs 5.7%) based on the EFS (P < .001). Radiographs of representative ACD and ATLD patients with a range of frailty severities are shown in Figure 1.

Figure 1.

Postero-anterior (PA, left) and lateral (right) radiographs of representative adult cervical deformity (A-F) and adult thoracolumbar deformity (G-L) patients with a range of frailty severities. A and B: 37-year-old woman with dropped head syndrome and “no frailty” based on Edmonton Frail Scale [EFS] score of 3 and Canadian Study on Health & Aging Clinical Frailty Scale (CFS) score of 3 (“managing well”). C and D: 82-year-old man with degenerative cervical kyphosis and “vulnerable” to frailty based on EFS score of 7 and CFS score of 3 (“managing well”). E and F: 35-year-old man with ankylosing spondylitis and “moderate frailty” based on EFS score of 11 and CFS score of 6 (“moderately frail”). G and H: 64-year-old woman with degenerative thoracolumbar scoliosis and “no frailty” based on EFS score of 3 and CFS score of 3 (“managing well”). I and J: 58-year-old woman degenerative thoracolumbar scoliosis and “vulnerable” to frailty based on EFS score of 6 and CFS score of 3 (“managing well”). K and L: 66-year-old woman with iatrogenic flatback and positive sagittal malalignment and “moderate frailty” based on EFS score of 10 and CFS score of 5 (“mildly frail”).

Multivariate Assessment of Factors Distinguishing Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Multivariate logistic regression analysis was performed in order to assess for baseline factors that independently distinguished between ACD and ATLD patients. Of all baseline factors from univariate analyses with a P < .1 (Table 3), 3 significant factors were identified: increased hand grip strength had an OR of 1.029 (95% CI = 1.017-1.041, P < .001) for ATLD vs ACD, increased EFS had an OR of .811 (95% CI = .744-.885, P < .001) for ATLD vs ACD, and female gender had an OR of 4.094 (95% CI = 2.403-6.974, P < .001) for ATLD vs ACD.

Correlations Between Baseline Disability and Frailty Measures

Table 4 provides a summary of correlations between frailty measures and baseline disability, function, health status and age based on the combined cohort of 616 ACD and ATLD patients. Patient age had a weak correlation (r = .2-.39) with hand grip strength, CFS, and EFS. Both the VR-12 PCS and the PROMIS PF Score demonstrated moderate correlations (r = .4-.59) with CFS and EFS. The PROMIS PF score also had a weak correlation with hand grip strength. BMI and ASA grade had weak correlations with CFS and EFS, but lacked any correlation with hand grip strength. The CCI had very weak or no correlation with the assessed measures of frailty.

Table 4.

Correlations Between Frailty Measures and Baseline Disability, Function, Health Status and Age in a Combined Cohort of 616 Adult Cervical and Thoracolumbar Spinal Deformity Patients.^a

^aVR = Veterans RAND, PROMIS = Pateint-Reported Outcomes Meausrement Information System, ASA = American Scoeity of Anesthesiologists; Pearson correlation coefficents are shown; cells shaded with dark gray reflect moderate correlations (r = .4-.59); cells shaded with light gray reflect weak correlations (r = .2-.39).

Discussion

The potential for operative treatment to markedly improve pain, function, and overall health-related quality of life for adults with spinal deformity has been shown through multiple clinical studies.^{2,15,17-21,23,26,36-38,44,45} However, our understanding of why these deformities develop and progress, as well as how best to treat these patients while minimizing adverse events, remains incomplete.^1,7,28,46 Study of ATLD has advanced considerably over recent decades. In contrast, study of ACD has only recently gained traction. Although each of these deformity groups consists of a heterogeneous collection of pathologies, it has become clear that there are key differences between ACD and ATLD. Perhaps most notable, are the higher rates of complications and all-cause mortality following operative treatment observed with ACD compared with ATLD patients.^{17-19,37,39,40} Although it remains unclear why ACD patients tend to face much greater risk despite surgical treatments employing similar techniques and types of implants, these differences have typically been loosely attributed to baseline poorer health state among ACD patients. The present study used 2 large prospective, multicenter registries of ACD and ATLD patients to provide comparisons of baseline frailty, disability and comorbidities. Based on an overall cohort of 616 patients (107 ACD and 509 ATLD), ACD patients had significantly worse baseline comorbidities, disability and frailty compared with ATLD patients. Collectively, these findings may help account for the greater risk of complications faced by ACD patients with surgery, may provide insights into the etiology of ACD, and may facilitate opportunities to provide better preoperative optimization for ACD patients.

Three separate baseline measures of frailty were used in the present study, hand grip strength, CFS, and EFS. Compared with ATLD patients, ACD patients had significantly worse baseline frailty across all measures. The grip test measures the maximum isometric strength of the hand and forearm and is used as a general indication of muscle functioning status.^47-49 The grip test has been shown to be associated with osteoporosis and fracture risk,^48,50,51 and low hand grip strength has been associated with adverse outcomes among older adults with gastric cancer.⁵² In the present study, ACD patients had 20% lower hand grip strength (44.6 vs 55.6 lbs, P < .001) compared with ATLD patients, despite a markedly lower proportion of women (51.9% vs 69.5%, P < .001) in the ACD group compared with ATLD patients. This suggests that at baseline ACD patients may have lower overall muscle strength and greater risk of bony fracture, both factors that would be expected to increase the risk of mechanical failures following deformity surgery. Notably, it is possible that grip strength could have been negatively impacted in a subset of patients in the ACD group with spinal cord or nerve root compromise. Although we attempted to help mitigate this impact by assessing both left and right hand grip strength and using the higher value, this remains a potential limitation of using hand grip strength assessment in cervical deformity patients.

The CFS is a general measure of frailty status, with a single score ranging from 1 to 9, and is assigned by the healthcare provider.⁴² The mean CFS score for ACD patients was almost a full point lower than for ATLD patients (4.0 vs 3.2, P < .001). Although these mean scores correspond to relatively low degrees of frailty (3 = “managing well” and 4 = “vulnerable”), it is important to recognize that the CFS was developed to capture frailty across the range of health conditions, from very fit to terminally ill. Both registries from which patients were drawn for the present study only include patients who were deemed surgical candidates. Therefore, some degree of selection bias is likely present, since surgeons may be less likely to offer major surgery to less healthy patients. Nevertheless, the CFS measure also demonstrates a significantly greater overall degree of baseline frailty among the ACD patients.

The EFS provides assessment of 9 domains and an overall frailty score.⁴¹ The EFS has been applied previously to older patients undergoing orthopedic procedures, and higher scores have been shown to correlate with greater risk of postoperative complications and prolonged hospital stay.⁵³ In the present study, ACD patients had a 60% higher EFS compared with ATLD patients (5.15 vs 3.21, P < .001). Across the majority of EFS domains, ACD patients had worse scores compared with ATLD patients. The only domains without a significant difference between the 2 groups were Cognition, Social Support, Nutrition, and Continence. Domains with the greatest differences included General Health Status I and II, and Functional Independence. For each of these domains, the scores for ACD patients were approximately twice as high as for ATLD patients. Medication Use I and II, Mood, and Functional Performance domains were also significantly worse for ACD patients. Collectively, assessment based on the EFS demonstrates overall greater frailty in ACD patients and offers insights into the specific domains that may be most impacted.

In addition to greater frailty, ACD patients also demonstrated worse clinical baseline health and function. ACD patients had a modest but significantly higher BMI (28.6 vs 27.1, P < .001) than ATLD patients, but both groups had mean values placing them in the “overweight” category. The CCI and ASA grade were also modestly but significantly worse in the ACD group, suggesting a greater degree of health compromise in ACD patients. Interestingly, all of the patient-reported outcomes measures were significantly worse at baseline for ACD patients, except those related to mental health (VR12-MCS and PROMIS Anxiety and Depression).

The mean age of the ACD patients was modestly but not significantly greater than that of the ATLD patients (64.6 yrs vs 60.8 yrs, P = .070). Notably, the ACD and ATLD groups had similar proportions of patients <40 years of age (6.5% vs 12.6%, P = .095). In order to assess for potential confounding effects of baseline factors on frailty differences between the 2 patient groups, multivariate analyses were performed. When baseline factors from the univariate analysis with a P < .1 were tested in multivariate regression, only 3 remained statistically significant: hand grip strength, EFS, and gender (all P-values <.001). This indicates that, even after adjusting for the differences in gender, both the hand grip strength and EFS remained significantly different between the ACD and ATLD patients.

The strongest correlations between frailty measures and other baseline parameters were between physical function scores (VR-12 PCS and PROMIS Physical Function) and the CFS and EFS scores. These correlations were all only moderate in strength, suggesting that the CFS and EFS assessments capture some information that overlaps with current patient-reported outcome measures while also reflecting unique measures of patient health status. Notably, increasing age correlated with worse frailty measures, but these correlations were weak and not as strong as patient-reported measures of physical function.

Although outcomes and occurrence of complications following adult spinal deformity surgery are complex and multifactorial, the present study may offer some insights. Compared with ATLD patients, ACD patients have worse baseline characteristics on all measures assessed, including greater comorbidities, worse disability, and a greater severity of frailty. Notably, the ATLD registry from which thoracolumbar deformity patients were extracted for the present study was focused specifically on more complex deformities, with inclusion criteria that favored older patients, greater severity of deformity, and more invasive corrective procedures. Thus, the differences in baseline measures between ACD and ATLD patients may be even more marked than those presented.

Strengths of the present study include the relatively large numbers of patients, multicenter design, and prospective patient enrollment. Limitations include the potential for selection bias, since only patients seeking surgery and deemed surgical candidates were enrolled in the patient registries. In addition, both the ACD and ATLD registries include considerable heterogeneity with regard to types of spinal deformities which could impact the results. However, the heterogeneity in each registry is reflective of the spinal pathologies encountered in practice at major centers across the United States and may add to the generalizability of the findings. The lack of specific spine deformity measures of frailty is another limitation of the current study. The available measures of frailty used in this study are relatively blunt and nonspecific. In addition, other factors beyond baseline frailty that were not specifically addressed in the present study may contribute to differences in surgical complication rates between ACD and ATLD patients, including potentially greater need for higher-grade osteotomies and greater challenges with anesthetic management and difficult airways in ACD patients compared with ATLD patients. Lastly, the current study does not include assessments of postoperative complications or outcome, as both registries were relatively recently created. Further maturity of both registries in the years ahead will enable comparisons between frailty and outcomes in these cohorts.

Conclusion

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from Medtronic, Globus, Stryker, SI Bone, and Carlsmed.

Disclosures

Dr. Smith reports consultancy fees from ZimVie, NuVasive, Cerapedics, SeaSpine, and Carlsmed; receives royalties from Zimmer Biomet and Nuvasive; holds stock in Alphatec and NuVasive; receives research funding to his institution from DePuy Synthes, International Spine Study Group Foundation (ISSGF), and AOSpine; receives fellowship grant funding to his institution from AOSpine; serves on the Executive Committee of the ISSGF; serves on the Board of Directors of the Scoliosis Research Society, and serves on the editorial boards of Journal of Neurosurgery Spine, Neurosurgery, Operative Neurosurgery, and Spine Deformity. Dr Kelly receives honoraria from Wolters Kluwer; received support for travel from AO Spine; has leadership roles with Scoliosis Research Society and AO Spine; and receives research support from the Setting Scoliosis Straight Foundation and San Diego Spine Foundation. Dr Buell receives research funding to his institution from ISSGF and NuVasive; and serves on the editorial boards of Operative Neurosurgery and Spine Deformity. Mr. Line is a consultant for ISSGF. Dr V. Lafage is a consultant for Globus Medical and Alphatec; receives royalties from NuVasive; receives research support from ISSG; receives honoraria from DePuy Synthes, Stryker, and Implanet; and has leadership roles in ISSG and the Scoliosis Research Society. Dr Klineberg is a consultant for DePuy Synthes, Stryker, and Medtronic, SI Bone, and Agnovos; receives honoraria and a fellowship grant paid to an institution from AO Spine; and has leadership roles with AOSpine. Dr Kim receives royalties from Zimmer Biomet, Acuity Surgical, and K2M-Stryker; is a consultant for NuVasive; receives research support from the ISSGF; is on advisory boards for Vivex Biology and Aspen Medical; and has other financial or non-financial interests with AOSpine. Dr Kim is a consultant for and receives royalties from ZimVie and receives royalties from Stryker and Acuity Surgical Devices, LLC. Dr Passias is a consultant for Medtronic, SpineWave, Terumo, and Royal Biologics; receives honoraria from Cervical Spine Research Society, Globus Medical, and Zimmer; serves on the editorial or governing board for Spine journal; and receives research support from Allosource. Dr Gum receives research support from Stryker, Biom’Up, Pfizer, the Alan L. & Jacqueline B. Stuart Spine Center, National Health Foundation, Cerapedics, Empirical Spine, Inc., TSRH, and Scoliosis Research Society; receives royalties from Acuity, Medtronic, and NuVasive; is a consultant for Acuity, DePuy, Medtronic, NuVasive, FYR Medical, and Stryker; receives honoraria from Baxter, Broadwater, NASS, and Pacira Pharmaceuticals; holds patents with Medtronic; participates on a data safety monitoring board or advisory board with Medtronic; has a leadership role in the National Spine Health Foundation; owns stock/stock options in Cingulate Therapeutics and FYR Medical; is an employee of Norton Healthcare, Inc.; and serves as a journal reviewer for Global Spine Journal, Spine Deformity, and The Spine Journal. Dr Kebaish is a consultant for DePuy Synthes and Ethicon; receives royalties from Stryker, Orthofix, and Spinecraft. Dr Eastlack and receives research/fellowship support from NuVasive, Medtronic, SeaSpine, SI Bone, and AONA; receives royalties from SI Bone, Nuvasive, Seaspine, Aesculap, and Globus Medical; is a consultant for Aesculap, NuVasive, SI Bone, SeaSpine, Spinal Elements, Biedermann-Motech, Silony, Neo Medical, Depuy, Medtronic, and Mainstay; has received payment/honoraria from Radius; has patents with Globus, Spine Innovation, and SI Bone; has leadership role with San Diego Spine Foundation; and has stock/stock options with Alphatec, Nuvasive, Seaspine, and SI Bone. Dr Daniels receives grants/research support from Medtronic and Orthofix; receives royalties from Spineart and Stryker; is a consultant for Stryker Spine, Spineart, and Medtronic; and has received payment for expert testimony from multiple law firms. Dr Soroceanu receives travel expenses to teach at the ISSG-Medtronic Spine Course for fellows and residents; and has a leadership role with the Canadian Spine Society. Dr Mundis is a consultant for NuVasive, Viseon, Carlsmed, SI Bone, and SeaSpine; holds patents with Stryker, NuVasive, and SeaSpine; has leadership roles with Global Spine Outreach and San Diego Spine Foundation; has stock or stock options with Alphatec, SeaSpine, and NuVasive; and receives royalties from NuVasive and K2M/Stryker. Dr Protopsaltis is a consultant for Globus, NuVasive, and Medtronic; receives royalties from Altus; receives grants from Medtronic; and has stock or stock options from One Point Surgical. Dr Hamilton receives grants/research support from Prosydiuan and NuVasive. Dr Gupta owns stock in J&J; is a consultant for DePuy, Medtronic, Globus; receives royalties from Innomed, DePuy, and Globus; receives honoraria from AO Spine, Wright State, and LSU; serves on the board of directors of the Scoliosis Research Society; receives travel reimbursements from DePuy, Globus, Scoliosis Research Society; and has a voluntary relationship with the National Spine Health Foundation. Dr Lewis is a consultant for Stryker Spine; receives grant/research support from Medtronic, DePuy Synthes, and AOSpine; receives honoraria from Medtronic, Stryker Spine, DePuy Synthes, Scoliosis Research Society, and AOSpine; receives support for travel from AO Spine and Scoliosis Research Society; and is on an advisory board/panel for AOSpine Research Commission and Scoliosis Research Society Research Task Force; and is Chair of the AO Spine Knowledge Forum Deformity. Dr Schwab is a consultant for MSD, Zimmer Biomet, and Mainstay Medical; receives royalties from Zimmer Biomet, Medtronic, and Stryker; owns stock in VFT Solutions and SeaSpine; is an executive committee member of ISSG. Dr Lenke is a consultant for Medtronic, ABRYX, and Acuity Surgical; receives research/grant support from AOSpine, Scoliosis Research Society, and Setting Scoliosis Straight Foundation; receives royalties from Medtronic and Acuity Surgical; and receives other financial support from Broadwater, AOSpine, and Scoliosis Research Society. Dr Shaffrey is a consultant for NuVasive, SI Bone, and Proprio; owns stock in NuVasive; holds patents with NuVasive; receives fellowship funding from Globus, Medtronic, and NuVasive; and receives royalties from NuVasive, Medtronic, and SI Bone; has leadership roles with SRS and CSRS; and receives study-related clinical or research support from DePuy Synthes and ISSGF. Dr Burton receives royalties from DePuy Spine, Globus, and Blue Ocean Spine; is a consultant for DePuy Spine, Globus, and Blue Ocean Spine; has a leadership role in the Scoliosis Research Society and International Spine Study Group Foundation; has stock or stock options in Progenerative Medical; and has received research support from DePuy Spine and ISSGF. Dr Ames receives royalties from Stryker, Biomet Zimmer Spine, DePuy Synthes, NuVasive, Next Orthosurgical, K2M, and Medicrea; is a consultant for DePuy Synthes, Medtronic, Medicrea, K2M, Agada Medical, and Carlsmed; receives research support from Titan Spine, DePuy Synthes, and ISSG; serves on the editorial board of Operative Neurosurgery; receives grant funding from SRS; serves on the executive committee of ISSG; is the director of Global Spinal Analytics; and is the safety and value committee chair of SRS. Dr Bess is a consultant for Alphatec, Stryker, and MiRus; receives honoraria from Stryker; holds patents with Stryker; receives study-related clinical or research support from Medtronic, Globus, NuVasive, Stryker, Carlsmed, and SI Bone; receives non–study-related clinical or research support from DePuy Synthes; and receives royalties from Stryker and NuVasive. Drs. Ben-Israel, Diebo, Scheer, R. Lafage, and Hostin report no conflicts of interest.

ORCID iDs

Justin S. Smith

Bassel Diebo

Breton Line

Virginie Lafage

Renaud Lafage

Han Jo Kim

Jeffrey L. Gum

Stephen J Lewis

References

Smith

Shaffrey

Ames

Lenke

. Treatment of adult thoracolumbar spinal deformity: past, present, and future. J Neurosurg Spine. 2019;30(5):551-567.

Diebo

Shah

Boachie-Adjei

, et al. Adult spinal deformity. Lancet. 2019;394(10193):160-172.

Schwab

Ungar

Blondel

, et al. Scoliosis Research Society-Schwab adult spinal deformity classification: a validation study. Spine. 2012;37(12):1077-1082.

Smith

Klineberg

Schwab

, et al. Change in classification grade by the SRS-Schwab Adult Spinal Deformity Classification predicts impact on health-related quality of life measures: prospective analysis of operative and nonoperative treatment. Spine. 2013;38(19):1663-1671.

Terran

Schwab

Shaffrey

, et al. The SRS-Schwab adult spinal deformity classification: assessment and clinical correlations based on a prospective operative and nonoperative cohort. Neurosurgery. 2013;73(4):559-568.

Schwab

Blondel

Chay

, et al. The comprehensive anatomical spinal osteotomy classification. Neurosurgery. 2014;74(1):112-120.

Ames

Smith

Pellise

, et al. Artificial intelligence based hierarchical clustering of patient types and intervention categories in adult spinal deformity surgery: towards a new classification scheme that predicts quality and value. Spine. 2019;44(13):915-926.

Lafage

Smith

Elysee

, et al. Sagittal age-adjusted score (SAAS) for adult spinal deformity (ASD) more effectively predicts surgical outcomes and proximal junctional kyphosis than previous classifications. Spine Deform. 2022;10(1):121-131.

Rabinovich

Buell

Sardi

Lazaro

BCR

Shaffrey

Smith

. A novel weave tether technique for proximal junctional kyphosis prevention in 71 adult spinal deformity patients: a preliminary case series assessing early complications and efficacy. Oper Neurosurg (Hagerstown). 2021;21(6):393-399.

10.

Rabinovich

Buell

Wang

Shaffrey

Smith

. Reduced occurrence of primary rod fracture after adult spinal deformity surgery with accessory supplemental rods: retrospective analysis of 114 patients with minimum 2-year follow-up. J Neurosurg Spine. 2021;35(4):504-515.

11.

Yilgor

Sogunmez

Boissiere

, et al. Global alignment and proportion (GAP) score development and validation of a new method of analyzing spinopelvic alignment to predict mechanical complications after adult spinal deformity surgery. J Bone Jt Surg Am Vol. 2017;99(19):1661-1672.

12.

Lafage

Schwab

Challier

, et al.

Defining spino-pelvic alignment thresholds: should operative goals in adult spinal deformity surgery account for age?

Spine. 2016;41(1):62-68.

13.

Bess

Line

, et al. The health impact of symptomatic adult spinal deformity: comparison of deformity types to United States population norms and chronic diseases. Spine. 2016;41(3):224-233.

14.

Glassman

Bridwell

Dimar

Horton

Berven

Schwab

. The impact of positive sagittal balance in adult spinal deformity. Spine. 2005;30(18):2024-2029.

15.

Acaroglu

Guler

Cetinyurek-Yavuz

, et al.

Decision analysis to identify the ideal treatment for adult spinal deformity: what is the impact of complications on treatment outcomes?

Acta Orthop Traumatol Turcica. 2017;51(3):181-190.

16.

Bridwell

Baldus

Berven

, et al. Changes in radiographic and clinical outcomes with primary treatment adult spinal deformity surgeries from two years to three- to five-years follow-up. Spine. 2010;35(20):1849-1854.

17.

Bridwell

Glassman

Horton

, et al. Does treatment (nonoperative and operative) improve the two-year quality of life in patients with adult symptomatic lumbar scoliosis: a prospective multicenter evidence-based medicine study. Spine. 2009;34(20):2171-2178.

18.

Elias

Bess

Line

, et al. Outcomes of operative treatment for adult spinal deformity: a prospective multicenter assessment with mean 4-year follow-up. J Neurosurg Spine. 2022;37:607-616.

19.

Kelly

Lurie

Yanik

, et al. Operative versus nonoperative treatment for adult symptomatic lumbar scoliosis. J Bone Joint Surg Am. 2019;101(4):338-352.

20.

Smith

Kelly

Yanik

, et al. Operative versus nonoperative treatment for adult symptomatic lumbar scoliosis at 5-year follow-up: durability of outcomes and impact of treatment-related serious adverse events. J Neurosurg Spine. 2021:1-13.

21.

Smith

Shaffrey

Berven

, et al. Operative versus nonoperative treatment of leg pain in adults with scoliosis: a retrospective review of a prospective multicenter database with two-year follow-up. Spine. 2009;34(16):1693-1698.

22.

Smith

Klineberg

Lafage

, et al. Prospective multicenter assessment of perioperative and minimum 2-year postoperative complication rates associated with adult spinal deformity surgery. J Neurosurg Spine. 2016;25(1):1-14.

23.

Smith

Shaffrey

Glassman

, et al. Risk-benefit assessment of surgery for adult scoliosis: an analysis based on patient age. Spine. 2011;36(10):817-824.

24.

Smith

Shaffrey

Kelly

, et al. Effect of serious adverse events on health-related quality of life measures following surgery for adult symptomatic lumbar scoliosis. Spine. 2019;44(17):1211-1219.

25.

Smith

Shaffrey

Klineberg

, et al. Complication rates associated with 3-column osteotomy in 82 adult spinal deformity patients: retrospective review of a prospectively collected multicenter consecutive series with 2-year follow-up. J Neurosurg Spine. 2017;27(4):444-457.

26.

Zuckerman

Cerpa

Lenke

, et al. Patient-reported outcomes after complex adult spinal deformity surgery: 5-year results of the scoli-risk-1 study. Global Spine J. 2021:1736-1744.

27.

Zuckerman

Lakomkin

Smith

Shaffrey

Devin

. Incidence and predictors of all-cause mortality within one year after adult spinal deformity surgery. J Spine Surg. 2018;4(2):333-341.

28.

Smith

Shaffrey

Bess

, et al. Recent and emerging advances in spinal deformity. Neurosurgery. 2017;80(3S):S70-S85.

29.

Bovill

Jr . Osteotomy of cervical part of the spine for ankylosing spondylitis with severe deformity. Calif Med. 1965;102(2):142-144.

30.

Simmons

. The surgical correction of flexion deformity of the cervical spine in ankylosing spondylitis. Clin Orthop Relat Res. 1972;86:132-143.

31.

Urist

. Osteotomy of the cervical spine; report of a case of ankylosing rheumatoid spondylitis. J Bone Joint Surg Am. 1958;40-A(4):833-843.

32.

Ames

Smith

Eastlack

, et al. Reliability assessment of a novel cervical spine deformity classification system. J Neurosurg Spine. 2015;23(6):673-683.

33.

Smith

Klineberg

Shaffrey

, et al. Assessment of surgical treatment strategies for moderate to severe cervical spinal deformity reveals marked variation in approaches, osteotomies, and fusion levels. World Neurosurg. 2016;91:228-237.

34.

Smith

Shaffrey

Lafage

, et al. Three-column osteotomy for correction of cervical and cervicothoracic deformities: alignment changes and early complications in a multicenter prospective series of 23 patients. Eur Spine J. 2017;26(8):2128-2137.

35.

Smith

Line

Bess

, et al. The health impact of adult cervical deformity in patients presenting for surgical treatment: comparison to United States population norms and chronic disease states based on the EuroQuol-5 dimensions questionnaire. Neurosurgery. 2017;80(5):716-725.

36.

Ailon

Smith

Shaffrey

, et al. Outcomes of operative treatment for adult cervical deformity: a prospective multicenter assessment with 1-year follow-up. Neurosurgery. 2018;83(5):1031-1039.

37.

Elias

Bess

Line

, et al. Operative treatment outcomes for adult cervical deformity: a prospective multicenter assessment with mean 3-year follow-up. J Neurosurg Spine. 2022;37(6):855-864.

38.

Smith

Shaffrey

Kim

, et al. Comparison of best versus worst clinical outcomes for adult cervical deformity surgery. Global Spine J. 2019;9(3):303-314.

39.

Smith

Buell

Shaffrey

, et al. Prospective multicenter assessment of complication rates associated with adult cervical deformity surgery in 133 patients with minimum 1-year follow-up. J Neurosurg Spine. 2020:1-13.

40.

Smith

Shaffrey

Kim

, et al. Prospective multicenter assessment of all-cause mortality following surgery for adult cervical deformity. Neurosurgery. 2018;83(6):1277-1285.

41.

Rolfson

Majumdar

Tsuyuki

Tahir

Rockwood

. Validity and reliability of the edmonton frail scale. Age Ageing. 2006;35(5):526-529.

42.

Rockwood

Song

MacKnight

, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ (Can Med Assoc J). 2005;173(5):489-495.

43.

Champain

Benchikh

Nogier

Mazel

Guise

Skalli

. Validation of new clinical quantitative analysis software applicable in spine orthopaedic studies. Eur Spine J. 2006;15(6):982-991.

44.

Smith

Lafage

Shaffrey

, et al. Outcomes of operative and nonoperative treatment for adult spinal deformity: a prospective, multicenter, propensity-matched cohort assessment with minimum 2-year follow-up. Neurosurgery. 2016;78(6):851-861.

45.

Smith

Shaffrey

Berven

, et al. Improvement of back pain with operative and nonoperative treatment in adults with scoliosis. Neurosurgery. 2009;65(1):86-93.

46.

Ames

Smith

Pellise

, et al. Development of deployable predictive models for minimal clinically important difference achievement across the commonly used health-related quality of life instruments in adult spinal deformity surgery. Spine. 2019;44(16):1144-1153.

47.

Bohannon

. Muscle strength: clinical and prognostic value of hand-grip dynamometry. Curr Opin Clin Nutr Metab Care. 2015;18(5):465-470.

48.

Luo

Jiang

. Association between grip strength and bone mineral density in general US population of NHANES 2013-2014. Arch Osteoporosis. 2020;15(1):47.

49.

Norman

Stobaus

Gonzalez

Schulzke

Pirlich

. Hand grip strength: outcome predictor and marker of nutritional status. Clin Nutr. 2011;30(2):135-142.

50.

Kaya

Ozgocmen

Ardicoglu

Kamanli

Gudul

. Relationship between grip strength and hand bone mineral density in healthy adults. Arch Med Res. 2005;36(5):603-606.

51.

Sirola

Rikkonen

Tuppurainen

Jurvelin

Alhava

Kroger

. Grip strength may facilitate fracture prediction in perimenopausal women with normal BMD: a 15-year population-based study. Calcif Tissue Int. 2008;83(2):93-100.

52.

Miao

Ding

, et al. Preoperative low handgrip strength (HGS) with HGS asymmetry is associated with adverse outcomes among older adults with gastric cancer. J Geriatr Oncol. 2023;14(7):101583.

53.

Roopsawang

Thompson

Zaslavsky

Belza

. Predicting hospital outcomes with the reported edmonton frail scale-Thai version in orthopaedic older patients. J Clin Nurs. 2020;29(23-24):4708-4719.

Adult Cervical Deformity Patients Have Higher Baseline Frailty,Disability,and Comorbidities Compared With Complex Adult Thoracolumbar Deformity Patients: A Comparative Cohort Study of 616 Patients

Abstract

Study Design

Objective

Methods

Results

Conclusions

Keywords

Introduction

Methods

Study Design and Patient Populations

Data Collection

Data Assessment and Statistical Analysis

Results

Patient Population

Comparisons of Clinical Parameters and Patient-Reported Outcomes Measures Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Comparisons of Frailty Measures Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Multivariate Assessment of Factors Distinguishing Between Adult Cervical Deformity and Adult Thoracolumbar Deformity Patients

Correlations Between Baseline Disability and Frailty Measures

Discussion

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

Disclosures

ORCID iDs

References