Sage Journals: Discover world-class research

Abstract

Study Design

Retrospective study.

Objective

Quantify the effect of obesity on elective thoracolumbar spine surgery patients.

Methods

Five hundred consecutive adult patients undergoing thoracolumbar spine surgery to treat degenerative pathologies with minimum follow-up of at least 1 year were included. Primary outcome measures included Numerical Rating Scales for back and leg pain, the Short Form 36 Physical Component Summary and Mental Component Summary, the modified Oswestry Disability Index, and patient satisfaction scores collected preoperatively and at 3, 6, 12, and 24 months postoperatively. Secondary outcome measures included perioperative and postoperative adverse events, postoperative emergency department presentation, hospital readmission, and revision surgeries. Patients were grouped according to World Health Organization body mass index (BMI) guidelines to isolate the effect of obesity on primary and secondary outcome measures.

Results

Mean BMI was 30 kg/m², reflecting a significantly overweight population. Each BMI group reported statistically significant improvement on all self-reported outcome measures. Contrary to our hypothesis, however, there was no association between BMI group and primary outcome measures. Patients with BMI of 35 to 39.99 visited the emergency department with complaints of pain significantly more often than the other groups. Otherwise, we did not detect any differences in the secondary outcome measures between BMI groups.

Conclusions

Patients of all levels of obesity experienced significant improvement following elective thoracolumbar spine surgery. These outcomes were achieved without increased risk of postoperative complications such as infection and reoperation. A risk–benefit algorithm to assist with surgical decision making for obese patients would be valuable to surgeons and patients alike.

Keywords

obesity body mass index BMI spine surgery outcomes complications

Introduction

The obesity epidemic in North America continues to worsen. More than 60% of citizens of the United States and Canada are overweight; 35 and 25% are obese, respectively.¹,² These numbers are rising, and projections suggest they will continue to rise.^3,4 Geographical variability means even greater rates of obesity in certain regions, thus challenging the surgical techniques and technologies of surgeons in these areas.⁵ Care providers need to understand the influence of body habitus on surgical outcomes to allow for optimal treatment decision making.

Body mass index (BMI) is presently the most widely used measure of body habitus.⁶,⁷ It is calculated as weight in kilograms divided by the square of height in meters (kg/m²).⁶ Elevated BMI has been identified as an independent risk factor for perioperative complications for a variety of surgeries.⁸,⁹,¹⁰ Specific assessments of the effect of obesity on spine surgery suggest increased rates of perioperative complications and increased rates of reoperation.¹¹,¹²

The effects of obesity on spine surgery success have been controversial. At best, obesity was not seen to adversely affect outcomes.¹³,¹⁴ Other studies, however, have identified deleterious effects of obesity.¹⁵ For example, obese patients may report improvement, but perhaps not to the same level obtained by patients of normal weight.¹⁶ These complications have been associated with higher costs for obese patients undergoing spine surgery.¹⁷ Furthermore, there is no predictable weight reduction observed following spine surgery in the obese patient.¹⁸ These mixed results highlight the complex relationship between obesity and spine surgery outcomes. It is clear that further investigation is required.

The purpose of this study was to evaluate the relationship between obesity and patient-reported outcomes following elective thoracolumbar spine surgery. We hypothesized that obese patients would demonstrate fewer postoperative benefits than nonobese patients.

Methods

Data was obtained retrospectively from the Canada East Spine Centre's database of consecutive patients who had spine surgery. Patients were treated by one of two fellowship-trained spine surgeons from a single tertiary-level institution. Inclusion criteria were patients 18 years of age or older undergoing elective thoracolumbar spine surgery for degenerative pathologies who completed at least 1 year of postoperative follow-up. Exclusion criteria were involvement in spine-related litigation, nondegenerative indication for surgery (malignancy, infection, trauma), or a previous spinal fusion. Institutional ethical review board approval was received prior to study commencement.

Data collection included the following variables.

Grouping Variable

The World Health Organization (WHO) has categorized BMI as normal (18.5 to 24.99), overweight (25 to 29.99), obese class I (30 to 34.99), obese class II (35 to 39.99), and obese class III (≥40).⁶ BMI in our study was calculated according to WHO standards, by dividing patient weight by the square of patient height.¹⁹ The cohort was then divided into four groups: normal weight (BMI ≤25, n = 107), overweight (BMI 25 to 29.99, n = 180), obese (BMI 30 to 34.99, n = 113), and morbidly obese (BMI ≥35, n = 100). Obese classes II and III were amalgamated into the morbidly obese category in this study for statistical reasons, due to the limited number of patients with BMI ≥40.

Demographics

Age, gender, number and type of comorbidities, diagnosis, symptom profile, and BMI were recorded prospectively at the patients’ presurgical evaluation.

Surgical Factors

Surgical details including traditional open versus minimally invasive technique, decompression versus decompression and fusion, primary versus revision surgery, number of levels treated, operative time, and blood loss were recorded immediately postoperatively. Length of hospital stay was recorded upon hospital discharge.

Outcome Measures

Primary study measures were patient-reported outcomes: Numerical Rating Scale for back pain (NRS-B) and leg pain (NRS-L), modified Oswestry Disability Index (mODI), Short Form 36 Physical Component Summary (SF-36 PCS) and Mental Component Summary (SF-36 MCS). These were evaluated preoperatively and at 3, 6, 12, and 24 months postoperatively. Patient satisfaction ratings were collected according to the same follow-up schedule.

Satisfaction scores were calculated using four questions: (1) “I was helped as much as I thought I would be by my spine treatment”; (2) “My pain was reduced as much as I expected it to be after my surgery”; (3) “Overall I am satisfied with the care I am receiving for my neck and/or back”; and (4) “All things considered, I would have my spine treatment again for the same condition.” Patients selected one of five responses: “definitely true,” “mostly true,” “don't know,” “mostly false,” and “definitely false.” Responses were then coded according to their answer to each question from 1 (definitely true) to 5 (definitely false) and assigned a total score. Scores from 4 to 9 represented satisfied patients, 10 to 14 represented neutral patients, and 15 to 20 represented dissatisfied patients.

Perioperative Adverse Events

Secondary outcome measures consisted of any unplanned surgery-related event. Each adverse event (AE) was recorded using the validated Spine Adverse Event Severity (v1.1) collection and scoring instrument.²⁰ Number, type, and timing of each AE were documented. Perioperative AEs included any event occurring between incision time and closure (e.g., dural tear); postoperative AEs included any surgery-related complication occurring between surgery and most recent follow-up (e.g., urinary retention). Revision surgery (performed or scheduled) reason and date was recorded if applicable.

Unscheduled emergency department presentation and hospital readmission were identified via retrospective review of the provincial electronic health record system. Otherwise, all data points were collected prospectively.

Statistics

An a priori power analysis was conducted using the minimum clinically important difference method described by Samsa et al.²¹,²²,²³ Baseline standard deviations of the main outcome measures were each multiplied by 0.2 (a small effect size) to determine the minimum clinically relevant effect size for each variable. The smallest of these effect size values was then used, and power was set at 90%, which yielded a minimum group size of 80 patients per arm. Each of the group sizes in the present study significantly exceeded this minimum value.

Data was analyzed utilizing BMI SPSS software (v20; IBM Corp., Armonk, NY, United States). Non-normally distributed variables were log-transformed. Categorical baseline variables were assessed using chi-square analyses. Differences in the pre- versus postoperative SF-36 PCS, SF-36 MCS, mODI, NRS-L, and NRS-B scores were assessed between BMI groups while controlling for age, number of levels, surgery type, open or minimally invasive approach, gender, number of comorbidities, primary symptom, primary diagnosis, and physician using multivariate analysis of covariance analyses. Significant group main effects were followed up with pairwise comparisons and least significant difference post hoc analyses. Multivariate analysis of covariance was also used to investigate pathology (disk pathology, stenosis, and spondylolisthesis) differences in the pre- versus postoperative SF-36 PCS, SF-36 MCS, mODI, NRS-L, and NRS-B scores between BMI groups. Significance was considered as p < 0.05.

Results

Between 2008 and 2013, 500 consecutive patients (50.4% female) met the study inclusion criteria. The mean age was 55.16 years with a mean number of comorbidities of 0.44 per patient (range: 0 to 5). The mean BMI measured 30 kg/m², reflecting a significantly overweight population. The average postoperative follow-up was 21 months, with a 1-year follow-up rate of 95%. The surgeon-reported primary indication for surgery included leg pain (40.4%), claudication (30.3%), equal back and leg pain (23.2%), or other symptoms (6.1%; back pain, deformity, neurologic deficit). The primary pathologies included stenosis (43.3%), disk pathology (39.5%), spondylolisthesis (11.7%), and other (5.5%; deformity, instability other than spondylolisthesis, failed fusion). Aside from BMI, there were some other statistically significant differences in demographic variables (Table 1), thereby justifying our controlled model.

Table 1

Baseline patient demographics

Measure	Sample total (n =500)	NW (BMI 18.5–24.99 kg/m²; n = 107)	OW (BMI 25.00–29.99 kg/m²; n = 180)	OB (BMI 30.00–34.99 kg/m²; n = 113)	MO (BMI ≥ 35; n = 100)	p Value
Mean age (SD)	55.16 (14.70)	50.49 (16.56)	55.83 (14.69)	57.55 (14.47)	55.83 (11.62)	NW–OW: 0.003 NW–OB: <0.001 NW–MO: 0.009 OW–OB: 0.324 OW–MO: 0.999 OB–MO: 0.389
% Female	50.4	65.4	44.4	45.1	52.0	NW–OW: 0.001 NW–OB: 0.004 NW–MO: 0.050 OW–OB: 0.908 OW–MO: 0.225 OB–MO: 0.317
Comorbidities (%) 1 2 ≥3	23 5.9 2.5	17.8 2.8 1.8	18.9 4.4 1.7	31.9 8.8 2.7	27.0 10.0 5.0	NW–OW: 0.898 NW–OB: 0.009 NW–MO: 0.014 OW–OB: 0.013 OW–MO: 0.017 OB–MO: 0.731
Primary symptom (%) Leg pain Neurogenic Back and leg pain Claudication Other	40.7 30.5 23.4 5.4 0.0	43.0 14.0 32.7 10.3 0.0	43.9 32.8 18.3 5.0 0.0	40.7 38.1 17.7 3.6 0.0	33.3 37.4 27.3 2.0 0.0	NW–OW: 0.001 NW–OB: <0.001 OW–OB: 0.785 NW–MO: <0.001 OW–MO: 0.113 OB–MO: 0.335
Primary diagnosis (%) Stenosis Disk pathology Spondylolisthesis Other	43.5 39.7 11.8 5.0	28.0 44.9 15.9 11.2	42.2 42.2 11.1 4.5	53.0 38.1 8.0 0.9	53.0 30.0 14.0 4.0	NW–OW: 0.025 NW–MO: 0.001 NW–OB: <0.001 OW–OB: 0.131 OW–MO: 0.176 OB–MO: 0.255

Abbreviations: BMI, body mass index; MO, morbidly obese; NW, normal weight; OB, obese; OW, overweight; SD, standard deviation.

There were also some statistically significant differences in the surgical factors between groups, including primary surgeon (chi-square [3, n = 500] = 10.681, p = 0.014) and number of levels of intervention (F[3,452] = 3.972, p = 0.008), which were accounted for in our model. There were no significant differences in the frequency of minimally invasive surgery versus open approach, percent of patients who had previous lumbar surgery, type of surgery (fusion versus nonfusion), surgical time, estimated blood loss, or length of stay between groups (Table 2).

Table 2

Surgical factors

Measure	Sample total (n = 500)	NW (BMI 18.5–24.99 kg/m²; n = 107)	OW (BMI 25.00–29.99 kg/m²; n = 180)	OB (BMI 30.00–34.99 kg/m²; n = 113)	MO (BMI ≥ 35; n = 100)	p Value
Surgical access (%) MIS Open	33.3 66.7	23.6 76.4	33.7 66.3	35.4 64.6	37.4 62.6	0.142
Primary surgeon (%) 1 2	61.3 38.7	72.9 27.1	66.1 33.9	56.6 43.4	54.0 46.0	NW–OW: 0.231 NW–OB: 0.012 NW–MO: 0.005 OW–OB: 0.103 OW–MO: 0.046 OB–MO: 0.669
Number of levels (SD)	1.76 (1.78)	2.30 (2.97)	1.63 (1.59)	1.58 (0.87)	1.70 (1.12)	NW–OW: 0.002 NW–OB: 0.003 NW–MO: 0.016 OW–OB: 0.802 OW–MO: 0.763 OB–MO: 0.622
% Previous surgery	13.4	14.0	13.4	9.1	15.2	0.568
Surgery type (%) Nonfusion Fusion	39.5 60.5	35.8 64.2	45.5 54.5	38.9 61.1	35.4 64.6	0.389
Mean OR time (SD)	125.75 (61.20)	127.22 (75.25)	121.13 (65.50)	121.64 (54.90)	136.00 (58.00)	0.335
Mean estimated blood loss (SD)	353.58 (471.56)	391.99 (605.58)	302.85 (403.62)	351.03 (433.81)	413.45 (480.65)	0.238
Mean length of hospital stay (SD)	3.78 (4.18)	4.2 (5.01)	3.6 (3.83)	4.1 (4.36)	3.1 (3.69)	0.209

Abbreviations: BMI, body mass index; mis, minimally invasive surgery; MO, morbidly obese; NW, normal weight; OB, obese; OR, operating room; OW, overweight; SD, standard deviation.

The primary end points were patient satisfaction and change in SF-36 PCS, SF-36 MCS, mODI, NRS-B, and NRS-L scores. All the groups demonstrated statistically significant improvement for all primary outcome measures (mean Δ [standard deviation]: SF-36 PCS: 10.48 [10.37]; SF-36 MCS: 6.47 [12.86]; mODI: −22.35 [20.28]; NRS-B: −3.68 [2.88]; NRS-L: −4.15 [3.27]; satisfaction: 74.9% satisfied, 16.5% neutral, 8.6% dissatisfied). Contrary to our hypothesis, BMI was not associated with the degree of change for any primary outcome measures (Table 3 and Figs. 1A to E).

Fig. 1

(A) Short Form 36 Physical Component Summary scores. (B) Short Form 36 Mental Component Summary scores. (C) Numerical Rating Scale back pain scores. (D) Numerical Rating Scale leg pain scores. (E) Modified Oswestry Disability Index scores.

Table 3

Primary outcome measure results

Measure	Sample total (n = 500)	Normal (BMI 18.5–24.99 kg/m²; n = 107)	Overweight (BMI 25.00–29.99 kg/m²; n = 180)	Obese (BMI 30.00–34.99 kg/m²; n = 113)	Morbidly obese (BMI ≥ 35 kg/m²; n = 100)	p Value
ΔSF-36 PCS (SD)	10.48 (10.37)	10.12 (12.43)	11.47 (9.74)	9.67 (9.56)	11.08 (10.01)	0.525
ΔSF-36 MCS (SD)	6.47 (12.86)	8.84 (12.42)	6.81 (12.79)	3.92 (13.34)	6.51 (12.85)	0.168
Δ mODI (SD)	−22.35 (20.28)	−24.75 (21.44)	−23.47 (19.57)	−20.07 (18.55)	−22.17 (21.07)	0.895
ΔNRS back (SD)	−3.68 (2.88)	−3.72 (2.86)	−3.80 (2.71)	−3.53 (3.14)	−3.75 (2.92)	0.975
ΔNRS leg (SD)	−4.15 (3.27)	−4.15 (3.20)	−4.37 (3.20)	−3.98 (3.50)	−4.07 (3.25)	0.992
Patient satisfaction (%) Satisfied Neutral Dissatisfied	74.9 16.5 8.6	79.0 13.4 8.6	79.4 14.9 5.7	68.5 22.2 9.3	68.8 18.3 12.9	0.162

Abbreviations: BMI, body mass index; MCS, Mental Component Summary; mODI, modified Oswestry Disability Index; NRS, Numerical Rating Scale; PCS, Physical Component Summary; SF-36, Short Form 36; SD, standard deviation.

The secondary end points included any unplanned surgery-related events. For the entire study population, the average number of events per 100 patients was observed as follows: perioperative AE: 4 events/100 patients; postoperative AE: 19 events/100 patients; postoperative emergency department assessment: 35 visits/100 patients; reoperation: 13 revisions/100 patients; and readmission: 79 readmission days/100 patients. None of these were significantly different between groups. However, when we broke emergency department visits down by primary complaint (pain-related, physiology-related, psychology-related, and other), we observed that morbidly obese patients presented to the ER for pain-related complaints significantly more frequently than normal-weight patients (p = 0.043) and overweight patients (p = 0.005; Table 4 and Figs. 2A to E). To explore this aspect further, we conducted a regression analysis between preoperative MCS values and postoperative emergency department utilization. The results suggest that preoperative MCS values may be a risk factor for postoperative emergency department utilization, even though there were no differences in baseline MCS values between groups (R² = 0.013, F[1,500] = 6.80, p = 0.009).

Fig. 2

(A) Perioperative adverse events. (B) Postdischarge emergency department utilization. (C) In-hospital adverse events. (D) Reoperation rate. (E) Hospital readmissions.

Table 4

Surgical complications

Measure	Sample total (n = 500)	NW (BMI 18.5–24.99 kg/m²; n = 107)	OW (BMI 25.00–29.99 kg/m²; n = 180)	OB (BMI 30.00–34.99 kg/m²; n = 113)	MO (BMI ≥35 kg/m²; n = 100)	p Value
Periop AEs/100 patients	4 AEs/100 patients	5 AEs/100 patients	6 AEs/100 patients	3 AEs/100 patients	3 AEs/100 patients	0.544
1 2 ≥3	3.6% 0.4% 0%	2.8% 0.9% 0%	5.0% 0.5% 0%	2.6% 0% 0%	3.0% 0% 0%	–
Postop AEs/100 patients	19 AEs/ 100 patients	21 AEs/ 100 patients	20 AEs/ 100 patients	14 AEs/ 100 patients	20 AEs/ 100 patients	0.779
1 2 ≥3	8.8% 2.5% 1.7%	10.3% 1.9% 1.9%	7.8% 2.2% 2.2%	7.1% 3.5% 0%	10.0% 2.0% 2.0%	–
Postdischarge ED Use^a	171 visits by 89 patients (35 visits/100 patients)	32 visits by 17 patients (29 visits/100 patients)	43 visits by 30 patients (23 visits/100 patients)	41 visits by 19 patients (34 visits/100 patients)	55 visits by 23 patients (55 visits/100 patients)	0.060
Pain-related	74 visits by 50 patients (18 visits/100 patients)	14 visits by 8 patients (13 visits/100 patients)	16 visits by 12 patients (9 visits/100 patients)	24 visits by 16 patients (21 visits/100 patients)	30 visits by 14 patients (30 visits/100 patients)	NW–OW: 0.567 NW–OB: 0.314 NW–MO: 0.043 OW–OB: 0.087 OW–MO: 0.005 OB–MO: 0.288
Psychology-related	16 visits by 9 patients (3 visits/100 patients)	3 visits by 1 patient (3 visits/100 patients)	1 visit by 1 patient (<1 visit/100 patients)	6 visits by 3 patients (5 visits/100 patients)	6 visits by 4 patients (6 visits/100 patients)	0.357
Physiology-related	35 visits by 29 patients (7 visits/100 patients)	2 visits by 2 patients (2 visits/100 patients)	18 visits by 15 patients (10 visits/100 patients)	6 visits by 5 patients (5 visits/100 patients)	9 visits by 7 patients (9 visits/100 patients)	0.123

Abbreviations: AE, adverse event; BMI, body mass index; ED, emergency department; MO, morbidly obese; NW, normal weight; OB, obese; OR, operating room; OW, overweight; periop, perioperative; postop, postoperative; SD, standard deviation.

Total visits by total number of patients who visited the ED after surgery (mean ED use/100 patients).

Results by primary pathology showed no statistically significant differences within disk pathology (p = 0.204), stenosis (p = 0.088), or spondylolisthesis (p = 0.642).

Discussion

The Center for Disease Control reported the U.S. national obesity rate as 35%.²⁴ Similarly, the Canadian Institute for Health Information reported their national obesity rate as 25%.25 The United States ranked first and Canada fourth in obesity prevalence of the Organization for Economic Co-operation and Development countries. As there is no projected improvement in population health regarding BMI, understanding its effect on surgery is essential.

There are two main patterns in the body of research assessing BMI and spine surgery outcomes: studies assessing complications and those assessing subjective patient outcomes. This study enhances our understanding of patient-reported outcomes while also allowing us to observe postoperative complications.

Three systematic reviews and one large population-based study have identified obesity as a strong risk factor for the occurrence of postoperative spine surgical site infection.⁸,¹⁰,²⁶ Two additional large population-based studies identified obesity as a strong risk factor for the occurrence of any perioperative complication for spine surgery.¹⁷,²⁷,²⁸,²⁹ A third such study by Gaudelli and Thomas reported greater reoperation rates in obese patients.¹²

A meta-analysis by Abdallah et al evaluated 10 studies and demonstrated a log-linear relationship between obesity and surgical site infection; for each 5-point increase in BMI, there was a 21% increase in risk for surgical site infection.¹¹ However, some authors reported no difference in complications between obese and nonobese patients, attributing this discrepancy to the use of minimally invasive techniques.³⁰,³¹,³²

Although the correlation of elevated BMI and surgical complications appears strong, the effect of obesity on postoperative outcomes remains controversial. Swedish Spine Registry stenosis data and Spine Patient Outcomes Research Trial (SPORT) disk herniation data both demonstrated greater improvement in the nonobese patients undergoing surgery for lumbar disk herniation.¹⁵

Conversely, the SPORT spondylolisthesis data demonstrated no difference in outcomes based on obesity. Several other authors have identified no deleterious effect of elevated BMI on patient-reported outcomes following spine surgery, suggesting the success may be related to the use of minimally invasive techniques.¹³,³³,³⁴

The present study assessed a real-world sample of patients having spine surgery for a variety of pathologies, which is valuable for the generalizability of the results. However, if the relationship between BMI and outcomes is mediated by pathology, that might explain why we did not detect significant differences in the present study. The current study found that BMI did not have a statistically significant effect on surgical outcomes within specific pathologies. The current study was powered with pathologies collapsed; further investigation where analysis by pathology is the primary goal of the study is warranted.

It is also important to note that we did detect significant differences in the number of levels of surgical intervention between groups, which was controlled for in our statistical model but may indicate a surgical selection bias. The study is unable to quantify the conscious and unconscious decision making involved in selecting an obese patient for surgery. Surgeon perceptions are prone to change based on the physical appearance and fitness of the patient being considered for surgery.³⁵,³⁶,^37,38 Surgeon-perceived risk versus benefit may bias surgeons toward nonoperative care in obese patients. Thus, this study may simply include a subset of obese patients who present the lowest risk for surgical complications. Future research should aim to compare patients with elevated BMI who are managed both operatively and nonoperatively.

Surgical complications have been linked to increased care costs.³⁹ It is reasonable to conclude that there may be a link between elevated BMI and elevated cost of care in light of the findings reviewed here. Kalanithi et al identified a 28% increase in perioperative costs for the morbidly obese patient.¹⁷ These costs were attributable to greater resource utilization for care of complications and length of hospital stay.

Our findings suggest that all other factors being equal (age, gender, number of levels, comorbidities, etc.), obese patients may obtain spine surgery outcomes that are as good as those reported by normal-weight patients. In light of this observation, BMI alone may not be an appropriate discriminator in surgical decision making. Although the magnification of risk and readmission and reoperation rates found in previous research need to be disclosed during the consent process, the potential for equivalent improvement is supported by this study. Surgeons prove sound decision makers in selecting those patients who will benefit from surgery, despite their body habitus.

There are several possible reasons for the discrepancy between our results and previous research.¹⁵,¹⁶ Patients of normal weight comprised only 21.4% of our total study population. It is possible this high volume of obesity makes the team more proficient at mitigating problems and maximizing surgical success in these patients. Case volume has been reported as an advantage in improved outcomes and decreased complications in several clinical scenarios.⁴⁰,⁴¹

Similar findings have been reported previously in the orthopedic joint arthroplasty literature. Multiple authors have confirmed equal or greater success in the obese patient following total knee or total hip arthroplasty despite a less favorable complication profile.⁴² So far, no one has defined a BMI above which surgical risk is too great or surgery is precluded.

The progression toward greater body habitus requires medical providers to reevaluate the provision of care in all areas of medicine and in spine care specifically. Clinical symptoms may present earlier, physical examination will be more challenging, diagnostic accuracy may be altered, and treatment efficacy may change. Surgical success will need reevaluation to understand the outcomes and complications specific to this new physiology. Technique modification may improve success—for example, the use of minimally invasive techniques. Payers should expect the evaluation and treatment of these patients to cost more. Ultimately, the care landscape must change to accommodate this new medical environment.

Advantages

The study outline follows the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting observational studies.⁴³ The sample size is large and well beyond the participant and group numbers needed to prevent type II error for primary outcomes. Perioperative measures, complications, revision surgery rates, and patient-reported outcomes are provided at minimum 1-year follow-up. The literature to date is limited on this outcome data and on medium-term follow-up. Finally, all surgical types were included, improving the generalizability of the data for surgical decision making.

Limitations

The study was designed to evaluate outcomes. It was not powered specifically to address the secondary measures of unplanned surgery-related events, and thus a type II error may be possible for detecting differences in variables such as readmission rates and revision surgery. The current study was also not powered by pathology; the ability to make conclusions by pathology could lead to enhanced understanding of the role of BMI in the surgical outcomes.

This study is also limited by the length of follow-up. Obese patients could be at greater risk of declined function, adjacent segment breakdown, and instrumentation/implant failure occurring beyond the period measured. Future research following patients for longer would be valuable.

At present, BMI represents the most widely used and easily obtained measure of obesity. However, measures such as subcutaneous fat thickness over the lumbar spine or percent body fat may be more accurate in correlating obesity and surgical complications.⁴⁴,⁴⁵ No correlation has been found between these measures and BMI in the literature.

The study was unable to quantify the surgical challenges associated with treating obese patients. Obesity may increase the difficulty of certain technical aspects of the surgery. Obesity also often increases the nursing care burden postoperatively. Increased efforts required to achieve success are often absorbed by the individual providers and the system in general and thus are more difficult to identify.

Conclusions

Patients of all levels of obesity experienced significant improvement following elective thoracolumbar spine surgery. These outcomes were achieved without increased risk of postoperative complications such as infection and reoperation. Therefore, obesity alone may not be enough to preclude patients from elective thoracolumbar spine surgery.

Future research should address (1) the effect of BMI on surgical decision making, (2) surgical team volumes/surgical techniques best suited to patients with elevated BMI, and (3) the relationship between elevated BMI and postoperative emergency department presentation.

Multicenter studies with longer follow-up would help elucidate long-term outcomes. A risk–benefit algorithm based on large population-based data sets to assist with surgical decision making would be valuable.

Disclosures

Neil A. Manson, Research grant: Medtronic Canada

Alana J. Green, Personal fees: Canada East Spine Centre

Edward P. Abraham, Research grant: Medtronic Canada; Personal fees: Medtronic Canada

Footnotes

Acknowledgments

Research administration and personnel were supported via an unconditional research grant provided by Medtronic Canada. The database and database administration were supported via an unconditional research grant provided by Nuvasive.

References

Flegal

K M

Carroll

M D

Kit

B K

Ogden

C L

Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010

JAMA 2012 307 5 491–497

Gotay

C C

Katzmarzyk

P T

Janssen

Dawson

M Y

Aminoltejari

Bartley

N L

Updating the Canadian obesity maps: an epidemic in progress

Can J Public Health 2013 104 1 e64–e68

Ogden

C L

Carroll

M D

Curtin

L R

McDowell

M A

Tabak

C J

Flegal

K M

Prevalence of overweight and obesity in the United States, 1999–2004

JAMA 2006 295 13 1549–1555

Tjepkema

Adult obesity in Canada: measured height and weight. Nutrition: Findings from the Canadian Community Health Survey

In:

Component of Statistics Canada Catalogue no. 82–620–MWE2005001

Ottawa, Canada

Statistics Canada

2005

Michimi

Wimberly

M C

Spatial patterns of obesity and associated risk factors in the conterminous U.S

Am J Prev Med 2010 39 2 e1–e12

Global Database on Body Mass Index

BMI Classification

World Health Organization. Updated January 12, 2014. Available at: http://apps.who.int/bmi/index.jsp?introPage=intro_3.html . Accessed January 12, 2014

Keys

Fidanza

Karvonen

M J

Kimura

Taylor

H L

Indices of relative weight and obesity

J Chronic Dis 1972 25 6 329–343

Xing

J X

X L

, et al.

A methodological, systematic review of evidence-based independent risk factors for surgical site infections after spinal surgery

Eur Spine J 2013 22 3 605–615

Kurtz

S M

Lau

Ong

K L

, et al.

Infection risk for primary and revision instrumented lumbar spine fusion in the Medicare population

J Neurosurg Spine 2012 17 4 342–347

10.

Pull ter Gunne

A F

Hosman

A J

Cohen

D B

, et al.

A methodological systematic review on surgical site infections following spinal surgery: part 1: risk factors

Spine (Phila Pa 1976) 2012 37 24 2017–2033

11.

Abdallah

D Y

Jadaan

M M

McCabe

J P

Body mass index and risk of surgical site infection following spine surgery: a meta-analysis

Eur Spine J 2013 22 12 2800–2809

12.

Gaudelli

Thomas

Obesity and early reoperation rate after elective lumbar spine surgery: a population-based study

Evid Based Spine Care J 2012 3 2 11–16

13.

Lau

Ziewacz

Park

Minimally invasive transforaminal lumbar interbody fusion for spondylolisthesis in patients with significant obesity

J Clin Neurosci 2013 20 1 80–83

14.

Rihn

J A

Radcliff

Hilibrand

A S

, et al.

Does obesity affect outcomes of treatment for lumbar stenosis and degenerative spondylolisthesis? Analysis of the Spine Patient Outcomes Research Trial (SPORT)

Spine (Phila Pa 1976) 2012 37 23 1933–1946

15.

Rihn

J A

Kurd

Hilibrand

A S

, et al.

The influence of obesity on the outcome of treatment of lumbar disc herniation: analysis of the Spine Patient Outcomes Research Trial (SPORT)

J Bone Joint Surg Am 2013 95 1 1–8

16.

Knutsson

Michaëlsson

Sandén

Obesity is associated with inferior results after surgery for lumbar spinal stenosis: a study of 2633 patients from the Swedish spine register

Spine (Phila Pa 1976) 2013 38 5 435–441

17.

Kalanithi

P A

Arrigo

Boakye

Morbid obesity increases cost and complication rates in spinal arthrodesis

Spine (Phila Pa 1976) 2012 37 11 982–988

18.

Anderson

P A

Dettori

J R

Hermsmeyer

J T

Does lumbar decompression in overweight patients assist in postoperative weight loss?

Evid Based Spine Care J 2010 1 2 34–38

19.

National Institutes of Health

Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report

Obes Res 1998 6 2 02 51S–209S

20.

Rampersaud

Y R

Neary

M A

White

Spine adverse events severity system: content validation and interobserver reliability assessment

Spine (Phila Pa 1976) 2010 35 7 790–795

21.

Samsa

Edelman

Rothman

M L

Williams

G R

Lipscomb

Matchar

Determining clinically important differences in health status measures: a general approach with illustration to the Health Utilities Index Mark II

Pharmacoeconomics 1999 15 2 141–155

22.

Hays

R D

Woolley

J M

The concept of clinically meaningful difference in health-related quality-of-life research. How meaningful is it?

Pharmacoeconomics 2000 18 5 419–423

23.

Copay

A G

Glassman

S D

Subach

B R

Berven

Schuler

T C

Carreon

L Y

Minimum clinically important difference in lumbar spine surgery patients: a choice of methods using the Oswestry Disability Index, Medical Outcomes Study questionnaire Short Form 36, and pain scales

Spine J 2008 8 6 968–974

24.

Ogden

C L

Carroll

M D

Kit

B K

Flegal

K M

Prevalence of obesity in the United States, 2009-2010

NCHS Data Brief 2012 82 82 1–8

25.

Hodgson

Obesity in Canada: A Joint Report from the Public Health Agency of Canada and the Canadian Institute for Health Information

Ottawa, Canada

Public Health Agency of Canada, Canadian Institute for Health Information

2011

26.

Schuster

J M

Rechtine

Norvell

D C

Dettori

J R

The influence of perioperative risk factors and therapeutic interventions on infection rates after spine surgery: a systematic review

Spine (Phila Pa 1976) 2010 35 (9, Suppl): S125–S137

27.

Shamji

M F

Parker

Cook

Pietrobon

Brown

Isaacs

R E

Impact of body habitus on perioperative morbidity associated with fusion of the thoracolumbar and lumbar spine

Neurosurgery 2009 65 3 490–498 , discussion 498

28.

Buerba

R A

M C

Gruskay

J A

Long

W D

III

Grauer

J N

Obese class III patients at significantly greater risk of multiple complications after lumbar surgery: an analysis of 10,387 patients in the ACS NSQIP database

Spine J 2014 14 9 2008–2018

29.

Marquez-Lara

Nandyala

S V

Sankaranarayanan

Noureldin

Singh

Body mass index as a predictor of complications and mortality after lumbar spine surgery

Spine (Phila Pa 1976) 2014 39 10 798–804

30.

Senker

Meznik

Avian

Berghold

Perioperative morbidity and complications in minimal access surgery techniques in obese patients with degenerative lumbar disease

Eur Spine J 2011 20 7 1182–1187

31.

Tomasino

Parikh

Steinberger

Knopman

Boockvar

Härtl

Tubular microsurgery for lumbar discectomies and laminectomies in obese patients: operative results and outcome

Spine (Phila Pa 1976) 2009 34 18 E664–E672

32.

Jiang

Teng

Fan

Khan

Xia

Does obesity affect the surgical outcome and complication rates of spinal surgery? A meta-analysis

Clin Orthop Relat Res 2014 472 3 968–975

33.

Rosen

D S

Ferguson

S D

Ogden

A T

Huo

Fessler

R G

Obesity and self-reported outcome after minimally invasive lumbar spinal fusion surgery

Neurosurgery 2008 63 5 956–960 , discussion 960

34.

Singh

A K

Ramappa

Bhatia

C K

Krishna

Less invasive posterior lumbar interbody fusion and obesity: clinical outcomes and return to work

Spine (Phila Pa 1976) 2010 35 24 2116–2120

35.

Puhl

R M

Andreyeva

Brownell

K D

Perceptions of weight discrimination: prevalence and comparison to race and gender discrimination in America

Int J Obes 2008 32 6 992–1000

36.

Puhl

R M

Heuer

C A

The stigma of obesity: a review and update

Obesity (Silver Spring) 2009 17 5 941–964

37.

Puhl

Brownell

K D

Bias, discrimination, and obesity

Obes Res 2001 9 12 788–805

38.

Brownell

K D

Puhl

R M

Schwartz

M B

Rudd

Weight Bias: Nature, Consequences, and Remedies

New York, NY

The Guilford Press

2005

39.

Rampersaud

Y R

Tso

Walker

K R

, et al.

Comparative outcomes and cost-utility following surgical treatment of focal lumbar spinal stenosis compared with osteoarthritis of the hip or knee: part 2—estimated lifetime incremental cost-utility ratios

Spine J 2014 14 2 244–254

40.

Meredith

D S

Katz

J N

Procedure volume as a quality measure for total joint replacement

Clin Exp Rheumatol 2007 25 (6, Suppl 47): 37–43

41.

Vitale

M A

Arons

R R

Hyman

J E

Skaggs

D L

Roye

D P

Vitale

M G

The contribution of hospital volume, payer status, and other factors on the surgical outcomes of scoliosis patients: a review of 3,606 cases in the State of California

J Pediatr Orthop 2005 25 3 393–399

42.

Workgroup of the American Association of Hip and Knee Surgeons Evidence Based Committee

Obesity and total joint arthroplasty: a literature based review

J Arthroplasty 2013 28 5 714–721

43.

von Elm

Altman

D G

Egger

Pocock

S J

Gøtzsche

P C

Vandenbroucke

J P

; STROBE Initiative.

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies

Prev Med 2007 45 4 247–251

44.

Waisbren

Rosen

Bader

A M

Lipsitz

S R

Rogers

S O

Eriksson

Percent body fat and prediction of surgical site infection

J Am Coll Surg 2010 210 4 381–389

45.

Mehta

A I

Babu

Karikari

I O

, et al.

2012 Young Investigator Award winner: The distribution of body mass as a significant risk factor for lumbar spinal fusion postoperative infections

Spine (Phila Pa 1976) 2012 37 19 1652–1656

Elevated Patient Body Mass Index Does Not Negatively Affect Self-Reported Outcomes of Thoracolumbar Surgery: Results of a Comparative Observational Study with Minimum 1-Year Follow-Up

Abstract

Study Design

Objective

Methods

Results

Conclusions

Keywords

Introduction

Methods

Grouping Variable

Demographics

Surgical Factors

Outcome Measures

Perioperative Adverse Events

Statistics

Results

Discussion

Advantages

Limitations

Conclusions

Disclosures Neil A. Manson, Research grant: Medtronic Canada Alana J. Green, Personal fees: Canada East Spine Centre Edward P. Abraham, Research grant: Medtronic Canada; Personal fees: Medtronic Canada

Disclosures

Footnotes

Acknowledgments

References

Disclosures

Neil A. Manson, Research grant: Medtronic Canada

Alana J. Green, Personal fees: Canada East Spine Centre

Edward P. Abraham, Research grant: Medtronic Canada; Personal fees: Medtronic Canada