Impact of Increased Body Mass Index on Outcomes of Elective Spinal Surgery
Seicean, Andreea MPH, PhD*,†; Alan, Nima BS*; Seicean, Sinziana MD, PhD, MPH‡,§; Worwag, Marta BA¶; Neuhauser, Duncan PhD†; Benzel, Edward C. MD‖; Weil, Robert J. MD**,††
*Case Western Reserve University School of Medicine, Cleveland, OH
†Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH
‡Departments of Pulmonary Critical Care and Sleep Medicine, University Hospitals, Cleveland, OH
§Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH
¶Medical University of Warsaw, Warsaw, Poland
‖Department of Neurosurgery, The Neurological Institute, Cleveland Clinic, Cleveland, OH
**The Rose Ella Burkhardt Brain Tumor & Neuro-Oncology Center, Cleveland Clinic, Cleveland, OH; and
††Department of Neurosurgery, Geisinger Health System, Danville, PA.
Address correspondence and reprint requests to Andreea Seicean, MPH, PhD, c/o ND4-40 LRI/Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195; E-mail: email@example.com
Acknowledgment date: January 26, 2014. Revision date: April 30, 2014. Acceptance date: May 9, 2014.
The manuscript submitted does not contain information about medical device(s)/drug(s).
No funds were received in support of this work.
Relevant financial activities outside the submitted work: royalties.
Study Design. Observational retrospective cohort study of prospectively collected database.
Objective. To determine whether overweight body mass index (BMI) influences 30-day outcomes of elective spine surgery.
Summary of Background Data. Obesity is prevalent in the United States, but its impact on the outcome of elective spine surgery remains controversial.
Methods. We used National Surgical Quality Improvement Program, a prospective clinical database with proven validity and reproducibility consisting of 256 perioperative standardized variables from surgical patients at nearly 400 academic and nonacademic hospitals nationwide. We identified 49,314 patients who underwent elective fusion, laminectomy or both between 2006 and 2012. We divided patients according to BMI (kg/m2) as normal (18.5–24.9), preobese (25.0–29.9), obese I (30.0–34.9), obese II (35.0–39.9), and obese III (≥40). Relationship between increased BMI and outcome of surgery measured as prolonged hospitalization, complications, return to the operating room, discharged with continued care requirement, readmission, and death was determined using logistic regression before and after propensity score matching.
Results. All overweight patients (BMI ≥25 kg/m2) showed increased odds of an adverse outcome compared with normal patients in unmatched analyses, with maximal effect seen in obese III group. In the propensity-matched sample, obese III patients continued to show increased odds for complications (odds ratio, 1.6; 95% confidence interval, 1.1–2.3), readmission (odds ratio, 2.3; 95% confidence interval, 1.1–4.9), and return to the operating room (odds ratio, 1.8; 95% confidence interval, 1.1–3.1).
Conclusion. Impact of obesity on elective spine surgery outcome is mediated, at least in part, by comorbidities in patients with BMI between 25.0 and 39.9 kg/m2. However, BMI itself is an independent risk factor for adverse outcomes in morbidly obese patients.
Level of Evidence: 3
Obesity is prevalent in United States, and associated with numerous comorbidities.1,2 In several surgical specialties, including spine surgery, relationships between obesity and surgical outcome have been investigated,3–8 although the results have been conflicting. Because patient selection contributes to the success of elective spine surgery,9 it is important to elucidate more definitively the relationship between obesity and surgical outcome.
We studied the impact of increased body mass index (BMI) on outcome of elective spine surgery during a recent, 7-year period, using the National Surgical Quality Improvement Program.
MATERIALS AND METHODS
We used the American College of Surgeons' National Surgical Quality Improvement Program (NSQIP) database to analyze patients operated on between 2006 and 2012. This study was approved by Cleveland Clinic Institutional Review Board.
NSQIP is a national, validated, and prospective clinical database collected from nearly 400 community and academic hospitals, and includes 30-day postoperative outcomes. At each site, a trained surgical clinical nurse collects data in a deidentified manner from randomly assigned patients according to standardized definitions.10–12 NSQIP undergoes annual quality checks to ensure that data reporting achieves more than 95% 30-day outcome follow-up across consecutive cycles at each institution, thus guaranteeing high accuracy and reproducibility.10,11,13
We originally identified 68,291 patients who underwent spine surgery between 2006 and 2012 (Figure 1). We excluded emergency cases (n = 1539), patients with septic shock (n = 42), and those who received preoperative transfusion (n = 269), features that dictate a distinct postoperative course. The focus on this study was in patients who underwent fusion, laminectomy, or both. Patients who did not undergo a laminectomy or fusion with the operative procedure were excluded (n = 7896). The following diagnoses, based on International Classification of Diseases, Ninth Revision classification were included: spondylosis (721.0–721. 42, 721.9, 721.91); disc displacement (722.0–722.2); disc degeneration (722.4–722.6); intervertebral disc disorder (722.7–722.73); spinal stenosis (723.0 and 724.0–724.09); and spondylolisthesis (738.4 and 756.12) (Figure 2A). Patients with other diagnoses were excluded (n = 8184) (Figure 2B). In the final round of determining which of the patients were to be included, those whose BMI could not be calculated because of missing data on weight, height, or both were excluded (n = 310) and patients with BMI less than 18.5 (n = 737), who may present with perioperative issues distinct from those with obesity, were also excluded. Our final sample consisted of 49,314 patients.
We stratified patients according to the World Health Organization's BMI classification system14 into 5 groups: normal (18.5–24.9 kg/m2; n = 10,088), preobese (25.0–29.9 kg/m2; n = 17,035), obese I (30.0–34.9 kg/m2; n = 12,647), obese II (35.0–39.9 kg/m2; n = 5938), and obese III (≥40 kg/m2; n = 3606). Also, we examined BMI as a continuous variable in sensitivity analyses.
We analyzed all available pre- and intraoperative factors, previously identified as having an effect on postoperative outcomes (Table 1). Insufficient studies have been conducted to reach definitive conclusion as to whether ethnicity affects outcome of spine surgery.15 Patient race and ethnicity variables recorded in the NSQIP database are self-reported as American Indian or Alaska Native, Asian, African American, Native Hawaiian or Pacific Islander, unknown or Caucasian, and Hispanic or non-Hispanic.16 For the purpose of this study, we combined the race and ethnicity variables to identify patients who defined themselves as non-Hispanic Caucasian versus any other combination of race and ethnicity.
Outcomes of Interest
We examined the following 30-day outcome measures after surgery: (1) prolonged length of hospital stay (LOS), defined as LOS longer than the third quartile (>75% of the sample, which was 5 d); (2) minor complications that included superficial surgical site infection, urinary tract infection, deep venous thrombosis, or thrombophlebitis; (3) major complications, which consisted of deep incision surgical site infection, organ or space surgical site infection, wound disruption, pneumonia, unplanned intubation, pulmonary embolism, more than 48-hour postoperative ventilator-assisted respiration, progressive renal insufficiency, acute renal failure, cerebrovascular accident with neurological deficit, coma of more than 24 hours, peripheral nerve injury, cardiac arrest requiring cardiopulmonary resuscitation, myocardial infarction, graft, prosthesis or flap failure, sepsis, septic shock, and/or 30-day return to the operation room (OR); (4) any complication, which was defined as having at least 1 minor or major complications; (5) unanticipated return to the OR, which was defined as return to the OR for any major surgical procedure; (6) discharged with continued care requirement, which was defined as discharge to a care facility (exempting those who were initially admitted from such facilities); (7) readmission, which was defined as any unplanned readmission to the same or another hospital within 30 days of index surgery; and (8) death within 30 days of index surgery.
We compared patients in the 4 study groups, the preobese, obese groups I–III, separately, with patients of normal BMI (Table 1). Because of retrospective nature of the analysis, we had to control for selection bias to ensure that patients were randomly assigned to each BMI category. Propensity score, as applied in this study, is defined as the probability of a patient being grouped in a specific BMI category, given the observed covariates. It is determined using multivariate logistic regression with BMI as the dependent variables and selected group of observed covariates as independent variables.17 Matching the propensity scores allows for balanced distribution of observed covariates in an observational study similar to randomization in a prospective study.18,19 This statistical measure has been used previously in similarly designed studies.20–23 We determined the propensity scores for each patient based on the variables that were unbalanced in comparison of normal and each category of overweight/obese. To determine covariate balance, we used absolute standardized difference.18,19 Unlike significance tests, where statistical difference is reported as P values, standardized difference does not depend on sample size, which is important in matched analyses because the inadvertently smaller size of the matched cohort may result in the false notion that improved covariate balance was achieved with matching.18 An absolute standardized difference of more than 0.20 was considered significant.19 The variables that had absolute standardized difference more than 0.20 for each category are shown boldfaced in Table 1. For example, sex and hypertension requiring medication were significantly different between normal weight and preobese patients. Thus, sex and hypertension were used to generate the propensity score. Using propensity scores, we matched patients in each overweight BMI category to that of a patient with a normal BMI with 1:1 greedy matching technique24 (Table 2). For example, we matched 10,088 normal to 10,088 preobese patients. Then, we checked to confirm that the baseline characteristic was similar between normal and preobese patients in the matched sample (Table 2).
We compared frequency of 30-day outcomes in the unmatched and matched cohorts using Pearson χ2 tests for categorical variables and analysis of variance for continuous variables (Tables 3, 4). Logistic regression analysis was used to examine the association between increased BMI and adverse outcomes, in the general cohort (Figure 3A–E). In the matched cohort, conditional logistic regression was used to take into account the matched nature of data.25 We also studied increased BMI as a continuous variable in increments of 5 units starting at 18.5 kg/m2. SAS (version 9.2, SAS Institute, Cary, NC) was used for all statistical analyses.
We compared baseline characteristics, including demographic variables, preoperative lab values and comorbidities, between patients in the preobese and obese I–III categories and those with normal BMI; these results are detailed in Table 1. Covariate imbalance was more pronounced with increasing levels of BMI. Both the number of imbalanced covariates and the level of imbalance for a given variable increased with advancement to next overweight category such that patients in obese III category have markedly different distribution of covariates compared with normal patients. Hypertension, diabetes, and American Association of Anesthesiologists classification, and smoking status were among these variables. Upon propensity score matching, covariate balance was achieved for all variables indicating random distribution of variables within each BMI category (Table 2).
In the general cohort, median length of hospitalization was 2 days for all patients, but prolonged LOS, determined to be more than 5 days, was more common in patients with higher BMI (Table 3). All other outcome measures were more common in increasingly obese patients. In the matched cohort, prolonged LOS was more common in only obese II and obese III patients (Table 4). All other adverse outcomes except return to OR and readmission were more frequent among obese III patients. Mortality rate, in the general or matched cohort, varied between 0.1% or 0.2% in all groups, with no significant difference.
Preobese patients did not have increased odds for prolonged length of stay, complications, 30-day return to operating room or discharged with continued care requirement when compared with patients with normal BMI, except for a slight increase for readmission (odds ratio [OR], 1.3; 95% confidence interval [CI] 1.1–1.5) (Figure 3A–D). This relationship did not persist in the matched cohort. Patients in obese I category had increased odds for complications (OR, 1.2; 95% CI, 1.1–1.3) and readmission (OR, 1.3; 95% CI, 1.1–1.5) in the unmatched cohort, but neither persisted in propensity score matched cohort (Figure 3B–E).
Patients in obese II category had increased odds for prolonged length of stay, complications, discharged with continued care requirement, and readmission in the unmatched sample (Figures 3A, B, D). In the matched sample, however, obese II category was associated with prolonged length of stay only (OR, 1.4; 95% CI, 1.3–1.5) (Figure 3A).
Morbidly obese patients (obese III) had significantly increased odds for all outcome measures prior to matching (Figure 3A–E). Upon matching, morbidly obese patients had increased odds for prolonged length of stay (OR, 1.3; 95% CI, 1.1–1.5), complications (OR, 1.4; 95% CI, 1.1–1.9), and discharged with continued care requirement (OR, 2.3; 95% CI, 1.1–4.4) (Figure 3A, B, D). Thus, BMI 40 kg/m2 or more was independently associated with a more morbid postoperative course.
In sensitivity analyses, BMI was assessed as a continuous variable. In univariate analyses, every 5 units increase in BMI was associated with slightly increased odds (between 1.1 and 1.3) for prolonged LOS, complications, return to the OR, and discharged with continued care requirement. These findings were consistent in multivariate analyses, whereby all significantly imbalanced covariates in Table 1 were included in the model. We also assessed race as Caucasian, African American, Hispanic, or other, which did not change our results (data not shown).
This study provides insight into the relationship between BMI and adverse outcomes after elective spine surgery. Increasing BMI is associated with poorer outcomes, regardless of the extent of BMI increase above the normal range of 18.5 to 24.9 kg/m2. In preobese, obese I, and obese II category patients, comorbidities alone may account for the increased odds for adverse outcomes. However, in the morbidly obese, BMI independently—and isolated from comorbidities included in this analysis—was associated with an increased risk of morbidity in the first 30 days after surgery.
Interpretations of Results
The relationship between increased BMI and postoperative outcomes is confounded with conditions associated with obesity. As one may have reason to expect, baseline characteristics of all overweight categories differed from that of patients with a normal BMI (Table 1). Propensity score reduces selection bias by providing a predicted probability of exposure based on measured baseline characteristics.17 Subsequently, matching the propensity score distributes baseline characteristics among exposed (i.e., overweight BMI) and unexposed (i.e., normal BMI) patients randomly and evenly,24 which allows for optimal isolation of a variable, namely increased BMI, as an independent risk factor. This methodology provides the closest approximation to a randomized clinical trial.23,26
In unmatched analyses, preobesity was associated with increased odds only for readmission, with a nonsignificant trend toward poor outcome for other outcome measures (Figure 3E). Patients in both the obese I and II categories had increased odds for readmission and postoperative complications. In addition, patients in obese II category had increased odds for being discharged to a higher level of care than was needed at the time of admission (e.g., admitted from home but discharge to a skilled nursing facility). Patients in obese III category had increased odds for all outcome measures (Figure 3A–E). Thus, increasing level of BMI was more strongly associated with adverse outcomes. This trend is also observed in the distribution of outcomes (Tables 3, 4), where patients at higher BMI categories more frequently experience all adverse outcomes. Increased BMI was not associated with an excess of mortality (data not shown), which may be related to the low rates of mortality, ranging from 0.1% to 0.2% in the normal and all the 4 study groups.
Distribution of procedures and diagnoses among the patients in each BMI category was similar (Figure 2A, B). As we have noted, the association between increased BMI and adverse outcomes in unmatched analyses may reflect the impact of comorbidities. Overweight and obese patients are more likely to have multiple associated acute and chronic conditions that affect physiological fitness,2 features also seen in our study sample of nearly 50,000 patients undergoing spine surgery (Table 1). With propensity score matching we were able to generate cohorts with similar distribution of covariates thus eliminating the confounding effect of the observed covariates. In the matched cohorts, patients in the preobese, obese I, and II groups did not have increased odds for adverse outcomes, except for prolonged length of stay in obese II. Thus, it is likely that the comorbidities found in these patients, individually or collectively, contribute to suboptimal outcomes observed in unmatched analyses, rather than the elevated BMI in isolation. In contrast, morbidly obese patients (group III) had significantly increased odds for suboptimal outcomes, which included prolonged length of stay, complications, and discharged with continued care requirement. Therefore, with BMI 40 kg/m2 or more, irrespective of other comorbidities, patients are at increased risk of poor outcome when undergoing elective spine surgery.
Interpretations in the Context of the Literature
Several studies have examined the relationship between increased BMI and outcome of spine surgery, but with inconclusive results. Gepstein et al27 reported improvement in subjective outcome after lumbar decompressive laminectomy, discectomy, or both in 298 patients older than 65 years. Andreshak et al9 found no difference with regard to blood loss, operative time, hospital stay, rate of complications, and functional outcome in lumbar spine surgery between 55 obese (defined as >20% of ideal body weight) and 104 nonobese patients. Hanigan et al28 reported no difference in length of hospitalization, duration of disability, or incidence of surgical complications or 6-month subjective symptom improvement between 17 obese patients and 88 nonobese patients. Peng et al29 found no difference between 33 obese and 41 nonobese patients with respect to blood loss, length of time to ambulation, and length of hospitalization in anterior lumbar surgery. In a retrospective analysis of the Spine Patient Outcome Research Trial, Rihn et al30 found no difference in subjective symptom improvement at 1- to 4-year follow-up in 261 obese and 373 nonobese patients undergoing surgery for lumbar stenosis and degenerative spondylolisthesis. However, obese patients with degenerative spondylolisthesis, but not stenosis, were more likely to experience surgical site infection and reoperation.30 Obese and nonobese patients with lumbar disc herniation enrolled in Spine Patient Outcome Research Trial benefitted similarly from surgery.31 In a recent study based on NSQIP by Buerba et al,32 obesity of any class was not associated with adverse 30-day outcome in anterior and posterior cervical fusion surgery. In contrast, Schoenfeld et al,33 also using NSQIP, identified BMI as a predictor of postoperative morbidity in nearly 6000 patients after spinal arthrodesis. In a single institution, retrospective study of 84 patients, of whom 60 were overweight, Patel et al8 reported correlation between increasing BMI and complications of thoracic or lumbar spine surgery for degenerative spinal conditions at 30-day follow-up. Finally, Gaudelli and Thomas34 reported that obese patients (n = 332) were at risk of reoperation at 3-month follow-up compared with nonobese (n = 3056) patients who underwent elective lumbar surgery. However, none of these studies used unmatched, then matched grouping, with propensity matching, to eliminate the potential effect of comorbidities, especially those that are frequently associated with elevated BMI. Like studies in other surgical specialties,3,4,35 comparison of studies that examine the relationship of BMI and outcome after spine surgery must be carried out cautiously because these studies differ in study design and extent of control for confounding variables, the specific surgery and diagnoses included, number of patients and power of analysis, comparison of different BMI categories, length of follow-up, and the use of subjective versus objective outcome measures, and the detail and number of pre-, intra-, and postoperative features available.
Although propensity score matching is an appropriate statistical measure to separate the impact of BMI from potential confounding variables, in clinical practice this is more problematic. The fact remains that overweight patients tend to have more comorbidities that impact outcome of surgery. Evaluation and treatment of comorbidities in all patients regardless of BMI is necessary. But in morbidly obese patients, management of comorbidities reduces but does not eliminate the risk of morbidity 30 days postoperatively. Thus, patient selection becomes even more important, and discussion of the potential for increased perioperative complications also assumes increased significance.
This study has limitations. The NSQIP database collects patient-level clinical data prospectively, but the present report is retrospective in nature. Thus, we cannot establish an unequivocal cause and effect relationship between increased BMI and adverse outcomes. NSQIP is a surgical database; patients who were not offered surgery due to high BMI, comorbidities or other conditions, are not captured, which may introduce selection bias. Despite matching the propensity scores, this is not a randomized study, which means that we cannot rule out that the possibility that normal patients are different from preobese and obese patients with regard to preoperative factors of which we are unaware or lack data for. Relationships reported in this study pertain to 30-day perioperative period only; extrapolation of the results beyond this period should be exercised with caution. NSQIP does not contain any institutional related data, including data on clustering to show patients operated on by the same surgeon or coming from the same institution. Thus, we were not able to account for this in our analyses. The exact details and extent of neurological deficit or pain, before or after surgery, and other outcomes of interest (e.g., long-term functional outcome, return to work, or rates of pseudarthrosis, and the presence of depression) are not included in NSQIP. With regard to readmission, we cannot discern the reason for readmission because NSQIP started to collect data on the exact diagnosis associated with a readmission only in 2012. The surgical population captured by NSQIP may not be wholly representative of the US population of patients who undergo spine surgery because participation in NSQIP is voluntary. However, the sex and race distributions in the NSQIP database are consistent with the distribution of the US population and all of the data are collected prospectively from a number and variety of institutions, which provides a large and diverse sample size. Finally, all NSQIP data are collected in a standardized manner, with annual quality checks, and data reporting achieves more than 95% 30-day outcome follow-up rate across consecutive cycle, with high accuracy and reproducibility.36
In this investigation of a prospectively-collected database from nearly 400 institutions, we analyzed about 50,000 patients undergoing elective laminectomy, fusion, or both. We found that BMI of 25 or greater infers increased risk for adverse outcome of spine surgery. This effect was mediated by comorbidities associated with being overweight in those with BMI less than 40 kg/m2. But in morbidly obese patients, BMI itself was predictive of increased risk of prolonged length of stay, complications, and discharged with continued care requirement. These findings may assist in the evaluation, selection, and management of obese being considered for spine surgery.
* In our full study population of patients undergoing elective spine surgery (N = 49,314), all patients with BMI 25 kg/m2 or more had an increased risk for adverse outcomes 30 days postoperatively.
* After matching the propensity scores to achieve baseline and intraoperative covariate balance between BMI groups, only morbidly obese patients had increased risk for complications, prolonged hospitalization and requiring continued care upon discharge.
* Adverse effect of overweight BMI is mediated by its associated comorbidities, but in the morbidly obese, BMI independently is a risk factor for morbid postoperative course in elective spine surgery.
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body mass index; obesity; overweight; spine surgery; fusion; laminectomy; risk factor; outcome; morbidity; health services research
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