Risk Factors for Surgical Site Infections After Single-Level Anterior Lumbar Interbody Fusion

Abstract

Background:

Anterior lumbar interbody fusion (ALIF) has become an increasingly popular and effective treatment modality for various conditions of the lumbar spine. However, complications after this procedure can be costly. Surgical site infections (SSIs) are one of these types of complications. The present study identifies independent risk factors for SSI after single-level ALIF to identify high-risk patients better.

Patients and Methods:

The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried to identify single-level ALIF patients from 2005 to 2016. Multilevel fusions and non-anterior approach procedures were excluded. Mann-Pearson χ² tests analyzed categorical variables, whereas one-way analysis of variance (ANOVA) and independent t-tests analyzed differences in mean values of continuous variables. Risk factors for SSI were identified via a multivariable logistic regression model. A receiver operating characteristic (ROC) curve was generated utilizing the predicted probabilities.

Results:

A total of 10,017 patients met inclusion criteria; 80 (0.80%) had developed SSI and 9,937 (99.20%) had not. On multivariable logistic regression models, class 3 obesity (p = 0.014), dialysis (p = 0.025), long-term steroid use (p = 0.010), and wound classification 4 (dirty/infected) (p = 0.002) all independently increased the risk for SSI in single-level ALIF. The area under the receiver operating characteristic curve (AUROC; C-statistic) was 0.728 (p < 0.001), indicating relatively strong reliability of the final model.

Conclusions:

Several independent risk factors including obesity, dialysis, long-term steroid use, and dirty wound classification all increased risk for SSI after single-level ALIF. By identifying these high-risk patients, surgeons and patients can have more informed pre-operative discussions. In addition, identifying and optimizing these patients prior to operative intervention may help to minimize infection risk.

Infection after spinal surgery can be a devastating complication and may require multiple operative debridements, extended antibiotic courses, and even removal of instrumentation.¹ Overall rates of post-operative spine surgical site infection (SSI) vary and have been reported to be between 0.7% and 16%.² Risk factors for post-operative spine infection are well described and include patient-specific factors such as increased age, increased American Society of Anesthesiologists (ASA) score, comorbidities, prior surgery, smoking, and nutrition status.² Surgery-specific factors for SSI include increased operative time, increased blood loss, post-operative blood transfusion, instrumentation, multiple surgeries, increased number of levels fused, and length of hospital stay.² Additionally, an increased number of individuals in the surgical suite has also been reported to be an independent risk factor for infection.³ Although smaller procedures are associated with a lower infection rate, risk factors for SSI for patients undergoing single-level lumbar fusion (irrespective of approach) are similar (including obesity, increased ASA score, and increased surgical length).⁴

However, the risk factors for SSI in patients undergoing a single-level lumbar interbody fusion through an anterior approach have not been fully elucidated. Complications associated with the posterior and anterior approaches for lumbar interbody fusion differ and include vascular complications and ileus for the anterior approach and dural/neurologic for the posterior approach, but risk factors specific to post-operative infections are not well established.⁵ The present study seeks to identify independent risk factors for SSI after single-level anterior lumbar interbody fusion (ALIF) so that high-risk patients can be identified and potentially optimized pre-operatively to mitigate infection risk.

Patients and Methods

Patient selection

Patients who had undergone single-level ALIF from 2005 to 2018 were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database by Current Procedure Terminology (CPT) codes. Cases with CPT code 22558 were included in this study; CPT codes 22585 (multilevel ALIFs) and 22630 (PLIF/TLIF) were excluded to ensure inclusion of only single-level ALIFs. Patients with incomplete demographic/pre-operative comorbidities were excluded to reduce the effects of missing data. After these criteria were applied, 10,017 patients who underwent single-level ALIF were ultimately included for analysis. These patients were then stratified into two separate cohorts: controls who did not experience SSI (n = 9,937) and those who experienced SSI after ALIF (n = 80).

Variables and statistical analysis

Patient demographics and pre-operative comorbidities were analyzed in these cohorts. A full list of demographic factors, pre-operative comorbidities, and peri-operative variables analyzed can be found in Table 1.

Table 1.

Demographics and Comorbities in Patients With SSI Versus Control

	No surgical site infections (n = 9,937)		SSIs (n = 80)		p
Demographics
Age (mean ± SD)^a	55.34 ± 13.639		57.45 ± 14.467		0.169
Gender					0.481
Female	5,321	53.55%	46	57.50%
Male	4,614	46.43%	34	42.50%
Race					0.526
American Indian or Alaska Native	43	0.43%	0	0.00%
Asian or Pacific Islander	137	1.38%	1	1.25%
Black or African American	724	7.29%	10	12.50%
Hispanic	5	0.05%	0	0.00%
White or Caucasian	8,486	85.40%	67	83.75%
Other	542	5.45%	2	2.50%
Body mass index (kg/m²)					< 0.001
Normal	2,063	20.76%	13	16.25%
Overweight	3,355	33.76%	17	21.25%
Class 1 obese	2,627	26.44%	19	23.75%
Class 2 obese	1,264	12.72%	17	21.25%
Class 3 obese	600	6.04%	13	16.25%
Pre-operative comorbidities
Obesity	4,491	45.19%	49	61.25%	0.003
Diabetes mellitus					< 0.001
No diabetes mellitus	8,618	86.73%	58	72.50%
Non-insulin dependent	902	9.08%	12	15.00%
Insulin dependent	417	4.20%	10	12.50%
Smoking history	2,299	23.14%	23	28.75%	0.236
COPD	377	3.79%	8	10.00%	0.011
Dyspnea					0.863
No dyspnea	9,459	95.19%	76	95.00%
Moderate exertion	447	4.50%	4	5.00%
At rest	31	0.31%	0	0.00%
Ventilator dependence	8	0.08%	0	0.00%	1.000
Ascites	3	0.03%	0	0.00%	1.000
Congestive heart failure	21	0.21%	2	2.50%	0.014
Hypertension	4,523	45.52%	48	60.00%	0.010
Acute renal failure	1	0.01%	1	1.25%	0.016
Dialysis	16	0.16%	4	5.00%	< 0.001
Disseminated cancer	20	0.20%	1	1.25%	0.155
Wound infection	45	0.45%	2	2.50%	0.054
Chronic steroid use	298	3.00%	8	10.00%	0.003
Weight loss	27	0.27%	2	2.50%	0.022
Bleeding disorders	103	1.04%	3	3.75%	0.053
Pre-operative transfusions	33	0.33%	2	2.50%	0.032
Systemic sepsis	59	0.59%	4	5.00%	0.002
Functional status					< 0.001
Independent	9,726	97.88%	74	92.50%
Partially dependent	160	1.61%	6	7.50%
Totally dependent	8	0.08%	0	0.00%
Peri-operative variables
Anesthesia administered					0.990
Epidural	3	0.03%	0	0.00%
General	9,853	99.15%	79	98.75%
MAC/intravenous sedation	3	0.03%	0	0.00%
Local/regional	3	0.03%	0	0.00%
Spinal	11	0.11%	0	0.00%
Other	64	0.64%	1	1.25%
ASA^b					< 0.001
1, No disturbance	448	4.51%	1	1.25%
2, Mild disturbance	5,488	55.23%	28	35.00%
3, Severe disturbance	3,832	38.56%	45	56.25%
4, Life threatening	154	1.55%	6	7.50%
None assigned	15	0.15%	0	0.00%
Wound classification					< 0.001
1, Clean	9,790	98.52%	70	87.50%
2, Clean/contaminated	80	0.81%	2	2.50%
3, Contaminated	19	0.19%	0	0.00%
4, Dirty/infected	48	0.48%	8	10.00%

Bold values indicate statistically significant results.

SSI = surgical site infections; SD = standard deviation; MAC = monitored anesthesia care; COPD = chronic obstructive pulmonary disease; ASA = American Society of Anesthesiologists.

Values expressed as mean ± SD. All other values expressed as (%) and n.

ASA 1, a normal healthy patient; ASA 2, a patient with mild systemic disease; ASA 3, a patient with a non-life–threatening, severe systemic disease; ASA 4, a patient with severe systemic disease that is a constant threat to life.

Univariable analyses were first utilized in establishing differences between the control cohort and the SSI cohort regarding patient demographic factors, pre-operative comorbidities, and peri-operative/post-operative outcomes. Pearson χ² tests were implemented in analyzing categorical variables, whereas one-way analysis of variance (ANOVA) and independent t-tests analyzed for differences in mean values of continuous variables including time or age. Continuous variables are reported as mean values with standard deviations (mean ± standard deviation). Categorical variables are reported as a proportion representing incidence rates.

Multivariable logistic regression models were utilized to identify independent risk factors for SSI. Different demographic factors and pre-operative comorbidities were entered into the regression model as covariables. To assess the discriminatory ability of the regression model in delegating patients to the SSI or non-SSI cohort based on the variables, the predicted probabilities from the logistic regression model were used to generate a receiver operating characteristic (ROC) curve. Post-regression diagnostics were assessed with C-statistic and the Hosmer and Lemeshow test. A statistical finding with p value ≤0.05 was considered significant. IBM SPSS Statistics version 25 software (IBM Corp, Armonk, NY) was utilized for analyses. Because this study utilized a publicly available database, no ethics approval was required.

Results

A total of 10,017 single-level ALIF from 2005 to 2016 were included in this study. Eighty patients (0.80%) experienced a superficial or deep SSI. The SSI cohort had a larger proportion of patients who were overweight or obese (61.25% vs. 45.19%; p < 0.001) compared with the control cohort. There were no differences observed in any other demographics, including age, gender, or race (p ≥ 0.169; Table 1).

A larger proportion of the SSI cohort presented with more pre-operative comorbidities than the control cohort. The SSI cohort had higher rates of diabetes mellitus (27.50% vs. 13.27%; p < 0.001), chronic obstructive pulmonary disease (COPD; 10.00% vs. 3.79%; p = 0.011), congestive heart failure (CHF; 2.50% vs. 0.21%; p = 0.014), hypertension requiring medication management (60.00% vs. 45.52%; p = 0.010), acute renal failure (1.25% vs. 0.01%; p = 0.016), dialysis (5.00% vs. 0.16%; p < 0.001), long-term steroid use (10.00% vs. 3.00%; p = 0.003), significant weight loss (2.50% vs. 0.27%; p = 0.022), pre-operative blood transfusions (2.50% vs. 0.33%; p = 0.032), systemic sepsis (5.00% vs. 0.59%; p = 0.002), and functional dependence (7.50% vs. 2.12%; p < 0.001; Table 1).

Although no differences were noted in the type of anesthesia administered between the two cohorts, the SSI cohort demonstrated higher rates of ASA classifications ≥3 (63.75% vs. 40.11%; p < 0.001) and a wound classification of >1 (clean/contaminated, contaminated, or dirty/infected) (12.50% vs. 1.48%; p < 0.001; Table 1).

On multivariable logistic regression analyses, several risk factors for SSIs were identified. Class 3 obesity (odds ratio [OR], 2.897; 95% confidence interval [CI], 1.244–5.742; p = 0.014), dialysis (OR, 7.365; 95% CI, 1.278–42.451; p = 0.025), long-term steroid use (OR, 2.857; 95% CI, 1.291–6.322; p = 0.010), and wound classification 4 (dirty/infected) (OR, 6.896; 95% CI, 2.059–23.089; p = 0.002) were identified as independent risk factors for experiencing SSIs (Table 2). The Hosmer-Lemeshow Test had a significance of 0.625, whereas the C-statistic was 0.728 (p < 0.001; Table 2; Fig. 1).

FIG. 1.

Discriminating model receiver operating characteristic (ROC) curve for logistic regression analysis.

Table 2.

Risk Factors for Superficial and Deep SSI in ALIF Patients

Risk factors	OR	95% CI		p
Age
<60 yr	Reference	—	—	—
≥60 yr	0.922	0.557	1.528	0.754
Body mass index (kg/m²)
Normal	Reference	—	—	—
Overweight	0.839	0.397	1.776	0.647
Class 1 obese	1.122	0.535	2.353	0.760
Class 2 obese	1.743	0.796	3.820	0.165
Class 3 obese	2.897	1.244	6.742	0.014
Diabetes mellitus
No diabetes mellitus	Reference	—	—	—
NIDDM	1.400	0.708	2.770	0.333
IDDM	1.916	0.887	4.140	0.098
COPD	1.947	0.894	4.238	0.093
CHF	5.036	0.756	33.553	0.095
Hypertension	1.084	0.638	1.840	0.766
Acute renal failure	22.548	0.491	1,036.333	0.111
Dialysis	7.365	1.278	42.451	0.025
Steroid Use	2.857	1.291	6.322	0.010
Significant weight loss	4.176	0.736	23.696	0.107
Transfusion within 72 hr pre-operative	1.850	0.262	13.084	0.538
Systemic sepsis	1.350	0.231	7.875	0.739
Functional status
Independent	Reference	—	—	—
Partially dependent	2.128	0.745	6.082	0.159
Totally dependent	0.000	0.000	—	0.999
ASA classification
ASA 1 or 2	Reference	—	—	—
ASA 3, 4, or 5	1.453	0.837	2.523	0.184
Wound classification
1, Clean	Reference	—	—	-
2, Clean/contaminated	3.384	0.793	14.443	0.100
3, Contaminated	0.000	0.000	—	0.999
4, Dirty/infected	6.896	2.059	23.089	0.002

Bold values indicate statistically significant results.

SSI = surgical site infection; ALIF = anterior lumbar interbody fusion; OR = odds ratio; Ci = confidence interval; MAC = monitored anesthesia care; COPD = chronic obstructive pulmonary disease; CHF = congestive heart failure; ASA = American Society of Anesthesiologists.

Discussion

Anterior lumbar interbody fusion has become increasingly common over the past two decades. Advances in microsurgical techniques and surgical instrumentation have led to decreased operative complications. As a result, ALIF has become an effective popular technique to treat a variety of lumbar conditions. However, it is not without complications including SSI, instrumentation failures requiring revision surgery, and systemic infections.^6,7 Surgical site infections constitute a substantial contribution to mortality after spine surgery because they have been shown to increase risk of revision surgery and longer hospitalization after spine procedures.⁸ Given these elevated risks of complications, preventing spine SSI is paramount. In the current report, we have identified independent risk factors for SSI after single-level ALIF. To the authors' knowledge, risk factors for SSI after this procedure have not been examined previously. By identifying modifiable risk factors for SSI after this widely utilized procedure, patients can be better optimized prior to surgical intervention to help reduce the risk of SSI. In addition, identifying risk factors for SSI allows clinicians and patients to have a better informed discussion prior to proceeding with operative intervention.

In general, the patients who had developed SSI after single-level ALIF had higher rates of diabetes mellitus, positive smoking history, CHF, dialysis dependence, and pre-operative transfusions (Table 1). These findings are in line with previous reports because diabetes mellitus and CHF have been previously shown to increase the risk of SSI in various procedures.^9,10 Each of these comorbidities impair the immune system in various ways including microvascular damage, cytokine signaling impairment, and neutrophil/macrophage dysfunction.¹¹ Unsurprisingly, the SSI cohort also had higher rates of a smoking history. Smoking has been well reported in the literature to increase risk of SSI orthopedic procedures with implants.^12,13 Although multifactorial, smoking's effect on SSI is most likely related to its effect on wound healing via nicotine induced vasoconstriction and impaired oxygen transport secondary to carbon monoxide.¹⁴ In addition, patients who developed SSI after single-level ALIF also had higher rates of pre-operative blood transfusions. This is expected because blood transfusions can cause immune suppression via various immunomodulatory actions.¹⁵ In a meta-analysis, He et al.¹⁶ found that peri-operative blood transfusions increased the risk of infections after spine surgery. Overall, the higher rates of these comorbidities in patients who developed SSI after single-level ALIF are in line with the literature because they have been reported previously to increase the risk of infection via different mechanisms.

In addition to identifying various comorbidities that were associated with increased rates of SSIs, the present report identified variables that independently increased the risk for SSI after single-level ALIF. Unsurprisingly, wound classification 4 (dirty/infected) (OR, 6.896; p = 0.002) increased the risk of SSI in single-level ALIF. Although ALIF is usually not performed in dirty wounds, ALIF can be performed in cases of spondylodiscitis in which the intervertebral disc space is inoculated and infected. Spondylodiscitis can occur after direct inoculation (i.e., post-operative infection) or hematogenous inoculation (i.e., intravenous drug abuse). In most early cases, mild spondylodiscitis can be treated with intravenous antibiotic agents, immobilization, and bracing. However, in more advanced or complex cases, surgical debridement and stabilization is required. In conjunction with antibiotic therapy, ALIF for the treatment of spondylodiscitis has shown good results in terms of pain control and source control.¹⁷ In cases in which the wound is already dirty/infected, thorough pre-incisional sterilization of the operative field and thorough intra-operative irrigation/debridement should be strived for to help mitigate any further infectious complications.

This study also identified class 3 obesity (OR, 2.897; p = 0.014) as an independent risk factor for SSI in single-level ALIF. This is in line with prior literature as obesity increased the risk of SSI in a multitude of orthopedic and non-orthopedic procedures including hepatic resection surgery, coronary artery bypass, total knee arthroplasty, and acetabular fixation.^18–24 The impact of obesity in lumbar spine surgery has also been documented. In a meta-analysis, Zhang et al.²⁵ report an almost three-fold increased risk of developing SSI after lumbar spine surgery in obese patients compared with non-obese patients. Miller et al.²⁶ also previously reported obesity classes 2 and 3 independently increased the risk of post-operative wound complications in ALIF in a retrospective analysis of the ACS-NSQIP database from 2009–2019. As opposed to analyzing outcome differences comparing obese versus non-obese cohorts, our study analyzed for a variety of risk factors that independently increased the risk of SSI after ALIF beyond obesity.

The role of obesity in contributing to increased rates of SSI in single-level ALIF is likely multifactorial. A suboptimal concentration level of prophylactic antibiotic agents in adipose tissue is one proposed mechanism for increased SSI risk in obese patients. An increase in adipose tissue can correlate to a decreased concentration of antimicrobial prophylaxis (AMP) in the soft tissues and therapeutic concentration levels would subsequently be decreased. Salm et al.²⁷ report in a study of abdominal procedures performed for traumatic, visceral, or vascular procedures, patients >80 kg who received double-dose AMP had lower rates of SSI compared with patients in the same weight class who received a single-dose AMP. In contrast, in a retrospective review of a single institution's adult orthopedic cases, Hasler et al.²⁸ reported no difference in rates of SSI in obese patients who received double-dose AMP compared with patients who received single-dose AMP. However, no laboratory values or assessments were recorded systematically to evaluate for AMP tissue concentration levels.²⁸ Although there is a lack of consensus on whether weight-based dosing results in lower rates of SSI, the authors of the present report recommend weight-based dosing of AMP with the aim of reducing SSI risk in single-level ALIF to achieve adequate therapeutic levels. In addition to suboptimal antibiotic dosing, obesity can predispose patients to SSI after ALIF for other reasons including increased dead space formation, increased intra-operative packing, and increased operative times.^18,25

In addition to obesity, the present report demonstrated long-term steroid use (OR, 2.857; p = 0.010) as an independent risk factor for SSI in single-level ALIF. This is congruent with prior reports as infectious complications such as septic shock and SSI have been reported in patients with long-term steroid use after cervical and lumbar fusion procedures.^29,30 The immunosuppressive effects of steroids are well documented. Steroids affect immune function by altering immune cell trafficking and cytokine signaling.³¹ Steroids can cause upregulation of genes that code for anti-inflammatory cytokines (i.e., interleukin-10), and conversely downregulate genes of proinflammatory cytokines, such as nuclear factor kappa-beta (NF-kB) through intranuclear alterations to gene expression.³² Lymphopenia is also common in long-term steroid use.³³ It is unsurprising, therefore, that long-term steroid use in the present report was a risk factor for SSI development in single-level ALIF. However, further work on defining steroid tapering protocols is needed to determine optimal timing of steroid discontinuation and its subsequent effects on SSI risk.

Finally, similar to prior reports in the literature, our study demonstrated dialysis dependence to independently increase SSI risk in single-level ALIF (OR, 7.365; p = 0.025). Dialysis dependence and chronic kidney disease (CKD) have been well documented to increase post-operative infection risk in various orthopedic procedures, such as arthroscopic knee procedures.³⁴ In a recent meta-analysis, Kim et al.³³ also reports an increased rate of peri-prosthetic joint infections in dialysis-dependent patients compared with non-dialysis–dependent patients after total hip arthroplasty. Dialysis dependence has also been shown to increase SSI risk, in addition to other systemic infectious complications such as pneumonia and sepsis, after spine surgery as well.³⁶ Chronic kidney disease has been shown to decrease immune system function in various ways. Lower levels of Toll-like receptor expression have been reported in patients with CKD, decreasing the efficiency of an innate immune system response.³⁷ Chronic kidney disease also affects the adaptive immune response by decreasing output of T-/B-cells and impairing T-cell response.³⁷ Dialysis-dependent patients should be counseled on the elevated risk of SSI with their providers when considering undergoing ALIF.

There were several limitations with the present study. Initially designed for insurance purposes, the use of CPT codes may present a confounding variable based on financial incentive for which this study could not control.³⁸ The lack of granularity of certain types of information is a limitation inherent to all database studies. For example, the ACS-NSQIP database does not report information such as type/method of intake of steroid, dosage/length of therapy, and indication for therapy. Future work examining these factors may help to develop steroid tapering protocols to help reduce SSI risk in ALIF. Similarly, length of time of dialysis therapy and indications for its initiation were also not reported. There can be multiple causes of kidney failure that necessitate dialysis such as diabetes mellitus, nephritic syndromes, or rare conditions such as autosomal dominant polycystic kidney disease. Although all can lead to end-stage renal disease, each has a unique set of comorbidities that can present as a systemic confounding variable for which this study could not account.

Conclusions

With an aging population and an increasing prevalence of degenerative spine disease, ALIF is an increasingly popular method to help treat a variety of lumbar conditions. Therefore, it is important to identify ways to reduce complications arising from this procedure. In this study, we identified class 3 obesity, dialysis, long-term steroid use, and dirty wound classification as independent risk factors for SSI after single-level ALIF. By identifying high-risk patients, surgeons can better counsel patients pre-operatively. Post-operatively, a lower threshold of suspicion should be held for these high-risk patients for developing SSI. Peri-operative antibiotic prophylaxis in spine surgery has been a source of debate; currently there is a lack of consensus on the role of extended peri-operative antibiotic prophylaxis use. No concrete guidelines have been published. In addition to a weight-based dose of pre-operative antibiotic agents, the authors recommend a patient-specific approach when considering an extended post-operative antibiotic course. Patient-specific factors, such as diabetes mellitus, obesity, or immunocompromised states that may predispose these patients to infection should be considered on an individual basis.

Footnotes

Authors' Contributions

Conceptualization: D. Lee, R. Lee, Winreb. Methodology: D. Lee, R. Lee, Winreb. Formal analysis: D. Lee, R. Lee, Winreb. Investigation: D. Lee, R. Lee, Winreb, Chalif, Mohile, Heyer, O'Brien. Writing—original draft: D. Lee, R. Lee, Winreb, Chalif, Mohile, Heyer, O'Brien. Writing—review and editing: D. Lee, R. Lee, Winreb, Chalif, Mohile, Heyer, O'Brien. Project administration: D. Lee, R. Lee, Winreb, Mohile, O'Brien.

Funding Information

No funding was required for this study.

Author Disclosure Statement

The authors have no conflicts of interest or disclosures relevant to this work to report.

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