Diabetes and Risk of Surgical Site Infection: A systematic review and meta-analysis

Abstract

Objective

To determine the independent association between diabetes and SSI across multiple surgical procedures.

Design

Systematic review and meta-analysis.

Methods

Studies indexed in PubMed published between December 1985 and through July 2015 were identified through the search terms “risk factors” or “glucose” and “surgical site infection”. A total of 3,631 abstracts were identified through the initial search terms. Full texts were reviewed for 522 articles. Of these, 94 articles met the criteria for inclusion. Standardized data collection forms were used to extract study-specific estimates for diabetes, blood glucose levels, and body mass index (BMI). Random-effects meta-analysis was used to generate pooled estimates and meta-regression was used to evaluate specific hypothesized sources of heterogeneity.

Results

The primary outcome was SSI, as defined by the Centers for Disease Control and Prevention surveillance criteria. The overall effect size for the association between diabetes and SSI was OR=1.53 (95% Predictive Interval 1.11, 2.12, I²: 57.2%). SSI class, study design, or patient BMI did not significantly impact study results in a meta-regression model. The association was higher for cardiac surgery 2.03 (95% Predictive Interval 1.13, 4.05) compared to surgeries of other types (p=0.001).

Conclusion

These results support the consideration of diabetes as an independent risk factor for SSIs for multiple surgical procedure types. Continued efforts are needed to improve surgical outcomes for diabetic patients.

INTRODUCTION

Diabetes prevalence is increasing in the United States ¹ (US), and the appropriate management of patients with diabetes has become increasingly important for the prevention of hospital-acquired infections. Much has been published in recent years about the impact of diabetes on increased rates of surgical site infection (SSI) and the potentially related impact of hyperglycemia on SSI. Surgical site infections are estimated to have an annual financial impact of over $3 billion dollars nationally and are the largest contributor to the overall cost of healthcare-associated infections.² Efforts to reduce the rates of SSIs are becoming more urgent since the introduction of Centers for Medicare & Medicaid Services penalties for hospital readmission rates. An understanding of patient risk factors for SSI is key to these efforts as hospitals with a more vulnerable case mix are more likely to incur readmission penalties.³ Furthermore, the substantial prevalence of hospital-associated infections due to antibiotic resistant pathogens⁴ highlights the importance of prevention in individuals at high risk of infection. To gain a greater understanding of the impact of pre-existing diabetes on the incidence of SSI, we performed a meta-analysis of risk factors for SSIs among patients undergoing surgery in US hospitals. We hypothesize that pre-existing diabetes is a significant contributor to the development of SSI, independently of hyperglycemia at the time of surgery. Secondarily, we hypothesize that hyperglycemia is itself an independent contributor to increased risk of SSI in surgical patients.

METHODS

A systematic literature search and meta-analysis was performed following MOOSE guidelines ⁵ (Supplementary Material). Data Sources and Searches: A systematic literature search was performed by four study investigators (M.S., C.K., H.N., R.E.) with questions referred to an adjudication team consisting of the study principal investigator (E.T.M.), one investigator with expertise in diabetes epidemiology (L.J.) and one investigator with expertise in infectious diseases and infection prevention (K.S.K.). The search was performed in PubMed and EMBASE using PubMed using combinations of the search terms “risk factors”, “diabetes”, “glucose” and surgical site infections” from December 1985 to July 2015 (Supplementary Material: Search Strategy). The starting date of the search, December 1985, was selected to correspond with the wide implementation of the Centers for Disease Control and Prevention (CDC) SSI surveillance guidelines. The search was inclusive of all study designs unless interventional control of glucose during the study prevented an assessment of the association between diabetes and SSI..

Study Selection

All abstracts were reviewed for eligibility and the full article text of potentially relevant studies were reviewed in depth. Reference lists for all reviewed articles were hand-searched to identify additional eligible articles. Eligibility criteria for study inclusion consisted of: (1) Original US data; (2) Adult participants; (3) Utilized the CDC definition for SSIs; (4) Provided measurable risk estimates of the association between diabetes and risk of SSI with 95% confidence intervals, or the study provided adequate information to calculate risk estimates and their 95% confidence intervals. Review articles, meta-analyses, or non-English studies were excluded (Supplementary Material: List of Excluded Studies).

Eligible studies included adult patients undergoing surgical procedures of any type, using NHSN operative procedure categories to define surgical procedures. All comparative study designs (including observational, randomized controlled, retrospective or prospective studies) were considered for inclusion provided they presented an assessment for the association between diabetes and SSI or the absolute patient numbers needed for the calculation of the measure. Each eligible study was required to include both diabetic and non-diabetic patients in the study population. Multiple publications on the same subject population were reviewed together and were restricted such that each patient population was included only once; this is notable particularly for multiple publications from large surveillance databases (e.g. National Surgical Quality Improvement Program; See Supplementary Material: Excluded Studies). SSI was defined using criteria specified by the CDC for the purposes of surveillance and reporting.

Data Extraction

Measures for the association between pre-existing diabetes and SSI were collected from studies that ascertained the presence of diabetes prior to the time of surgery either through the patient’s medical record or hemoglobin A1c testing (HbA1c). Assessments of HbA1c levels were noted; however too few such studies were identified to merit a separate meta-analysis based on this measure. Measures of the association between peri- or post-operative blood glucose levels were collected from studies that assessed thresholds of glucose levels. Studies that presented only comparisons of mean or median blood glucose levels were excluded from the analysis of peri- or post-operative hyperglycemia due to our inability to define the absolute number of patients with hyperglycemia in the infected and uninfected groups.

Data were abstracted onto standardized forms that included study characteristics, study population, types of SSI (superficial, deep incisional, or organ/space), and crude and adjusted estimates and confidence intervals. From each study we observed and recorded how diabetes was determined and whether blood glucose was measured prior to, during, or after surgeries. Studies were assigned to the following categories based on the type of surgery: obstetrical and gynecological, colorectal, arthroplasty, breast, cardiac, spinal, or other. The abstraction team received training by the principal investigator, including the abstraction of multiple practice cases, before beginning data abstraction. A subset of studies included was re-reviewed by two study investigators to ensure consistency.

Data Synthesis and Analysis

The most-adjusted estimate (i.e. the adjusted odds ratio for the multivariate regression with the most variables) was used to generate summary estimates.⁶ Summary estimates and predictive intervals were calculated using a DerSimonian and Laird random-effects model for each estimate type. Confidence intervals were used for smaller analyses of diabetes and glucose combined models. The use of random-effects models was based on I² values exceeding 30% in each overall fixed-effects analysis.⁷ Funnel plots were generated to assess publication bias (data not shown)(Stata 11). Sensitivity analysis was performed through the generation of stratified estimates and the use of multiple meta-regression analyses to assess the presence of meta-confounding by study characteristics including surgery type, study type, inclusion of BMI in the adjusted estimate and diabetes prevalence in the study population. We determined a priori that the primary confounder of concern was BMI.

RESULTS

The combined search strategies resulted in 3,631 abstracts. All identified abstracts were reviewed and the full texts of 522 articles were reviewed in depth. 3,109 studies were excluded during abstract review (Figure 1) and 428 studies were excluded during full text review (Supplementary Material: List of Excluded Studies).

Figure 1.

Flow diagram of search and selection processes

Meta-analysis for diabetes and SSI

Ninety studies provided estimates for the association between diabetes and SSI, including two studies that provided multiple estimates (Appendix Table 1). Included studies comprised a total of 866,427 procedures and 32,067 SSIs meeting CDC surveillance criteria. All studies were observational with the exception of three randomized controlled trials. Fourteen studies (16%) used prospectively-collected data. Diabetes prevalence among included study populations ranged from 2% to 39% (median 17%). History of diabetes was ascertained by medical record review in all but two studies.^{8, 9} No included studies differentiated between Type 1 and Type 2 diabetes.

Appendix Table 1.

Articles included in three meta-analyses of diabetes and pre- and post-operative hyperglycemia

Author	Year	N procedures	N SSI	Surgery	Diabetes	Preoperative glucose	Postoperative glucose
Abdul-Jabbar25	2012	6628	193	spinal	X
Anaya26	2012	503	122	any elective	X	X
Anthony27	2011	197	69	elective transabdominal colorectal	X
Apisarnthanarak28	2003	60	13	spinal	X
Bachoura29	2011	1,783	75	orthopaedic trauma	X
Bertin30	1998	55	18	breast	X
Boston31	2009	234	55	spinal	X		X
Bundy32	2006	3,878	322	CABG	X
Bykowski33	2011	8,850	31	elective hand	X
Cannon34	2012	9,940	1,497	elective colorectal resection	X
Caputo17	2013	3,138	115	orthopaedic spine	X		X
Chaichana35	2015	401	21	tumor resection	X
Chapman36	2015	338	89	gynecologic oncology	X
Chen37	2009	195	27	elective posterior instrumented lumbar arthrodesis	X
Chen38	2010	253	86	any	X		X
Chiang39	2014	416	104	craniotomy or craniectomy	X	X
Chopra40	2012	751	91	Roux-en-Y gastric bypass surgery (RYGBS)	X
Chu41	2015	528	36	stoma reversal	X
Chung42	2015	2,899	143	free flap breast reconstruction	X
Coakley43	2012	59	16	colectomy for fulminant ulcerative colitis (UC)	X
Coleman44	2014	77	17	hysterectomy	X
Davies45	2012	268	49	ventral hernia repair	X
deFreitas46	2012	40,669	1301	elective vascular procedures	X
Deierhoi47	2013	5,750	709	colorectal	X
Elfenbein48	2014	49,326	179	thyroidectomy	X
Everhart49	2012	1875	29	total joint arthroplasty	X
Fakih50	2007	3,578	144	coronary artery bypass graft (CABG)	X
Farrow51	2008	152	30	umbilical hernia repairs	X
Fowler52	2005	370,133	11,636	cardiac	X
Friedman16	2007	123	41	laminectomy	X
George53	2011	556	14	laproscopic urological procedures	X
Haas54	2005	12	14	cardiac	X
Haley55	2012	13,894	303	CABG	X
Harbarth56	2000	2,641	231	CABG	X
Hardy21	2010	114	57	craniotomy	X		X
Harness57	2010	2,336	11	carpal tunnel release	X
Hellinger58	2011	1,036	166	liver transplantation	X
Hendren59	2013	4,331	380	colectomy			X
Jackson60	2012	7,576a 5,773b	N/A	colectomy		X	X
Jeon22	2012	13,800	260	any		X	X
Kaafarani61	2010	145	21	ventral hernia repair	X
Kalra62	2013	9,006	27	multiple	X
Koutsoumbelis63	2011	3,218	84	posterior lumbar	X	X	X
Kuy64	2014	106	33	lower extremity revascularization	X
Latham8	2001	1,000	74	cardiothoracic	X	X	X
Liang9	2013	128	46	stoma reversal	X
Lim65	2014	3,353	86	single level lumbar fusion	X
Liu66	2012	256	44	microsurgical breast reconstruction	X
Lovecchio67	2014	43,299	468	arthroplasty	X
Lynch68	2009	869	162	renal transplant	X
Mahajan69	2013	615	47	intra-abdominal	X
Mahdi70	2014	6854	369	gynecologic cancer	X
Maragakis71	2009	208	104	spinal	X
Marschall72	2007	76	19	pacemaker and implantable cardioverter-defibrillator	X
Mehta73	2012	298	24	lumbar spine fusion	X
Mehta74	2013	213	22	cervical spine fusion	X
Miransky75	2001	209	15	colorectal	X
Namba76	2012	30,491	155	total hip replacement	X
Namba77	2013	56,216	404	total knee arthroplasty	X
Nash78	2011	11,879	491	cardiac	X
Neumayer79	2007			multiple	X
Nguyen80	2012	9,315	330	mastectomy with or without immediate reconstruction	X
Olsen81	2002	1,980	83	CABG	X
Olsen82	2008	325	57	major breast	X
Olsen83	2008	1,605	81	low transverse cesarean section	X
Olsen10	2008	273	46	spinal	X	X	X
Olsen84	2009	807	85	hysterectomy	X
Park85	2009	680	76	hepatic transplant	X	X
Paryavi86	2013	235	33	lower extremity fracture	X
Pastor87	2010	491	95	elective colorectal resection			X
Ponce88	2014	18,830	264	arthroplasty	X
Rao89	2011	1,587	57	spinal fusion	X
Saleh90	2002	97	33	total knee and hip arthroplasty	X
Segal91	2014	51,644	7,721	colon resesection	X
Senekjian92	2013	61,830	802	appendectomy	X
Sharma93	2009	3,578	86	CABG	X
Shields94	2013	586	31	lung transplantation	X
Shuman95	2012	84	14	head and neck	X
Singh96	2012	902	78	varicose vein surgery	X
Smith97	2004	176	45	elective colorectal resection	X
Spaniolas98	2014	503	23	ventral hernia repair	X
Suzuki99	2010	326	17	acetabular fracture fixation	X
Talbot100	2004	153	39	median sternotomy for CABG, valve repair, and/or replacement	X
Tomov101	2015	311	16	orthopedic spinal	X
Townsend102	1993	2,759	241	non-emergent median sternotomy for cardiac operation	X
Trick103	2000	120	30	CABG	X	X
Trinh104	2009	202	101	any	X
Trussell23	2008	808a, 647b	28/10	CABG	X
Tserenpuntsa105	2014	2,656	698	colon	X
Walcott106	2014	399	17	cranial neurosurgery	X
Wilson11	2003	258	129	open heart surgery	X	X
Woods107	2013	1799	56	lumbar surgery	X
Wooldridge108	2013	106	11	high-grade soft tissue sarcoma	X
Young109	2011	216	18	elective total abdominal hysterectomy	X

The overall effect size for the association between diabetes and SSI was OR=1.53 (95% Predictive Interval 1.11, 2.12, I²: 57.2%) (Figure 2). Thirty eight of the studies (42%) provided estimates that were adjusted for potential confounding factors. When stratifying the meta-analysis by the availability of crude versus adjusted measures, the effect size was similar (OR=1.68 (95% Predictive Interval 1.03, 2.72, I²: 63.6%;) for all available crude measures (71 studies); OR=1.77 (95% Predictive Interval 1.13, 2.78), I²: 71.1%) for all adjusted measures(38 studies). Funnel plots demonstrated greater evidence of potential publication bias for adjusted estimates (data not shown).

Figure 2.

Meta-analysis of diabetes and surgical site infection, by surgery type

Evaluation of sources of heterogeneity for diabetes estimate

Study design did not have a significant impact on the overall pooled estimate (p=0.13 for retrospective versus prospective data collection; p=0.41 for case-control versus cohort or interventional design). Prevalence of diabetes among study participants was also not a significant source of heterogeneity (p=0.80). Among studies presenting estimates restricted to specific SSI classes, the combined OR was 1.95 (95% Predictive Interval 0.65, 5.87) for deep SSIs (seven estimates from six studies) and 1.38 (95% Predictive Interval 0.66, 2.88) for superficial SSIs (six estimates from five studies).

Among studies reporting on a single surgical category, the most common category was cardiac (15 studies) followed by spinal (14 studies) (Table 1). Estimates by surgery type for the association between diabetes and SSI ranged from 1.16 (95% Predictive Interval 0.93, 1.44) for colorectal surgeries to 2.03 (95% Predictive Interval 1.13, 4.05) for cardiac surgeries(Table 1). Meta-regression for impact of surgery type on the association between diabetes and SSI indicated that the combined SSI effect was higher for cardiac surgery than for all other surgery categories (p=0.001). BMI was hypothesized a priori to be an important confounder in the association between diabetes and SSI. Study estimates were stratified on whether the presented measure controlled for the effect of BMI. The estimate pooled from the twenty studies controlling for BMI was higher than that pooled from those that did not; however this factor was not significant when evaluated by meta-regression (p=0.79).

Table 1.

Pooled estimates of the association between diabetes and SSI by surgery type

Surgery Type	Number of Studies	Pooled Estimate	95% Prediction Interval	I2, %
Gynecological	6	1.61	(1.15, 2.24)	4.0
Colorectal	7	1.16	(0.93, 1.44)	9.5
Arthroplasty	6	1.26	(1.01, 1.66)	11.7
Breast	5	1.58	(0.91, 2.72)	2.7
Cardiac	15	2.03	(1.13, 4.05)	22.4
Spinal	14	1.66	(1.10, 2.32)	8.1
Other/Multiple Surgery types combined	37	1.46	(1.07, 2.00)	41.5

Meta-analysis for blood glucose and SSI

Sixteen total studies were available to assess the association between hyperglycemia and SSI with ten papers (n=27,844 procedures) including pre- or intra-operative assessments of blood glucose levels and eleven papers (n=32,625 procedures) including post-operative assessments of blood glucose levels. We observed a wide range in the threshold for defining hyperglycemia. Six out of ten studies assessing pre-operative blood glucose used a threshold of 200 mg/dL, with the remaining three studies using thresholds of 125 mg/dL (two studies), 180 mg/dL (one study) and 100mg/dL (one study). Five of the eleven studies assessing post-operative blood glucose used thresholds of 200 mg/dL with the remaining studies using lower thresholds ranging from 125 mg/dL to 180 mg/dL. One paper presented a composite exposure of pre- or post-operative hyperglycemia, and this estimate was included in both pooled calculations.¹⁰ The overall estimate for the association between elevated blood glucose and SSI in the pre- or intra-operative period was OR=1.88 (95% Predictive Interval 0.66, 5.34) (Figure 3). The overall estimate for the association between elevated blood glucose in the post-operative period and SSI was 1.45 (95% Predictive Interval 0.77, 3.04) (Figure 4).

Figure 3.

Meta-analysis of pre-operative hyperglycemia and surgical site infection

Figure 4.

Meta-analysis of post-operative hyperglycemia and surgical site infection

Only three studies presented multivariate models adjusting for blood glucose levels and diabetes in the same model.^{8, 10, 11} These studies used thresholds of ≥200 mg/dL⁸ and ≥126 mg/dL¹¹ to define elevated pre-operative glucose levels or combined pre- and post-operative thresholds into one definition.¹⁰ Pooled estimates of the association between diabetes and SSI, controlling for glucose level was OR=2.55 (95% Confidence Interval 1.70, 3.82). Pooled estimates of the association between elevated glucose level and SSI, controlling for a history of diabetes was OR=2.22 (95% Confidence Interval 1.36, 3.60).

CONCLUSIONS

We found a significant association between diabetes and SSI that was consistent across multiple types of surgeries and after controlling for BMI. While we also confirmed an association between both pre- and post-operative hyperglycemia and SSI, history of diabetes remained a significant risk factor in meta-analyses of studies that controlled for hyperglycemia.

Consistency of Included Studies

We limited our analysis to studies performed at U.S. hospitals after 1985 in an effort to narrow our review to surgeries evaluated with the standard SSI surveillance methods and definitions required by the CDC. We observed some variation in the definitions for hyperglycemia among included studies. Approximately half of the studies used thresholds that met, or were more conservative than, those proposed by the Society of Thoracic Surgeons¹² and the American Diabetes Association¹³. The remaining studies used a slightly higher threshold of 200 mg/dL to define hyperglycemia, and it is possible that this variation may have introduced heterogeneity into our combined estimates for hyperglycemia.

Almost all included studies used medical record review to assess a patient’s reported history of diabetes. This data may be prone to error and may not reliably identify all patients with diabetes or assess the degree to which an individual patient’s diabetic condition is adequately controlled. Likewise, the assessment of diabetes for use with the revised surgical risk index from the Centers of Disease Control does not recommend the use of HbA1c or other markers of severity of diabetes to gather risk information.¹⁴

Generalizability of Study Estimates

Our requirement that all studies be based in the U.S. excluded available data from other countries; however it allowed us to strictly assess SSIs using CDC definitions from hospitals participating in standardized surveillance procedures. While specific quality ratings were not performed for each study, we have explored several potential sources of heterogeneity in our pooled estimates through the use of meta-regression. Our stratum specific estimates show a very consistent association between diabetes and SSIs across categories, including study characteristics, and after controlling for BMI. We were unable to assess variation due to SSI surveillance practices in different hospitals. While studies using active follow-up protocols would be expected to have increased SSI rates, we do not expect that this effect would be differential by diabetes status. Our pooled estimates are based on the use of the most adjusted estimate available in each study.⁶ To assess the impact of this rule, summary estimates were generated separately for all available crude effects and all available adjusted effects and the findings in these models were similar to the most-adjusted models. The funnel plot for the adjusted estimates indicated the possible presence of publication bias for these estimates in this body of literature (data not shown). This is likely due to the tendency of authors to publish only those variables that are significant in multivariate analyses. Given our findings of an association between diabetes and SSI in almost every category of surgery type, it is likely that non-significant findings for diabetes in smaller studies may be due to insufficient sample size in individual studies, rather than a lack of underlying impact. For that reason, it may be prudent to include diabetes as an a priori hypothesized risk factor in future studies, with inclusion of diabetes in adjusted models for risk of SSIs.

Interpretation of Findings

Our finding of increased SSI among patients with diabetes was consistent across surgery types, with the exception of obstetrical and gynecological surgery which was based on two studies, both conducted at the same hospital. The surgery-specific findings were statistically significant for arthroplasty, breast, cardiac, and spinal surgeries and the actual pooled estimate was highest among patients undergoing cardiac surgery. This is in contrast to the analysis of National Healthcare Safety Network data that serves as the basis for the revised procedure-specific SSI risk-adjustment calculations. This analysis found diabetes to only be associated with SSI for spinal fusion or refusion.¹⁴ In patients with diabetes receiving colorectal resection, glucose levels were consistently higher in patients with an SSI compared to uninfected patients, even when mean glucose levels were below 200 mg/dL in those with or without SSI.¹⁵ Similar findings have been reported in patients undergoing laminectomy.¹⁶ Elevated blood glucose has been found to be associated with increased rates of infection in orthopaedic spine surgery¹⁷, cardiac surgery^{11, 18, 19}, and colorectal and bariatric surgery²⁰; however this association has not been consistently found^{21, 22}.

The notion that diabetes is a significant contributor to SSI risk through mechanisms other than hyperglycemia at the time of surgery is supported by the few studies that included both glucose levels and history of diabetes in the multivariate models. In the pooled estimate from these studies, the magnitude of the effect of diabetes was stronger than that of our primary analysis that included all eligible studies. The results of an interventional study by Trussel et al²³ corroborates this finding. Diabetes remained a significant risk factor for SSI with an odds ratio of 4.71 despite the implementation of a patient care pathway targeting glucose control during the time of surgery and resulting in successfully reducing the overall rates of infections. However, we found few studies from which to analyze potential independent effects of diabetes and hyperglycemia on SSI.

Our study has found diabetes to be a significant contributor to the risk of SSIs, potentially beyond its role in causing hyperglycemia during or after surgery. The reasons for this finding are unclear. It is possible that diabetes is a marker for other conditions that may put a patient at risk of infection, including vascular changes and white blood cell dysfunction. Furthermore, the occurrence of perioperative hyperglycemia and subsequent immune suppression is affected by the complex contributions of factors in addition to the diabetic history of the patient, including physiologic stressors and exogenous glucose administration.²⁴ While we were able to assess the confounding effect of body mass index, and found no change to our conclusions, our ability to fully assess potential confounders in the current meta-analysis is limited by the variables assessed in the original studies. However, the most adjusted estimate from each study was used in the final analysis, which should benefit from control of other confounding variables at the individual study level. Our findings point to several directions for future research. Few studies have assessed whether a more detailed assessment of diabetes severity would improve the management of SSI risk in these patients. Secondly, few studies address the cause of the infection, and thus we are unable to rule out whether the increased risk of SSI among diabetics is related to differences in bacterial etiology.

Overall, these results support the consideration of diabetes as an independent risk factor for SSIs for multiple procedure types and continued efforts are needed to improve surgical outcomes for diabetic patients.