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BASIC RESEARCH

Does Preoperative Glycemic Control Restore Immune Defense Against Implant-related Infection in Mice With Diabetes?

Lin, Junqing MBBS1; Huang, Tengli MBBS1; Wei, Haifeng MD, PhD1; Bao, Bingbo MBBS1; Gao, Tao MBBS1; Zheng, Xianyou MD, PhD1; Zhu, Hongyi MD, PhD1

Author Information
Clinical Orthopaedics and Related Research: May 2022 - Volume 480 - Issue 5 - p 1008-1017
doi: 10.1097/CORR.0000000000002041

Abstract

Introduction

Bone and joint infection is a serious complication of arthroplasty and fracture fixation, leading to tremendous healthcare, social, and economic costs [24, 25]. Type II diabetes is a well-established risk factor for bone and joint infection, especially in patients with poor glycemic control [20, 36, 43]. Approximately half a billion people worldwide are currently living with Type II diabetes, and the number of patients with Type II diabetes is projected to increase by more than 50% before 2045 [32]. The rapidly increasing prevalence of bone and joint infection is largely attributed to an epidemiologic change in Type II diabetes, warranting further investigation into options to mitigate this source of increased risk of bone and joint infection [14, 18, 30]. Because only observational data have been reported, it is currently unclear whether preoperative glycemic intervention might reduce the risk of surgical site infection and, if so, what is a reasonable, achievable, and safe glycemic goal [34].

The preoperative blood glucose level is modifiable and could serve as a therapeutic target to reduce the postoperative infection risk [28, 40]. The American Diabetes Association and European Association for the Study of Diabetes recommend hemoglobin A1c (HbA1c) for monitoring glycemic control [10, 11]. Naturally, most previous clinical investigations focused on HbA1c as a marker for risk stratification in orthopaedic patients, and controversial results have been reported regarding its predictive value and cutoff points [1, 7, 8, 29, 36, 41]. One hypothesis regarding this controversy is that hyperglycemia in a more recent period preoperatively more closely correlates with surgical site infections than the HbA1c level, which reflects the average blood glucose levels of the past several months [17]. Supporting this hypothesis, an experimental study revealed that neutrophil dysfunction caused by hyperglycemia could be largely attenuated after insulin therapy for only a few days [12]. A potentially more useful indicator preoperatively is fructosamine, a biomarker that reflects a shorter period of blood glucose levels before testing. As expected, fructosamine levels have been shown to have a higher power for predicting infection than HbA1c [37].

To address this knowledge gap, we designed an animal study and asked the following questions: (1) Is there an effect of the duration of preoperative insulin therapy in mice with diabetes receiving an experimental intra-articular implant? (2) Of the three commonly used biomolecules for monitoring blood glucose levels (HbA1c, fructosamine, and 1,5-anhydroglucitol), is one more closely related to decrease in infection proportion after presurgical insulin therapy?

Materials and Methods

Study Overview

Type II diabetes was modeled in mice by maintaining them on a high-fat diet (60% fat), and control mice without diabetes received a normal low-fat diet (10% fat). Mice with Type II diabetes (n = 560) and mice without diabetes (n = 80) were respectively randomized, and group information was blinded to reduce potential bias. Mice with diabetes assigned to each group then received preoperative intravenous insulin therapy for 0, 1, 3, 5, 7, 14, or 28 days (n = 20 for each bacteria/challenge [systemic or local]/timepoint). We then assessed whether these increasingly longer preoperative glycemic interventions reduced the proportion of bone and joint infection in an intra-articular implant model subjected to local or systemic challenge with Staphylococcus aureus or Escherichia coli (Fig. 1A).

F1
Fig. 1:
A-B (A) This schematic illustration shows the study design of the proportion of bone and joint infection after different durations of insulin therapy preoperatively. (B) This schematic illustration shows the study design of the three biomolecule changes after 28 days of insulin therapy in mice with induced Type II diabetes. A color image accompanies the online version of this article.

Mice and Details of Diabetes Induction

Female C57BL/6 mice (initially 10 weeks old) were maintained (four mice per cage) in a specific pathogen-free grade animal facility controlled for temperature and humidity (20° to 23° C; 50% humidity). Female mice were chosen because fighting among cage companions is rare in contrast to their male counterparts. Room lighting was set on a 12-hour to 12-hour light-dark schedule. Mice had free access to food and water. To model Type II diabetes, we fed mice a high-fat diet (60% kcal from fat; Research Diets Inc) for 32 weeks; mice without diabetes were fed a normal low-fat diet (10% kcal from fat; Research Diets Inc) for 32 weeks [3, 27]. The diagnostic criterion for diabetes was a randomly sampled blood glucose level of greater than 300 mg/dL after the 32-week high-fat diet [44]. Only mice with successful induction of Type II diabetes received further randomization in this study.

Perioperative Insulin Therapy

Tail-tip blood samples were obtained, and the blood glucose level was measured using a glucometer (Johnson & Johnson) every 12 hours in high-fat diet mice before randomization and during the insulin therapy [39]. Neutral protamine Hagedorn (NPH) insulin (Eli Lilly) was administered by subcutaneous injection immediately after blood glucose was measured. We set the blood glucose level target to less than 200 mg/dL and used a predefined protocol to determine the insulin dose. When the measured blood glucose level was less than 200 mg/dL, we injected 1 IU of NPH; when measured blood glucose level was 200 mg/dL to 400 mg/dL, we injected 2 IUs of NPH; when measured blood glucose levels was greater than 600 mg/dL, we injected 3 IUs of NPH [38]. The different groups of diabetic mice received different durations of preoperative insulin: 0, 1, 3, 5, 7, 14, or 28 days. After this regimen and implant surgery, all groups with diabetes received an additional 7 days of insulin.

Bacterial Inoculum Preparation

S. aureus (ATCC 29213) and E. coli (ATCC 25922) (American Type Culture Collection) represented gram-positive and gram-negative pathogens, respectively, for the bacterial challenge. The inoculum was prepared according to the following procedures. Stocks of the two bacteria species were cultured on tryptic soy agar containing 5% sheep blood (Sigma-Aldrich Millipore) using standard culturing techniques. We prepared fresh cultures of the two bacteria and adjusted the concentration to 1 × 107 colony-forming units (CFUs) per mL using a standard optical density curve. For the local and systemic challenge, 1 × 103 and 1 × 105 CFUs of bacteria were applied respectively. The challenging volume of bacteria was determined by whether we were able to reliably cause joint infection in at least 80% of the mice with diabetes.

Measurement of Glycemic Biomarkers

An additional 10 mice with diabetes that received 28-day insulin therapy were assessed using three common glycemic biomarkers: HbA1c, fructosamine, and 1,5-anhydroglucitol [23]. 1,5-anhydroglucitol, a 1-deoxy form of glucose, has been used to monitor short-term glycemic control in patients [6], whereas HbA1c levels reflect the average blood glucose levels during the previous 2 to 3 months [5]. Measurements were made at 0, 1, 3, 5, 7, 14, and 28 days after insulin therapy. HbA1c and fructosamine levels were measured with commercially available ELISA kits (ELISA Genie) according to the manufacturer’s instructions. The level of 1,5-anhydroglucitol was measured with a commercially available colorimetric assay kit (BioVision Inc). The absolute levels of HbA1c, fructosamine, and 1,5-anhydroglucitol were standardized according to baseline concentrations before insulin therapy on day 0. The relative level of HbA1c, fructosamine, and 1,5-anhydroglucitol refers to the ratio between the level at any timepoints and day 0 (Fig. 1B).

Surgical Procedures and Bacterial Challenge

Details of anesthesia and surgical protocols were reported in our previous study [45]. Briefly, after an initial intraperitoneal injection of ketamine (80 mg/kg) and xylazine (7.5 mg/kg), anesthesia was maintained using 2.5% inhalational isoflurane. In addition, mice were administered buprenorphine (1 mg/kg) for postoperative pain relief. A medial parapatellar approach was adopted to expose the articular surface of the distal femur. A surgery-grade K-wire (0.88 mm in diameter and 12 mm long) was inserted in a retrograde fashion through the intercondylar notch. The K-wire protruded 1 mm into the knee. Microorganisms can invade the musculoskeletal system directly through a wound as a consequence of contamination or via bloodstream commonly after wound closure [42]. These two major invasion routes in bone and joint infection (termed “local” and “systemic” in this study) were mimicked to challenge the mice. For local bacterial challenge, 1 × 103 CFUs of bacteria were applied to the K-wire immediately before insertion. The surgical site was then thoroughly irrigated with 300 mL of normal saline using a 50-mL syringe bulb before wound closure. For the systemic bacterial challenge, mice received an intravenous injection of 1 × 105 CFUs into the tail vein immediately after wound closure.

Postoperative Care

No dressing was applied to the surgical wound in this study. All mice initially returned to their original cage after surgery. When deemed necessary, researchers would keep any mice in a separate cage without a cage companion (for example, a mouse was attacked by cage companions). Mice were maintained on the original diet and kept ambulatory.

Post challenge Bacterial Cultures and Bacterial Species Identification

One week after surgery, mice were euthanized with carbon dioxide, and the knee was harvested under sterile conditions for bacterial culturing. The joint capsule, femur, and intramedullary K-wire were harvested separately and placed into three sterile tubes containing 3 mL of normal saline solution. The femur and joint capsule were homogenized with a tissue grinder (Beyotime). K-wires in tubes were sonicated to release any bacteria from the biofilm. For culturing, we inoculated tryptic soy agar culture plates with 30 µL of the supernatant and cultured the plates at 37°C for 48 hours. Digital images of each plate were taken, and colony counting was automatically performed with ImageJ analysis (National Institutes of Health) and the colony counter plugin [33]. We set an a priori threshold at 20 colonies for the reliable detection of bone and joint infection. If the sum of three colony counts (joint capsule, femur, and K-wire) in a given mouse was less than 20 colonies, its results were excluded from the analysis. No mice were excluded in this study because of this criterion. Bacterial species were identified with 16S ribosomal DNA sequencing using a MicroSeq™ 500 Microbial Identification System (ThermoFisher Scientific), according to the manufacturer’s instructions.

Sample Size Calculation, Randomization, and Blinding

The sample size we used was based on calculations with the Type I error (α) set at 0.05 and with 80% power (1-β). Based on the data obtained from a pilot study, a bacterial challenge could cause bone and joint infection in at least 80% of mice with diabetes. To detect at least a 40% (absolute) difference in the infection proportion, calculations showed that 18 mice per group would be required. In anticipation of possible animal loss, we set the final sample size at 20 mice per group. Block randomization was performed to assign mice with diabetes into seven treatment groups (insulin therapy for 0, 1, 3, 5, 7, 14, or 28 days). Although the group assignment information was blinded, mice with diabetes and those without could be distinguished by casual visual inspection because mice with diabetes were obviously obese. When any mice died or otherwise could not be analyzed, the outcome was recorded as “having infection.” In this study, all groups had at least 18 mice available for analysis and thus no intergroup differences on animal loss were encountered in this study.

Primary and Secondary Study Endpoints

Our primary endpoint was bone and joint infection determined by joint culture. The joint capsule, the femur, and the K-wire were cultured separately, and if the sum of three colony counts of the joint capsule, the femur, and the K-wire in a given mouse was more than 20 colonies, the mouse was considered to have bone and joint infection.

Our secondary endpoint was the change of blood glucose biomarker in response to insulin therapy. HbA1c, fructosamine, and 1,5-anhydroglucitol were measured at 0, 1, 3, 5, 7, 14, and 28 days after the beginning of insulin therapy.

Ethical Approval

Ethical approval was obtained from the Shanghai Jiaotong University Affiliated Sixth People’s Hospital (2020-0084). All animal experiments and animal welfare protocols were conducted in accordance with protocols approved by our institutional animal care and use committee. The study was designed and performed according to the Animal Research: Reporting In Vivo Experiments guidelines [19].

Statistical Analyses

Differences in the proportions of infection between groups of mice receiving a different duration of insulin therapy were compared using Fisher exact tests. Nonparametric Wilcoxon rank sum tests were used to compare the different change of the level of glycemic biomarkers. SPSS version 26.0 (SPSS Inc) was used for statistical analyses. Significance was defined as a p value < 0.05. No mice were excluded in this study because of the a priori threshold of 20 colonies for the reliable detection of bone and joint infection (described previously). Continuous variables are expressed as means ± SDs, and categorical data are expressed as a percentage with counts.

Results

Preoperative Insulin Reduces Musculoskeletal Infections in Mice with Diabetes

Preoperative insulin therapy reduced the proportion of bone and joint infections in our experimental model of mice with Type II diabetes (Fig. 2). We compared the positive culture results of insulin therapy versus no insulin therapy (Supplemental Table 1; Supplemental Digital Content 1, https://links.lww.com/CORR/A658) as well as in control mice without diabetes (Supplementary Table 2; Supplemental Digital Content 2, https://links.lww.com/CORR/A659). After the S. aureus challenge, the proportion of bone and joint infection decreased for both local and systemic inoculation of S. aureus and reached a plateau (Fig. 2A-B) when the duration of insulin therapy lasted for 3 or more days after the systemic challenge (7 of 20 on 3-day therapy, p < 0.001; 8 of 20 on 5-day, p = 0.002; 10 of 20 on 7-day, p = 0.01; 9 of 20 on 14-day, p = 0.006; and 8 of 20 on 28-day therapy, p = 0.002 versus 18 of 20 in the no insulin therapy group) or the local challenge (11 of 20 on 3-day therapy, p = 0.001; 12 of 20 on 5-day, p = 0.003; 10 of 20 on 7-day, p < 0.001; 12 of 20 on 14-day, p = 0.003; and 13 of 20 on 28-day, p = 0.008 versus 20 of 20 in the no insulin therapy group).

F2
Fig. 2:
A-D The proportion of bone and joint infections after bacterial challenge is plotted as a function of the duration of insulin therapy before intra-articular implantation of a K-wire in mice with diabetes (n = 20 for each bacteria challenge [systemic or local]/timepoint]). The proportions of bone and joint infections in mice without diabetes (n = 20 for each bacteria challenge [systemic or local]) were calculated after systemic or local inoculation with two bacteria strains. (A) The proportion of bone and joint infections after systemic injection of 1 × 105 CFUs of S. aureus. (B) The proportion of bone and joint infections with a local inoculation of 1 × 103 CFUs of S. aureus. (C) The proportion of bone and joint infections with a systemic injection of 1 × 105 CFUs of E. coli. (D) The proportion of bone and joint infections with a local inoculation of 1 × 103 CFUs of E. coli. Exact p values are presented as different durations of insulin therapy versus no insulin therapy/different durations of insulin therapy versus control mice without diabetes (Fisher exact tests) above each timepoint.

Similar patterns were observed (Fig. 2C-D) with E. coli when challenged by systemic inoculation (6 of 20 on 3-day therapy, p = 0.004; 7 of 20 on 5-day, p = 0.01; 7 of 20 on 7-day, p = 0.01; 6 of 20 on 14-day, p = 0.004; and 7 of 20 on 28-day, p = 0.01 versus 16 of 20 the in the no insulin therapy group) or local inoculation (10 of 20 on 3-day therapy, p = 0.003; 10 of 20 on 5-day, p = 0.003; 9 of 20 on 7-day, p = 0.001; 11 of 20 on 14-day, p = 0.008; and 10 of 20 on 28-day, p = 0.003 versus 19 of 20 in the no insulin therapy group).

After 28 days of insulin therapy, the proportion of bone and joint infections in mice with diabetes compared with control mice without diabetes after the systemic challenge was as follows: For S. aureus, 8 of 20 mice with diabetes on 28-day insulin therapy had infections versus 4 of 20 mice without diabetes (p = 0.30). For E. coli, 7 of 20 mice with diabetes on 28-day therapy had infections versus 1 of 20 mice without diabetes (p = 0.04). After the local S. aureus challenge, 13 of 20 mice with diabetes had an infection after 28-day therapy versus 8 of 20 control mice without diabetes (p = 0.21); after the E. coli inoculation, 10 of 20 mice with diabetes on 28-day insulin therapy had an infection versus 5 of 20 mice without diabetes (p = 0.19).

Glycemic Biomarkers After Insulin Therapy in Mice with Diabetes

The level of HbA1c did not change over time in mice with diabetes that received preoperative insulin therapy (Fig. 3). The level of fructosamine did not change over time in mice with diabetes that received preoperative insulin therapy with two exceptions: It was lower in the group of mice receiving 14 and 28 days of insulin (different duration of insulin therapy 14 days: 0.75 ± 0.10 [95% CI 0.04 to 0.45]; p = 0.01; 28 days: 0.49 ± 0.11 [95% CI 0.31 to 0.71]; p˂0.001 versus no insulin therapy 1.00 ± 0.12) (Fig. 3). However, a different pattern was observed for 1,5-anhydroglucitol. In contrast to HbA1c and fructosamine, the level of 1,5-anhydroglucitol increased quickly in response to short-term glycemic change, reflecting lower blood glucose levels with as little as 3 days (different duration of insulin therapy 3 days: 1.86 ± 0.20 [95% CI -1.27 to -0.45]; p˂0.001; 5 days: 1.95 ± 0.49 [95% CI -1.36 to -0.54]; p˂0.001; 7 days: 1.97 ± 0.31 [95% CI -1.38 to -0.56]; p˂0.001; 14 days: 2.17 ± 0.47 [95% CI -1.58 to -0.76]; p˂0.001; 28 days: 2.19 ± 0.31 [95% CI -1.60 to -0.78]; p˂0.001 versus no insulin therapy 1.00 ± 0.11) (Fig. 3).

F3
Fig. 3:
The relative levels of HbA1c, fructosamine, and 1,5-anhydroglucitol (mean ± SD) with the different durations of insulin therapy in mice with diabetes (n = 10 mice). Exact p value for the level of 1,5-anhydroglucitol (orange), fructosamine (blue), and HbA1c (red) after different durations of insulin therapy compared with baseline level at day 0 are labeled above each timepoint in different colors (nonparametric Wilcoxon rank sum tests). A color image accompanies the online version of this article.

Discussion

Type II diabetes is a well-established risk factor for bone and joint infection and has greatly contributed to the rapidly increasing prevalence of bone and joint infection. Because only observational data have been reported, it is currently unclear whether preoperative glycemic intervention might reduce the risk of surgical site infection and, if so, what is a reasonable duration for this intervention. In the present study, our main finding was that the increased proportion of bone and joint infection in mice with diabetes could be largely attenuated by 3-day preoperative therapy with insulin. The proportion of bone and joint infections decreased after bacterial challenge in mice with diabetes, reaching asymptotic levels with 3 days of insulin therapy. We observed that there was no further benefit in the model regarding the decrease in the proportion of bone and joint infections when preoperative insulin therapy was longer than 3 days. In our model, 1,5-anhydroglucitol was a better preoperative surrogate biochemical marker of blood glucose level because it had a more rapid response time to short-term glycemic change than HbA1c and fructosamine.

Limitations

The major limitation of this study is the natural gap between animal model and clinical practice. First, a high-fat diet is a classic method to induce obesity, insulin resistance, and eventually Type II diabetes in mice [21]. However, many other genetic, environmental, and lifestyle factors are also closely related to the development of Type II diabetes [22]. Therefore, considering the complex pathogenesis in humans and the genetic gap between animals and humans, we should be careful when extrapolating these findings to the clinical setting. Second, bone and joint infection actually refers to multiple infectious diseases in the musculoskeletal system, including periprosthetic joint infection, osteomyelitis, and trauma-related bone infection. Currently, we used a model with an intra-articular implant which involves bone, joint, and soft tissues. We believe the current model is one of the most representative models for bone and joint infection among all established models. Of course, it remains possible the results and conclusions might be different when another model is used.

Finally, to establish bone and joint infection reliably in mice, we inoculated the joint with nearly three orders of magnitude higher than the bacterial load typically found in a clinical surgical field [9]. The decrease in bone and joint infection proportion we observed in our model might be less impressive in a real-world setting with lower bacterial burden.

The study has several additional limitations. First, the 3-day insulin therapy was solely determined based on the decrease in infection proportion of bone and joint infection. In real clinical practice, the rapid and intense intervention on the blood glucose level might be impractical and risky in some patients. Investigators should pay close attention to this issue in future translational studies. Second, we did not determine the mechanism of how the insulin intervention reduced the proportion of bone and joint infection. Our experiment was performed with a model of mice with diabetes, and mice and humans differ substantially with respect to their immune system [31]. Thus, the mechanism underlying the decrease in infection proportion of bone and joint that we observed is yet to be studied or discerned. Considering these differences, future studies that would use large animals with an immune system more similar to that of humans are warranted. Such an approach might reveal the mechanism and could represent a reasonable path toward clinical translation. Third, we only used female mice for our investigation. There was, to the best of knowledge, no evidence suggesting that the sex of the mice might exert a major impact on the conclusion of studies on musculoskeletal infection.

Preoperative Insulin Reduces Musculoskeletal Infections in Mice with Diabetes

This study found that 3-day insulin therapy before surgical insertion of an intra-articular implant would strongly decrease the proportion of bone and joint infection in a Type II diabetes mouse model. Prolonged (> 3 days) insulin therapy gained no more benefit in terms of reducing bone and joint infection proportion. For those diabetic patients with poor glycemic control, the preoperative intervention on blood glucose is vital for reducing infection risk [14, 18, 30]. It is important to determine a suitable duration of this glycemic intervention to minimize infection risk as well as surgical delay. Our findings might be informative in guiding clinical investigation on the appropriate duration of insulin therapy in patients with Type II diabetes. Notably, even after long-term insulin therapy, the infection proportion of mice with diabetes remained qualitatively higher than that of mice without diabetes. The increased infection risk in patients with diabetes involves various mechanisms, including neutrophil or lymphocyte dysfunction, peripheral neurovascular disorders, and hyperglycemia-induced increase of bacterial virulence [2]. Diabetes-induced angiopathy and neuropathy are barely reversible via glycemic intervention [4]; therefore, the diabetes-related infection risk in a patient with diabetes likely can only be reduced but not entirely eliminated. In contrast, the hyperglycemia-induced increase in bacterial virulence could be rapidly eliminated after glycemia reduction [13, 35]. Recently, an experimental study revealed that neutrophil dysfunction caused by hyperglycemia can be largely attenuated after insulin therapy for only a few days [12]. Together, this prompted us to test whether short-term (several days) glycemic control could successfully reduce the proportion of bone and joint infection.

Glycemic Biomarkers After Insulin Therapy in Mice with Diabetes

Of the three biomarkers we studied (HbA1c, fructosamine, and 1,5-anhydroglucitol), 1,5-anhydroglucitol was the one that best reflected the state of immune restoration after glycemic control in mice. Circulating 1,5-anhydroglucitol is a biomolecule that indicates the short-term fluctuation of blood glucose. In contrast, HbA1c reflects the long-term blood glucose level and was the most extensively investigated biomarker for assessing the infection risk in orthopaedic patients [26]. Controversial results have been reported regarding the predictive value of HbA1c for surgical infection [1, 7, 8, 29, 36, 41]. In addition, a previous investigation revealed that 41% of patients who postponed arthroplasty because of poor glycemic control were not able to reach the HbA1c target (< 7%) [15]. The authors also reported that the mean duration for reaching this target was more than 8 months in the remaining 59% of patients [15]. Based on our observation in this study, a good biomarker for the preoperative assessment of the proportion of infection and guiding surgical timing should be quickly responsive (in several days) to changes in blood glucose levels. Thus, HbA1c, to some extent, was not a useful biomarker in monitoring the short-term response of changes in blood glucose in mice in this study. Unlike HbA1c, fructosamine more accurately reflects blood glucose levels during a shorter period after testing, has a higher predictive power for infection risk, and allows patients with diabetes to reach more achievable levels of glycemic control compared with that achieved with HbA1c as the biomarker [37]. Our study using a model of mice with diabetes found that 1,5-anhydroglucitol has a rapid response in a short period of time after glycemic control, while fructosamine took nearly 28 days to have an obvious response, which demonstrated that 1,5-anhydroglucitol was even better as a glycemic biomarker than fructosamine, at least in mice. Currently, 1,5-anhydroglucitol is a commercially available and FDA-approved assay (Glycomark™) [16]. Future clinical investigations are expected based on patient samples to assess the role of 1,5-anhydroglucitol as a glycemic biomarker for guiding blood glucose levels immediately before surgery.

Conclusion

In this model of mice with diabetes, prolonged glycemic intervention with insulin (> 3 days) before surgery did not reduce the proportion of bone and joint infection further compared with longer durations (5, 7, 14, 28 days) of insulin treatment before surgery. Changes in HbA1c and fructosamine levels lagged behind changes in glycemic control and thus might not be as useful for surgical timing as 1,5-anhydroglucitol, which seemed to be the most responsive of the three biomarkers we studied. These results justify future studies in larger-animal models. Our results suggest that relatively short, aggressive interventions of insulin therapy applied preoperatively in conjunction with 1,5-anhydroglucitol-monitored glycemic control may be a promising approach to reduce surgical site infections in patients with diabetes. Further study needs to assess the value of 1,5-anhydroglucitol in monitoring blood glucose levels before surgery based on a patient’s clinical sample.

Acknowledgments

We thank Kai Fu PhD, Jinlong Suo PhD, and Weiguo Zou PhD for their constructive suggestions.

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