FormalPara Key Summary Points

Diabetic foot ulcers (DFUs) have high rates of disability and mortality; however, the choice of antibiotics is still controversial because the types of bacteria that infect vary.

This study tests whether or not the bacterial species profile is different for different Wagner classifications.

We found that as the Wagner grade increases, the complexity of the infected bacteria increases.

Understanding the pathogen profile of DFUs is critical to preventing antimicrobial misuse and antibiotic resistance.

Introduction

Diabetes is becoming a global epidemic. According to reports from authoritative research institutions, the number of people with diabetes was only 194 million in 2003 and is expected to reach 700 million by the end of 2045 [1]. The prevalence of diabetes also remains high in China. Diabetic foot ulcer (DFU) is one of the most serious and costly chronic complications of diabetes [2]. Up to one-third of people with diabetes will develop DFUs during their lifetime [3]. Diabetic foot (DF) is the infection, ulceration, or destruction of tissues beyond the foot and ankle associated with lower extremity neuropathy and/or peripheral arterial disease in patients with a history of diabetes [4]. Once an ulcer occurs, the risk of lower extremity amputation increases eightfold in patients with diabetes [5]. Worldwide, an estimated 18.6 million people live with DFUs; an additional 131 million people (1.77% of the global population) have predisposing risk factors for developing DFUs without intervention [6]. In developing countries, the incidence of DFUs is higher and increasing as a result of low socioeconomic status and lack of health awareness [7, 8]. The prognosis of DF is very poor and associated with higher mortality and disability rates than most cancers (except lung cancer, pancreatic cancer, etc.). If DF is not properly treated, severe cases can lead to amputation or even death [9]. The annual mortality rate for patients with DF is as high as 11%, and for amputees it is as high as 22% [10]. A patient with diabetes undergoes an amputation every 20 s worldwide [11]. DF is a leading cause of diabetes-related disability and death and the most common cause of non-traumatic lower extremity amputation. Its 5-year mortality rate is as high as 43–55%, which is even higher than Hodgkin’s disease, breast cancer, and common cancers such as prostate cancer [12,13,14]. It not only seriously endangers the physical and mental health of patients and increases the financial burden on patients’ families [15, 16] but it is also a major public health problem that imposes a heavy burden on society [17]. If patients with DF receive appropriate care and medication at the appropriate time, the possibility of amputation is greatly reduced. One of the key measures for its treatment is the timely and effective use of antibacterial drugs and early etiologic examination of the wound. It is very important to select sensitive antibiotics based on the results of drug susceptibility testing. Therefore, classification of local pathogen distribution and resistance patterns is important to guide effective treatment and develop appropriate infection control policies. The purpose of this study is establish the characteristics of pathogenic microorganisms and antibiotic resistance classification unique to the local special zone based on the distribution of causative pathogens and drug susceptibility results of DFUs in the coastal areas of southeastern China, to guide clinical practice and prevent the misuse of antimicrobial drugs, and to reduce the emergence of drug-resistant strains.

Methods

General Information

A total of 212 inpatients with DF in the Third Hospital of Xiamen from July 2018 to July 2023 were collected. All of them met the 1999 World Health Organization diagnostic criteria for diabetes. This study was approved by the ethics committee of our hospital. Given the retrospective nature of this study, written informed consent was waived. There were 129 male patients and 83 female patients, aged 27–92 years old, with an average age of 65 ± 13 years. All patients had foot ulcers and, in severe cases, soft tissue abscesses, osteomyelitis, local gangrene, or even total foot gangrene. DFIs were classified according to severity using Wagner’s classification: there were 1 case of grade 1, 57 cases of grade 2, 85 cases of grade 3, 68 cases of grade 4, and 1 case of grade 5. We conducted an analysis of the characteristics of the DF population according to Wagner grade (Table 1).

Table 1 Baseline epidemiologic features among hospitalized patients with DFU according to the Wagner grade (n = 212)
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Bacterial Strain Identification and Drug Susceptibility Testing

Before administering antibiotics to hospitalized patients, samples were collected using a scalpel or tweezers to scrape the wound, allowing tissue fragments to detach. A sterile cotton swab was then used to gather these fragments and any exudate. The samples were immediately placed in sterile test tubes and sent for laboratory analysis. All specimens were subjected to bacterial strain identification and drug sensitivity testing. The identification results and process judgments are in line with the standards set by the National Committee for Clinical Laboratory Standards (NCCLSI).

Statistical Methods

Continuous variables were expressed as mean ± standard deviation, categorical variables were expressed as frequency (percentage), and gender, PAD, LOPS, CKD, and smoking were considered as dichotomous variables. t tests and chi-square/Fisher’s exact tests were used for baseline data to compare quantitative and qualitative variables between groups, respectively. Differences between G+ bacteria, G− bacteria, and mixed bacteria between Wagner classification ≤ 2 and Wagner classification ≥ 3 were compared using the chi-squared test, and the statistical program was run in EmpowerStats (version  4.1).

Results

Distribution of Pathogenic Bacteria

Among the 212 patients with DF treated in this study, 129 were male patients and 83 were female. Pathogenic bacteria were cultured in 163 DF wounds (76.89%). A total of 207 strains of pathogenic bacteria were cultured, including 75 Gram-positive (G+) bacteria strains (36.23%), 118 Gram-negative (G−) bacteria strains (57.00%), and 14 fungi strains (6.76%) (Fig. 1). There were 120 cases of single microorganism infection (73.62%), 43 cases of mixed infection (26.38%), and 15 strains of multidrug-resistant bacteria (7.25%). The top three pathogenic bacteria were Staphylococcus aureus (24.64%), Klebsiella pneumoniae (7.73%), and Pseudomonas aeruginosa (7.25%). G+ bacteria were mainly S. aureus, Streptococcus agalactiae, and Streptococcus pyogenes, accounting for 68%, 10.67%, and 5.33% of G+ bacteria, respectively. G− bacteria were mainly K. pneumoniae, P. aeruginosa, Escherichia coli, Proteus mirabilis, and Morganella morganii, accounting for 13.56%, 12.71%, 11.86%, 11.86%, and 8.47% of the G− bacilli, respectively; others include Enterobacter cloacae, Proteus vulgaris, Proteus hauseri, etc. The detection rate of multidrug-resistant bacteria was 7.25%, mainly S. aureus, E. coli, P. aeruginosa, and K.  pneumoniae. Fungi were isolated: Candida albicans (6 strains, 42.86%), Candida parapsilosis (7 strains, 50%), and Candida sake (1 strain, 7.14%). Further analysis found that one strain of pathogenic bacteria detected in Wagner grade 1 ulcers was G+ bacteria. There were more single G+ strains (19 strains, 46.34%) in Wagner grade 2 wounds than single G− strains (10 strains, 24.39%), mixed infections (8 strains, 19.51%) and fungi (4 strains, 9.76%). With the increase of Wagner grade, G+ bacteria gradually decreased and G− bacteria and mixed infection bacteria increased. There were more single G− strains (32 strains in grade 3, 47.06%, 23 strains in grade 4, 44.23%) than single G+ strains (15 strains in grade 3, 22.06%, 13 strains in grade 4, 25%) and fungi (1 strain in grade 3, 1.47%, 2 strains in grade 4, 3.85%) in Wagner grade 3 and Wagner grade 4. Mixed infections were significantly more frequent in Wagner grades 3 and 4 (29.41% in grade 3 and 26.92% in grade 4) than in Wagner grade 2 (19.51%) (Fig. 2). Mixed infections were most often a mixture of G− and G+ bacteria and, to a lesser extent, multiple G− bacteria (Fig. 3). The infection rates of G+ bacteria, G− bacteria, and mixed bacteria in Wagner grade ≤ 2 were 52.63%, 26.31%, and 21.05% respectively. The infection rates of G+ bacteria, G− bacteria, and mixed bacteria in Wagner grade ≥ 3 were 23.72%, 46.61%, and 29.66% ,respectively. The difference between the two groups was statistically significant (P < 0.05) (Table 2).

Fig. 1
figure 1

Distribution of pathogenic microorganisms in diabetic foot ulcers

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Fig. 2
figure 2

Distribution of pathogens (strains) in diabetic foot ulcers with different Wagner grades

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Fig. 3
figure 3

Pathogens of polymicrobial infections in diabetic foot ulcers with different Wagner grades

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Table 2 Comparison of bacteria in wound cultures according to Wagner grade ≤ 2 vs. ≥ 3 (n = 156)
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Pathogen Drug Susceptibility Test Results

Gram-positive bacteria were highly susceptible to vancomycin, linezolid, tigecycline, quinupristin/dalfopristin, rifampicin, and furotoxin, and somewhat resistant to penicillin, erythromycin, clindamycin, and cefoxitin (Table 3). In G− bacterial infections, carbapenems such as imipenem and ertapenem were the most effective antibacterial drugs, followed by amikacin, piperacillin-tazobactam, the second- and third-generation cephalosporins, while these bacteria were resistant to penicillins and first-generation cephalosporins (Table 4).

Table 3 Susceptibility of Gram-positive bacteria to antibiotics in diabetic foot ulcers
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Table 4 Susceptibility of Gram-negative bacteria to antibiotics in diabetic foot ulcers
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Discussion

Different studies in different countries have revealed differences in microbial composition and drug susceptibility associated with DFU [18, 19]. Before the culture results of DF secretions are known, broad-spectrum antibiotics are often selected on the basis of clinical experience. In order to prevent the abuse of antimicrobial drugs and reduce the emergence of drug-resistant strains, it is of great significance to the diagnosis and treatment of DF to accurately understand the spectrum of pathogenic bacteria in DF wounds and determine effective antimicrobial drugs. In the past, the pathogenic bacteria of DF infections were mostly G+ bacteria. However, recent studies have shown that G− bacterial infections are gradually increasing, and the proportion of polymicrobial infections is also increasing. A large number of studies have shown that S. aureus is the main pathogen of DFUs in Western countries [20], and Pseudomonas is the main pathogen in Asian and African countries [21]. The prevalence of these pathogenic microorganisms varies depending on disease pattern, duration, previous antibiotic use, and geographic relatedness of nosocomial infections [22].

In this study, S. aureus had the highest detection rate, which is consistent with the results of most studies, followed by K.  pneumoniae, P. aeruginosa, E. coli, and Proteus. The results of this study show that there were significantly more G− bacterial infections in DFUs than G+ bacteria, which is consistent with recent research results [23,24,25], and we found that as the Wagner grade increases, the distribution of pathogenic bacteria changes from G+ bacteria to G−, and the mixed infection rate increases, mostly a mixture of G+ bacteria and G− bacteria. Therefore, when empirically selecting antibiotics, for patients with DF with Wagner grades 1 and 2, antibiotics targeting G+ bacteria should be selected, while for patients with DF with Wagner grades 3–5, the infection rate of G− bacteria is high and mixed infections are prone to occur. This observation may be related to the body’s systemic inflammatory response and decreased immunity when DFUs are infected. It is suggested that when using medication, attention should be paid to combined medication or broad-spectrum antibiotics to ensure coverage of both G+ bacteria and G− bacteria. The detection rate of fungi in this study was 6.76%. The main reason may be that long-term irregular abuse of antibiotics is common in daily life, and most patients are transferred from primary hospitals or other hospitals after ineffective treatment, and antibiotics are used in other hospitals. It is related to causing bacterial imbalance and requires antifungal treatment when necessary.

Our antibiotic susceptibility test data shows that G+ bacteria are highly sensitive to vancomycin, linezolid, tigecycline, quinupristin/dalfopristin, rifampicin, and nitrofurantoin, while they are resistant to penicillin, erythromycin, clindamycin, and cefoxitin. For G− bacterial infections, carbapenems such as imipenem and ertapenem remain the most effective antimicrobial agents against G− strains, followed by amikacin, piperacillin, tazobactam, and second- and third-generation cephalosporins, whereas resistance to penicillin and first-generation cephalosporins has increased significantly, which is a guiding factor in the choice of antibiotics for the treatment of DFUs in our institution. On the basis of our study findings, prior to the availability of culture results, for patients with lower Wagner grades predominantly infected with G+ bacteria, particularly S. aureus, we recommend the use of oral first-line antibiotics such as penicillinase-resistant penicillins, clindamycin, levofloxacin, and ciprofloxacin. For patients with higher Wagner grades, who are primarily infected with G− bacteria or have mixed infections, the recommended oral first-line antibiotics are levofloxacin and ciprofloxacin. Upon obtaining culture results, one should tailor the antibiotics on the basis of susceptibility testing to ensure targeted and effective treatment.

Although empiric antibiotic therapy is an important component of DFU treatment, in recent years, the increasing prevalence of multidrug-resistant bacteria in DF wounds has made antibiotic selection difficult. In this study, a total of 15 cases (7.39%) of multidrug-resistant bacteria were isolated, which may be related to previous use of antibacterial drugs, repeated hospitalization for the same wound, combined osteomyelitis, neuroischemic wounds, and other factors [26]. Worrying among them is the discovery of carbapenem-resistant strains, which is a wake-up call. Today, with the abuse of antibiotics, we should strictly grasp the indications for antibiotic use, put an end to indiscriminate use and abuse, and prevent the emergence of a large number of drug-resistant bacteria and even superbugs. To date, many articles have described the distribution of pathogenic bacteria or antibiotic resistance in DFUs in different regions of different countries [27,28,29], but they are not suitable for every region. A limitation of this study is that it is a single-center study conducted in the Southeast China Sea region. Therefore, the results may not be fully applicable to patients in other regions or at different levels of hospitals. Geographic and healthcare resource differences may affect pathogen distribution and resistance patterns. In addition, differences and limitations in laboratory diagnostic methods may also affect the accuracy of pathogen identification and drug sensitivity testing. Therefore, we recommend selecting antibiotics on the basis of the distribution and resistance patterns of DF pathogens in each country’s local area. Later, when antibiotic susceptibility results are reported, switching to the antibiotic with the highest susceptibility is critical to minimizing DFU treatment failure, reducing antibiotic resistance, drug-related adverse events, and the likelihood of unnecessary financial costs and other adverse events.

Conclusion

As the Wagner grade of DF wound pathogens increases, the proportion of G+ bacteria decreases, the proportion of G− bacteria increases, and the proportion of mixed infections increases. The more severe the infection, the less effective the treatment, the worse the prognosis, and the higher the amputation rate. The timely and effective application of sensitive antibiotics has important clinical significance for reducing antimicrobial resistance, improving cure rates, and reducing amputation rates. Therefore, mapping the distribution of pathogenic bacteria and antimicrobial resistance patterns consistent with local conditions is important to guide effective treatment and formulate appropriate infection control policies.