Bacteriological Profile and Antibiotic Resistance Patterns in Diabetic Foot Infections: A Monocentric Tertiary Care Study in Lebanon (2017–2024)

Bacteriological Profile and Antibiotic Resistance Patterns in Diabetic Foot Infections: A Monocentric Tertiary Care Study in Lebanon (2017–2024) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bacteriological Profile and Antibiotic Resistance Patterns in Diabetic Foot Infections: A Monocentric Tertiary Care Study in Lebanon (2017–2024) Roy Saade, Jacques Choucair This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7391175/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Diabetic foot infections (DFIs) are a serious complication of poorly controlled diabetes mellitus (DM), often resulting in significant morbidity, recurrent hospital admissions, and an increased mortality risk. The bacteriological profile and resistance patterns of DFIs vary based on geographical and socio-economic factors, with Gram-negative bacteria more prevalent in humid, lower-income regions, including the Middle East. Data on DFI’s microbiological landscape in Lebanon remain limited, with few studies tracking the evolution of antibiotic resistance over time. This retrospective, monocentric study analyzes the bacteriological trends of DFIs in Lebanon over seven years, comparing findings with previously published research from the same center and other national and regional studies. Results Gram-negative bacteria were identified in 68.23% of all DFIs. However, Staphylococcus species remained the most frequently isolated bacteria, accounting for 20.7% of cases, followed by E. coli (16.3%) and Pseudomonas species (13.8%). A substantial increase in ESBL-producing Enterobacterales was observed compared to earlier data from the same center (36.86% vs 16.3% in 2011). Severe diabetic foot infections were also significantly associated with higher rates of diabetic neuropathy and peripheral arterial disease compared to milder infections. Conclusions DFI-causing bacteria exhibit increasing resistance to standard oral and parenteral antibiotics. As a result, preventing diabetic foot infections through regular foot assessment, strict glycemic control, and long-term follow-up is crucial in minimizing ulcer formation and subsequent infections. Bacteriology Cardiac & Cardiovascular Systems Endocrinology & Metabolism Diabetic Foot Infection Osteomyelitis Bacterial Classification Antibiotic Resistance Epidemiology Lebanon 1 Introduction Diabetes mellitus (DM) is a major global public health concern, affecting approximately 540 million individuals worldwide, with 240 million remaining undiagnosed and untreated 1 . The burden of DM is particularly significant in the Middle East and North Africa, which has the single highest age-standardized prevalence globally, estimated at 12.2% (55 million cases) 2 . In Lebanon, the lack of comprehensive national data collection hampers the accurate assessment of DM prevalence. However, estimates range from 8.9% (400,000 cases), according to the International Diabetes Federation (IDF) 3 , to 15–17% in more recent studies 3 , 4 . Chronic DM frequently leads to microvascular and macrovascular complications, as well as peripheral neuropathy, immune dysfunction, and metabolic disturbances. These factors contribute to accelerated breakdown of the skin and deeper tissues of the feet, often resulting in deformities and ulceration in up to 20% of patients 5 . Ulcers, many of which remain unrecognized, can progress to infections in as many as 40% of cases 6 . Diabetic foot infections (DFIs) impose a significant burden on patients, encompassing increased healthcare costs, frequent hospitalizations 7 , 8 , reduced quality of life, and complications such as foot deformities, lower extremity amputations, recurrent infections, and increased mortality 9 . Frequent foot examinations and close patient follow-up 6 are essential for early intervention and improved prognosis. Several classification systems have been developed to standardize the evaluation of DFIs, focusing on factors such as infection depth, bone involvement, and systemic manifestations. These include the Meggitt-Wagner system, the University of Texas classification, and the Wound, Ischemia, and Foot Infection (WIfI) system 10 . More recently, the International Working Group on the Diabetic Foot (IWGDF) introduced a four-grade classification system, ranging from 1 to 4 in order of increasing severity, accompanied by recommendations for effective diagnosis and treatment 11 . Profiling the bacteria responsible for DFIs has gained importance amid the global rise in antibiotic resistance. DFIs commonly involve a range of bacteria, including Gram-positive organisms such as Staphylococcus aureus —the most frequently implicated worldwide—and Enterococcus , as well as Gram-negative bacilli like Pseudomonas and Enterobacterales 12 . The emergence of methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and extended-spectrum beta-lactamase-producing (ESBL) Gram-negative bacteria is alarming. This underscores the need for studies tracking resistance profiles both nationally and regionally. To date, only three studies 13 – 15 have been published on the bacteriological resistance patterns of DFIs in Lebanon, including one 14 from the same tertiary care center as this study. A single one 13 was multicentric. 2 Material and methods This retrospective study analyzed all patients diagnosed with diabetic foot infections (DFI) admitted to Hôtel-Dieu de France Hospital, Beirut, between January 2017 and July 2024. Included were diabetics aged 18 years or older with confirmed DFIs requiring inpatient care. Exclusion criteria included prediabetic patients, patients diagnosed or treated exclusively in an outpatient setting, cases with insufficient samples for culture, and those with incomplete medical records that hindered disease categorization. Diagnosis of diabetic foot infections was based on clinical and radiological signs, with imaging (e.g., X-rays or MRI) used for suspected osteomyelitis. Debridement of tissue was performed following established surgical principles 16 , ensuring the excision of all necrotic and devitalized tissues. For cases involving osteomyelitis, limited amputations were performed when necessary. Infected wounds were left open to heal by secondary intention. Resected tissues were sent to the laboratory for histopathological analysis and aerobic and anaerobic cultures. Fungal cultures were not included in this study. All specimens were processed following the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines 17 . Tissue samples were cultured on blood agar, MacConkey agar, Columbia Nalidixic Acid (CAN) agar, and schädler agar for anaerobic identification. They were incubated at 37°C. Gram staining was performed for the preliminary classification of bacterial isolates. Antibiotic susceptibility testing was conducted using either the Kirby-Bauer disk diffusion method, with results interpreted according to EUCAST breakpoints, or the Pheonix BD automated identification system. The tested antibiotic panel included penicillins (ampicillin, amoxicillin-clavulanate, piperacillin, and piperacillin-tazobactam), cephalosporins (cephalexin, cefotaxime, cefixime, cefepime, and ceftazidime-avibactam or ceftolozane-tazobactam when necessary), and carbapenems (ertapenem, imipenem, and meropenem). Additional antibiotics tested included vancomycin, aminoglycosides, and colistin (when necessary). Fluoroquinolones (e.g., ciprofloxacin) and trimethoprim-sulfamethoxazole (TMP-SMX) were also evaluated for outpatient oral antibiotic therapy. Bacteria were classified as either Gram-positive species, with special consideration for Staphylococcus and Enterococcus , or Gram-negative species, further subdivided into the Enterobacterales order and Pseudomonas species. Staphylococcus isolates were categorized as methicillin-sensitive (MSSA) or methicillin-resistant (MRSA), while Enterococcus isolates were identified as vancomycin-resistant (VRE) following molecular confirmation when necessary. For Enterobacterales , resistance was classified as penicillinase-producing, cephalosporinase-producing, carbapenem-sensitive extended-spectrum beta-lactamase (ESBL)-producing, or carbapenemase-producing strains (CRE). Pseudomonas isolates were further analyzed for resistance to piperacillin-tazobactam, imipenem, and fluoroquinolones. Patient data was collected from electronic medical records, anonymized using patient-specific electronic codes, and transcribed into Excel for statistical analysis. Extracted variables included demographic information (e.g., sex and age during infection diagnosis), cardiovascular risk factors, diabetic complications, and comorbidities. Ethical approval for the study was obtained from the Institutional Review Board of Hôtel-Dieu de France Hospital. Statistical analyses were conducted using R software (version 4.1.3), with the prettyR and Tableone packages. Descriptive statistics summarized patient characteristics, with continuous variables expressed as means (± standard deviation) and categorical variables as counts and percentages. Stratified analyses compared subgroups, with the Student’s t-test applied to quantitative variables and the Chi-square test used for categorical variables, provided conditions for validity were met. Statistical significance was set at p < 0.05 . 3 Results Patient Demographics (Table 1 ) A total of 240 DFIs were included in the analysis, involving 152 unique patients. Among these, 50 patients experienced recurrent infections, resulting in multiple hospital admissions, with an average of 2.78 readmissions per patient. Notably, readmissions for DFI were classified as separate events only if the time between discharge and readmission exceeded one month. The mean age at diagnosis was 68.33 years. Men represented most cases (73.75%, n = 178), with a mean age of 66.61 years (range 42–91, SD 9.54). Women accounted for 26.25% of cases (n = 63), with a mean age of 73.21 years (range 36–100, SD 14.32). Most patients (62.50%) were between 60 and 80 years old. Notably, only one woman under 40 was treated for a DFI. In patients over 80, women outnumbered men 2:1 (24 vs. 12), comprising over a third (38.10%) of all hospitalized women. The majority of patients (65.83%) had poorly controlled diabetes (HbA1c > 7%). A high proportion (95.42%) had hypertension or were taking antihypertensive medication (ACE inhibitor, ARB, diuretics…). Dyslipidemia was present in 70% of patients, while 37.08% were current smokers. Common comorbidities included diabetic neuropathy (64.58%), chronic kidney disease (67.50%), and peripheral arterial disease (74.17%). 66.67% underwent coronary artery bypass grafting or percutaneous angioplasty and/or stenting for coronary artery disease. Compared to women, men were more likely to have poorly controlled diabetes (69.49% vs. 55.56%) and to smoke (42.37% vs. 22.22%). Hypertension and hypercholesterolemia rates were similar between the sexes (96.05% vs. 93.65% and 69.49% vs. 71.43%, respectively). Men exhibited higher rates of all measured diabetic comorbidities. Data regarding diabetes duration and type, pack-years of smoking, length of hospitalization, revascularization procedures, and other comorbidities (e.g., diabetic retinopathy, stroke) were inconsistently documented or insufficient for analysis. Bacteriological profile (Table 2 ) Of 240 DFIs analyzed, 318 distinct bacterial isolates were identified through standard laboratory culture, yielding an average of 1.32 bacteria per patient. Of particular interest, only 42.2% of patients showed polymicrobial infections. Gram-negative bacteria comprised the majority of isolates (68.2%), while Gram-positive bacteria accounted for 31.2%. Enterobacterales were the most prevalent (51.76% of isolates, n = 164), followed by Pseudomonas species (13.83%, n = 44). Overall, 71.5% of positive cultures contained at least one Gram-negative bacterium, and 42.9% contained at least one Gram-positive bacterium. Among Gram-positive isolates, Staphylococcus species were most frequent (20.75%, n = 70), followed by Enterococcus species (8.17%, n = 26). Streptococcus species constituted only 2% of Gram-positive isolates. Within the Enterobacterales order, Escherichia coli was the most common (32.1% of Enterobacterales isolates, n = 52), followed by Proteus (17.9%), Klebsiella (14.8%), Enterobacter (14.1%), Morganella (9.25%), and Citrobacter (6.17%). Other Enterobacterales (e.g., Serratia, Providencia) and other Gram-negative genera (e.g., Stenotrophomonas, Bacteroides, Acinetobacter) were present in smaller numbers. Despite the overall predominance of Gram-negative Enterobacterales , Staphylococcus species were the single most frequently isolated group, followed by E. coli and then Pseudomonas species. Resistance profile (Table 3 ) Resistance profiles were evaluated for the most prominent bacterial groups. Among Staphylococcus aureus species, methicillin-resistant Staphylococcus aureus (MRSA) was identified in 17 out of 62 cases, accounting for 27.42%. In Enterococcus faecium isolates, vancomycin-resistant Enterococcus (VRE) was detected in 3 cases (50%). Pseudomonas species, representing 13.83% of all isolates, exhibited notable resistance patterns. Resistance to piperacillin-tazobactam was observed in 31.82% of Pseudomonas isolates (n = 14/44), with similar rates observed for carbapenems. All carbapenemase-producing Pseudomonas isolates, however, remained susceptible to colistin. Fluoroquinolone resistance was high (50%), with an additional 7.15% demonstrating intermediate susceptibility, limiting the potential for oral outpatient therapy. Among other Gram-negative bacilli, 37.57% produced carbapenem-sensitive extended-spectrum beta-lactamases (ESBLs), and 9.24% produced carbapenemases, totaling 46.81% of these isolates. Penicillinase enzymes were expressed by 38.72% of isolates, and cephalosporinase enzymes by 9.24%. Resistance to oral outpatient antibiotics was also prevalent in this group, with 52.6% resistant to fluoroquinolones and 45.66% resistant to trimethoprim-sulfamethoxazole (TMP-SMX). An additional 3.46% of isolates showed intermediate susceptibility to fluoroquinolones. Antibiotic Use (Table 4) Antibiotics were routinely used, as empiric therapy was administered to 87.5% of DFI patients (n = 210), with 58.1% receiving combination therapy. Across the 240 DFIs, 349 antibiotic prescriptions were recorded, averaging 1.45 antibiotics per admitted patient. Piperacillin-tazobactam was the most frequently used empiric antibiotic, prescribed in 23.5% of cases, often as monotherapy or in combination with vancomycin (16.02%). These were followed by meropenem (12%), teicoplanin (8%), and imipenem-cilastatin (7.45%). Less frequently used antibiotics, such as linezolid, metronidazole, and clindamycin, were typically reserved for patients with prior infections and known antibiograms to guide therapy. Infection severity and comorbidities (Table 5) DFIs were classified as either deep-tissue (n = 186, 79.1%) or soft-tissue (n = 49, 20.9%) infections, based on the IWGDF classification system (grade 3–4 vs grade 2). Since ulcer size and depth could not be consistently assessed across all records, deep-tissue infections were defined by the presence of at least one of the following criteria: radiologically confirmed osteomyelitis, bone amputation at any level, septic shock, or death attributable to the infection. The mortality rate was 5.83% (n = 14), while amputations were performed in 28.3% of cases (n = 68). While most cardiovascular risk factors and diabetic comorbidities were similar between the two groups, diabetic neuropathy and peripheral arterial disease (PAD) were significantly more prevalent in the deep-tissue infection group (p < 0.001). Specifically, diabetic neuropathy was present in 72.04% of deep-tissue infections compared to 36.73% of soft-tissue infections. PAD was observed in 83.33% of deep-tissue infections versus 46.94% of soft-tissue infections. No significant differences were found between the two groups regarding poor diabetes control (HbA1c > 7%), smoking rates, or nephropathy (p = 0.303, p = 0.179, and p = 0.324, respectively). The average number of bacterial isolates was higher in deep-tissue infections (p = 0.001), with more ESBL-producing Gram-negatives. No difference was found relating to bacteria type or other resistance profiles. Data limitations precluded analysis of factors such as hospital length of stay (LOS) or previous amputations. 4 Discussion (Table 6) DFUs carry a 5-year mortality rate between 30 and 50%, comparable to that of cancer, with an even worse prognosis in cases of critical limb ischemia 18 . These poor outcomes are largely attributed to the burden of DM comorbidities such as nephropathy and CAD, which significantly complicate patient management 19 . The present study reveals a high burden of comorbidities and complications among patients hospitalized for diabetic foot infections (DFIs). Notably, 65.8% of patients had poorly controlled DM, 65% had neuropathy, and 74% had peripheral arterial disease (PAD). Hypertension or the use of antihypertensive medication was found in nearly all patients (95.42%). The severity of the infection burden is further underscored by the 32.8% readmission rate (50/152 patients) due to poor disease control. Interestingly, the prevalence of these comorbidities appears slightly lower than that reported at Hôtel-Dieu Hospital between 2000 and 2011, where poorly controlled diabetes affected 75.4% of patients, neuropathy 77.8%, and PAD 93.1%. Only 60.38% had arterial hypertension. The disparity in hypertension and peripheral arterial disease between both studies could be attributed to several factors. First, in this study, hypertension was defined not only by a previously established diagnosis but also by the use of antihypertensive medications, including ACE inhibitors, which are commonly prescribed for diabetic nephropathy rather than hypertension alone. Second, the observed changes in both categories may reflect improvements in healthcare access, early screening of diabetic comorbidities and complications, and increased patient compliance with medical treatment. Finally, such a change could simply be the result of a changing, older population. Epidemiological data consistently demonstrate a higher prevalence of DM in men compared to women. However, women are typically diagnosed at an older age (post-60) and tend to experience higher rates of cardiovascular complications 20 , possibly due to less stringent follow-up care and later complication onset. Specifically regarding DFIs, men are 1.57 times more likely to be diagnosed and experience higher amputation rates 20 . Our findings regarding sex distribution in diabetic foot infections (DFIs) align with established patterns. Men constituted the majority of cases (73.75%) and predominated in age groups under 80. Women were more prevalent in the over-80 age group, exhibiting a 2:1 female-to-male ratio. Men also presented with a higher overall prevalence of diabetic comorbidities, including both microvascular and macrovascular complications (71.3% vs. 57.3%). It has been suggested that the bacteriological profile of DFIs differs between developing and developed countries, with Gram-negative organisms predominating in the former and Gram-positive in the latter. A global meta-analysis 21 found that 62.4% of bacteria in high-income countries were Gram-positive, while 59.6% in lower-income countries were Gram-negative. This difference was statistically significant, with Streptococcus species more prevalent in high-income countries and Klebsiella and E. coli more common in lower-income countries. The reasons for this variability are not fully understood. A meta-analysis of DFIs in Middle Eastern countries 22 suggested that Gram-negative bacteria are more prevalent in severe, hospitalized infections, while Gram-positive bacteria are more common in superficial, outpatient-treated DFIs. Factors such as delayed care-seeking 23 (potentially due to lower awareness), high rates of barefoot walking, and limited access to medical and foot care services suggest that socioeconomic and healthcare accessibility factors may be more influential than purely geographical location 22 . In this study, Gram-negative bacteria comprised 68.23% of all cultured isolates, with Gram-positive bacteria accounting for the remaining 31.77%. 71.5% of patients had at least one Gram-negative bacterium cultured, while 42.9% had at least one Gram-positive bacterium. Notably, Staphylococcus aureus was the most frequently isolated organism (20%), followed by E. coli (16.3%) and Pseudomonas species (13.8%), consistent with other studies from lower-income countries. These findings contrast with our previous analysis 14 , which showed Pseudomonas as the most prevalent organism (19.15%), followed by E. coli (11.9%) and S. aureus (11.1%), but align with other studies in Lebanon 13 , 15 and neighboring countries, including Jordan 24 , Egypt 25 , and Saudi Arabia 26 . Interestingly, 42.2% of infections in this study were polybacterial, representing a decrease from the 52.26% reported in our earlier analysis 14 . Other studies in Lebanon have shown varied rates, including 54% 15 and 38% 13 , while a global meta-analysis 12 reported a higher prevalence of 58.9%. The role of anaerobic bacteria in DFIs remains difficult to assess. Older studies suggested an increased presence of anaerobes in deep DFIs, particularly those associated with severe peripheral arterial disease (PAD) 27 . However, research has primarily focused on aerobic Gram-positive and Gram-negative bacteria due to their predominance in cultures. A 2015 study 27 highlighted inconsistencies in the literature but reported an average anaerobic pathogen prevalence of 11% across analyzed studies. A more recent (2020) study using PCR-based genomic analysis 28 demonstrated a much higher prevalence of anaerobes, detecting Prevotella and Bacteroides species in 93% and 70% of cultures, respectively, compared to conventional methods. In our study, anaerobic bacteria were isolated in only 1.5% of cases, highlighting the limitations of standard culture techniques for detecting these organisms. The most striking finding of this study is the substantial increase in multidrug-resistant organisms, especially Gram-negative bacteria, compared to our previous work. Among Enterobacterales , nearly half (46.81%) were either ESBL or carbapenemase-producing, a significant rise from the previously reported 16.3% ESBL rate, where cephalosporinase-producing species predominated (41.3%). Fluoroquinolone resistance also increased from 39.13–52.6%, while TMP-SMX resistance remained relatively stable (47.83% vs. 45.66%). Pseudomonas species exhibited increased carbapenem resistance (25.9–31.8%). Methicillin resistance among Staphylococcus species remained consistent (27.42% vs. 28.78%). Vancomycin resistance among Enterococcus faecium isolates was 50% (3/6). Comparative data from our previous study are unavailable. Multiple recent studies 29 – 31 have reported increased bacterial resistance in diabetic foot ulcers, with several contributing factors identified. One significant factor is prolonged antibiotic therapy. Patients with severe diabetic foot infections often present with comorbid neuropathy and peripheral arteriopathy 32 , as observed in this study, along with structural foot deformities. These factors predispose patients to poor foot care, chronic ulceration, and frequent ulcer recurrence, all of which can lead to increased antibiotic use 33 . Additionally, antibiotic therapy for DFIs tends to be prolonged. Soft tissue infections typically require 1–2 weeks of treatment, which is often extended for slow-healing ulcers 6 . A 5–6 week course is generally recommended for osteomyelitis, although amputation of infected bone with clear margins can reduce the duration to 1 week 34 . However, patients are often reluctant to undergo such procedures. The COVID-19 pandemic has also been proposed as a contributing factor to poor wound care 31 . Between 2020 and 2023, many patients avoided hospital admissions, often presenting with more severe infections and systemic manifestations. Stress-related dietary changes during this period also likely worsened glycemic control, contributing to higher infection rates and delayed wound healing 35 . Other factors, such as poor medication compliance 36 , may have also played a role. While showing a statistically significantly higher bacterial load compared to superficial infections, deep infections were associated with a greater prevalence of extended-spectrum beta-lactamase (ESBL)-producing Gram-negative bacteria (p = 0.0136). No other significant differences in bacterial type or resistance profiles were observed between the two groups, nor were rates of poorly controlled diabetes (59% in superficial vs. 68% in deep infections, p = 0.30). Furthermore, patients with deep infections had a higher prevalence of both diabetic neuropathy and peripheral arterial disease (PAD), with no evidence of higher incidence in other diabetic microvascular complications (e.g., nephropathy). These findings suggest that infection severity correlates with both higher bacterial burden and more resistant strains. Contrary to a previous meta-analysis 22 , this study found no significant difference in Gram staining between deep and superficial infections, which is plausible in a uniformly severe (IWGDF 3–4) inpatient cohort. The distinction between deep and superficial infections, despite established classification systems like the University of Texas and WIfI 10 , remains a subject of debate. Empiric antibiotic therapy was common (87.5% of cases), with piperacillin-tazobactam being the most frequently used (23.5%), consistent with our prior findings (21.3%). However, amoxicillin-clavulanate use decreased substantially (from 15.2–2.87%), while empiric vancomycin use increased significantly (from 3.6–16.62%). Carbapenem use also increased (from 11.2–19.48%). This increased reliance on broad-spectrum intravenous antibiotics may reflect a perceived increase in antibiotic resistance and the treatment of more severe infections, particularly during the COVID-19 pandemic. The rising resistance, including ESBL- and carbapenemase-producing organisms, may warrant broader empiric coverage pending cultures in severe presentations. This could potentially lead to prolonged periods of inadequate pathogen coverage and greater reliance on last-resort antibiotics (colistin), which are associated with significant side effects. It is important to acknowledge the limitations of our approach, both in terms of data collection and study design. As a monocentric, retrospective analysis, our findings rely on patient records that were sometimes incomplete. Additional data, such as diabetes type, diabetes duration, hospitalization length, revascularization attempts (both open and endovascular techniques), ulcer size and number, depth of amputations (e.g., toe vs. ankle), outpatient follow-up efforts, and the inclusion of fungal culture results, as well as an increased number of patients would have strengthened our analysis and provided a more comprehensive understanding of the factors influencing diabetic foot infections. 5 Conclusion Diabetic foot infections (DFIs) represent a serious complication of chronic, poorly controlled diabetes mellitus, often associated with multiple cardiovascular risk factors and both microvascular and macrovascular complications. They significantly reduce life expectancy due to high rates of complications and recurrence. In our study, we observed a concerning rise in antibiotic resistance, particularly among Gram-negative bacteria. Empiric antibiotic therapy was noted to be more aggressive, with increased use of broad-spectrum agents, yet often inadequate when compared to the resistance profiles of the isolated pathogens. The presence of increased peripheral arterial disease and diabetic neuropathy was notably associated with deep infections. These findings reinforce the importance of early detection and routine follow-up in the prevention of diabetic foot ulcers and infections. Regular foot examinations—ideally performed annually—and consistent blood glucose monitoring are effective, cost-saving strategies that play a critical role in preventing long-term diabetic complications. Abbreviations Diabetes Mellitus DM Diabetic foot ulcer DFU Diabetic foot infection DFI International Working Group on the Diabetic Foot IWGDF Methicillin-resistant Staphylococcus aureus MRSA Methicillin-sensitive Staphylococcus aureus MSSA Extended-spectrum beta-lactamase-producing ESBL Vancomycin-Resistant Enterococcus VRE Clinical and Laboratory Standards Institute CLSI Trimethoprim-sulfamethoxazole TMP-SMX peripheral arterial disease PAD Gram-negative GN Declarations Conflict of Interest The authors, Roy Saade and Jacques Choucair, declare no potential conflicts of interest concerning the research, authorship, and publication of this article. Funding No funding was received for research, authorship, and publication of this article. Authors’ contributions Roy Saade: Data gathering, Data Analysis, writing initial draft, writing final manuscript. Acknowledgment We would like to express our gratitude to the Center for Clinical Research at Hôtel-Dieu de France Hospital, Beirut, and its director, Dr. Maissa Safieddine, for their valuable support in conducting the statistical analysis for this study. Availability of Data and Materials The raw data supporting the conclusions of this article will be made available by the authors without undue reservation. References Hossain MJ, Md A-M, Islam MR (2024) Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused. Health Sci Rep 7(3):e2004. 10.1002/hsr2.2004 Namazi N, Moghaddam SS, Esmaeili S et al (2024) Burden of type 2 diabetes mellitus and its risk factors in North Africa and the Middle East, 1990–2019: findings from the Global Burden of Disease study 2019. 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Germs 11(4):570–582. 10.18683/germs.2021.1292 Alkhatieb M, Alrayiqi R, Alsulami OA, Albassam ZM, Wali SM, Alnahdi H (2022) Common Pathogens Isolated from Infected Diabetic Foot Ulcers at King Abdulaziz University Hospital, Saudi Arabia: A Retrospective Study. J Med Res Surg 3(4):71–78. 10.52916/jmrs224084 Charles PGP, Uçkay I, Kressmann B, Emonet S, Lipsky BA (2015) The role of anaerobes in diabetic foot infections. Anaerobe 34:8–13. 10.1016/j.anaerobe.2015.03.009 Villa F, Marchandin H, Lavigne JP et al (2024) Anaerobes in diabetic foot infections: pathophysiology, epidemiology, virulence, and management. Schuetz AN, ed. Clin Microbiol Rev . ;37(3):e00143-23. 10.1128/cmr.00143-23 Coşkun B, Ayhan M, Ulusoy S, Guner R (2024) Bacterial Profile and Antimicrobial Resistance Patterns of Diabetic Foot Infections in a Major Research Hospital of Turkey. Antibiotics 13(7):599. 10.3390/antibiotics13070599 Matta-Gutiérrez G, García-Morales E, García-Álvarez Y, Álvaro-Afonso FJ, Molines-Barroso RJ, Lázaro-Martínez JL (2021) The Influence of Multidrug-Resistant Bacteria on Clinical Outcomes of Diabetic Foot Ulcers: A Systematic Review. J Clin Med 10(9):1948. 10.3390/jcm10091948 Moya-Salazar J, Chamana JM, Porras-Rivera D, Goicochea-Palomino EA, Salazar CR, Contreras-Pulache H (2023) Increase in antibiotic resistance in diabetic foot infections among peruvian patients: a single-center cross-sectional study. Front Endocrinol 14:1267699. 10.3389/fendo.2023.1267699 Rizk MN, Ameen AI (2013) Comorbidities associated with Egyptian diabetic foot disease subtypes. Egypt J Intern Med 25(3):154–158. 10.7123/01.EJIM.0000432184.51306.20 Department of Surgery, Government Medical College, Kozhikode, Kerala, India, Valappil RK (2017) Multidrug Resistant Organisms in Diabetic Foot Ulcers-Analysis of Risk Factors and Clinical Outcome. J Med Sci Clin Res . ;05(02):18138–18183. 10.18535/jmscr/v5i2.144 Rossel A, Lebowitz D, Gariani K et al (2019) Stopping antibiotics after surgical amputation in diabetic foot and ankle infections-A daily practice cohort. Endocrinol Diabetes Metab 2(2):e00059. 10.1002/edm2.59 Pardhan S, Islam MS, López-Sánchez GF, Upadhyaya T, Sapkota RP (2021) Self-isolation negatively impacts self-management of diabetes during the coronavirus (COVID-19) pandemic. Diabetol Metab Syndr 13(1):123. 10.1186/s13098-021-00734-4 Wasnik RN, Marupuru S, Mohammed ZA, Rodrigues GS, Miraj SS (2019) Evaluation of antimicrobial therapy and patient adherence in diabetic foot infections. Clin Epidemiol Glob Health 7(3):283–287. 10.1016/j.cegh.2018.10.005 Tables Table 1: General Demographic Data of Patients Diagnosed with DFIs Category Women (n=63, 26.25%) Men (n=177, 73.75%) Total (n=240) Age 80 24 (38.10%) 12 (6.78%) 36 (15.00%) Risk Factors HBA1c > 7% 35 (55.56%) 123 (69.49%) 158 (65.83%) Hypertension 59 (93.65%) 170 (96.05%) 229 (95.42%) Hypercholesterolemia 45 (71.43%) 123 (69.49%) 168 (70.00%) Smoking 14 (22.22%) 75 (42.37%) 89 (37.08%) Comorbidities Neuropathy 32 (50.79%) 123 (69.49%) 155 (64.58%) Nephropathy 33 (52.38%) 129 (72.88%) 162 (67.50%) Coronary Artery Disease 31 (49.21%) 129 (72.88%) 160 (66.67%) Peripheral Arterial Disease 40 (63.49%) 138 (77.97%) 178 (74.17%) Table 2: Bacterial profile of DFIs Bacterial Group or Type Percentage of Positive Cultures Number of Cases (n=318) Percentage within Enterobacterales (if applicable) Gram Negative Bacteria 68.2 217 Gram Positive Bacteria 31.7 101 Major Bacteria Families Gram Negative Bacteria (excluding Pseudomonas) 54.4 173 Enterobacterales 51.76 164 Pseudomonas 13.8 44 Enterococcus 8.17 26 Staphylococcus 20.75 66 Other Gram + 2.83 9 Specific Gram Negative Bacteria E. coli 16.35 52 32.1% Proteus 9.11 29 17.9% Klebsiella 7.54 24 14.8% Enterobacter 7.23 23 14.1% Morganella 4.71 15 9.25% Citrobacter 3.14 10 6.17% Serratia 1.57 5 3.1% Providencia 1.49 4 2.4% Stenotrophomonas 1.57 5 Bacteroides 1.49 4 Acinetobacter 0.62 2 Table 3: Antibiotic Resistance Profile of Bacteria Involved in DFIs Bacteria MRSA VRE ESBL Carbapenemase Fluoroquinolone Resistance TMP-SMX Resistance Staphylococcus Aureus (n=62) 17 (27.42%) Enterococcus Faecium (n=6) 3 (50%) Enterococcus Faecalis (n=20) 0 (0%) Gram Negative Bacilli (excluding Pseudomonas) 65 (37.57%) 16 (9.24%) 91 (52.6%) 79 (45.66%) Pseudomonas 14 (31.82%) 22 (50%) Table 4: Empiric Antibiotic in the treatment of DFIs Antibiotic Count Percentage (%) Total 349 100 Piperacillin-tazobactam 82 23.5 Vancomycin 58 16.62 Meropenem 42 12.03 Teicoplanin 28 8.02 Imipenem-Cilastatin 26 7.45 Tigecycline 22 6.3 Amikacin 16 4.58 Ciprofloxacin 14 4.01 Clindamycin 12 3.44 Linezolid 11 3.15 Amoxicillin/clavulanate 10 2.87 Colistin 7 2.01 Ceftazidime/Avibactam 5 1.43 Metronidazole 4 1.15 Ceftaroline 4 1.15 Ceftriaxone 4 1.15 Cefepime 2 0.57 TMP-SMX 1 0.29 Cefazoline 1 0.29 Table 5: Comorbidities and Risk Factors in Patients with Deep vs. Superficial DFIs Variable Deep (n=186) Superficial (n=49) p-value Diabetic Neuropathy 134 (72.04%) 18 (36.73%) 7%) 127 (68.28%) 29 (59.18%) 0.303 Peripheral Arterial Disease (PAD) 155 (83.33%) 23 (46.94%) <0.001 Smoking 75 (40.32%) 14 (28.57%) 0.179 Coronary Artery Disease 130 (69.89%) 29 (59.18%) 0.210 Hypercholesterolemia 129 (69.35%) 36 (73.47%) 0.700 Dialysis 37 (19.89%) 5 (10.20%) 0.179 Number of Germs (Mean ± SD) 1.59 ± 0.79 1.37 ± 0.58 0.001 Germ Type: GN Bacilli (excluding Pseudomonas) 119 (63.98%) 26 (53.06%) 0.2174 Germ Type: Pseudomonas 36 (19.35%) 10 (20.41%) 1.0 Germ Type: Enterococcus 22 (11.83%) 2 (4.08%) 0.1842 Germ Type: Staphylococcus 57 (30.65%) 14 (28.57%) 0.9153 Germ Type: Other Gram + 8 (4.30%) 3 (6.12%) 0.8753 GN Bacilli (excluding Pseudomonas): ESBL 58 (41.43%) 6 (21.43%) 0.0136 GN Bacilli (excluding Pseudomonas): Carbapenemase 14 (10.00%) 1 (3.57%) 0.285 Table 6: Comparative Bacterial Profile and Resistance Pattern of DFIs in Studies from Lebanon and Abroad. DFI Studies HDF 2017-2024 HDF 2000-2011 [14] AUBMC 2008-2017 [15] 5-Center Study 2015-2016 [13] Middle East Meta-analysis [22] Global Meta-analysis [12] Polybacterial Infections 42.20% 52.26% 54% 38% 53% 58.90% Enterobacterales 51.76% 40.99% 42% 46.15% 34% N/A Pseudomonas 13.80% 19.15% 11% 12.60% 10% 9.90% Enterococci 8.17% 13.19% 14% 6.04% 8% 7.10% Staphylococci 20.70% 11.06% 9% 18.60% 20% 21.30% MRSA/All Staphylococci 28.78% 29.40% 50% 17.60% 36.16% 18% ESBL Enterobacterales 37.57% 16.30% 17.40% N/A N/A 11-53% Carbapenemase Enterobacterales 9.24% N/A 1.50% N/A N/A N/A Fluoroquinolone-Resistant Enterobacterales 52.60% 39.13% 37.12% 51.40% N/A N/A Pseudomonas Carbapenemase 31.82% N/A 2.90% N/A N/A N/A Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7391175","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501431122,"identity":"834f8e2a-1146-4380-9410-cf7cf5b7e348","order_by":0,"name":"Roy Saade","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYPACZgZ+EPWAgcGAeC2SDQyMDQkkaTE4QKwW8/Ye4w8/aqzljI/3mD9IqLAxZmA/fHQDPi0yZ86YSfYcSzc2O3PGsCHhTJoZA09a2g18WiQkcoCK2A4nbruRY9iQ2HbYhkGCx4yQFuOPf/4drt88gwQtBtK8bYcTDCQgWswIa+E5ViYt25duOOPMscIZQL8YsxH0C3vz5o9vvlnL87c3b/jwocLGsJ/98DG8WhgYONBigg2/chBgf0BYzSgYBaNgFIxsAABO0UkKqsvbeAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0009-1077-3406","institution":"Saint Joseph University","correspondingAuthor":true,"prefix":"","firstName":"Roy","middleName":"","lastName":"Saade","suffix":""},{"id":501431123,"identity":"b84b05db-6346-4418-b845-589a14c8885a","order_by":1,"name":"Jacques Choucair","email":"","orcid":"","institution":"Saint Joseph University","correspondingAuthor":false,"prefix":"","firstName":"Jacques","middleName":"","lastName":"Choucair","suffix":""}],"badges":[],"createdAt":"2025-08-17 08:12:57","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7391175/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7391175/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89354077,"identity":"d7a9f8cb-6a19-40d2-9da3-74a23eaa3b67","added_by":"auto","created_at":"2025-08-19 06:58:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":845921,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7391175/v1/40704cc1-1537-4ad1-ae1d-0b591fab967f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBacteriological Profile and Antibiotic Resistance Patterns in Diabetic Foot Infections: A Monocentric Tertiary Care Study in Lebanon (2017–2024)\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eDiabetes mellitus (DM) is a major global public health concern, affecting approximately 540\u0026nbsp;million individuals worldwide, with 240\u0026nbsp;million remaining undiagnosed and untreated \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The burden of DM is particularly significant in the Middle East and North Africa, which has the single highest age-standardized prevalence globally, estimated at 12.2% (55\u0026nbsp;million cases) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In Lebanon, the lack of comprehensive national data collection hampers the accurate assessment of DM prevalence. However, estimates range from 8.9% (400,000 cases), according to the International Diabetes Federation (IDF) \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, to 15\u0026ndash;17% in more recent studies \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eChronic DM frequently leads to microvascular and macrovascular complications, as well as peripheral neuropathy, immune dysfunction, and metabolic disturbances. These factors contribute to accelerated breakdown of the skin and deeper tissues of the feet, often resulting in deformities and ulceration in up to 20% of patients \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Ulcers, many of which remain unrecognized, can progress to infections in as many as 40% of cases \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDiabetic foot infections (DFIs) impose a significant burden on patients, encompassing increased healthcare costs, frequent hospitalizations \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, reduced quality of life, and complications such as foot deformities, lower extremity amputations, recurrent infections, and increased mortality \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Frequent foot examinations and close patient follow-up \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e are essential for early intervention and improved prognosis.\u003c/p\u003e\u003cp\u003eSeveral classification systems have been developed to standardize the evaluation of DFIs, focusing on factors such as infection depth, bone involvement, and systemic manifestations. These include the Meggitt-Wagner system, the University of Texas classification, and the Wound, Ischemia, and Foot Infection (WIfI) system \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. More recently, the International Working Group on the Diabetic Foot (IWGDF) introduced a four-grade classification system, ranging from 1 to 4 in order of increasing severity, accompanied by recommendations for effective diagnosis and treatment \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eProfiling the bacteria responsible for DFIs has gained importance amid the global rise in antibiotic resistance. DFIs commonly involve a range of bacteria, including Gram-positive organisms such as \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u0026mdash;the most frequently implicated worldwide\u0026mdash;and \u003cem\u003eEnterococcus\u003c/em\u003e, as well as Gram-negative bacilli like \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eEnterobacterales\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The emergence of methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA), vancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e (VRE), and extended-spectrum beta-lactamase-producing (ESBL) Gram-negative bacteria is alarming. This underscores the need for studies tracking resistance profiles both nationally and regionally.\u003c/p\u003e\u003cp\u003eTo date, only three studies \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e have been published on the bacteriological resistance patterns of DFIs in Lebanon, including one \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e from the same tertiary care center as this study. A single one \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e was multicentric.\u003c/p\u003e"},{"header":"2 Material and methods","content":"\u003cp\u003eThis retrospective study analyzed all patients diagnosed with diabetic foot infections (DFI) admitted to H\u0026ocirc;tel-Dieu de France Hospital, Beirut, between January 2017 and July 2024. Included were diabetics aged 18 years or older with confirmed DFIs requiring inpatient care. Exclusion criteria included prediabetic patients, patients diagnosed or treated exclusively in an outpatient setting, cases with insufficient samples for culture, and those with incomplete medical records that hindered disease categorization. Diagnosis of diabetic foot infections was based on clinical and radiological signs, with imaging (e.g., X-rays or MRI) used for suspected osteomyelitis.\u003c/p\u003e\u003cp\u003eDebridement of tissue was performed following established surgical principles \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, ensuring the excision of all necrotic and devitalized tissues. For cases involving osteomyelitis, limited amputations were performed when necessary. Infected wounds were left open to heal by secondary intention. Resected tissues were sent to the laboratory for histopathological analysis and aerobic and anaerobic cultures. Fungal cultures were not included in this study.\u003c/p\u003e\u003cp\u003eAll specimens were processed following the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Tissue samples were cultured on blood agar, MacConkey agar, Columbia Nalidixic Acid (CAN) agar, and sch\u0026auml;dler agar for anaerobic identification. They were incubated at 37\u0026deg;C. Gram staining was performed for the preliminary classification of bacterial isolates.\u003c/p\u003e\u003cp\u003eAntibiotic susceptibility testing was conducted using either the Kirby-Bauer disk diffusion method, with results interpreted according to EUCAST breakpoints, or the Pheonix BD automated identification system.\u003c/p\u003e\u003cp\u003eThe tested antibiotic panel included penicillins (ampicillin, amoxicillin-clavulanate, piperacillin, and piperacillin-tazobactam), cephalosporins (cephalexin, cefotaxime, cefixime, cefepime, and ceftazidime-avibactam or ceftolozane-tazobactam when necessary), and carbapenems (ertapenem, imipenem, and meropenem). Additional antibiotics tested included vancomycin, aminoglycosides, and colistin (when necessary). Fluoroquinolones (e.g., ciprofloxacin) and trimethoprim-sulfamethoxazole (TMP-SMX) were also evaluated for outpatient oral antibiotic therapy.\u003c/p\u003e\u003cp\u003eBacteria were classified as either Gram-positive species, with special consideration for \u003cem\u003eStaphylococcus\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e, or Gram-negative species, further subdivided into the \u003cem\u003eEnterobacterales\u003c/em\u003e order and \u003cem\u003ePseudomonas\u003c/em\u003e species. \u003cem\u003eStaphylococcus\u003c/em\u003e isolates were categorized as methicillin-sensitive (MSSA) or methicillin-resistant (MRSA), while \u003cem\u003eEnterococcus\u003c/em\u003e isolates were identified as vancomycin-resistant (VRE) following molecular confirmation when necessary. For \u003cem\u003eEnterobacterales\u003c/em\u003e, resistance was classified as penicillinase-producing, cephalosporinase-producing, carbapenem-sensitive extended-spectrum beta-lactamase (ESBL)-producing, or carbapenemase-producing strains (CRE). \u003cem\u003ePseudomonas\u003c/em\u003e isolates were further analyzed for resistance to piperacillin-tazobactam, imipenem, and fluoroquinolones.\u003c/p\u003e\u003cp\u003ePatient data was collected from electronic medical records, anonymized using patient-specific electronic codes, and transcribed into Excel for statistical analysis. Extracted variables included demographic information (e.g., sex and age during infection diagnosis), cardiovascular risk factors, diabetic complications, and comorbidities.\u003c/p\u003e\u003cp\u003eEthical approval for the study was obtained from the Institutional Review Board of H\u0026ocirc;tel-Dieu de France Hospital. Statistical analyses were conducted using R software (version 4.1.3), with the prettyR and Tableone packages. Descriptive statistics summarized patient characteristics, with continuous variables expressed as means (\u0026plusmn;\u0026thinsp;standard deviation) and categorical variables as counts and percentages. Stratified analyses compared subgroups, with the Student\u0026rsquo;s t-test applied to quantitative variables and the Chi-square test used for categorical variables, provided conditions for validity were met. Statistical significance was set at \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e.\u003c/p\u003e\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003ePatient Demographics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eA total of 240 DFIs were included in the analysis, involving 152 unique patients. Among these, 50 patients experienced recurrent infections, resulting in multiple hospital admissions, with an average of 2.78 readmissions per patient. Notably, readmissions for DFI were classified as separate events only if the time between discharge and readmission exceeded one month.\u003c/p\u003e\n\u003cp\u003eThe mean age at diagnosis was 68.33 years. Men represented most cases (73.75%, n\u0026thinsp;=\u0026thinsp;178), with a mean age of 66.61 years (range 42\u0026ndash;91, SD 9.54). Women accounted for 26.25% of cases (n\u0026thinsp;=\u0026thinsp;63), with a mean age of 73.21 years (range 36\u0026ndash;100, SD 14.32). Most patients (62.50%) were between 60 and 80 years old. Notably, only one woman under 40 was treated for a DFI. In patients over 80, women outnumbered men 2:1 (24 vs. 12), comprising over a third (38.10%) of all hospitalized women.\u003c/p\u003e\n\u003cp\u003eThe majority of patients (65.83%) had poorly controlled diabetes (HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7%). A high proportion (95.42%) had hypertension or were taking antihypertensive medication (ACE inhibitor, ARB, diuretics\u0026hellip;). Dyslipidemia was present in 70% of patients, while 37.08% were current smokers. Common comorbidities included diabetic neuropathy (64.58%), chronic kidney disease (67.50%), and peripheral arterial disease (74.17%). 66.67% underwent coronary artery bypass grafting or percutaneous angioplasty and/or stenting for coronary artery disease.\u003c/p\u003e\n\u003cp\u003eCompared to women, men were more likely to have poorly controlled diabetes (69.49% vs. 55.56%) and to smoke (42.37% vs. 22.22%). Hypertension and hypercholesterolemia rates were similar between the sexes (96.05% vs. 93.65% and 69.49% vs. 71.43%, respectively). Men exhibited higher rates of all measured diabetic comorbidities.\u003c/p\u003e\n\u003cp\u003eData regarding diabetes duration and type, pack-years of smoking, length of hospitalization, revascularization procedures, and other comorbidities (e.g., diabetic retinopathy, stroke) were inconsistently documented or insufficient for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacteriological profile\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eOf 240 DFIs analyzed, 318 distinct bacterial isolates were identified through standard laboratory culture, yielding an average of 1.32 bacteria per patient. Of particular interest, only 42.2% of patients showed polymicrobial infections.\u003c/p\u003e\n\u003cp\u003eGram-negative bacteria comprised the majority of isolates (68.2%), while Gram-positive bacteria accounted for 31.2%. \u003cem\u003eEnterobacterales\u003c/em\u003e were the most prevalent (51.76% of isolates, n\u0026thinsp;=\u0026thinsp;164), followed by Pseudomonas species (13.83%, n\u0026thinsp;=\u0026thinsp;44). Overall, 71.5% of positive cultures contained at least one Gram-negative bacterium, and 42.9% contained at least one Gram-positive bacterium. Among Gram-positive isolates, Staphylococcus species were most frequent (20.75%, n\u0026thinsp;=\u0026thinsp;70), followed by Enterococcus species (8.17%, n\u0026thinsp;=\u0026thinsp;26). Streptococcus species constituted only 2% of Gram-positive isolates.\u003c/p\u003e\n\u003cp\u003eWithin the \u003cem\u003eEnterobacterales\u003c/em\u003e order, Escherichia coli was the most common (32.1% of \u003cem\u003eEnterobacterales\u003c/em\u003e isolates, n\u0026thinsp;=\u0026thinsp;52), followed by Proteus (17.9%), Klebsiella (14.8%), Enterobacter (14.1%), Morganella (9.25%), and Citrobacter (6.17%). Other \u003cem\u003eEnterobacterales\u003c/em\u003e (e.g., Serratia, Providencia) and other Gram-negative genera (e.g., Stenotrophomonas, Bacteroides, Acinetobacter) were present in smaller numbers.\u003c/p\u003e\n\u003cp\u003eDespite the overall predominance of Gram-negative \u003cem\u003eEnterobacterales\u003c/em\u003e, Staphylococcus species were the single most frequently isolated group, followed by E. coli and then Pseudomonas species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResistance profile\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eResistance profiles were evaluated for the most prominent bacterial groups.\u003c/p\u003e\n\u003cp\u003eAmong \u003cem\u003eStaphylococcus aureus\u003c/em\u003e species, methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA) was identified in 17 out of 62 cases, accounting for 27.42%. In \u003cem\u003eEnterococcus faecium\u003c/em\u003e isolates, vancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e (VRE) was detected in 3 cases (50%).\u003c/p\u003e\n\u003cp\u003ePseudomonas species, representing 13.83% of all isolates, exhibited notable resistance patterns. Resistance to piperacillin-tazobactam was observed in 31.82% of \u003cem\u003ePseudomonas\u003c/em\u003e isolates (n\u0026thinsp;=\u0026thinsp;14/44), with similar rates observed for carbapenems. All carbapenemase-producing \u003cem\u003ePseudomonas\u003c/em\u003e isolates, however, remained susceptible to colistin. Fluoroquinolone resistance was high (50%), with an additional 7.15% demonstrating intermediate susceptibility, limiting the potential for oral outpatient therapy.\u003c/p\u003e\n\u003cp\u003eAmong other Gram-negative bacilli, 37.57% produced carbapenem-sensitive extended-spectrum beta-lactamases (ESBLs), and 9.24% produced carbapenemases, totaling 46.81% of these isolates. Penicillinase enzymes were expressed by 38.72% of isolates, and cephalosporinase enzymes by 9.24%. Resistance to oral outpatient antibiotics was also prevalent in this group, with 52.6% resistant to fluoroquinolones and 45.66% resistant to trimethoprim-sulfamethoxazole (TMP-SMX). An additional 3.46% of isolates showed intermediate susceptibility to fluoroquinolones.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibiotic Use\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Table 4)\u003c/p\u003e\n\u003cp\u003eAntibiotics were routinely used, as empiric therapy was administered to 87.5% of DFI patients (n\u0026thinsp;=\u0026thinsp;210), with 58.1% receiving combination therapy. Across the 240 DFIs, 349 antibiotic prescriptions were recorded, averaging 1.45 antibiotics per admitted patient.\u003c/p\u003e\n\u003cp\u003ePiperacillin-tazobactam was the most frequently used empiric antibiotic, prescribed in 23.5% of cases, often as monotherapy or in combination with vancomycin (16.02%). These were followed by meropenem (12%), teicoplanin (8%), and imipenem-cilastatin (7.45%). Less frequently used antibiotics, such as linezolid, metronidazole, and clindamycin, were typically reserved for patients with prior infections and known antibiograms to guide therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfection severity and comorbidities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Table 5)\u003c/p\u003e\n\u003cp\u003eDFIs were classified as either deep-tissue (n\u0026thinsp;=\u0026thinsp;186, 79.1%) or soft-tissue (n\u0026thinsp;=\u0026thinsp;49, 20.9%) infections, based on the IWGDF classification system (grade 3\u0026ndash;4 vs grade 2). Since ulcer size and depth could not be consistently assessed across all records, deep-tissue infections were defined by the presence of at least one of the following criteria: radiologically confirmed osteomyelitis, bone amputation at any level, septic shock, or death attributable to the infection.\u003c/p\u003e\n\u003cp\u003eThe mortality rate was 5.83% (n\u0026thinsp;=\u0026thinsp;14), while amputations were performed in 28.3% of cases (n\u0026thinsp;=\u0026thinsp;68).\u003c/p\u003e\n\u003cp\u003eWhile most cardiovascular risk factors and diabetic comorbidities were similar between the two groups, diabetic neuropathy and peripheral arterial disease (PAD) were significantly more prevalent in the deep-tissue infection group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, diabetic neuropathy was present in 72.04% of deep-tissue infections compared to 36.73% of soft-tissue infections. PAD was observed in 83.33% of deep-tissue infections versus 46.94% of soft-tissue infections.\u003c/p\u003e\n\u003cp\u003eNo significant differences were found between the two groups regarding poor diabetes control (HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7%), smoking rates, or nephropathy (p\u0026thinsp;=\u0026thinsp;0.303, p\u0026thinsp;=\u0026thinsp;0.179, and p\u0026thinsp;=\u0026thinsp;0.324, respectively).\u003c/p\u003e\n\u003cp\u003eThe average number of bacterial isolates was higher in deep-tissue infections (p\u0026thinsp;=\u0026thinsp;0.001), with more ESBL-producing Gram-negatives. No difference was found relating to bacteria type or other resistance profiles.\u003c/p\u003e\n\u003cp\u003eData limitations precluded analysis of factors such as hospital length of stay (LOS) or previous amputations.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003e(Table\u0026nbsp;6)\u003c/p\u003e\u003cp\u003eDFUs carry a 5-year mortality rate between 30 and 50%, comparable to that of cancer, with an even worse prognosis in cases of critical limb ischemia \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. These poor outcomes are largely attributed to the burden of DM comorbidities such as nephropathy and CAD, which significantly complicate patient management \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe present study reveals a high burden of comorbidities and complications among patients hospitalized for diabetic foot infections (DFIs). Notably, 65.8% of patients had poorly controlled DM, 65% had neuropathy, and 74% had peripheral arterial disease (PAD). Hypertension or the use of antihypertensive medication was found in nearly all patients (95.42%). The severity of the infection burden is further underscored by the 32.8% readmission rate (50/152 patients) due to poor disease control.\u003c/p\u003e\u003cp\u003eInterestingly, the prevalence of these comorbidities appears slightly lower than that reported at H\u0026ocirc;tel-Dieu Hospital between 2000 and 2011, where poorly controlled diabetes affected 75.4% of patients, neuropathy 77.8%, and PAD 93.1%. Only 60.38% had arterial hypertension.\u003c/p\u003e\u003cp\u003eThe disparity in hypertension and peripheral arterial disease between both studies could be attributed to several factors. First, in this study, hypertension was defined not only by a previously established diagnosis but also by the use of antihypertensive medications, including ACE inhibitors, which are commonly prescribed for diabetic nephropathy rather than hypertension alone. Second, the observed changes in both categories may reflect improvements in healthcare access, early screening of diabetic comorbidities and complications, and increased patient compliance with medical treatment. Finally, such a change could simply be the result of a changing, older population.\u003c/p\u003e\u003cp\u003eEpidemiological data consistently demonstrate a higher prevalence of DM in men compared to women. However, women are typically diagnosed at an older age (post-60) and tend to experience higher rates of cardiovascular complications \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, possibly due to less stringent follow-up care and later complication onset. Specifically regarding DFIs, men are 1.57 times more likely to be diagnosed and experience higher amputation rates \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur findings regarding sex distribution in diabetic foot infections (DFIs) align with established patterns. Men constituted the majority of cases (73.75%) and predominated in age groups under 80. Women were more prevalent in the over-80 age group, exhibiting a 2:1 female-to-male ratio. Men also presented with a higher overall prevalence of diabetic comorbidities, including both microvascular and macrovascular complications (71.3% vs. 57.3%).\u003c/p\u003e\u003cp\u003eIt has been suggested that the bacteriological profile of DFIs differs between developing and developed countries, with Gram-negative organisms predominating in the former and Gram-positive in the latter. A global meta-analysis \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e found that 62.4% of bacteria in high-income countries were Gram-positive, while 59.6% in lower-income countries were Gram-negative. This difference was statistically significant, with \u003cem\u003eStreptococcus\u003c/em\u003e species more prevalent in high-income countries and \u003cem\u003eKlebsiella\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e more common in lower-income countries.\u003c/p\u003e\u003cp\u003eThe reasons for this variability are not fully understood. A meta-analysis of DFIs in Middle Eastern countries \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e suggested that Gram-negative bacteria are more prevalent in severe, hospitalized infections, while Gram-positive bacteria are more common in superficial, outpatient-treated DFIs. Factors such as delayed care-seeking \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (potentially due to lower awareness), high rates of barefoot walking, and limited access to medical and foot care services suggest that socioeconomic and healthcare accessibility factors may be more influential than purely geographical location \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, Gram-negative bacteria comprised 68.23% of all cultured isolates, with Gram-positive bacteria accounting for the remaining 31.77%. 71.5% of patients had at least one Gram-negative bacterium cultured, while 42.9% had at least one Gram-positive bacterium. Notably, Staphylococcus aureus was the most frequently isolated organism (20%), followed by E. coli (16.3%) and Pseudomonas species (13.8%), consistent with other studies from lower-income countries. These findings contrast with our previous analysis \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, which showed Pseudomonas as the most prevalent organism (19.15%), followed by E. coli (11.9%) and S. aureus (11.1%), but align with other studies in Lebanon \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and neighboring countries, including Jordan \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, Egypt \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and Saudi Arabia \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eInterestingly, 42.2% of infections in this study were polybacterial, representing a decrease from the 52.26% reported in our earlier analysis \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Other studies in Lebanon have shown varied rates, including 54% \u003csup\u003e15\u003c/sup\u003e and 38% \u003csup\u003e13\u003c/sup\u003e, while a global meta-analysis \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e reported a higher prevalence of 58.9%.\u003c/p\u003e\u003cp\u003eThe role of anaerobic bacteria in DFIs remains difficult to assess. Older studies suggested an increased presence of anaerobes in deep DFIs, particularly those associated with severe peripheral arterial disease (PAD) \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, research has primarily focused on aerobic Gram-positive and Gram-negative bacteria due to their predominance in cultures. A 2015 study \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e highlighted inconsistencies in the literature but reported an average anaerobic pathogen prevalence of 11% across analyzed studies. A more recent (2020) study using PCR-based genomic analysis \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e demonstrated a much higher prevalence of anaerobes, detecting Prevotella and Bacteroides species in 93% and 70% of cultures, respectively, compared to conventional methods.\u003c/p\u003e\u003cp\u003eIn our study, anaerobic bacteria were isolated in only 1.5% of cases, highlighting the limitations of standard culture techniques for detecting these organisms.\u003c/p\u003e\u003cp\u003eThe most striking finding of this study is the substantial increase in multidrug-resistant organisms, especially Gram-negative bacteria, compared to our previous work. Among \u003cem\u003eEnterobacterales\u003c/em\u003e, nearly half (46.81%) were either ESBL or carbapenemase-producing, a significant rise from the previously reported 16.3% ESBL rate, where cephalosporinase-producing species predominated (41.3%). Fluoroquinolone resistance also increased from 39.13\u0026ndash;52.6%, while TMP-SMX resistance remained relatively stable (47.83% vs. 45.66%). Pseudomonas species exhibited increased carbapenem resistance (25.9\u0026ndash;31.8%).\u003c/p\u003e\u003cp\u003eMethicillin resistance among \u003cem\u003eStaphylococcus\u003c/em\u003e species remained consistent (27.42% vs. 28.78%). Vancomycin resistance among \u003cem\u003eEnterococcus faecium\u003c/em\u003e isolates was 50% (3/6). Comparative data from our previous study are unavailable.\u003c/p\u003e\u003cp\u003eMultiple recent studies \u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e have reported increased bacterial resistance in diabetic foot ulcers, with several contributing factors identified. One significant factor is prolonged antibiotic therapy. Patients with severe diabetic foot infections often present with comorbid neuropathy and peripheral arteriopathy \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, as observed in this study, along with structural foot deformities. These factors predispose patients to poor foot care, chronic ulceration, and frequent ulcer recurrence, all of which can lead to increased antibiotic use \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAdditionally, antibiotic therapy for DFIs tends to be prolonged. Soft tissue infections typically require 1\u0026ndash;2 weeks of treatment, which is often extended for slow-healing ulcers \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. A 5\u0026ndash;6 week course is generally recommended for osteomyelitis, although amputation of infected bone with clear margins can reduce the duration to 1 week \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. However, patients are often reluctant to undergo such procedures.\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic has also been proposed as a contributing factor to poor wound care \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Between 2020 and 2023, many patients avoided hospital admissions, often presenting with more severe infections and systemic manifestations. Stress-related dietary changes during this period also likely worsened glycemic control, contributing to higher infection rates and delayed wound healing \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Other factors, such as poor medication compliance \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, may have also played a role.\u003c/p\u003e\u003cp\u003eWhile showing a statistically significantly higher bacterial load compared to superficial infections, deep infections were associated with a greater prevalence of extended-spectrum beta-lactamase (ESBL)-producing Gram-negative bacteria (p\u0026thinsp;=\u0026thinsp;0.0136). No other significant differences in bacterial type or resistance profiles were observed between the two groups, nor were rates of poorly controlled diabetes (59% in superficial vs. 68% in deep infections, p\u0026thinsp;=\u0026thinsp;0.30). Furthermore, patients with deep infections had a higher prevalence of both diabetic neuropathy and peripheral arterial disease (PAD), with no evidence of higher incidence in other diabetic microvascular complications (e.g., nephropathy).\u003c/p\u003e\u003cp\u003eThese findings suggest that infection severity correlates with both higher bacterial burden and more resistant strains. Contrary to a previous meta-analysis \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, this study found no significant difference in Gram staining between deep and superficial infections, which is plausible in a uniformly severe (IWGDF 3\u0026ndash;4) inpatient cohort. The distinction between deep and superficial infections, despite established classification systems like the University of Texas and WIfI \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, remains a subject of debate.\u003c/p\u003e\u003cp\u003eEmpiric antibiotic therapy was common (87.5% of cases), with piperacillin-tazobactam being the most frequently used (23.5%), consistent with our prior findings (21.3%). However, amoxicillin-clavulanate use decreased substantially (from 15.2\u0026ndash;2.87%), while empiric vancomycin use increased significantly (from 3.6\u0026ndash;16.62%). Carbapenem use also increased (from 11.2\u0026ndash;19.48%).\u003c/p\u003e\u003cp\u003eThis increased reliance on broad-spectrum intravenous antibiotics may reflect a perceived increase in antibiotic resistance and the treatment of more severe infections, particularly during the COVID-19 pandemic. The rising resistance, including ESBL- and carbapenemase-producing organisms, may warrant broader empiric coverage pending cultures in severe presentations. This could potentially lead to prolonged periods of inadequate pathogen coverage and greater reliance on last-resort antibiotics (colistin), which are associated with significant side effects.\u003c/p\u003e\u003cp\u003eIt is important to acknowledge the limitations of our approach, both in terms of data collection and study design. As a monocentric, retrospective analysis, our findings rely on patient records that were sometimes incomplete. Additional data, such as diabetes type, diabetes duration, hospitalization length, revascularization attempts (both open and endovascular techniques), ulcer size and number, depth of amputations (e.g., toe vs. ankle), outpatient follow-up efforts, and the inclusion of fungal culture results, as well as an increased number of patients would have strengthened our analysis and provided a more comprehensive understanding of the factors influencing diabetic foot infections.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eDiabetic foot infections (DFIs) represent a serious complication of chronic, poorly controlled diabetes mellitus, often associated with multiple cardiovascular risk factors and both microvascular and macrovascular complications. They significantly reduce life expectancy due to high rates of complications and recurrence.\u003c/p\u003e\u003cp\u003eIn our study, we observed a concerning rise in antibiotic resistance, particularly among Gram-negative bacteria. Empiric antibiotic therapy was noted to be more aggressive, with increased use of broad-spectrum agents, yet often inadequate when compared to the resistance profiles of the isolated pathogens.\u003c/p\u003e\u003cp\u003eThe presence of increased peripheral arterial disease and diabetic neuropathy was notably associated with deep infections. These findings reinforce the importance of early detection and routine follow-up in the prevention of diabetic foot ulcers and infections. Regular foot examinations\u0026mdash;ideally performed annually\u0026mdash;and consistent blood glucose monitoring are effective, cost-saving strategies that play a critical role in preventing long-term diabetic complications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDiabetes Mellitus\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDiabetic foot ulcer\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDFU\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDiabetic foot infection\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDFI\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eInternational Working Group on the Diabetic Foot\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIWGDF\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMethicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMRSA\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMethicillin-sensitive \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMSSA\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eExtended-spectrum beta-lactamase-producing\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eESBL\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVancomycin-Resistant Enterococcus\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVRE\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eClinical and Laboratory Standards Institute\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCLSI\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTrimethoprim-sulfamethoxazole\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTMP-SMX\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eperipheral arterial disease\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePAD\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGram-negative\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGN\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors, Roy Saade and Jacques Choucair, declare no potential conflicts of interest concerning the research, authorship, and publication of this article.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNo funding was received for research, authorship, and publication of this article.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eRoy Saade: Data gathering, Data Analysis, writing initial draft, writing final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgment\u003c/h2\u003e\n\u003cp\u003eWe would like to express our gratitude to the Center for Clinical Research at H\u0026ocirc;tel-Dieu de France Hospital, Beirut, and its director, Dr. Maissa Safieddine, for their valuable support in conducting the statistical analysis for this study.\u003c/p\u003e\n\u003ch2\u003eAvailability of Data and Materials\u003c/h2\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors without undue reservation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHossain MJ, Md A-M, Islam MR (2024) Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused. 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Clin Epidemiol Glob Health 7(3):283\u0026ndash;287. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cegh.2018.10.005\u003c/span\u003e\u003cspan address=\"10.1016/j.cegh.2018.10.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eGeneral Demographic Data of Patients Diagnosed with DFIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eWomen (n=63, 26.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eMen (n=177, 73.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eTotal (n=240)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026lt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1 (1.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1 (0.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e40-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e11 (17.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e42 (23.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e53 (22.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e60-80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e27 (42.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e123 (69.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e150 (62.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026gt;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e24 (38.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e12 (6.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e36 (15.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eHBA1c \u0026gt; 7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e35 (55.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e123 (69.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e158 (65.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e59 (93.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e170 (96.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e229 (95.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eHypercholesterolemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e45 (71.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e123 (69.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e168 (70.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14 (22.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e75 (42.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e89 (37.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eNeuropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e32 (50.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e123 (69.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e155 (64.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eNephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e33 (52.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e129 (72.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e162 (67.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e31 (49.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e129 (72.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e160 (66.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePeripheral Arterial Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e40 (63.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e138 (77.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e178 (74.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eBacterial profile of DFIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBacterial Group or Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePercentage of Positive Cultures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eNumber of Cases (n=318)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePercentage within \u003cem\u003eEnterobacterales\u0026nbsp;\u003c/em\u003e(if applicable)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGram Negative Bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e68.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGram Positive Bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e31.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajor Bacteria Families\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGram Negative Bacteria (excluding Pseudomonas)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e54.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eEnterobacterales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e51.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePseudomonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eEnterococcus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e8.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eStaphylococcus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e20.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eOther Gram +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecific Gram Negative Bacteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eE. coli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e16.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e32.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eProteus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e9.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e17.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eKlebsiella\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e7.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eEnterobacter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eMorganella\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e9.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eCitrobacter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e6.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eSerratia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eProvidencia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e2.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eStenotrophomonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eBacteroides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eAcinetobacter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eAntibiotic Resistance Profile of Bacteria Involved in DFIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBacteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003eMRSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003eVRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003eESBL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003eCarbapenemase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003eFluoroquinolone Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003eTMP-SMX Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003eStaphylococcus Aureus (n=62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e17 (27.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003eEnterococcus Faecium (n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003e3 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003eEnterococcus Faecalis (n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003eGram Negative Bacilli (excluding Pseudomonas)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003e65 (37.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003e16 (9.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003e91 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e79 (45.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.109%;\"\u003e\n \u003cp\u003ePseudomonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.0577%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9808%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.2244%;\"\u003e\n \u003cp\u003e14 (31.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.9487%;\"\u003e\n \u003cp\u003e22 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.3397%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eEmpiric Antibiotic in the treatment of DFIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003ePiperacillin-tazobactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eVancomycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e16.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eMeropenem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e12.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eTeicoplanin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e8.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eImipenem-Cilastatin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e7.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eTigecycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAmikacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eClindamycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eLinezolid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAmoxicillin/clavulanate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eColistin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCeftazidime/Avibactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eMetronidazole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCeftaroline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCeftriaxone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCefepime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eTMP-SMX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eCefazoline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u0026nbsp;\u003c/strong\u003eComorbidities and Risk Factors in Patients with Deep vs. Superficial DFIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDeep (n=186)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eSuperficial (n=49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDiabetic Neuropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e134 (72.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e18 (36.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDiabetic Nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e130 (69.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e30 (61.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePoor Diabetes Control (HBA1C \u0026gt;7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e127 (68.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e29 (59.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003ePeripheral Arterial Disease (PAD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e155 (83.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e23 (46.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e75 (40.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14 (28.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e130 (69.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e29 (59.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eHypercholesterolemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e129 (69.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e36 (73.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eDialysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e37 (19.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e5 (10.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eNumber of Germs (Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.59 \u0026plusmn; 0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.37 \u0026plusmn; 0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGerm Type: GN Bacilli (excluding Pseudomonas)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e119 (63.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e26 (53.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.2174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGerm Type: Pseudomonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e36 (19.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e10 (20.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGerm Type: Enterococcus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e22 (11.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e2 (4.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.1842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGerm Type: Staphylococcus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e57 (30.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14 (28.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.9153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGerm Type: Other Gram +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e8 (4.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3 (6.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.8753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGN Bacilli (excluding Pseudomonas): ESBL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e58 (41.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e6 (21.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.0136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003eGN Bacilli (excluding Pseudomonas): Carbapenemase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e14 (10.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1 (3.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003eComparative Bacterial Profile and Resistance Pattern of DFIs in Studies from Lebanon and Abroad.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDFI Studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eHDF 2017-2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eHDF 2000-2011 [14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eAUBMC 2008-2017 [15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e5-Center Study 2015-2016 [13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eMiddle East Meta-analysis [22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eGlobal Meta-analysis [12]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003ePolybacterial Infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e42.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e52.26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e58.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e\u003cem\u003eEnterobacterales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e51.76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e40.99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e46.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003ePseudomonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e13.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e19.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e12.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e9.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eEnterococci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e8.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e13.19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e6.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e7.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eStaphylococci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e20.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e11.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e18.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e21.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eMRSA/All Staphylococci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e28.78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e29.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e17.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e36.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e18%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eESBL \u003cem\u003eEnterobacterales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e37.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e16.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e17.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e11-53%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eCarbapenemase \u003cem\u003eEnterobacterales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e9.24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e1.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eFluoroquinolone-Resistant \u003cem\u003eEnterobacterales\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e52.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e39.13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e37.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e51.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003ePseudomonas Carbapenemase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e31.82%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003e2.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.2857%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Saint Joseph University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetic Foot Infection, Osteomyelitis, Bacterial Classification, Antibiotic Resistance, Epidemiology, Lebanon","lastPublishedDoi":"10.21203/rs.3.rs-7391175/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7391175/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDiabetic foot infections (DFIs) are a serious complication of poorly controlled diabetes mellitus (DM), often resulting in significant morbidity, recurrent hospital admissions, and an increased mortality risk. The bacteriological profile and resistance patterns of DFIs vary based on geographical and socio-economic factors, with Gram-negative bacteria more prevalent in humid, lower-income regions, including the Middle East. Data on DFI\u0026rsquo;s microbiological landscape in Lebanon remain limited, with few studies tracking the evolution of antibiotic resistance over time. This retrospective, monocentric study analyzes the bacteriological trends of DFIs in Lebanon over seven years, comparing findings with previously published research from the same center and other national and regional studies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGram-negative bacteria were identified in 68.23% of all DFIs. However, \u003cem\u003eStaphylococcus\u003c/em\u003e species remained the most frequently isolated bacteria, accounting for 20.7% of cases, followed by \u003cem\u003eE. coli\u003c/em\u003e (16.3%) and \u003cem\u003ePseudomonas\u003c/em\u003e species (13.8%). A substantial increase in ESBL-producing \u003cem\u003eEnterobacterales\u003c/em\u003e was observed compared to earlier data from the same center (36.86% vs 16.3% in 2011). Severe diabetic foot infections were also significantly associated with higher rates of diabetic neuropathy and peripheral arterial disease compared to milder infections.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDFI-causing bacteria exhibit increasing resistance to standard oral and parenteral antibiotics. As a result, preventing diabetic foot infections through regular foot assessment, strict glycemic control, and long-term follow-up is crucial in minimizing ulcer formation and subsequent infections.\u003c/p\u003e","manuscriptTitle":"Bacteriological Profile and Antibiotic Resistance Patterns in Diabetic Foot Infections: A Monocentric Tertiary Care Study in Lebanon (2017–2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 06:42:47","doi":"10.21203/rs.3.rs-7391175/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab393a22-4ecb-4bf9-9102-ffde3c137222","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53258953,"name":"Bacteriology"},{"id":53258954,"name":"Cardiac \u0026 Cardiovascular Systems"},{"id":53258955,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2025-08-19T06:42:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 06:42:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7391175","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7391175","identity":"rs-7391175","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}