Characterization of Bacterial Strains Involved in Suppurative Wound Infections and Their Antibiotic Resistance Profiles in Southern Benin

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This study aimed to characterize the bacteriological profile and antibiotic resistance patterns of pathogens isolated from wound suppurations in hospitals in southern Benin. Methods A total of 384 wound swab samples were collected from hospitalized patients in multiple hospitals across southern Benin presenting with clinical signs of suppuration. Bacteriological identification was performed using VITEK automated system. Antibiotic susceptibility testing was conducted via the Kirby-Bauer method. Molecular detection of resistance and virulence genes was performed by PCR. Results Of the 384 wound samples, 326 (84.9%) yielded positive bacterial cultures. The most prevalent pathogens were Staphylococcus aureus (49.39%), Enterococcus faecalis (22.89%), Klebsiella pneumoniae (37.09%), and Escherichia coli (27.41%). The most affected age group was 11–20 years (42.8%), and females were slightly more affected (56.02%). Antibiotic susceptibility testing revealed high levels of resistance to beta-lactams among bacilli, while resistance to carbapenems remained low. Among cocci, high resistance rates were observed for ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%). Statistically significant associations were observed between the presence of resistant bacteria and both wound etiology (p = 0.0013) and diabetic status (p = 0.009). Molecular analysis revealed the presence of blaZ (27.38%) and mecA (13.68%) among Gram-positive cocci, and multiple ESBL-associated genes ( blaCTX-M1, blaSHV, blaOXA-1, blaTEM, blaCTX-M9 ) among Gram-negative bacilli. Conclusion The study highlights a high prevalence of multidrug-resistant bacteria in wound infections, with significant implications for antibiotic stewardship and infection control. Antibiotic resistance Suppurative wound infections Benin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Wound infections represent a significant global public health concern, particularly in low- and middle-income countries where healthcare resources are limited and infection control practices are often inadequate [ 1 ]. These infections commonly arise from surgical procedures, traumatic injuries, or chronic conditions such as diabetes, and are associated with considerable morbidity, prolonged hospitalization, and increased healthcare costs [ 2 ]. Studies have shown that wound infections contribute to 7–10% of nosocomial infections worldwide and are associated with up to 20 additional days of hospitalization and an increased cost of treatment by 300%, representing a substantial economic burden on both patients and healthcare systems [ 3 ].Etiologically, wound infections are polymicrobial in nature, predominantly caused by both Gram-positive cocci such as Staphylococcus aureus and Enterococcus species and Gram-negative bacilli, including Escherichia coli and Klebsiella pneumoniae [ 4 ] . The clinical management of these infections has become increasingly difficult due to the emergence and spread of multidrug-resistant (MDR) bacterial strains, which severely limit therapeutic options and lead to higher mortality rates [ 5 ]. Globally, about 35% of K. pneumoniae and E. coli isolates from wounds show resistance to third-generation cephalosporins, while more than 25% of S. aureus isolates are methicillin-resistant [ 6 ]. The World Health Organization has therefore classified MDR pathogens such as MRSA and extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae as critical threats, underscoring the urgent need for local and global surveillance [ 7 ]. In sub-Saharan Africa, surgical site infections (SSIs) account for 60% of all hospital-acquired infections, contributing to substantial morbidity and increased healthcare cost [ 8 ]. In Benin, the situation is particularly alarming. Several studies have documented a high prevalence of infected wounds in local healthcare facilities, many of which are caused by multidrug-resistant organisms [ 9 , 10 ]. The excessive and often inappropriate use of antibiotics combined with poor hygiene, limited diagnostic capacities, and lack of public awareness exacerbated the development and dissemination of antimicrobial resistance [ 11 ]. The burden of antimicrobial resistance is further amplified by the presence of genetic mechanisms such as β-lactamase production, altered target sites, and active efflux pumps, which confer resistance to multiple antibiotic classes including β-lactams, carbapenems, aminoglycosides, and fluoroquinolones [ 12 ]. Given this context, an in-depth understanding of the phenotypic resistance profiles and underlying genetic determinants of MDR bacteria in wound infections is important. Such knowledge not only informs empirical therapy but also supports the development of locally relevant infection prevention and control measures [ 13 ]. Therefore, the present study aimed to characterize multidrug-resistant bacterial strains isolated from infected wounds in hospitals in southern Benin. Methods Study Design and Setting This cross-sectional, prospective, and descriptive study was conducted between October 2023 and May 2024 across multiple hospitals located in the southern region of Benin. The study aimed to investigate the bacteriological profile and antibiotic resistance patterns associated with wound infections in hospitalized patients. A systematic sampling approach was adopted, targeting patients presenting with infected wounds exhibiting clinical signs of suppuration. The participating hospitals were selected based on patient volume and accessibility of microbiological diagnostic services. All patients provided written informed consent before sample collection, ensuring compliance with ethical principles and protection of patient rights. The Ethics and Research Committee of the Institute of Applied Biomedical Sciences (CER-ISBA) reviewed and granted approval to the research proposal with the reference number 161. Prior to participating in the study, every patient provided written informed consent and received a brief explanation regarding the study’s purpose. Sampling Procedure A total of 384 wound suppuration swabs were collected from infected patients meeting the inclusion criteria. Inclusion was based on the clinical presence of an infected wound, characterized by purulent discharge, local inflammation, delayed healing, or other clinical signs of infection. Sample collection was carried out by trained personnel using sterile swabs, following standard clinical protocols. Samples were immediately stored in transport media and delivered under cold chain conditions to the Research Unit in Applied Microbiology and Pharmacology of Natural Substances at the University of Abomey-Calavi. The transport and handling of samples were carried out in accordance with internationally recommended procedures for the safe transfer of biological materials. Bacteriological Identification In the laboratory, each swab underwent Gram staining to differentiate bacterial groups. The bacterial isolates were cultured on selective media based on their gram reaction and morphological characteristics. Gram-negative bacilli were cultured on MacConkey agar, while Gram-positive cocci were plated on Chapman agar, Bile Esculin Agar (BEA), fresh blood agar, and chocolate agar enriched with Polyvitex. After incubation at 37°C for 18 to 48 hours, the resulting colonies were subcultured and used for further identification. Colonies isolated from Chapman agar were transferred to Mueller-Hinton (MH) medium supplemented with NaCl and subsequently inoculated onto CHROMagar MRSA to identify methicillin-resistant Staphylococcus aureus (MRSA). Colonies from MacConkey agar were subcultured onto MH medium with cefotaxime and then plated onto mSuperESBL™ agar (BioMérieux) to detect extended-spectrum beta-lactamase (ESBL) production. All bacterial strains were identified using the VITEK automated system, and additional biochemical tests, such as catalase and coagulase tests, were conducted to differentiate among Streptococcus species, coagulase-positive Staphylococcus , and coagulase-negative Staphylococcus . Antibiotic Susceptibility Testing Antibiotic susceptibility was determined using the Kirby-Bauer disk diffusion method according to EUCAST guidelines [ 14 ]. Two panels of nine antibiotics were selected for testing: one for cocci and the other for bacilli. For cocci, the antibiotics tested included Imipenem, Cefotaxime, Vancomycin, Clindamycin, Erythromycin, Pristinamycin, Oxacillin, Gentamicin, and Ciprofloxacin. For bacilli, the antibiotics included Amoxicillin, Amoxicillin + Clavulanic Acid, Aztreonam, Ceftriaxone, Fosfomycin, Ertapenem, Imipenem, Gentamicin, and Ciprofloxacin. The antibiotic susceptibility profiles were determined by measuring the inhibition zones and classified according to the EUCAST guidelines. Pure cultures were then stored at -80°C in Trypticase Soy broth supplemented with 10% glycerol for future use. Genotypic Detection of Resistance Genes Genomic DNA was extracted from resistant isolates using the heat lysis method. Targeted PCR amplification was carried out to detect resistance genes. Amplification products were separated on 1.5% agarose gels stained with ethidium bromide and visualized under UV transillumination. The presence or absence of specific resistance genes was inferred based on amplicon size compared to a molecular weight marker. Data Management and Statistical Analysis All microbiological and clinical data were entered into a structured Excel (version 2019) database and statistically analyzed using GraphPad Prism (version 10.3). Descriptive statistics were used to calculate frequencies and proportions. The Chi-square test was applied to assess the association between wound suppuration and potential risk factors such as age, sex, antibiotic usage, cause of injury, and type of wound. A p-value of < 0.05 was considered statistically significant. Results Bacterial presence in wound samples In this study, 384 wound suppuration samples were collected by swabbing from patients. The majority of the analyzed samples, 326 in total, tested positive for the presence of bacteria, while a smaller number, 58 samples, were negative (Fig. 1 ). Staining examination revealed that some samples exhibited bimicrobial flora, while others were negative. A total of 265 strains of Gram-negative bacilli and 237 strains of Gram-positive cocci were isolated (Figs. 2 ). Factors associated to the wound infection The most represented age group was 11–20 years (42.8%), followed by 21–30 years (25.9%) (Table 1 ). A female predominance was observed, with 56.02% of patients being female (215/384). Additionally, 86.8% of the patients had not received antibiotic treatment, and 6.4% were diabetic. The chi-square test revealed a statistically significant association between the wound cause and the presence of resistant bacteria (p = 0.0013), as well as between diabetic status and bacterial resistance (p = 0.009). Logistic regression also identified surgical wounds as being specifically associated with the presence of resistant bacteria (Table 1 ). Table 1 Socio-demographic characteristics of patients as well as factors associated with the presence or absence of bacteria in wound suppurations. Characteristics Absolute Frequence Pourcentage OR 95% CI p -value Age (Year) 0.3 0 to 10 26 6,77% — — 11 to 20 165 42,86% 1.44 0.62, 3.47 0.4 21 to 30 100 25,94% 2.12 0.90, 5.19 0.090 31 to 40 72 18,80% 1.63 0.67, 4.09 0.3 41 to 50 20 5,26% 1.97 0.55, 7.23 0.3 Over 50 1 0,38% 10.5 1.28, 227 0.052 Total 384 100,00% Gender > 0.9 Female 215 56,02% — — Male 169 43,98% 1.07 0.70, 1.65 0.7 Total 384 100,00% Causes 0.013 Accident 88 22,93% — — Other 173 45,11% 0.63 0.24, 1.60 0.3 Diabetic wound 6 1,50% 2.29 0.65, 9.43 0.2 Abscess 27 7,14% 1.10 0.37, 3.23 0.9 Operating wound 22 5,64% 0.05 0.00, 0.40 0.009 Burn 68 17,67% 0.84 0.35, 2.00 0.7 Total 384 100,00% Location 0.8 Head 80 21,05% — — Upper limbs 42 10,53% 1.38 0.51, 3.78 0.5 Trunk 29 7,52% 1.01 0.47, 2.14 > 0.9 Legs 65 16,92% 1.00 0.37, 2.69 > 0.9 Lower abdomen 17 4,51% 0.81 0.22, 2.87 0.7 Back 22 5,64% 0.88 0.29, 2.62 0.8 Abdomen 130 33,83% 1.07 0.47, 2.48 0.9 Total 384 100,00% Diabetic state 0.3 No 359 93,61% — — Yes 25 6,39% 2.21 0.54, 11.3 0.3 Total 384 100,00% ATB 0.8 Yes 51 13,16% — — No 333 86,84% 0.89 0.50, 1.59 0.7 Total 384 100,00% Bacterial identification Bacterial identification tests detected several pathogens, with a predominance of Klebsiella pneumoniae (37.09%) and Escherichia coli (27.41%) among bacilli. Staphylococcus aureus (49.39%) and Enterococcus faecalis (22.89%) were the most represented among gram positive cocci (Fig. 4 ). Antibiotic resistance rate among isolates Antibiotic susceptibility tests revealed complete resistance to several beta-lactams, including amoxicillin, amoxicillin + clavulanic acid, ceftriaxone, and aztreonam. However, resistance to ertapenem and imipenem was very low among bacilli (Table 2 ). Table 2 Percentage of Gram negative bacilli isolates resistant to the antibiotics tested Species AML AMC CRO ATM ERT IMP GNM CIP FOS Klebsiella pneumoniae 23/23 23/23 23/23 23/23 4/23 0/23 20/23 16/23 16/23 100,00% 100,00% 100,00% 100,00% 17,39% 0,00% 86,69% 69,56% 69,65% Escherichia coli 17/17 17/17 17/17 17/17 0/17 0/17 12/17 15/17 3/17 100,00% 100,00% 100,00% 100,00% 0,00% 0,00% 70,58% 88,23% 17,64% Enterobacter spp 8/8 8/8 8/8 8/8 3/8 2/8 8/8 8/8 3/8 100% 100% 100% 100% 37,50% 25% 100% 100% 37,50% Acinetobacter baumanii - - 0 6/6 3/6 1/6 4/6 2/6 2/6 0% 0% 0% 100% 50% 13,66% 66,66% 33,33% 33,33% Citrobacter spp 3/3 3/3 3/3 3/3 1/3 0/3 3/3 1/3 2/3 100% 100% 1S00% 100% 33% 0% 100% 33% 66,66% Aeromonas spp 0/3 0/3 0/3 3/3 1/3 0/3 0/3 1/3 1/3 0% 0% 0% 100% fifty% 0% 0% fifty% fifty% Sphingomonas paucimobilis 0 0 0 0% 0% 0% Providence stuartii 1 1 1 1 1 0 1 1 1 100% 100% 100% 100% 100% 0% 100% 100% 100% Melting sawdust 1 1 1 1 0 0 1 1 1 100% 100% 100% 100% 0% 0% 100% 100% 100% Among cocci, high resistance levels were observed for ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%) (Fig. 5 ). Distribution of genes Regarding genes, the SasX virulence gene was detected only in Enterococcus faecalis (Table 3 ). The most common resistance genes among cocci were BlaZ (27.38%), followed by MecA (13.68%), MupA (2.98%), and qacA/B (1.79%). Among bacilli, several ESBL-associated resistance genes were identified, including blaCTX-M1, blaSHV, blaOXA-1, blaTEM, and blaCTX-M9 (Table IV). Finally, blaKPC gene was detected in a single Klebsiella pneumoniae strain, and blaVIM was present in all Acinetobacter baumannii , indicating carbapenemase production. Table 3 Presence of Sas X genes across gram positive cocci isolates Species Species numbers Sas X Enterococcus faecium Enterococcus faecalis Enterococcus galinarum Granucatella elegans Kocuria kristinae Lactococcus garvieae Staphylococcus aureus Staphylococcus cohnii Staphylococcus epidermidis Staphylococcus haemolyticus Staphylococcus hominis Staphylococcus lentus Staphylococcus saprophyticus Staphylococcus sciuri Staphylococcus warneri Streptococcus thoraltensis Streptococcus uberis 5/167 38/167 1/167 1/167 5/167 1/167 83/167 2/167 4/167 8/167 1/167 3/167 6/167 5/167 1/167 1/167 2/167 - + (2) - - - - - - - - - - - - - - - Table 4 Antibiotic resistance genes distribution across Gram negative bacilli isolates Species blaKPC blaVIM blaNDM blaOXA 48 bla IMP bla TEM bla SHV bla OXA-1 Like bla CTX-M15 bla CTX-M1 bla CTX-M9 bla GES Klebsiella pneumoniae 0 0 0 0 0 37.50% 50% 45.16% 16.66% 59.25% 36.36% 0 Escherichia coli 0 0 0 0 0 12,5% 27,77% 32,25 33,33% 22,22% 27,27% 0 Citrobacter spp 0 0 0 0 0 0% 5,55% 0% 16,66% 3,70% 0% 0 Aeromonas spp 0 0 0 0 0 12,5% 0% 3,22% 16,66% 3,70% 0% 0 Enterobacter spp 100% 0 0 0 0 12,5% 11,11% 16,12 16,66% 11,11% 18,18% 0 Acinetobacter baumanii 0 100% 0 0 0 12,5% 0% 0% 0% 0% 0% 0 Serratia liquefacien 0 0 0 0 12,5% 0% 3,22% 0% 0% 9.09% 0 0 P0rovidentia stuartii 0 0 0 0 0% 5.55% 0% 0% 0% 9.09% 0 0 Total 100% 0 0 0 100% 100% 100% 100% 100% 100% 0 0 Discussion In this study, 384 wound suppuration samples were collected by swabbing infected wounds. Gram staining revealed that some samples harbored bimicrobial flora, while others showed no detectable microorganisms. Similar findings were reported by in Niger, where a proportion of surgical site infections yielded negative cultures [ 15 ]. A total of 265 Gram-negative bacilli and 237 Gram-positive cocci were isolated, with a predominance of Gram-negative bacteria an observation consistent with previous studies [ 15 , 16 ]. Sociodemographic analysis revealed that the age group most affected was 11–20 years (42.8%), followed by 21–30 years (25.9%). This contrasts with findings by Omoruyi and Edeh (2024), who reported the highest infection rate in the 41–45 age group. A slight female predominance (56.02%) was observed, consistent with the 64.52% reported [ 17 ]. Notably, 86.8% of patients had not received prior antibiotic therapy, and 6.4% were diabetic. Statistical analysis revealed significant associations between the type of wound and the presence of resistant bacteria (p = 0.0013), as well as between diabetic status and bacterial resistance (p = 0.009). Diabetic patients are known to be at increased risk of chronic infection due to impaired immunity, poor vascularization, and delayed healing [ 18 ]. Logistic regression further identified surgical wounds as being significantly associated with the presence of resistant organisms, underscoring the need for stringent infection control measures, particularly in hospital settings. Microbiological identification revealed a predominance of Klebsiella pneumoniae (37.09%) and Escherichia coli (27.41%) among Gram-negative bacilli, and Staphylococcus aureus (49.39%) and Enterococcus faecalis (22.89%) among Gram-positive cocci. These organisms are well-known opportunistic pathogens implicated in nosocomial infections such as wound and urinary tract infections, and septicemia. The high prevalence of Staphylococcus aureus , particularly its methicillin-resistant form (MRSA), aligns with previous studies conducted in Benin and elsewhere [ 19 , 20 ]. Antimicrobial susceptibility testing showed high resistance rates among Gram-negative bacilli to beta-lactams, including amoxicillin, amoxicillin–clavulanate, ceftriaxone, and aztreonam, suggesting the likely production of extended-spectrum beta-lactamases (ESBLs) and/or carbapenemases. Nonetheless, low resistance rates were observed for ertapenem and imipenem, indicating partial retention of efficacy. These results are in line with those reported by Gadou et al. (2019) in Côte d'Ivoire. Carbapenem resistance was detected in 25.80% of bacilli, mainly against ertapenem. Among Gram-positive cocci, high resistance was observed to ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%). Phenotypic testing confirmed ESBL production in 37.09% of isolates, consistent with data from Morocco (Ayyad et al., 2016), though lower than the 88% reported in Côte d'Ivoire [ 21 ]. Carbapenemase production, assessed by meropenem inactivation, was observed in 3.22% of isolates. Molecular analysis revealed the presence of the SasX virulence gene exclusively in Enterococcus faecalis . This gene, typically associated with Staphylococcus aureus , enhances biofilm formation, potentially increasing resistance to antibiotics and immune defenses. Its detection in E. faecalis may result from horizontal gene transfer or mutation, highlighting the risk of virulence gene dissemination in clinical settings. This concern is supported by findings from Dougnon et al . (2020), who linked wound contamination to the reuse of inadequately disinfected dressing materials. The detection of SasX in E. faecalis raises important questions about interspecies gene transfer and its role in enhancing pathogenicity and resistance. Biofilm-associated genes such as SasX may contribute to persistent infections and complicate clinical management, warranting further research into their transmission dynamics and impact on wound care protocols. Concerning antimicrobial resistance genes, blaZ (27.38%) and mecA (13.68%) were the most frequently detected in Gram-positive strains, confirming the circulation of multidrug-resistant organisms such as MRSA and resistant E. faecalis (Murray et al ., 2022). In Gram-negative bacilli, several ESBL-related genes were identified, including CTX-M1 , blaSHV , blaOXA-1 , blaTEM , and blaCTX-M9 . Notably, the KPC gene was detected in one K. pneumoniae isolate, while all Acinetobacter baumannii isolates carried the VIM gene, confirming carbapenemase production. The 3.22% prevalence of carbapenemase-producing bacteria is markedly lower than the 59% reported in Iraq, suggesting regional differences in antimicrobial resistance epidemiology [ 22 ]. Overall, these findings emphasize the urgent need for antimicrobial stewardship, effective infection control practices, and continued molecular surveillance to mitigate the spread of multidrug-resistant and virulent pathogens in healthcare settings. Conclusion This study provides a comprehensive overview of the bacteriological landscape and antibiotic resistance profiles associated with wound infections in hospitals in southern Benin. The high prevalence of multidrug-resistant organisms, particularly Staphylococcus aureus , Enterococcus faecalis , and Gram-negative bacilli producing extended-spectrum β-lactamases, presents a serious therapeutic challenge. The detection of critical resistance genes highlights the growing threat of resistance to last-resort antibiotics such as carbapenems. The significant associations between resistance patterns and factors such as diabetes, wound etiology, and prior antibiotic use underscore the importance of integrating clinical risk factors into infection management strategies. Strengthening microbiological diagnostic capacity, enforcing rational antibiotic use, and implementing targeted infection control measures are urgently needed to curb the spread of antimicrobial resistance and improve patient outcomes in the region. Declarations Ethics Approval and Consent to Participate The study proposal was reviewed and approved by the Ethics and Research Committee of the Institute of Applied Biomedical Sciences (CER-ISBA) under number 161. Written informed consent was obtained from each patient or their parent/guardian before participation, accompanied by a concise explanation of the study's objective. The research work (sampling from hospitalized patients, sample processing and data analysis) in our study was conducted in accordance with the Declaration of Helsinki. Consent to Publish Not applicable Availability of Data and Materials All data generated and/or analyzed during the current study are included in this published article. The datasets used and/or analyzed during this study are also available from the corresponding author on reasonable request. Competing Interests The authors declare no conflict of interest. Funding This research received no external funding. Author Contributions M.H., H.K., and K.S., equally contribute to this manuscript. L.B., M.H., H.K., and K.S., wrote the protocol. K.F., L.H., M.H., and K.V., collected and processed the samples. H.K. and K.S. did the statistical analyses. M.H and H.K. wrote the draft of the manuscript. All authors have read and agreed to the published version of the manuscript. Acknowledgments The authors are very grateful to all the staff of the hospitals involved in the study and their willing to support any kind of interventions for a better care of patients. They thank the patients who accepted to participate in this study. References Sen CK. Human Wound and Its Burden: Updated 2022 Compendium of Estimates. Adv Wound Care. 2023;12:657–70. Falanga V, Isseroff RR, Soulika AM, Romanelli M, Margolis D, Kapp S et al. Chronic wounds. Nat Rev Dis Primer. 2022;8. Raoofi S, Kan FP, Rafiei S, Hosseinipalangi Z, Mejareh ZN, Khani S et al. Global prevalence of nosocomial infection: A systematic review and meta-analysis. PLoS ONE. 2023;18. Kaftandzieva A, Kostovski M, Mehmeti B, Mirchevska G. The most common bacterial isolates from wound samples – a three-year study. Arch Public Health. 2021;13:77–90. Catalano A, Iacopetta D, Ceramella J, Scumaci D, Giuzio F, Saturnino C, et al. Multidrug Resistance (MDR): A Widespread Phenomenon in Pharmacological Therapies. Molecules. 2022;27:1–18. OMS. Global report on infection prevention and control. World Health Organization; 2022. WHO. WHO bacterial priority pathogens list. 2024. Bact Pathog Public Health Importance Guide Res Dev Strateg Prev Control Antimicrob Resist. 2024;72. Nakhleh H, Samuel Fatokun B, Nakyanzi H, Mshaymesh S, Wellington J, Uwishema O. Surgical site infections in sub-Saharan Africa: epidemiology, risk factors, and prevention strategies. Ann Med Surg. 2025. Dougnon V, Assogba P, Koudouvo N, Ohouko F, Hounkpatin M, Klotoe JR et al. An ethnopharmacological survey about the Togolese plants used in the treatment of infectious diseases: a way to explore new substances. Ann Ayurvedic Med. 2020. Yehouenou CL, Soleimani R, Kpangon AA, Simon A, Dossou FM, Dalleur O. Carbapenem-Resistant Organisms Isolated in Surgical Site Infections in Benin: A Public Health Problem. Trop Med Infect Dis. 2022;7. Sariola S, Butcher A, Cañada JA, Aïkpé M, Compaore A. Closing the GAP in Antimicrobial Resistance Policy in Benin and Burkina Faso. mSystems. 2022;7. Belay WY, Getachew M, Tegegne BA, Teffera ZH, Dagne A, Zeleke TK, et al. Mechanism of antibacterial resistance, strategies and next-generation antimicrobials to contain antimicrobial resistance: a review. Front Pharmacol. 2024;15:1–26. Pronyk PM, de Alwis R, Rockett R, Basile K, Boucher YF, Pang V, et al. Advancing pathogen genomics in resource-limited settings. Cell Genomics. 2023;3:100443. EUCAST/CA-SFM. Comité de l ’ antibiogramme de la Société Française de Microbiologie Recommandations 2024. Com Antibiogramme Société Fr Microbiol. 2024;181. Doutchi M, Adamou H, Yahaya ML, Ousmane L, Magagi IA, Halidou M, et al. Infections Du Site Opératoire À l’Hôpital National De Zinder, Niger: Aspects Épidémiologiques Et Bactériologiques. Eur Sci J ESJ. 2020;16:576–89. Hodonou AHM, Fany H, Alexandre AS, Romaric TS, Holden FO, Bio TS, et al. Aspects Bacteriologiques Des Infections Du Site Operatoire Au Centre Hospitalier Departemental Du Borgou A Parakou (Benin). Eur Sci J ESJ. 2016;12:353. Omoruyi Z, Edeh DO. Determination of antibacterial activity of honey on wound. 2024;9:74–83. Okonkwo UA, Dipietro LA. Diabetes and Wound Angiogenesis. Int J Mol Sci. 2017;18:1419. Ibadin EE, Enabulele IO, Muinah F. Prevalence of mecA gene among staphylococci from clinical samples of a tertiary Prevalence of mecA gene among staphylococci from clinical samples of a tertiary hospital in Benin City. Nigeria. 2017. Kaapu KG, Maguga-phasha NT, Seloma NM, Nkambule MC. Prevalence and Antibiotic Profile of Multidrug Resistance Gram-Negative Pathogens Isolated from Wound Infections at Two Tertiary Hospitals in Limpopo Province, South Africa : A Retrospective Study. 2022;141–55. Gadou V, Gadou V, Moleculaire E, Enterobacteries DES, De CES, Spectre LA et al. Epidemiologie moleculaire des enterobacteries productrices de β lactamases a spectre elargi resistantes aux aminosides et aux fluoroquinolones dans le district d’abidjan. côte d’ivoire. 2019. Haji SH, Aka STH, Ali FA. Prevalence and characterisation of carbapenemase encoding genes in multidrug-resistant Gram-negative bacilli. PLoS ONE. 2021;16:e0259005. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6838967","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":487065236,"identity":"70df1727-f9fc-4ca7-97ca-11373715b990","order_by":0,"name":"Mathieu HOUNKPATIN","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Mathieu","middleName":"","lastName":"HOUNKPATIN","suffix":""},{"id":487065237,"identity":"0d6ecb14-c587-41a8-9e02-62bc8b0e3fef","order_by":1,"name":"Hornel KOUDOKPON","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDACCSB+wMCQAOY8qGBgMAAxKghpSYBpSTgD1XKGaC2JbURo4Z/d/OxDQkVdHr/02YMPEucdljdnbz7AcHAPHkvuHDOekXDmcLFkX16yQeK2w4Y7e44lMBx4hluLgUSCMdA9BxI3nOExkwBqYdxwI8eA+cMBfFrSPzMk/qsDaTH/kTjnsD1IC8MBvFpygLY0MINtATIOJxLUInEjp5gh4djhxJk9PMYSCcfSkzecOZZwAJ8W/hnpmxk+1NQl9vPwGH74UGNtu+F488EH+LSgg2YwSYIGBoY6UhSPglEwCkbBCAEAt+BdMEiqn/cAAAAASUVORK5CYII=","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":true,"prefix":"","firstName":"Hornel","middleName":"","lastName":"KOUDOKPON","suffix":""},{"id":487065238,"identity":"43609e30-7051-4a6c-983b-3b9f71d62137","order_by":2,"name":"Kévin SINTONDJI","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Kévin","middleName":"","lastName":"SINTONDJI","suffix":""},{"id":487065239,"identity":"41f3495f-fb8a-4bd7-a3d0-19e93aa4c2aa","order_by":3,"name":"Kafayath FABIYI","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Kafayath","middleName":"","lastName":"FABIYI","suffix":""},{"id":487065240,"identity":"d8ad4999-e525-419f-883a-a8b85bc337ac","order_by":4,"name":"Lauriano HOUNGBO","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Lauriano","middleName":"","lastName":"HOUNGBO","suffix":""},{"id":487065241,"identity":"12454edb-9d15-45b8-a92d-e249aa71d332","order_by":5,"name":"Manoir HOUNKANRIN","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Manoir","middleName":"","lastName":"HOUNKANRIN","suffix":""},{"id":487065242,"identity":"924d5e37-7793-468c-8f88-78d1590d6f5d","order_by":6,"name":"Kévine VODOUNNOU","email":"","orcid":"","institution":"Research Unit in Applied Microbiology and Pharmacology of natural substances","correspondingAuthor":false,"prefix":"","firstName":"Kévine","middleName":"","lastName":"VODOUNNOU","suffix":""},{"id":487065243,"identity":"cba39010-a1b5-4d29-835c-fb288aa6b3e2","order_by":7,"name":"Lamine BABA MOUSSA","email":"","orcid":"","institution":"Laboratory of Biology and Molecular Typing in Microbiology","correspondingAuthor":false,"prefix":"","firstName":"Lamine","middleName":"BABA","lastName":"MOUSSA","suffix":""}],"badges":[],"createdAt":"2025-06-06 18:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6838967/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6838967/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87383445,"identity":"8f743fab-0b04-40c9-8945-f0a5f0bb6c58","added_by":"auto","created_at":"2025-07-23 08:42:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20424,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial presence in samples\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/0f91d6c3062a26ff95fc77fe.png"},{"id":87380556,"identity":"77efc8f5-2926-4aeb-97c6-52178dcae280","added_by":"auto","created_at":"2025-07-23 08:34:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14370,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of bacteria after Gram staining\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/357618ba3c73f36da324f99b.png"},{"id":87380559,"identity":"63ff88a7-fbce-4549-a71e-a1a023866739","added_by":"auto","created_at":"2025-07-23 08:34:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88856,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of isolated Gram-negative bacilli species\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/39095c757ad5668cbfdcde6c.png"},{"id":87380558,"identity":"0de3f85b-13e8-4b0e-8737-addbd253074c","added_by":"auto","created_at":"2025-07-23 08:34:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":34678,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of isolated Gram-positive cocci species\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/84175f45a1d94b5a719b0543.png"},{"id":87384715,"identity":"f43e1680-1fd5-4020-93fd-75de1601a3b3","added_by":"auto","created_at":"2025-07-23 08:50:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":24807,"visible":true,"origin":"","legend":"\u003cp\u003eAntibiotic susceptibility of isolated Gram-positive cocci\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend: OX: Oxacillin; CTX: Cefotaxime; IPM: Imipenem; VA: Vancomycin; E: Erythromycin; DA: Clindamycin; PNM: Pristinamycin; CIP: Ciprofloxacin; GMN: Gentamicin.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/59487db4188696295e7b51a7.png"},{"id":87386565,"identity":"bbe319a3-1def-472e-98c6-b0b9d4ba68f6","added_by":"auto","created_at":"2025-07-23 08:59:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1315281,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6838967/v1/fe69d721-d739-4cce-b0b1-50e676db5129.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Characterization of Bacterial Strains Involved in Suppurative Wound Infections and Their Antibiotic Resistance Profiles in Southern Benin","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWound infections represent a significant global public health concern, particularly in low- and middle-income countries where healthcare resources are limited and infection control practices are often inadequate [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These infections commonly arise from surgical procedures, traumatic injuries, or chronic conditions such as diabetes, and are associated with considerable morbidity, prolonged hospitalization, and increased healthcare costs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Studies have shown that wound infections contribute to 7\u0026ndash;10% of nosocomial infections worldwide and are associated with up to 20 additional days of hospitalization and an increased cost of treatment by 300%, representing a substantial economic burden on both patients and healthcare systems [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].Etiologically, wound infections are polymicrobial in nature, predominantly caused by both Gram-positive cocci such as \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e species and Gram-negative bacilli, including \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e. The clinical management of these infections has become increasingly difficult due to the emergence and spread of multidrug-resistant (MDR) bacterial strains, which severely limit therapeutic options and lead to higher mortality rates [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Globally, about 35% of \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e isolates from wounds show resistance to third-generation cephalosporins, while more than 25% of \u003cem\u003eS. aureus\u003c/em\u003e isolates are methicillin-resistant [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The World Health Organization has therefore classified MDR pathogens such as MRSA and extended-spectrum beta-lactamase (ESBL)-producing \u003cem\u003eEnterobacteriaceae\u003c/em\u003e as critical threats, underscoring the urgent need for local and global surveillance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn sub-Saharan Africa, surgical site infections (SSIs) account for 60% of all hospital-acquired infections, contributing to substantial morbidity and increased healthcare cost [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In Benin, the situation is particularly alarming. Several studies have documented a high prevalence of infected wounds in local healthcare facilities, many of which are caused by multidrug-resistant organisms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe excessive and often inappropriate use of antibiotics combined with poor hygiene, limited diagnostic capacities, and lack of public awareness exacerbated the development and dissemination of antimicrobial resistance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The burden of antimicrobial resistance is further amplified by the presence of genetic mechanisms such as β-lactamase production, altered target sites, and active efflux pumps, which confer resistance to multiple antibiotic classes including β-lactams, carbapenems, aminoglycosides, and fluoroquinolones [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given this context, an in-depth understanding of the phenotypic resistance profiles and underlying genetic determinants of MDR bacteria in wound infections is important. Such knowledge not only informs empirical therapy but also supports the development of locally relevant infection prevention and control measures [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, the present study aimed to characterize multidrug-resistant bacterial strains isolated from infected wounds in hospitals in southern Benin.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003eThis cross-sectional, prospective, and descriptive study was conducted between October 2023 and May 2024 across multiple hospitals located in the southern region of Benin. The study aimed to investigate the bacteriological profile and antibiotic resistance patterns associated with wound infections in hospitalized patients. A systematic sampling approach was adopted, targeting patients presenting with infected wounds exhibiting clinical signs of suppuration. The participating hospitals were selected based on patient volume and accessibility of microbiological diagnostic services. All patients provided written informed consent before sample collection, ensuring compliance with ethical principles and protection of patient rights. The Ethics and Research Committee of the Institute of Applied Biomedical Sciences (CER-ISBA) reviewed and granted approval to the research proposal with the reference number 161. Prior to participating in the study, every patient provided written informed consent and received a brief explanation regarding the study\u0026rsquo;s purpose.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSampling Procedure\u003c/h3\u003e\n\u003cp\u003eA total of 384 wound suppuration swabs were collected from infected patients meeting the inclusion criteria. Inclusion was based on the clinical presence of an infected wound, characterized by purulent discharge, local inflammation, delayed healing, or other clinical signs of infection. Sample collection was carried out by trained personnel using sterile swabs, following standard clinical protocols. Samples were immediately stored in transport media and delivered under cold chain conditions to the Research Unit in Applied Microbiology and Pharmacology of Natural Substances at the University of Abomey-Calavi. The transport and handling of samples were carried out in accordance with internationally recommended procedures for the safe transfer of biological materials.\u003c/p\u003e\n\u003ch3\u003eBacteriological Identification\u003c/h3\u003e\n\u003cp\u003eIn the laboratory, each swab underwent Gram staining to differentiate bacterial groups. The bacterial isolates were cultured on selective media based on their gram reaction and morphological characteristics. Gram-negative bacilli were cultured on MacConkey agar, while Gram-positive cocci were plated on Chapman agar, Bile Esculin Agar (BEA), fresh blood agar, and chocolate agar enriched with Polyvitex. After incubation at 37\u0026deg;C for 18 to 48 hours, the resulting colonies were subcultured and used for further identification. Colonies isolated from Chapman agar were transferred to Mueller-Hinton (MH) medium supplemented with NaCl and subsequently inoculated onto CHROMagar MRSA to identify methicillin-resistant Staphylococcus aureus (MRSA). Colonies from MacConkey agar were subcultured onto MH medium with cefotaxime and then plated onto mSuperESBL\u0026trade; agar (BioM\u0026eacute;rieux) to detect extended-spectrum beta-lactamase (ESBL) production. All bacterial strains were identified using the VITEK automated system, and additional biochemical tests, such as catalase and coagulase tests, were conducted to differentiate among \u003cem\u003eStreptococcus\u003c/em\u003e species, coagulase-positive \u003cem\u003eStaphylococcus\u003c/em\u003e, and coagulase-negative \u003cem\u003eStaphylococcus\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eAntibiotic Susceptibility Testing\u003c/h3\u003e\n\u003cp\u003eAntibiotic susceptibility was determined using the Kirby-Bauer disk diffusion method according to EUCAST guidelines [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Two panels of nine antibiotics were selected for testing: one for cocci and the other for bacilli. For cocci, the antibiotics tested included Imipenem, Cefotaxime, Vancomycin, Clindamycin, Erythromycin, Pristinamycin, Oxacillin, Gentamicin, and Ciprofloxacin. For bacilli, the antibiotics included Amoxicillin, Amoxicillin\u0026thinsp;+\u0026thinsp;Clavulanic Acid, Aztreonam, Ceftriaxone, Fosfomycin, Ertapenem, Imipenem, Gentamicin, and Ciprofloxacin. The antibiotic susceptibility profiles were determined by measuring the inhibition zones and classified according to the EUCAST guidelines. Pure cultures were then stored at -80\u0026deg;C in Trypticase Soy broth supplemented with 10% glycerol for future use.\u003c/p\u003e\n\u003ch3\u003eGenotypic Detection of Resistance Genes\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted from resistant isolates using the heat lysis method. Targeted PCR amplification was carried out to detect resistance genes. Amplification products were separated on 1.5% agarose gels stained with ethidium bromide and visualized under UV transillumination. The presence or absence of specific resistance genes was inferred based on amplicon size compared to a molecular weight marker.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Management and Statistical Analysis\u003c/h2\u003e\u003cp\u003eAll microbiological and clinical data were entered into a structured Excel (version 2019) database and statistically analyzed using GraphPad Prism (version 10.3). Descriptive statistics were used to calculate frequencies and proportions. The Chi-square test was applied to assess the association between wound suppuration and potential risk factors such as age, sex, antibiotic usage, cause of injury, and type of wound. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eBacterial presence in wound samples\u003c/h2\u003e\u003cp\u003eIn this study, 384 wound suppuration samples were collected by swabbing from patients. The majority of the analyzed samples, 326 in total, tested positive for the presence of bacteria, while a smaller number, 58 samples, were negative (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eStaining examination revealed that some samples exhibited bimicrobial flora, while others were negative. A total of 265 strains of Gram-negative bacilli and 237 strains of Gram-positive cocci were isolated (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eFactors associated to the wound infection\u003c/h2\u003e\u003cp\u003eThe most represented age group was 11\u0026ndash;20 years (42.8%), followed by 21\u0026ndash;30 years (25.9%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A female predominance was observed, with 56.02% of patients being female (215/384). Additionally, 86.8% of the patients had not received antibiotic treatment, and 6.4% were diabetic.\u003c/p\u003e\u003cp\u003eThe chi-square test revealed a statistically significant association between the wound cause and the presence of resistant bacteria (p\u0026thinsp;=\u0026thinsp;0.0013), as well as between diabetic status and bacterial resistance (p\u0026thinsp;=\u0026thinsp;0.009). Logistic regression also identified surgical wounds as being specifically associated with the presence of resistant bacteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics of patients as well as factors associated with the presence or absence of bacteria in wound suppurations.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbsolute Frequence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePourcentage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep -value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (Year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 to 10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,77%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11 to 20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42,86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.62, 3.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21 to 30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25,94%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.90, 5.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e31 to 40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18,80%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.67, 4.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e41 to 50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,26%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.55, 7.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOver 50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,38%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28, 227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56,02%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43,98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.70, 1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCauses\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccident\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22,93%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45,11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.24, 1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetic wound\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.65, 9.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbscess\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37, 3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOperating wound\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,64%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00, 0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17,67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.35, 2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHead\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21,05%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUpper limbs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10,53%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.51, 3.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrunk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.47, 2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLegs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16,92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37, 2.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower abdomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,51%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.22, 2.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,64%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.29, 2.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbdomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33,83%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.47, 2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetic state\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93,61%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,39%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.54, 11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eATB\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13,16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86,84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.50, 1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eBacterial identification\u003c/h2\u003e\u003cp\u003eBacterial identification tests detected several pathogens, with a predominance of \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (37.09%) and \u003cem\u003eEscherichia coli\u003c/em\u003e (27.41%) among bacilli.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e (49.39%) and \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (22.89%) were the most represented among gram positive cocci (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eAntibiotic resistance rate among isolates\u003c/h2\u003e\u003cp\u003eAntibiotic susceptibility tests revealed complete resistance to several beta-lactams, including amoxicillin, amoxicillin\u0026thinsp;+\u0026thinsp;clavulanic acid, ceftriaxone, and aztreonam. However, resistance to ertapenem and imipenem was very low among bacilli (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePercentage of Gram negative bacilli isolates resistant to the antibiotics tested\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAML\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAMC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCRO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eATM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eERT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIMP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGNM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCIP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFOS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKlebsiella pneumoniae\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e20/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e16/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e16/23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17,39%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e86,69%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e69,56%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e69,65%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEscherichia coli\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e15/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3/17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e70,58%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e88,23%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e17,64%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnterobacter spp\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3/8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e37,50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e37,50%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAcinetobacter baumanii\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2/6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13,66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e66,66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e33,33%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e33,33%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCitrobacter spp\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2/3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1S00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e33%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e66,66%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAeromonas spp\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1/3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003efifty%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003efifty%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003efifty%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSphingomonas paucimobilis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eProvidence stuartii\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMelting sawdust\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAmong cocci, high resistance levels were observed for ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eDistribution of genes\u003c/h2\u003e\u003cp\u003eRegarding genes, the SasX virulence gene was detected only in Enterococcus faecalis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The most common resistance genes among cocci were BlaZ (27.38%), followed by MecA (13.68%), MupA (2.98%), and qacA/B (1.79%). Among bacilli, several ESBL-associated resistance genes were identified, including \u003cem\u003eblaCTX-M1, blaSHV, blaOXA-1, blaTEM, and blaCTX-M9\u003c/em\u003e (Table IV). Finally, \u003cem\u003eblaKPC\u003c/em\u003e gene was detected in a single \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e strain, and \u003cem\u003eblaVIM\u003c/em\u003e was present in all \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, indicating carbapenemase production.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePresence of Sas X genes across gram positive cocci isolates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecies numbers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSas X\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterococcus faecium\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEnterococcus faecalis\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEnterococcus galinarum\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eGranucatella elegans\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eKocuria kristinae\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eLactococcus garvieae\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus cohnii\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus hominis\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus lentus\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus sciuri\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStaphylococcus warneri\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStreptococcus thoraltensis\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eStreptococcus uberis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5/167\u003c/p\u003e\u003cp\u003e38/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e5/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e83/167\u003c/p\u003e\u003cp\u003e2/167\u003c/p\u003e\u003cp\u003e4/167\u003c/p\u003e\u003cp\u003e8/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e3/167\u003c/p\u003e\u003cp\u003e6/167\u003c/p\u003e\u003cp\u003e5/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e1/167\u003c/p\u003e\u003cp\u003e2/167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e+ (2)\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAntibiotic resistance genes distribution across Gram negative bacilli isolates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eblaKPC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eblaVIM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eblaNDM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eblaOXA 48\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ebla IMP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ebla TEM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ebla SHV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ebla OXA-1 Like\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003ebla CTX-M15\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003ebla CTX-M1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003ebla CTX-M9\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003ebla GES\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e45.16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e16.66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e59.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e36.36%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e27,77%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e32,25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e33,33%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e22,22%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e27,27%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCitrobacter spp\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5,55%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e16,66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3,70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAeromonas spp\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3,22%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e16,66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e3,70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e100%\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e11,11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e16,12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e16,66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e11,11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e18,18%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter baumanii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSerratia liquefacien\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3,22%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e9.09%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP0rovidentia stuartii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.55%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e9.09%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, 384 wound suppuration samples were collected by swabbing infected wounds. Gram staining revealed that some samples harbored bimicrobial flora, while others showed no detectable microorganisms. Similar findings were reported by in Niger, where a proportion of surgical site infections yielded negative cultures [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A total of 265 Gram-negative bacilli and 237 Gram-positive cocci were isolated, with a predominance of Gram-negative bacteria an observation consistent with previous studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSociodemographic analysis revealed that the age group most affected was 11\u0026ndash;20 years (42.8%), followed by 21\u0026ndash;30 years (25.9%). This contrasts with findings by Omoruyi and Edeh (2024), who reported the highest infection rate in the 41\u0026ndash;45 age group. A slight female predominance (56.02%) was observed, consistent with the 64.52% reported [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Notably, 86.8% of patients had not received prior antibiotic therapy, and 6.4% were diabetic.\u003c/p\u003e\u003cp\u003eStatistical analysis revealed significant associations between the type of wound and the presence of resistant bacteria (p\u0026thinsp;=\u0026thinsp;0.0013), as well as between diabetic status and bacterial resistance (p\u0026thinsp;=\u0026thinsp;0.009). Diabetic patients are known to be at increased risk of chronic infection due to impaired immunity, poor vascularization, and delayed healing [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Logistic regression further identified surgical wounds as being significantly associated with the presence of resistant organisms, underscoring the need for stringent infection control measures, particularly in hospital settings.\u003c/p\u003e\u003cp\u003eMicrobiological identification revealed a predominance of \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (37.09%) and \u003cem\u003eEscherichia coli\u003c/em\u003e (27.41%) among Gram-negative bacilli, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (49.39%) and \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (22.89%) among Gram-positive cocci. These organisms are well-known opportunistic pathogens implicated in nosocomial infections such as wound and urinary tract infections, and septicemia. The high prevalence of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, particularly its methicillin-resistant form (MRSA), aligns with previous studies conducted in Benin and elsewhere [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAntimicrobial susceptibility testing showed high resistance rates among Gram-negative bacilli to beta-lactams, including amoxicillin, amoxicillin\u0026ndash;clavulanate, ceftriaxone, and aztreonam, suggesting the likely production of extended-spectrum beta-lactamases (ESBLs) and/or carbapenemases. Nonetheless, low resistance rates were observed for ertapenem and imipenem, indicating partial retention of efficacy. These results are in line with those reported by Gadou et al. (2019) in C\u0026ocirc;te d'Ivoire. Carbapenem resistance was detected in 25.80% of bacilli, mainly against ertapenem. Among Gram-positive cocci, high resistance was observed to ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%).\u003c/p\u003e\u003cp\u003ePhenotypic testing confirmed ESBL production in 37.09% of isolates, consistent with data from Morocco (Ayyad et al., 2016), though lower than the 88% reported in C\u0026ocirc;te d'Ivoire [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Carbapenemase production, assessed by meropenem inactivation, was observed in 3.22% of isolates. Molecular analysis revealed the presence of the \u003cem\u003eSasX\u003c/em\u003e virulence gene exclusively in \u003cem\u003eEnterococcus faecalis\u003c/em\u003e. This gene, typically associated with \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, enhances biofilm formation, potentially increasing resistance to antibiotics and immune defenses. Its detection in \u003cem\u003eE. faecalis\u003c/em\u003e may result from horizontal gene transfer or mutation, highlighting the risk of virulence gene dissemination in clinical settings. This concern is supported by findings from Dougnon \u003cem\u003eet al\u003c/em\u003e. (2020), who linked wound contamination to the reuse of inadequately disinfected dressing materials.\u003c/p\u003e\u003cp\u003eThe detection of \u003cem\u003eSasX\u003c/em\u003e in \u003cem\u003eE. faecalis\u003c/em\u003e raises important questions about interspecies gene transfer and its role in enhancing pathogenicity and resistance. Biofilm-associated genes such as \u003cem\u003eSasX\u003c/em\u003e may contribute to persistent infections and complicate clinical management, warranting further research into their transmission dynamics and impact on wound care protocols. Concerning antimicrobial resistance genes, \u003cem\u003eblaZ\u003c/em\u003e (27.38%) and \u003cem\u003emecA\u003c/em\u003e (13.68%) were the most frequently detected in Gram-positive strains, confirming the circulation of multidrug-resistant organisms such as MRSA and resistant \u003cem\u003eE. faecalis\u003c/em\u003e (Murray \u003cem\u003eet al\u003c/em\u003e., 2022). In Gram-negative bacilli, several ESBL-related genes were identified, including \u003cem\u003eCTX-M1\u003c/em\u003e, \u003cem\u003eblaSHV\u003c/em\u003e, \u003cem\u003eblaOXA-1\u003c/em\u003e, \u003cem\u003eblaTEM\u003c/em\u003e, and \u003cem\u003eblaCTX-M9\u003c/em\u003e. Notably, the \u003cem\u003eKPC\u003c/em\u003e gene was detected in one \u003cem\u003eK. pneumoniae\u003c/em\u003e isolate, while all \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e isolates carried the \u003cem\u003eVIM\u003c/em\u003e gene, confirming carbapenemase production. The 3.22% prevalence of carbapenemase-producing bacteria is markedly lower than the 59% reported in Iraq, suggesting regional differences in antimicrobial resistance epidemiology [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOverall, these findings emphasize the urgent need for antimicrobial stewardship, effective infection control practices, and continued molecular surveillance to mitigate the spread of multidrug-resistant and virulent pathogens in healthcare settings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides a comprehensive overview of the bacteriological landscape and antibiotic resistance profiles associated with wound infections in hospitals in southern Benin. The high prevalence of multidrug-resistant organisms, particularly \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eEnterococcus faecalis\u003c/em\u003e, and Gram-negative bacilli producing extended-spectrum β-lactamases, presents a serious therapeutic challenge. The detection of critical resistance genes highlights the growing threat of resistance to last-resort antibiotics such as carbapenems. The significant associations between resistance patterns and factors such as diabetes, wound etiology, and prior antibiotic use underscore the importance of integrating clinical risk factors into infection management strategies. Strengthening microbiological diagnostic capacity, enforcing rational antibiotic use, and implementing targeted infection control measures are urgently needed to curb the spread of antimicrobial resistance and improve patient outcomes in the region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study proposal was reviewed and approved by the Ethics and Research Committee of the Institute of Applied Biomedical Sciences (CER-ISBA) under number 161. Written informed consent was obtained from each patient or their parent/guardian before participation, accompanied by a concise explanation of the study\u0026apos;s objective. The research work (sampling from hospitalized patients, sample processing and data analysis) in our study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated and/or analyzed during the current study are included in this published article. The datasets used and/or analyzed during this study are also available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.H., H.K., and K.S., equally contribute to this manuscript. L.B., M.H., H.K., and K.S., wrote the protocol. K.F., L.H., M.H., and K.V., collected and processed the samples. H.K. and K.S. did the statistical analyses. M.H and H.K. wrote the draft of the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are very grateful to all the staff of the hospitals involved in the study and their willing to support any kind of interventions for a better care of patients. They thank the patients who accepted to participate in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSen CK. Human Wound and Its Burden: Updated 2022 Compendium of Estimates. Adv Wound Care. 2023;12:657\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFalanga V, Isseroff RR, Soulika AM, Romanelli M, Margolis D, Kapp S et al. Chronic wounds. Nat Rev Dis Primer. 2022;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaoofi S, Kan FP, Rafiei S, Hosseinipalangi Z, Mejareh ZN, Khani S et al. Global prevalence of nosocomial infection: A systematic review and meta-analysis. PLoS ONE. 2023;18.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaftandzieva A, Kostovski M, Mehmeti B, Mirchevska G. The most common bacterial isolates from wound samples \u0026ndash; a three-year study. Arch Public Health. 2021;13:77\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCatalano A, Iacopetta D, Ceramella J, Scumaci D, Giuzio F, Saturnino C, et al. Multidrug Resistance (MDR): A Widespread Phenomenon in Pharmacological Therapies. Molecules. 2022;27:1\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOMS. Global report on infection prevention and control. World Health Organization; 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO. WHO bacterial priority pathogens list. 2024. Bact Pathog Public Health Importance Guide Res Dev Strateg Prev Control Antimicrob Resist. 2024;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakhleh H, Samuel Fatokun B, Nakyanzi H, Mshaymesh S, Wellington J, Uwishema O. Surgical site infections in sub-Saharan Africa: epidemiology, risk factors, and prevention strategies. Ann Med Surg. 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDougnon V, Assogba P, Koudouvo N, Ohouko F, Hounkpatin M, Klotoe JR et al. An ethnopharmacological survey about the Togolese plants used in the treatment of infectious diseases: a way to explore new substances. Ann Ayurvedic Med. 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYehouenou CL, Soleimani R, Kpangon AA, Simon A, Dossou FM, Dalleur O. Carbapenem-Resistant Organisms Isolated in Surgical Site Infections in Benin: A Public Health Problem. Trop Med Infect Dis. 2022;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSariola S, Butcher A, Ca\u0026ntilde;ada JA, A\u0026iuml;kp\u0026eacute; M, Compaore A. Closing the GAP in Antimicrobial Resistance Policy in Benin and Burkina Faso. mSystems. 2022;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBelay WY, Getachew M, Tegegne BA, Teffera ZH, Dagne A, Zeleke TK, et al. Mechanism of antibacterial resistance, strategies and next-generation antimicrobials to contain antimicrobial resistance: a review. Front Pharmacol. 2024;15:1\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePronyk PM, de Alwis R, Rockett R, Basile K, Boucher YF, Pang V, et al. Advancing pathogen genomics in resource-limited settings. Cell Genomics. 2023;3:100443.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEUCAST/CA-SFM. Comit\u0026eacute; de l \u0026rsquo; antibiogramme de la Soci\u0026eacute;t\u0026eacute; Fran\u0026ccedil;aise de Microbiologie Recommandations 2024. Com Antibiogramme Soci\u0026eacute;t\u0026eacute; Fr Microbiol. 2024;181.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDoutchi M, Adamou H, Yahaya ML, Ousmane L, Magagi IA, Halidou M, et al. Infections Du Site Op\u0026eacute;ratoire \u0026Agrave; l\u0026rsquo;H\u0026ocirc;pital National De Zinder, Niger: Aspects \u0026Eacute;pid\u0026eacute;miologiques Et Bact\u0026eacute;riologiques. Eur Sci J ESJ. 2020;16:576\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHodonou AHM, Fany H, Alexandre AS, Romaric TS, Holden FO, Bio TS, et al. Aspects Bacteriologiques Des Infections Du Site Operatoire Au Centre Hospitalier Departemental Du Borgou A Parakou (Benin). Eur Sci J ESJ. 2016;12:353.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOmoruyi Z, Edeh DO. Determination of antibacterial activity of honey on wound. 2024;9:74\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkonkwo UA, Dipietro LA. Diabetes and Wound Angiogenesis. Int J Mol Sci. 2017;18:1419.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIbadin EE, Enabulele IO, Muinah F. Prevalence of mecA gene among staphylococci from clinical samples of a tertiary Prevalence of mecA gene among staphylococci from clinical samples of a tertiary hospital in Benin City. Nigeria. 2017.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaapu KG, Maguga-phasha NT, Seloma NM, Nkambule MC. Prevalence and Antibiotic Profile of Multidrug Resistance Gram-Negative Pathogens Isolated from Wound Infections at Two Tertiary Hospitals in Limpopo Province, South Africa : A Retrospective Study. 2022;141\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGadou V, Gadou V, Moleculaire E, Enterobacteries DES, De CES, Spectre LA et al. Epidemiologie moleculaire des enterobacteries productrices de β lactamases a spectre elargi resistantes aux aminosides et aux fluoroquinolones dans le district d\u0026rsquo;abidjan. c\u0026ocirc;te d\u0026rsquo;ivoire. 2019.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaji SH, Aka STH, Ali FA. Prevalence and characterisation of carbapenemase encoding genes in multidrug-resistant Gram-negative bacilli. PLoS ONE. 2021;16:e0259005.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","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":"Antibiotic resistance, Suppurative wound infections, Benin","lastPublishedDoi":"10.21203/rs.3.rs-6838967/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6838967/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eWound infections represent a significant clinical burden in healthcare settings, particularly in low- and middle-income countries. This study aimed to characterize the bacteriological profile and antibiotic resistance patterns of pathogens isolated from wound suppurations in hospitals in southern Benin.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA total of 384 wound swab samples were collected from hospitalized patients in multiple hospitals across southern Benin presenting with clinical signs of suppuration. Bacteriological identification was performed using VITEK automated system. Antibiotic susceptibility testing was conducted via the Kirby-Bauer method. Molecular detection of resistance and virulence genes was performed by PCR.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf the 384 wound samples, 326 (84.9%) yielded positive bacterial cultures. The most prevalent pathogens were \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (49.39%), \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (22.89%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (37.09%), and \u003cem\u003eEscherichia coli\u003c/em\u003e (27.41%). The most affected age group was 11\u0026ndash;20 years (42.8%), and females were slightly more affected (56.02%). Antibiotic susceptibility testing revealed high levels of resistance to beta-lactams among bacilli, while resistance to carbapenems remained low. Among cocci, high resistance rates were observed for ciprofloxacin (97%), gentamicin (55.08%), and oxacillin (48.50%). Statistically significant associations were observed between the presence of resistant bacteria and both wound etiology (p\u0026thinsp;=\u0026thinsp;0.0013) and diabetic status (p\u0026thinsp;=\u0026thinsp;0.009). Molecular analysis revealed the presence of \u003cem\u003eblaZ\u003c/em\u003e (27.38%) and \u003cem\u003emecA\u003c/em\u003e (13.68%) among Gram-positive cocci, and multiple ESBL-associated genes (\u003cem\u003eblaCTX-M1, blaSHV, blaOXA-1, blaTEM, blaCTX-M9\u003c/em\u003e) among Gram-negative bacilli.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe study highlights a high prevalence of multidrug-resistant bacteria in wound infections, with significant implications for antibiotic stewardship and infection control.\u003c/p\u003e","manuscriptTitle":"Characterization of Bacterial Strains Involved in Suppurative Wound Infections and Their Antibiotic Resistance Profiles in Southern Benin","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 08:34:54","doi":"10.21203/rs.3.rs-6838967/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":"ef99624c-2a76-47bc-b7e3-b026b35e65ef","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-23T08:34:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 08:34:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6838967","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6838967","identity":"rs-6838967","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}