Abstract
Background
Wound infections significantly impact morbidity, mortality, and healthcare costs globally. The Kashmir Valley's unique geographical and climatic conditions, coupled with resource constraints and antibiotic misuse, complicate managing these infections effectively. This study aimed to identify predominant bacterial pathogens in wound infections at a tertiary care hospital in Kashmir, determine their antibiotic susceptibility profiles, and estimate the prevalence of multidrug-resistant (MDR) strains.
Materials and Methods
A prospective cross-sectional study was conducted from January to June 2023 at the Government Medical College, Srinagar. Pus samples from wound infections were aseptically collected and processed following standard microbiological protocols. Antibiotic susceptibility testing utilized the Kirby-Bauer disk diffusion method, adhering to Clinical and Laboratory Standards Institute guidelines. Data were analyzed using IBM SPSS statistics.
Results
Out of 4,378 samples analyzed, bacterial growth was observed in 1,921 samples, representing 43.9% of the total. Among the bacterial isolates, Gram-negative bacilli accounted for 73.5%, with Escherichia coli being the most prevalent at 27.9%. Among Gram-positive cocci, Staphylococcus aureus predominated, comprising 25.9% of the isolates. Methicillin-resistant S. aureus exhibited 100% susceptibility to linezolid but low susceptibility to erythromycin (27.0%) and clindamycin (24.0%). E. coli demonstrated high susceptibility to tigecycline (97.4%) and amikacin (75.0%), but lower susceptibility to imipenem (45.0%) and piperacillin-tazobactam (57.8%).
Conclusion
The substantial wound infection burden and high MDR prevalence in Kashmir necessitate comprehensive antimicrobial stewardship and infection control programs. Regular surveillance, education, and research are crucial to address antibiotic resistance and ensure effective wound infection management in the region.
Keywords: Wound infection, Antibiotic resistance, Staphylococcus aureus, Methicillin-resistant Staphylococcus aureus, Gram-negative bacteria
Graphical Abstract
Introduction
Wound infections pose a significant challenge in healthcare settings, contributing to increased morbidity, mortality, and financial burden on healthcare systems worldwide [1]. The Kashmir Valley, a region with unique geographical and climatic conditions, presents specific challenges in managing wound infections due to factors such as limited resources, antibiotic misuse, and the potential emergence of antibiotic-resistant pathogens [2]. The epidemiology of wound infections is influenced by various factors, including the type of wound, patient demographics, underlying medical conditions, and exposure to healthcare settings [3]. Surgical site infections (SSIs) are among the most common healthcare-associated infections, accounting for approximately 20% of all nosocomial infections [4]. In developing countries, the burden of SSIs is significantly higher, with reported rates ranging from 2.5% to 30.9% [5]. Chronic wound infections, such as those associated with diabetic foot ulcers, pressure ulcers, and venous leg ulcers, also contribute substantially to the overall burden of wound infections [6]. The etiological agents responsible for wound infections can vary depending on the geographical location, healthcare settings, and patient populations [7]. Gram-positive bacteria, particularly Staphylococcus aureus and Streptococcus pyogenes, are commonly isolated from wound infections [8]. However, Gram-negative bacteria, such as Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae, have also been implicated in wound infections, especially in healthcare settings [9]. Antibiotic resistance is a growing concern in the management of wound infections, as it limits treatment options and increases the risk of treatment failure [10]. The emergence of multidrug-resistant (MDR) strains, such as methicillin-resistant S. aureus (MRSA) and extended-spectrum beta-lactamase (ESBL)-producing Gram-negative bacteria, has further complicated the management of wound infections [11,12].
Antibiotic resistance is a global challenge, and its impact is particularly significant in resource-limited settings like the Kashmir Valley. Regular surveillance of bacterial pathogens and their antibiotic susceptibility patterns is crucial for guiding empirical therapy and developing appropriate antimicrobial stewardship programs [13]. By understanding the local epidemiology of wound infections and the associated antibiotic resistance profiles, healthcare professionals can make informed decisions regarding antibiotic prescribing practices and infection control measures. With this aim we conducted this study to identify the predominant bacterial pathogens associated with wound infections in a tertiary care hospital in the Kashmir Valley, to determine the antibiotic susceptibility patterns of the isolated bacterial strains and to estimate the prevalence of MDR strains among the isolates.
This study represents one of the first comprehensive investigations into wound infections and antibiotic resistance patterns in the Kashmir Valley, Jammu and Kashmir, India. The unique geographical and climatic conditions of this region, coupled with limited healthcare resources and potential antibiotic misuse, create a distinct environment for the development, and spread of antibiotic-resistant pathogens. By providing detailed data on the prevalence of MDR strains, particularly MRSA, in this specific geographic context, our findings will offer crucial insights for tailoring local antimicrobial stewardship programs and infection control strategies.
Materials and Methods
1. Study design and setting
This prospective cross-sectional study was conducted Government Medical College, Srinagar, a tertiary care hospital of the Kashmir Valley, Jammu and Kashmir, India over a period of six months from January 2023 to June 2023. The study included patients admitted to various wards and outpatient departments with wound infections. Pus samples were collected aseptically from patients with wound infections using sterile swabs or aspiration techniques, as per standard microbiological protocols [14]. The samples were transported promptly to the microbiology laboratory for further processing.
The pus samples were inoculated onto appropriate culture media, such as blood agar, MacConkey agar, and other selective media, as per standard microbiological procedures [15]. The inoculated plates were incubated at the appropriate temperature and atmospheric conditions for 18–24 hours. Bacterial isolates were identified based on colony morphology, Gram staining characteristics, and a series of biochemical tests, including catalase, oxidase, and other specific tests as required [16]. Antibiotic susceptibility testing was performed using the Kirby-Bauer disk diffusion method, following the guidelines of the Clinical and Laboratory Standards Institute [17]. A panel of antibiotics commonly used for the treatment of wound infections were tested, including ampicillin (Amp)-10µg, amoxicillin/clavulate (20/10 µg), gentamicin (10 µg), amikacin (30 µg), ciprofloxacin (5 µg), levofloxacin (5 µg), ceftazidime (30 µg), cefotaxime (30 µg), ampicillin/sulbactam (20 µg), aztreonam (10 µg), imipenem (10 µg), piperacillin/tazobactam (100/10 µg), azithromycin (30 µg), cefoxitin (30 µg), doxycycline (30 µg), trimethoprim/sulfamethoxazole (1.25 g/23.75 µg), erythromycin (5 µg), clindamycin (2 µg), linezolid (30 µg), and vancomycin (30 µg). The antibiotic disks were procured from a reliable commercial source. Quality control measures were implemented throughout the study to ensure the accuracy and reliability of the results. Reference strains of known antibiotic susceptibility patterns, such as E. coli ATCC 25922 and S. aureus ATCC 25923, were used for quality control during each batch of antibiotic susceptibility testing [17]. The bacterial isolates and their antibiotic susceptibility patterns were recorded and analyzed using appropriate statistical methods. Descriptive statistics were used to summarize the data. All the analysis was performed using the SPSS (Version 29.0.2.0, IBM Corp., Armonk, NY, USA).
2. Ethics statement
This study was conducted in accordance with the principles outlined in the Declaration of Helsinki. Approval was obtained from the Institutional Ethics Committee of Government Medical College, Srinagar (IRB no. GMC 243/23/IRB). Informed consent was obtained from all participants or their legally authorized representatives prior to study inclusion. Confidentiality was strictly maintained, and participants were not subjected to coercion or exploitation. The study adhered to the ethical principles of beneficence, non-maleficence, autonomy, and justice.
Results
Table 1 shows the microbial distribution and characteristics in the studied samples. Out of 4,378 samples analyzed, 1,921 (43.9%) were positive for bacterial growth, indicating a significant burden of wound infections in the study setting. Gram-negative bacilli accounted for 73.5% (1,413/1,921) of the isolates, while Gram-positive constituted 26.4% (508/1,921) positive isolates. Table 2 describes the distribution and proportion of identified organisms. Among the Gram-positive isolates, S. aureus was the predominant organism, comprising 26.0% (499/1,921) of the total isolates and 98.2% (499/508) of the Gram-positive isolates. Notably, 59.1% (295/499) of the S. aureus isolates were MRSA, indicating a high prevalence of MDR strains within this species. Enterococcus accounted for a relatively small proportion (0.5%, 9/1,921) of the isolates. In the Gram-negative group, E. coli was the most prevalent organism, constituting 20.6% (395/1,921) of the total isolates and 28.0% (395/1,413) of the Gram-negative isolates. Other major Gram-negative pathogens included Klebsiella (17.0%, 326/1,921), Acinetobacter (14.0%, 268/1,921), and Pseudomonas (11.5%, 220/1,921).
Table 1. Microbial distribution and characteristics of sampled specimens.
| Parameter | No. of samples (%) | |
|---|---|---|
| Possible pathogen | 1,921 (43.9) | |
| Gram-positive cocci | 508/1,921 (26.4% of possible pathogens) | |
| Gram-negative bacilli | 1,413/1,921 (73.5% of possible pathogens) | |
| Contamination | 108 (2.5) | |
| No growth | 2,555 (58.4) | |
| Total | 4,378 | |
Table 2. Distribution and proportion of identified organisms in positive samples.
| Organism | Count | % of total organisms (N=1,921) |
% of Gram-positive (N=508) |
% of Gram-negative (N=1,413) |
|
|---|---|---|---|---|---|
| Staphylococcus aureus | 499 | 25.9 | 98.2 | - | |
| Methicillin-resistant S. aureus | 295 | 15.3 | 59.1 | ||
| Methicillin-susceptible S. aureus | 204 | 10.6 | 40.8 | ||
| Enterococcus | 9 | 0.4 | 1.77 | - | |
| Escherichia coli | 395 | 20.5 | - | 27.9 | |
| Klebsiella | 326 | 16.9 | - | 23.0 | |
| Acinetobacter | 268 | 13.9 | - | 18.9 | |
| Pseudomonas | 220 | 11.4 | - | 15.5 | |
| Citrobacter | 69 | 3.5 | - | 4.8 | |
| Proteus | 89 | 4.6 | - | 6.2 | |
| Others | 46 | 2.3 | - | 3.2 | |
| Enterobacter | |||||
| Stenotrophomonas | |||||
Table 3 describes antibiotic susceptibility patterns in the analyzed samples. MRSA strains exhibited 100.0% susceptibility to linezolid and 85.0% susceptibility to levofloxacin, but showed relatively low susceptibility to erythromycin (27.0%) and clindamycin (24.0%). On the other hand, methicillin-susceptible S. aureus (MSSA) strains demonstrated 100.0% susceptibility to linezolid, 90.0% susceptibility to clindamycin, and relatively high susceptibility to levofloxacin (88.2%) and erythromycin (64.0%).
Table 3. Antibiotic susceptibility pattern of sampled specimens.
| Microorganism | Antibiotic | Susceptible (Count/Total) | Percentage (%) | |
|---|---|---|---|---|
| Antibiotic susceptibility for Staphylococcus aureus | ||||
| Methicillin-resistant S. aureus | Linezolid | 294/294 | 100.0 | |
| Tetracycline | 194/294 | 66.0 | ||
| Erythromycin | 59/294 | 27.0 | ||
| Levofloxacin | 250/294 | 85.0 | ||
| Clindamycin | 91/294 | 24.0 | ||
| Methicillin-susceptible S. aureus | Linezolid | 205/205 | 100 | |
| Levofloxacin | 181/205 | 88.2 | ||
| Tetracycline | 160/205 | 78.0 | ||
| Clindamycin | 143/205 | 90.0 | ||
| Erythromycin | 121/205 | 64.0 | ||
| Antibiotic susceptibility for Gram-negative bacteria | ||||
| Escherichia coli | Tigecycline | (385/395) | 97.4 | |
| Levofloxacin | (332/395) | 84.0 | ||
| Piperacillin-tazobactam | (281/395) | 32.4 | ||
| Amikacin | (296/395) | 75.0 | ||
| Amoxicillin-clavulanic acid | (31/395) | 7.8 | ||
| Imipenem | (179/395) | 45.0 | ||
| Ceftriaxone | (88/395) | 22.2 | ||
| Cefoperazone-sulbactam | (21/395) | 6.8 | ||
| Piperacillin-tazobactam | (225/395) | 57.8 | ||
| Klebsiella spp. | Tigecycline | (306/326) | 94.0 | |
| Levofloxacin | (179/326) | 55.0 | ||
| Imipenem | (84/326) | 26.2 | ||
| Ceftazidime-tazobactam | (49/326) | 15.0 | ||
| Ceftriaxone | (91/326) | 28.0 | ||
| Amikacin | (71/326) | 22.0 | ||
| Piperacillin-tazobactam | (101/326) | 31.0 | ||
| Cefoperazone-sulbactam | (178/326) | 54.7 | ||
| Ampicillin-sulbactam | (11/326) | 3.0 | ||
| Pseudomonas spp. | Imipenem | (39/220) | 18.1 | |
| Piperacillin-tazobactam | (40/220) | 13.1 | ||
| Ceftazidime-tazobactam | (25/220) | 5.7 | ||
| Tobramycin | (34/220) | 35.9 | ||
| Levofloxacin | (40/220) | 77.5 | ||
| Amikacin | (42/220) | 19.0 | ||
| Colistin | (186/220) | 84.0 | ||
| Aztreonam | (48/220) | 31.8 | ||
| Actinobacter spp. | Tigecycline | (245/268) | 93.3 | |
| Piperacillin-tazobactam | (46/268) | 17.1 | ||
| Cefoperazone | (150/268) | 56.1 | ||
| Imipenem | (80/268) | 29.8 | ||
| Amikacin | (99/268) | 36.9 | ||
| Ciprofloxacin | (21/268) | 7.8 | ||
| Ceftazidime-tazobactam | (12/268) | 4.4 | ||
| Cefoperazone-sulbactam | (90/268) | 30.8 | ||
E. coli displayed high susceptibility to tigecycline (97.4%) and amikacin (75.0%), but lower susceptibility to imipenem (45.0%), piperacillin-tazobactam (57.8%), and ceftriaxone (22.2%). Klebsiella spp. exhibited high susceptibility to tigecycline (94.0%) and cefoperazone-sulbactam (55.0%), but lower susceptibility to imipenem (26.2%), amikacin (22.0%), and ceftriaxone (28.0%). Pseudomonas spp. showed high susceptibility to colistin (84.0%) and levofloxacin (75.5%), but lower susceptibility to imipenem (18.1%) and piperacillin-tazobactam (13.1%). Acinetobacter spp. demonstrated high susceptibility to tigecycline (93.3%) but lower susceptibility to imipenem (29.8%), amikacin (36.9%), and piperacillin-tazobactam (17.1%).
Discussion
The present study aimed to investigate the bacteriological profile and antibiotic susceptibility patterns of pus isolates from wound infections in a tertiary care hospital in the Kashmir Valley. The findings reveal a significant burden of wound infections, with a positivity rate of 43.9% among the analyzed samples. This high rate underscores the importance of implementing effective infection control measures and promoting judicious antibiotic use in the study setting.
Gram-positive cocci, particularly S. aureus, emerged as the predominant pathogens associated with wound infections, accounting for 25.9% of the positive isolates. This observation is consistent with previous studies that have reported the dominance of S. aureus in wound infections [18,19]. Notably, 59.1% of the S. aureus isolates were MRSA, indicating a high prevalence of MDR strains. The high incidence of MRSA in wound infections poses a significant challenge in clinical management and highlights the need for stringent infection control practices and antimicrobial stewardship programs.
Among the Gram-negative pathogens, E. coli (27.9%) was the most prevalent organism, followed by Klebsiella, Acinetobacter, and Pseudomonas species. These findings align with the existing literature, which has consistently identified these Gram-negative bacteria as common etiological agents in wound infections, particularly in healthcare settings [20,21]. The presence of these pathogens, which are known to harbor various resistance mechanisms, underscores the importance of appropriate empirical antibiotic therapy and targeted treatment strategies.
While limited data exist on antibiotic resistance patterns in the Kashmir Valley, our findings show higher trends compared to neighboring regions. A study by Mir et al. in a tertiary care hospital in North India reported low rates of MRSA (32.2%) [22], comparable to our observed rate of 59.1%. Additionally, our study found a higher prevalence of Gram-negative isolates (73.5%) compared to their reported 40.0%, suggesting potential regional variations in pathogen distribution. These differences underscore the importance of local surveillance studies to inform targeted interventions.
The antibiotic susceptibility patterns observed in this study reveal concerning levels of resistance among the isolated pathogens. MRSA strains exhibited 100% susceptibility to linezolid, a promising finding as linezolid remains an effective treatment option for MRSA infections. However, the low susceptibility of MRSA to erythromycin (27.0%) and clindamycin (24.0%) is concerning, as these antibiotics are commonly used for the treatment of staphylococcal infections.
MSSA strains demonstrated high susceptibility to linezolid, clindamycin, and levofloxacin, indicating the potential utility of these antibiotics in treating MSSA infections. However, it is crucial to monitor the emergence of resistance to these agents through regular surveillance. Among the Gram-negative bacteria, E. coli displayed high susceptibility to tigecycline and amikacin but lower susceptibility to other commonly used antibiotics, such as imipenem, piperacillin-tazobactam, and ceftriaxone. Klebsiella spp. exhibited a similar pattern, with high susceptibility to tigecycline and cefoperazone-sulbactam but lower susceptibility to imipenem, amikacin, and ceftriaxone. These findings highlight the importance of tailoring antibiotic therapy based on local resistance patterns and emphasize the need for judicious use of broad-spectrum antibiotics. Pseudomonas spp. and Acinetobacter spp. displayed high susceptibility to colistin and tigecycline, respectively, but exhibited varying degrees of resistance to other commonly used antibiotics. These results are concerning, as Pseudomonas and Acinetobacter infections are associated with significant morbidity and mortality, particularly in immunocompromised and critically ill patients [23,24].
While our study primarily focused on antimicrobial susceptibility patterns, understanding the underlying resistance mechanisms is crucial for a comprehensive approach to combating antibiotic resistance. For instance, in S. aureus, methicillin resistance is primarily mediated by the mecA gene, which encodes for an altered penicillin-binding protein 2a [25]. In Gram-negative pathogens like P. aeruginosa and E. coli, resistance often involves multiple mechanisms, including the production of ESBLs and carbapenemases [26]. Efflux pumps, which actively expel antibiotics from bacterial cells, also play a significant role in multidrug resistance, particularly in P. aeruginosa [27]. Future studies should consider molecular characterization of isolated strains to identify specific resistance genes and their prevalence. This could include screening for genes like bla NDM, bla KPC, and bla OXA-48 in carbapenem-resistant isolates [28], or investigating the presence of mcr genes in colistin-resistant strains [29]. Understanding these molecular mechanisms could inform the development of novel therapeutic strategies and improve surveillance of emerging resistance patterns.
While this study provides valuable insights into the bacteriological profile and antibiotic susceptibility patterns of wound infections in the study region, it is essential to acknowledge some limitations. Firstly, the study was conducted in a single tertiary care hospital, and the findings may not be generalizable to other healthcare settings or geographical regions. The results may not represent variations across Kashmir. To address this limitation, the study could be expanded to include multiple hospitals across Kashmir. This would enhance external validity and provide a more comprehensive understanding of regional variations in wound infections and antibiotic resistance patterns. Secondly, this study provides valuable insights into antimicrobial resistance patterns in pus samples, it's important to acknowledge that focusing solely on this specimen type may limit the broader applicability of our findings. Different types of wound infections or specimen sources could potentially exhibit varying resistance patterns. For instance, surgical site infections, diabetic foot ulcers, or burn wounds might harbor distinct bacterial profiles or resistance mechanisms. Future research comparing resistance patterns across various wound types could provide a more comprehensive understanding of antimicrobial resistance in wound infections. This limitation in scope, while allowing for a focused analysis, suggests that our findings should be interpreted cautiously when considering other types of wound infections. Clinicians should consider these potential differences when applying our results to guide empiric antibiotic therapy for diverse wound presentations.
A limitation of our study is the absence of exploration into risk factors contributing to the observed antibiotic resistance patterns. While our findings provide valuable data on resistance trends, understanding the underlying factors driving these patterns could offer more comprehensive insights. Potential risk factors such as patients' prior antibiotic use, hospitalization history, underlying medical conditions, and demographic characteristics (e.g., age, gender, socioeconomic status) may play significant roles in the development and spread of antibiotic resistance. Future studies should aim to correlate these factors with resistance patterns to provide a more nuanced understanding of the issue. Additionally, exploring these risk factors could help clinicians make more informed decisions about empiric antibiotic therapy, potentially improving patient outcomes and reducing the further development of resistance. Our study's findings, therefore, should be viewed as a starting point for more in-depth investigations into the complex interplay between patient factors and antibiotic resistance in wound infections.
While our study provides important data on current resistance patterns, we acknowledge the limitation of its cross-sectional nature. Future research should consider implementing longitudinal surveillance to monitor changes in resistance patterns over time. This approach could reveal emerging trends, seasonal variations, and the impact of interventions on resistance rates, thereby informing more dynamic and responsive treatment guidelines and infection control practices. Also, our study focused primarily on microbiological findings and susceptibility patterns. Future research would benefit from integrating data on patient outcomes, treatment regimens, and infection control practices. Such clinical correlations could provide insights into the effectiveness of different antibiotic regimens based on susceptibility profiles and the impact of specific infection control measures on patient outcomes. This more comprehensive approach would bridge the gap between laboratory findings and clinical practice, potentially improving patient care and informing evidence-based antimicrobial stewardship policies.
This study highlights the significant burden of wound infections and the alarming prevalence of MDR pathogens, particularly MRSA, in the study setting. The observed antibiotic resistance patterns emphasize the need for implementing comprehensive antimicrobial stewardship programs, strengthening infection control measures, and promoting judicious antibiotic use. Regular surveillance, education, and research efforts are crucial to combat the rising threat of antibiotic resistance and ensure effective management of wound infections in the region.
To address the alarming prevalence of MDR pathogens observed in this study, we recommend implementing the following measures:
a) Establish robust antibiotic stewardship programs in healthcare facilities, emphasizing appropriate antibiotic selection and duration of therapy [30].
b) Conduct regular educational sessions for healthcare providers on judicious antibiotic use and the latest antimicrobial resistance trends.
c) Enhance infection control measures, including strict hand hygiene protocols and proper wound care practices.
d) Implement ongoing surveillance of antibiotic resistance patterns to guide empiric therapy choices and policy decisions.
e) Launch public awareness campaigns to educate the community about the dangers of antibiotic misuse and the importance of adherence to prescribed treatments [31].
These targeted interventions, tailored to the unique challenges of the Kashmir Valley, are crucial for mitigating the escalation of antibiotic resistance and ensuring effective management of wound infections in the region.
Footnotes
Funding: None.
Conflict of Interest: No conflict of interest.
- Conceptualization: NN, TM.
- Data curation: NN, TM, DA.
- Formal analysis: DA.
- Investigation: NN, TM.
- Methodology: NN, TM.
- Project administration: NN, TM.
- Supervision: NN, TM.
- Writing - original draft: NN, TM.
- Writing - review & editing: NN, TM, DA.
- Validation: NN, TM.
References
- 1.Percival SL, Suleman L. Slough and biofilm: removal of barriers to wound healing by desloughing. J Wound Care. 2015;24:498, 500–493, 506–410. doi: 10.12968/jowc.2015.24.11.498. [DOI] [PubMed] [Google Scholar]
- 2.Trojan R, Razdan L, Singh N. Antibiotic susceptibility patterns of bacterial isolates from pus samples in a tertiary care hospital of Punjab, India. Int J Microbiol. 2016;2016:9302692. doi: 10.1155/2016/9302692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bowler PG, Duerden BI, Armstrong DG. Wound microbiology and associated approaches to wound management. Clin Microbiol Rev. 2001;14:244–269. doi: 10.1128/CMR.14.2.244-269.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Allegranzi B, Bagheri Nejad S, Combescure C, Graafmans W, Attar H, Donaldson L, Pittet D. Burden of endemic health-care-associated infection in developing countries: systematic review and meta-analysis. Lancet. 2011;377:228–241. doi: 10.1016/S0140-6736(10)61458-4. [DOI] [PubMed] [Google Scholar]
- 5.Kefale B, Tegegne GT, Degu A, Molla M, Kefale Y. Surgical site infections and prophylaxis antibiotic use in the surgical ward of public hospital in Western Ethiopia: a hospital-based retrospective cross-sectional study. Infect Drug Resist. 2020;13:3627–3635. doi: 10.2147/IDR.S281097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Frykberg RG, Banks J. Challenges in the treatment of chronic wounds. Adv Wound Care (New Rochelle) 2015;4:560–582. doi: 10.1089/wound.2015.0635. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Bessa LJ, Fazii P, Di Giulio M, Cellini L. Bacterial isolates from infected wounds and their antibiotic susceptibility pattern: some remarks about wound infection. Int Wound J. 2015;12:47–52. doi: 10.1111/iwj.12049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Puca V, Marulli RZ, Grande R, Vitale I, Niro A, Molinaro G, Prezioso S, Muraro R, Di Giovanni P. Microbial species isolated from infected wounds and antimicrobial resistance analysis: data emerging from a three-years retrospective study. Antibiotics (Basel) 2021;10:1162. doi: 10.3390/antibiotics10101162. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tamma PD, Cosgrove SE, Maragakis LL. Combination therapy for treatment of infections with Gram-negative bacteria. Clin Microbiol Rev. 2012;25:450–470. doi: 10.1128/CMR.05041-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Uçkay I, Aragón-Sánchez J, Lew D, Lipsky BA. Diabetic foot infections: what have we learned in the last 30 years? Int J Infect Dis. 2015;40:81–91. doi: 10.1016/j.ijid.2015.09.023. [DOI] [PubMed] [Google Scholar]
- 11.Alghizzi M, Shami A. The prevalence of Staphylococcus aureus and methicillin resistant Staphylococcus aureus in milk and dairy products in Riyadh, Saudi Arabia. Saudi J Biol Sci. 2021;28:7098–7104. doi: 10.1016/j.sjbs.2021.08.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Upreti N, Rayamajhee B, Sherchan SP, Choudhari MK, Banjara MR. Prevalence of methicillin resistant Staphylococcus aureus, multidrug resistant and extended spectrum β-lactamase producing Gram negative bacilli causing wound infections at a tertiary care hospital of Nepal. Antimicrob Resist Infect Control. 2018;7:121. doi: 10.1186/s13756-018-0408-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Laxminarayan R, Duse A, Wattal C, Zaidi AK, Wertheim HF, Sumpradit N, Vlieghe E, Hara GL, Gould IM, Goossens H, Greko C, So AD, Bigdeli M, Tomson G, Woodhouse W, Ombaka E, Peralta AQ, Qamar FN, Mir F, Kariuki S, Bhutta ZA, Coates A, Bergstrom R, Wright GD, Brown ED, Cars O. Antibiotic resistance-the need for global solutions. Lancet Infect Dis. 2013;13:1057–1098. doi: 10.1016/S1473-3099(13)70318-9. [DOI] [PubMed] [Google Scholar]
- 14.Garcia LS, Isenberg HD. Clinical Microbiology Procedures Handbook. 3rd ed. Washington, DC: ASM Press; 2010. [Google Scholar]
- 15.Baron S. Medical microbiology. 4th ed. Galveston, TX: University of Texas Medical Branch at Galveston; 1996. [PubMed] [Google Scholar]
- 16.Dawodu OG, Akanbi RB. Isolation and identification of microorganisms associated with automated teller machines on Federal Polytechnic Ede campus. PLoS One. 2021;16:e0254658. doi: 10.1371/journal.pone.0254658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Chanda W, Manyepa M, Chikwanda E, Daka V, Chileshe J, Tembo M, Kasongo J, Chipipa A, Handema R, Mulemena JA. Evaluation of antibiotic susceptibility patterns of pathogens isolated from routine laboratory specimens at Ndola Teaching Hospital: a retrospective study. PLoS One. 2019;14:e0226676. doi: 10.1371/journal.pone.0226676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Idowu OJ, Onipede AO, Orimolade AE, Akinyoola LA, Babalola GO. Extended-spectrum beta-lactamase orthopedic wound infections in Nigeria. J Glob Infect Dis. 2011;3:211–215. doi: 10.4103/0974-777X.83524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Lister PD, Wolter DJ, Hanson ND. Antibacterial-resistant Pseudomonas aeruginosa: clinical impact and complex regulation of chromosomally encoded resistance mechanisms. Clin Microbiol Rev. 2009;22:582–610. doi: 10.1128/CMR.00040-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Peleg AY, Seifert H, Paterson DL. Acinetobacter baumannii: emergence of a successful pathogen. Clin Microbiol Rev. 2008;21:538–582. doi: 10.1128/CMR.00058-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Barlam TF, Cosgrove SE, Abbo LM, MacDougall C, Schuetz AN, Septimus EJ, Srinivasan A, Dellit TH, Falck-Ytter YT, Fishman NO, Hamilton CW, Jenkins TC, Lipsett PA, Malani PN, May LS, Moran GJ, Neuhauser MM, Newland JG, Ohl CA, Samore MH, Seo SK, Trivedi KK. Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis. 2016;62:e51–e77. doi: 10.1093/cid/ciw118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Mir BA, Srikanth Prevalence and antimicrobial susceptibility of methicillin resistant Staphylococcus aureus and coagulase-negative staphylococci in a tertiary care hospital. Asian J Pharm Clin Res. 2013;6(Suppl 3):231–234. [Google Scholar]
- 23.Allegranzi B, Pittet D. Preventing infections acquired during health-care delivery. Lancet. 2008;372:1719–1720. doi: 10.1016/S0140-6736(08)61715-8. [DOI] [PubMed] [Google Scholar]
- 24.Aiken AM, Allegranzi B, Scott JA, Mehtar S, Pittet D, Grundmann H. Antibiotic resistance needs global solutions. Lancet Infect Dis. 2014;14:550–551. doi: 10.1016/S1473-3099(14)70709-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Lakhundi S, Zhang K. Methicillin-Resistant Staphylococcus aureus: Molecular characterization, evolution, and epidemiology. Clin Microbiol Rev. 2018;31:e00020–e00018. doi: 10.1128/CMR.00020-18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Pang Z, Raudonis R, Glick BR, Lin TJ, Cheng Z. Antibiotic resistance in Pseudomonas aeruginosa: mechanisms and alternative therapeutic strategies. Biotechnol Adv. 2019;37:177–192. doi: 10.1016/j.biotechadv.2018.11.013. [DOI] [PubMed] [Google Scholar]
- 27.Li XZ, Plésiat P, Nikaido H. The challenge of efflux-mediated antibiotic resistance in Gram-negative bacteria. Clin Microbiol Rev. 2015;28:337–418. doi: 10.1128/CMR.00117-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Nordmann P, Poirel L. Epidemiology and diagnostics of carbapenem resistance in Gram-negative bacteria. Clin Infect Dis. 2019;69(Suppl 7):S521–S528. doi: 10.1093/cid/ciz824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Liu YY, Wang Y, Walsh TR, Yi LX, Zhang R, Spencer J, Doi Y, Tian G, Dong B, Huang X, Yu LF, Gu D, Ren H, Chen X, Lv L, He D, Zhou H, Liang Z, Liu JH, Shen J. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect Dis. 2016;16:161–168. doi: 10.1016/S1473-3099(15)00424-7. [DOI] [PubMed] [Google Scholar]
- 30.Giamarellou H, Galani L, Karavasilis T, Ioannidis K, Karaiskos I. Antimicrobial stewardship in the hospital setting: a narrative review. Antibiotics (Basel) 2023;12:1557. doi: 10.3390/antibiotics12101557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Sakeena MHF, Bennett AA, McLachlan AJ. Non-prescription sales of antimicrobial agents at community pharmacies in developing countries: a systematic review. Int J Antimicrob Agents. 2018;52:771–782. doi: 10.1016/j.ijantimicag.2018.09.022. [DOI] [PubMed] [Google Scholar]