Resistance Patterns of Gram-Negative Bacteria and Surgical Site Infections Across the Middle East: A Systematic Review and Meta-Analysis

Introduction Surgical site infections (SSIs) are a leading healthcare-associated infection, driven by multidrug-resistant Gram-negative bacteria. Regional data from the Middle East remain limited. This meta-analysis aimed to estimate pooled antimicrobial resistance (AMR) profiles of Gram-negative isolates (GNI) recovered from SSIs. Methods PubMed/MEDLINE and Google Scholar were searched in January 2026 for studies reporting AMR in SSI GNI. Eligible studies were English-language reports from the Middle East presenting AMR patterns of Gram-negative bacteria recovered from SSIs. Case reports, laboratory and animal studies, conference papers, and abstract-only publications were ineligible. Proportions were pooled using DerSimonian-Laird random-effects models with Freeman-Tukey double-arcsine transformation, heterogeneity assessed by I². Results Twenty-three studies from 8 countries were included. GNI comprised 71.9% (95% CI 60.5-82.2) of all culture-positive isolates and, when restricted to SSI-confirmed specimens, 86.4% (95% CI 63.6-99.3). Escherichia coli was most frequent (27.9%), followed by Pseudomonas aeruginosa (25.8%) and Klebsiella pneumoniae (21.3%). Resistance exceeded 65% for ampicillin in E. coli and for ceftriaxone in both E. coli and K. pneumoniae, with resistance to the remaining third-generation cephalosporins (cefotaxime, ceftazidime) ranging from 46.5% to 85.9%. Conclusion Gram-negative SSI isolates in the Middle East showed high resistance across many agent classes, with substantial multidrug resistance, carbapenem resistance, and ESBL production. This regional resistance profile reinforces the need for local, SSI-specific surveillance and antimicrobial stewardship. Introduction Surgical site infections (SSIs) are among the most frequent and challenging complications following surgical procedures, significantly impacting patient outcomes, hospital costs, and quality of care worldwide. They are the most frequent healthcare-associated infection in low- and middle-income countries (LMICs) [1]. The proportion of SSIs is reported to be up to 27% of healthcare-associated infections in LMICs [2]. The pooled incidence of SSIs in LMICs is reported to be 5.9 per 100 surgical operations and 11.2 per 100 surgical patients, with rates reaching 11.7% after caesarean section [1]. Even though SSIs were historically dominated by Gram-positive organisms, current epidemiological data show the emergence of multidrug-resistant Gram-negative bacteria (MDR-GNB), which is clinically significant in various healthcare settings. The most commonly reported GNBs were Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. [3]. Despite the use of perioperative antibiotics, SSIs continue to burden postoperative patients, a problem attributed to the emergence of antimicrobial resistance (AMR) [4]. Globally, AMR is a dire health threat [4]. It is estimated to be responsible for approximately five million deaths annually [5]. In the United States, a significant number of pathogens contributing to the SSI were reported to be resistant to standard prophylactic antibiotics [6]. The problem of AMR is particularly pronounced in developing countries [7]. To address this threat, the World Health Organization (WHO) prioritizes antibiotic-resistant bacteria to guide research and control strategies. In its 2024 Bacterial Priority Pathogens List, GNB dominate the critical tier [8]. Despite this global attention, robust regional data regarding resistance patterns in SSI from the Middle East remain scarce [6]. Continuous surveillance is therefore needed and requires a systematic approach that accounts for patient-, procedure-, and environment-related risk factors [9]. This systematic review and meta-analysis aimed to estimate the regional pooled antibiotic-resistance profiles of Gram-negative isolates (GNI) recovered from SSI. Methods Study Protocol This systematic review and meta-analysis study was conducted in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement guidelines. Data Sources and Search Strategy A comprehensive systematic search was conducted in PubMed/MEDLINE and Google Scholar in January 2026 to identify published studies reporting antibiotic resistance patterns of GNI from SSIs in the Middle East. The search strings were as follows. PubMed/MEDLINE: ("Antimicrobial Resistance"[tiab] OR "Antibiotic Resistance"[tiab] OR MDR[tiab] OR "multidrug-resistant"[tiab]) AND ("Surgical Wound Infection"[Mesh] OR "Surgical Site Infection"[ti] OR SSI[ti] OR "Postoperative Wound Infection"[ti]) AND ("Gram-Negative Bacteria"[Mesh] OR Enterobacteriaceae[tiab] OR "Escherichia coli"[tiab] OR "Klebsiella pneumoniae"[tiab] OR "Pseudomonas aeruginosa"[tiab] OR "Acinetobacter baumannii"[tiab]). Google Scholar: allintitle: "Gram negative" OR Enterobacteriaceae OR "Escherichia coli" OR "E coli" OR Klebsiella OR Pseudomonas OR Acinetobacter "Wound Infection" OR "Surgical Wound Infection" OR "Surgical Site Infection". Manual citation searching of all retrieved articles was performed for additional relevant studies. Eligibility Criteria Studies were included if: (1) they were published in English; (2) reported human clinical samples of GNI recovered from SSIs; (3) reported AMR patterns for SSI GNI; (4) were conducted in the Middle East, which for this review was defined as the transcontinental region comprising the Arabian Peninsula, the Levant, Iraq, Iran, Türkiye, and Egypt; and (5) for studies that sampled mixed clinical specimens, SSI-specific isolates and their antimicrobial-susceptibility data could be extracted separately. Studies were excluded if they: (1) had insufficient data on bacterial species identification, antimicrobial susceptibility testing, or confirmation of SSI; (2) were case reports, in vitro or animal studies, or conference papers; (3) were abstract-only publications; or (4) were in non-recommended journals/publishers [10]. Study Selection Process Two reviewers independently screened the titles and abstracts of all studies to identify studies meeting the eligibility criteria. Retrieved eligible articles underwent full-text review by both reviewers. A third reviewer was enlisted to cast the deciding vote and resolve discrepancies by evaluating conflicting data and reaching a consensus. Duplicate records were removed manually. Data-Collection Process Two reviewers independently extracted data using a structured Microsoft Excel spreadsheet. Discrepancies in extracted data were resolved by consulting a third reviewer. Data extracted from eligible studies included: (1) study characteristics (first author, year of publication, country, study design, study period, and sample size); (2) patient characteristics included demographic variables (age, sex), type of surgery, surgical urgency (elective and emergency), surgical wound classification (clean, clean contaminated, contaminated, dirty), and SSI classification (superficial incisional, deep incisional, organ/space); (3) microbiological profile included total clinical sample counts, culture-positive isolate counts, microbial growth patterns (monomicrobial and polymicrobial), the total number of Gram-negative isolates (GNI), and the number of GNI recovered specifically from SSIs (SSI-specific GNI, i.e., defined by specimen source rather than by species); (4) susceptibility of antimicrobials for SSI-specific GNI across the following antibiotic classes: aminoglycosides (gentamicin, amikacin), carbapenems (imipenem, meropenem), cephalosporins (cefotaxime, ceftazidime, ceftriaxone, cefepime, cefoxitin, cefuroxime), fluoroquinolones (ciprofloxacin, levofloxacin), folate pathway inhibitors (co-trimoxazole), beta-lactam beta-lactamase inhibitors (ampicillin/sulbactam, piperacillin/tazobactam, amoxicillin/clavulanate), penicillins (ampicillin) and monobactams (aztreonam); and (5) antibiotic resistance patterns: MDR, extended-spectrum beta-lactamase (ESBL) and carbapenem resistance (CR). For studies reporting mixed clinical specimens, only data that could be specifically attributed to surgical site infections were extracted for SSI-specific resistance analyses. Outcomes The primary outcome was the AMR profile of GNI recovered from SSIs. For each species, this comprised the pooled proportion of resistance to each individual antimicrobial agent, together with the pooled proportions of isolates classified as MDR, CR, and ESBL-producing. Secondary outcomes were (i) the pooled proportion of GNI among all culture-positive isolates recovered by the included studies (the all-isolate denominator), (ii) the pooled proportion of GNI among isolates confirmed to derive from SSIs (the SSI-restricted denominator), and (iii) the pooled prevalence of each individual species among SSI GNI. These outcomes characterize the organisms that underlie the resistance estimates. Pooled proportions of MDR, CR, and ESBL production were analyzed only when these categories were classified and reported by the primary studies themselves; they were not derived from agent-level resistance percentages. Accordingly, the number of studies and isolates contributing to the MDR, CR, and ESBL estimates may differ from those contributing to agent-level resistance estimates. Quality Assessment Methodological quality was appraised using design-specific Joanna Briggs Institute critical appraisal checklists [11]. Studies were assessed using the checklist corresponding to their design: cross-sectional (8 items), case-control (10 items), cohort (11 items), or case series (10 items). These appraisals informed the risk-of-bias domain of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) certainty assessment. Data Analysis Data were analyzed using the meta package in R version 4.6.0. Proportions were pooled using a DerSimonian-Laird random-effects model with the Freeman-Tukey double-ar