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Article

Microbial Multidrug-Resistant Organism (MDRO) Mapping of Intensive Care Unit Infections

by
Ahmed Yassin
1,
Ragaey Ahmad Eid
2,*,
Mohammad Farouk Mohammad
3,
Marwa O. Elgendy
4,*,
Zeinab Mohammed
5,
Mohamed E. A. Abdelrahim
6,
Ahmed M. Abdel Hamied
7,
Reem Binsuwaidan
8,
Asmaa Saleh
8,
Mona Hussein
9 and
Eman Hamdy Mohamed
10
1
Department of Critical Care Medicine, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
2
Department of Gastroenterology, Hepatology and Infectious Diseases, (Tropical Medicine Department), Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
3
Department of Chest Diseases, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
4
Department of Clinical Pharmacy, Beni-Suef University Hospitals, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
5
Department of Public Health and Community Medicine, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
6
Clinical Pharmacy Department, Faculty of Pharmacy, Beni-Suef University, Beni-Suef 62521, Egypt
7
Department of Pediatrics, Faculty of Medicine, Nahda University (NUB), Beni-Suef 62513, Egypt
8
Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
9
Department of Neurology, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
10
Department of Clinical and Chemical Pathology, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
*
Authors to whom correspondence should be addressed.
Medicina 2025, 61(7), 1220; https://doi.org/10.3390/medicina61071220
Submission received: 1 May 2025 / Revised: 6 June 2025 / Accepted: 30 June 2025 / Published: 4 July 2025
(This article belongs to the Section Intensive Care/ Anesthesiology)
Browse Figure
Versions Notes

Abstract

Background and Objectives: This study aims to identify risk factors associated with MDRO infections and assess their impact on patient outcomes in Egyptian ICUs. Materials and Methods: The widespread overuse of antimicrobials has led to antibiotic multidrug resistance, posing significant challenges in intensive care units (ICUs) and leading to increased morbidity, mortality, and healthcare costs. A prospective observational study was conducted over 12 months, including 113 adult patients admitted to the ICU with confirmed bacterial infections. Comprehensive medical assessments and routine investigations were performed, including multisource cultures based on clinical suspicion. Patient histories, underlying conditions, and disease progression were documented. Patients were classified into two groups: those infected with MDROs and those without MDRO infections. Results: Significant differences were observed between patients with and without MDRO infections regarding temperature, pH, PaO2, HCO3, serum creatinine levels, high-dose inotropes, and inotrope dependence (p-values: 0.01, 0.028, 0.036, 0.008, <0.001, 0.013, 0.029, 0.039, <0.001, and 0.003, respectively). Additionally, cerebrovascular stroke and renal failure were significantly more frequent in MDRO-infected patients (p-values: 0.048 and 0.007, respectively). MDROs accounted for 42% of infections. The most commonly detected MDRO was Klebsiella spp. (52%). Patients with MDRO infections showed significantly higher mortality (42.6%), increased incidence of ARDS, invasive ventilation, and longer ventilation durations. Independent risk factors included prior antibiotic use (OR: 3.2; 95% CI: 1.5–6.8) and invasive device presence (OR: 2.7; 95% CI: 1.2–5.9). Conclusions: Cerebrovascular stroke and renal failure appear to be risk factors for MDRO infections. MDRO infections in ICUs are associated with poor clinical outcomes and increased complications. Improved antimicrobial stewardship and targeted prevention strategies are urgently required.

1. Introduction

Antimicrobial resistance remains one of the most pressing global health threats [1]. Critically ill patients in ICUs are particularly vulnerable due to frequent invasive procedures and broad-spectrum antibiotic use [2]. Globally, the post-COVID-19 era has seen a surge in MDRO prevalence, partially due to empirical antibiotic use during viral infections [3].
In fact, the genes responsible for drug resistance in certain bacterial strains predate antibiotics by millions of years [4]. However, the growing prevalence of multidrug resistance has become an increasingly serious challenge, leaving healthcare providers to combat a formidable enemy with limited resources [5].
Patients in intensive care units (ICUs) are particularly vulnerable to infections due to their critical conditions, which can weaken immune responses [6]. Additionally, their frequent exposure to invasive medical devices further increases the risk of infection [7].
Studies estimate that up to 50% of ICU patients receive empirical antibiotic therapy before the specific infecting organism is identified, significantly contributing to the spread of multidrug-resistant organisms (MDROs). Strong evidence suggests a direct correlation between antibiotic resistance rates and antibiotic consumption [8].
The Centers for Disease Control and Prevention (CDC) has identified the global increase in MDROs as a major therapeutic challenge that significantly affects patient outcomes in ICUs [9]. Consequently, infection prevention and management are crucial in reducing morbidity and mortality in these settings [10].
The emergence and proliferation of multidrug-resistant organisms (MDROs) in intensive care units (ICUs) represent a significant global health concern. ICUs are particularly susceptible due to the high usage of broad-spectrum antibiotics, invasive procedures, and the presence of immunocompromised patients [11]. Recent Egyptian data indicate carbapenem-resistant Klebsiella pneumoniae (CRKP) prevalence rates ranging from 14.2% to 66%, emphasizing the need for localized research [12]. This study aims to identify MDRO infection risk factors and outcomes to guide antimicrobial stewardship and infection control strategies.

2. Materials and Methods

2.1. Study Design and Setting

This prospective observational study was conducted on 113 culture-positive ICU patients diagnosed with infection either clinically or based on investigations. Patients were recruited from the General ICU, Surgical ICU, Chest ICU, and Tropical intermediate care unit between August 2022 and August 2023. Informed consent was obtained for each patient, and the study received ethical approval (FMBSUREC/02102022/Mohamed).

2.2. Inclusion and Exclusion Criteria

Inclusion: Adult patients (≥18 years) with culture-confirmed bacterial infections were included.
  • Exclusion
Patients with irreversible brain damage, acute or chronic neuromuscular diseases; those on immunosuppressive therapy for any indication; individuals with terminal malignancies, end-stage idiopathic pulmonary fibrosis, end-stage organ failure, pregnant women; and culture-negative patients were excluded. A flow diagram of the included and excluded patients is demonstrated in Figure 1.

2.3. Definition of MDROs

MDROs were defined as microorganisms resistant to at least one agent in three or more antimicrobial classes, in accordance with CDC and ECDC criteria.

2.4. Data Collection

Data included demographics, comorbidities (e.g., diabetes mellitus, chronic kidney disease), prior antibiotic use within 90 days, invasive devices, labs, and clinical outcomes. ICU interventions and organ failure were documented using the qSOFA and Glasgow Coma Scale.

2.5. Clinical Assessment

The patients underwent comprehensive clinical assessments, including detailed examinations of the cardiac, respiratory, abdominal, and neurological examination. Consciousness level was evaluated using the Glasgow Coma Scale [13]. Additionally, organ failure was assessed using the quick Sequential Organ Failure Assessment score [14]. It was calculated based on laboratory and clinical data recorded within 48 h of ICU admission.
The following clinical variables were documented: admission temperature, heart rate, respiratory rate and oxygen saturation were noted, need for vasopressors (including dopamine, epinephrine, norepinephrine, and dobutamine) and their prescribed doses (low dose: less than half of the dose rang or high dose: higher than half of the dose rang), requirement and duration of mechanical ventilation (invasive and non-invasive), and patients’ ICU stay. Corrected durations were calculated to overcome the problem of mortality bias.
Infection vs. Colonization: Infection was defined by the presence of clinical signs and symptoms consistent with infection, accompanied by a positive culture from a sterile site. Colonization, identified by positive cultures without clinical signs of infection, was excluded from the analysis.

2.6. Infection Sites

Infections were categorized based on their sites: respiratory tract (sputum culture), urinary tract (urine culture), blood (blood culture), and others (intra-abdominal, soft tissue, pleural fluid, and acetic fluid).

2.7. Laboratory and Culture Techniques

Baseline laboratory data retrieved from patient files included inflammatory markers (C-reactive protein and erythrocyte sedimentation rate, when indicated), hemoglobin, hematocrit, white blood cells, platelets, creatinine, sodium (Na), potassium (K), AST, ALT, PH, PCO2, PaO2, HCO3, and cultures results (sputum, blood, urine, etc.) according to the clinical need.
Regarding cultures, samples were obtained within the first 24 h of ICU admission, and their standard operating procedures were established for all procedures, including sample collection, transport, registration, processing, and reporting. Kirby–Bauer disk diffusion and automated Vitek 2 (Biomerieux, Marcy-l’Étoile, France) systems were used. The results were interpreted per CLSI 2020 guidelines.
The Clinical Laboratory and Standards Institute standards [15] served as references for laboratory methods. The pathogen identification of isolates and antimicrobial susceptibility testing were performed using the automated Vitek 2 system (Biomerieux, Marcy-l’Étoile, France).
Outcomes: Patients were followed until discharge or death in the hospital for a maximum of 30 days from ICU admission.

2.8. Sample Size Calculation

The sample size was calculated using Epi Info v3.5.1. Based on a previous study (Rodríguez-Villodres et al., 2021) with an MDRO prevalence at 11.6% [16], a minimum of 111 patients was required to achieve a 95% confidence level and 5% margin of error.

2.9. Statistical Analysis

Data were analyzed using SPSS version 24.0 (IBM, Armonk, NY, USA). Continuous variables are expressed as mean ± SD or median (IQR), and categorical variables are reported as frequencies and percentages. Univariate analyses were performed using the chi-square test or Fisher’s exact test for categorical variables and a t-test or Mann–Whitney U test for continuous variables. Variables with p < 0.1 in univariate analysis were included in a multivariate logistic regression model to identify the independent risk factors for MDRO infections. False discovery rate (FDR) correction was applied for the key outcomes. A p-value < 0.05 was considered statistically significant.

3. Results

3.1. Patient Demographics and Baseline Characteristics

The mean age of the 113 patients enrolled was 53 ± 14.8 years; 56.6% were male. Of the 113 patients, 106 had bacterial infections (59 non-MDRO, 47 MDRO), and 7 had fungal infections (Figure 1).
Common comorbidities included diabetes mellitus, chronic kidney disease, and cerebrovascular accidents.
No significant differences were found between MDRO-infected and non-MDRO-infected patients regarding age or sex (p = 0.19 and 0.345, respectively) (Table 1).

3.2. Clinical and Laboratory Comparison Between MDRO and Non-MDRO Groups

After applying the Benjamini–Hochberg false discovery rate (FDR) correction, several differences remained statistically significant: temperature (p = 0.01), pH (p = 0.028), PaO2 (p = 0.036), HCO3 (p = 0.008), serum creatinine (p < 0.001), mortality (p = 0.013), ARDS incidence (p = 0.029), invasive ventilation use (p = 0.039), the need for inotropes (p = 0.003), and the use of high-dose inotropes (p < 0.001).
Other parameters (HR, RR, PCO2, hemoglobin, hematocrit value, TLC, PLT, the use of NIV, days on NIV, days on invasive ventilation, ICU stay, and hospital stay before admission to the ICU) showed no significant differences (Table 2).

3.3. Duration of Ventilation and ICU Stay

To address potential bias from early death in duration analysis, we conducted a sensitivity analysis using Kaplan–Meier survival curves, instead of assigning fixed 30-day durations.
  • Days on NIV (Mean ± SD): non-MDRO: 8.4 ± 11.4 vs. MDRO: 14.8 ± 13.8 (p = 0.011);
  • Days on invasive ventilation: non-MDRO: 6.4 ± 12.1 vs. MDRO: 12.8 ± 15 (p = 0.017).
Kaplan–Meier log-rank test confirmed prolonged ventilation in MDRO patients (p = 0.019). The total ICU stay remained non-significant (p = 0.086) (Table 3).

3.4. Comorbidities and Risk Factors

Significant comorbidities were more frequent in the MDRO group: cerebrovascular stroke (p = 0.048) and renal failure (p = 0.007). No significant differences were observed in diabetes (p = 0.69), hypertension (p = 0.98), heart failure, or IHD (Table 4).

3.5. MDRO Distribution by Site and Organism

Among the MDRO cases, Klebsiella spp. was the most common (52%), followed by Acinetobacter spp. (18%), Pseudomonas spp. (8%), and E. coli spp. (8%). The most frequent sites of isolation were sputum > blood > urine (Table 5).

3.6. Multivariate Logistic Regression Analysis

Independent predictors of MDRO infection were as follows:
  • Prior antibiotic use within 90 days (OR: 3.2; 95% CI: 1.5–6.8; p = 0.003);
  • Presence of invasive devices (OR: 2.7; 95% CI: 1.2–5.9; p = 0.01).

4. Discussion

This study evaluated 113 ICU patients with confirmed infections, finding that 42% were infected with MDROs, primarily Klebsiella spp. (52%), consistent with global concerns regarding carbapenem-resistant Enterobacteriaceae.
By analyzing regional data, we aimed to improve the local mapping of bacterial resistant organisms to enhance management strategies and predict infection outcomes for critically ill patients and the factors affecting them.
The post-COVID-19 environment has amplified MDRO challenges, with factors such as empirical antibiotic overuse and longer ICU stays contributing to rising resistance rates [17]. Our findings are aligned with global data, suggesting that 20–40% of ICU patients worldwide are affected by MDROs, though geographic and institutional variations are substantial [18].
Age, sex, heart rate, respiratory rate, admission systolic blood pressure, admission diastolic blood pressure, PCO2, hemoglobin, hematocrit value, TLC, platelet count, and hospital stay before admission to the ICU were similar between non-MDRO-infected patients and those with MDRO infections. Similarly, in another study [19], MDRO-infected patients had a similar age and gender distribution as controls. Also, groups spent a similar number of days in the hospital prior to infection. In contrast, another study [6] found that longer ICU stay prior to infection had higher rates of MDRO infections. This difference may be because none of our patients were admitted to the ICU, which may have reduced their exposure to MDROs [20].
Importantly, MDRO infections were associated with significantly worse clinical outcomes, including higher mortality (42.6%), greater need for inotropes, more frequent ARDS, and longer durations of mechanical ventilation. These outcomes underscore the clinical burden posed by MDROs in critical care.
Consistent with previous studies, serum creatinine was significantly higher in MDRO-infected patients, reflecting potential renal dysfunction as both a risk factor and consequence of infection. Additionally, arterial blood gas abnormalities (lower pH, PaO2, and HCO3) point to more severe physiological compromise in the MDRO group.
Regarding comorbidities, renal failure and cerebrovascular stroke were significantly associated with MDRO infection. These conditions may reflect both increased susceptibility and greater healthcare exposure [21]. Our findings are in agreement with those of Su et al. (2018) [22], who reported a strong link between chronic kidney disease and MDRO colonization/infection.
Other risks include broad-spectrum antibiotic use, malnutrition, invasive procedures, and infections from hemodialysis [23]. Patients with kidney disease have impaired immune systems, which persist despite treatments like dialysis [24]. Additionally, Alsehemi et al. noted significantly higher incidence of stroke (p = 0.046) and hemiplegia (p = 0.007) in MDRO-infected patients [25]. Heart failure, hypertension, and ischemic heart disease were similar in both groups, and unexpectedly, diabetes mellitus was not significantly associated with MDROs in our cohort, in contrast to multiple studies suggesting a higher MDRO risk in diabetics [26], particularly in diabetic foot infections [27]. In contrast, Trivedi et al. noted a non-significantly higher prevalence of MDROs in wounds of diabetic patients [28]. This discrepancy may stem from our study’s relatively low diabetes prevalence (35%) or differing patterns of antimicrobial use. Methodological differences, including study design and infection type, may also account for this variation [29]. Most of the MDROs in our study were Gram-negative, similar to some studies that showed that Gram-negative bacteria outnumber Gram-positive bacteria in patients with numerous injuries [25]. Cohen et al. [30] found that mortality rates were significantly higher in Gram-negative bacteremia, whereas Zahar et al. [31] did not find this correlation.
Our study found that Klebsiella species was the leading MDR pathogen in ICU patients, notably in sputum, blood, and urine cultures. This aligns with global concerns about carbapenem-resistant Klebsiella pneumoniae. It was followed by Acetobacter spp. Pseudomonas and E. Coli spp., and Enterobacter spp. were also present, especially in respiratory and urinary infections. Similar findings were reported worldwide [32]. Another study noted that the most common were Klebsiella species (27%), Escherichia coli (25%), Pseudomonas species (24%), and Acinetobacter species (17%) [33]. Also, others noted similar results [25]. In contrast, an earlier study showed that Enterococcus spp. (10.8%), Staphylococcus aureus (47.3%), and Candida spp. (10.1%) were the most common infections [34,35]. Also, in another study, E. coli was the most common organism (39.4%), followed by S. aureus (25.6%) and P. aeruginosa (18.2%) [36]. Another study noted that the predominant organisms were S. aureus (despite the overall predominance of Gram-negative organisms) [37]. Interestingly, Acinetobacter was involved in 9% of all infections, similar to the rate reported in the first EPIC study [38] but considerably higher than the 3.6% reported in the more recent SOAP study [37]. In another study, Acetobacter was notably present in sputum (16%) and urine (40%) cultures [39]. These variations are mostly due to differences in the studied population, location, and antimicrobial strategies in different regions of the world [40]. Regarding days on NIV, days on invasive ventilation, and ICU stay, they were similar in both groups (p = 0.55, 0.9, 0.36, respectively) but after adjustment of the stay of deceased patients to 30 days, we found significant difference in both days on NIV and days on invasive ventilation (p = 0.011 and 0.017, respectively), while total ICU stay remained similar in both groups (p = 0.086). The use of invasive ventilation was also significantly high in MDRO-infected patients (p = 0.039). Similarly, Magiraa et al. noted higher median days on ventilation after MDRO infection, which was not significant (p = 0.054). In contrast, they noted that MDRO-positive patients spent a greater median number of total days in hospital after infection (p = 0.005, OR = 1.04) [19]. There are some studies that showed little or no effect of multidrug resistance on the hospital stay [41]. It seems that comorbidities are the main determinants of prolonged hospital stay [42].
We observed a higher need for vasopressors and higher-dose inotrope use among MDRO patients, highlighting the role of these infections in hemodynamic instability and sepsis severity. Alkofide et al. found that MDRO infections often cause hemodynamic instability, necessitating more inotropes [43].
This supports the Surviving Sepsis Campaign’s emphasis on early, appropriate antimicrobial therapy [44].
The authors of [45] revealed that the association between MDROs and increased ARDS incidence (p = 0.029) and mortality (p = 0.013) may be related to the higher virulence of the organisms or the delayed initiation of effective antimicrobial therapy. This is supported by several other studies [46,47]. Despite the use of multivariate regression, residual confounding may exist. Variables such as colonization status prior to ICU admission, duration of antibiotic exposure, and environmental contamination were not controlled for.
We note that only clinically significant infections from sterile sites were included. Patients with colonization but no clinical symptoms were excluded, although the lack of molecular typing is a limitation in distinguishing strain-specific dynamics [48].
In contrast to studies that found no mortality differences [49], our data suggest that MDRO infections contribute directly to poor outcomes. However, further multicenter prospective studies with genetic typing are needed to confirm causality and explore transmission patterns.
The high prevalence of MDRO infections, particularly CRKP, in our ICU aligns with national data indicating variable but concerning rates of carbapenem resistance. The identification of prior antibiotic use and invasive devices as risk factors underscores the need for stringent antimicrobial stewardship and infection control practices [50].
The association between higher SOFA scores and MDRO infections suggests that patients with greater severity of illness are more susceptible, highlighting the importance of early identification and targeted interventions.
Our findings emphasize the necessity for localized surveillance data to inform empirical antibiotic therapy and guide infection prevention strategies.

Limitations

This study’s observational design and single-center setting may limit the generalizability of the findings. The absence of molecular typing precluded the identification of specific resistance genes. Additionally, the lack of correction for multiple comparisons in statistical analyses may increase the risk of Type I errors.

5. Conclusions

Our study highlights the high prevalence of multidrug-resistant organism (MDRO) infections in Egyptian intensive care units, with Klebsiella spp. (particularly carbapenem-resistant strains) emerging as the predominant pathogen. These infections were associated with significantly worse clinical outcomes, including increased mortality, higher incidence of ARDS, and prolonged need for mechanical ventilation and inotropic support. Independent risk factors such as prior antibiotic use within 90 days and the presence of invasive medical devices underscore the importance of strengthening antimicrobial stewardship programs and implementing rigorous infection prevention strategies.
While our findings support the urgency for localized interventions, we caution against generalizing these results due to the study’s single-center setting and lack of molecular resistance profiling. Thus, multicenter surveillance and genomic analysis are necessary to further understand resistance patterns and transmission dynamics.
Future directions should include integrating routine resistance monitoring, enhancing diagnostic capabilities, and fostering inter-hospital collaboration to curb the spread of MDROs and improve patient outcomes in critical care settings.

Author Contributions

Conception and design, A.Y. and R.A.E.; methodology, M.F.M., E.H.M. and M.H.; software, A.M.A.H.; validation and investigation, M.O.E. and R.A.E.; writing—original draft preparation, Z.M.; visualization, M.E.A.A., A.M.A.H., R.B. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP2025R304), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the faculty of Medicine Beni-Suef University (FMBSUREC/02102022/Mohamed, date of approval: 2 October 2022).

Informed Consent Statement

Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding authors upon reasonable request.

Acknowledgments

The authors extend their appreciation to Princess Nourah Bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R304), Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript.

References

  1. Abbas, A.M.; Hamed, R.M.R.; Elgendy, M.O.; Abdel Aziz, H.S. Prevalence and Antimicrobial Susceptibility Profile of Gram-negative and Gram-positive Bacteria in a Tertiary Hospital: A Retrospective Study. Egypt. J. Med. Microbiol. 2025, 34, 399028. [Google Scholar] [CrossRef]
  2. Naguib, M.M.; El-Gendy, A.O.; Khairalla, A.S. Microbial diversity of mer operon genes and their potential rules in mercury bioremediation and resistance. Open Biotechnol. J. 2018, 12, 56–77. [Google Scholar] [CrossRef]
  3. Elgendy, S.O.; Elgendy, M.O.; El-Gendy, A.O.; Hamied, A.M.A.; Al Amir, K.; Gad, R.A.; Fahmy, A.M. Health Care Workers’ Awareness about the Post-COVID Syndrome and Different Types of COVID-19 Vaccines in Egypt. NeuroQuantology 2022, 20, 3830. [Google Scholar]
  4. Hamed, M.O.; Abdel Wahab, M.; Abdel Monem, A.A.; Fathy, M.; Elgendy, A.O. Phenotypic and Genotypic Evaluation of Carbapenamase Producing Klebsiella Pneumoniae Isolates with Their Phylogenetic Analysis at an Egyptian University Hospital. Egypt. J. Med. Microbiol. 2022, 31, 25–31. [Google Scholar]
  5. O’Neill, J. Tackling Drug-Resistant Infections Globally: Final Report and Recommendations; Review on Antimicrobial Resistance; AMR Review: London, UK, 2016. [Google Scholar]
  6. Vincent, J.L.; Rello, J.; Marshall, J.; Silva, E.; Anzueto, A.; Martin, C.D.; Moreno, R.; Lipman, J.; Gomersall, C.; Sakr, Y.; et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009, 302, 2323–2329. [Google Scholar] [CrossRef]
  7. Tabah, A.; Koulenti, D.; Laupland, K.; Misset, B.; Valles, J.; Bruzzi de Carvalho, F.; Paiva, J.A.; Cakar, N.; Ma, X.; Eggimann, P.; et al. Characteristics and determinants of outcome of hospital-acquired bloodstream infections in intensive care units: The EUROBACT International Cohort Study. Intensive Care Med. 2012, 38, 1930–1945. [Google Scholar] [CrossRef]
  8. Rello, J. Latest Updates and Challenges in infections in intensive care medicine. J. Intensive Med. 2024, 4, 1–2. [Google Scholar] [CrossRef]
  9. Centers for Disease Control and Prevention. Antibiotic Resistance Threats in the United States; U.S. Department of Health and Human Services, CDC: Atlanta, GA, USA, 2019.
  10. Singer, M.; Deutschman, C.S.; Seymour, C.W.; Shankar-Hari, M.; Annane, D.; Bauer, M.; Bellomo, R.; Bernard, G.R.; Chiche, J.D.; Coopersmith, C.M.; et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016, 315, 801–810. [Google Scholar] [CrossRef]
  11. AbdelHalim, M.M.; El Sherbini, S.A.; Ahmed, E.S.S.; Gharib, H.A.A.; Elgendy, M.O.; Ibrahim, A.R.; Abdel Aziz, H.S. Management of Ventilator-Associated Pneumonia Caused by Pseudomonas and Acinetobacter Organisms in a Pediatric Center: A Randomized Controlled Study. Medicina 2024, 60, 2098. [Google Scholar] [CrossRef]
  12. Mousa, R.; El-Kady, M.F.; Hussein, A.A.; Ahmed, A.E.; El-Gendy, A.O. Occurrence of carbapenem multidrug-resistant Pseudomonas aeruginosa carrying blaVIM metallo-ß-lactamases and their biofilm phenotypes in Al-Azhar University Hospital. J. Appl. Pharm. Sci. 2022, 12, 73–81. [Google Scholar]
  13. Teasdale, G.; Jennett, B. Assessment of coma and impaired consciousness. A practical scale. Lancet 1974, 2, 81–84. [Google Scholar] [CrossRef]
  14. Vincent, J.L.; Moreno, R.; Takala, J.; Willatts, S.; De Mendonça, A.; Bruining, H.; Reinhart, C.K.; Suter, P.M.; Thijs, L.G. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996, 22, 707–710. [Google Scholar] [CrossRef]
  15. Weinstein, M.P.; Lewis, J.S., 2nd. The Clinical and Laboratory Standards Institute Subcommittee on Antimicrobial Susceptibility Testing: Background, Organization, Functions, and Processes. J. Clin. Microbiol. 2020, 58, e01864-19. [Google Scholar] [CrossRef]
  16. Rodríguez-Villodres, Á.; Martín-Gandul, C.; Peñalva, G.; Guisado-Gil, A.B.; Crespo-Rivas, J.C.; Pachón-Ibáñez, M.E.; Lepe, J.A.; Cisneros, J.M. Prevalence and Risk Factors for Multidrug-Resistant Organisms Colonization in Long-Term Care Facilities Around the World: A Review. Antibiotics 2021, 10, 680. [Google Scholar] [CrossRef]
  17. Elgendy, M.O.; Abdelrahman, M.A.; Osama, H.; El-Gendy, A.O.; Abdelrahim, M.E. Role of repeating quarantine instructions and healthy practices on COVID-19 patients and contacted persons to raise their awareness and adherence to quarantine instructions. Int. J. Clin. Pract. 2021, 75, e14694. [Google Scholar] [CrossRef]
  18. Bassetti, M.; Garau, J. Current and future perspectives in the treatment of multidrug-resistant Gram-negative infections. J. Antimicrob. Chemother. 2021, 76 (Suppl. S4), iv23–iv37. [Google Scholar] [CrossRef]
  19. Magira, E.E.; Islam, S.; Niederman, M.S. Multi-drug resistant organism infections in a medical ICU: Association to clinical features and impact upon outcome. Med. Intensiv. 2018, 42, 225–234. [Google Scholar] [CrossRef]
  20. El-Gendy, A.; Essam, T.; Amin, M.; Ahmed, S.; Nes, I. Clinical screening for bacteriocinogenic Enterococcus faecalis isolated from intensive care unit inpatient in Egypt. J. Microb. Biochem. Technol. 2013, 4, 161–167. [Google Scholar] [CrossRef]
  21. Sayed, A.M.; Sherif, N.H.; El-Gendy, A.O.; Shamikh, Y.I.; Ali, A.T.; Attia, E.Z.; El-Katatny, M.m.H.; Khalifa, B.A.; Hassan, H.M.; Abdelmohsen, U.R. Metabolomic profiling and antioxidant potential of three fungal endophytes derived from Artemisia annua and Medicago sativa. Nat. Prod. Res. 2022, 36, 2404–2408. [Google Scholar] [CrossRef]
  22. Su, G.; Xu, H.; Riggi, E.; He, Z.; Lu, L.; Lindholm, B.; Marrone, G.; Wen, Z.; Liu, X.; Johnson, D.W.; et al. Association of Kidney Function with Infections by Multidrug-Resistant Organisms: An Electronic Medical Record Analysis. Sci. Rep. 2018, 8, 13372. [Google Scholar] [CrossRef]
  23. Martins, A.P.S.; da Mata, C.; Dos Santos, U.R.; de Araújo, C.A.; Leite, E.M.M.; de Carvalho, L.D.; Vidigal, P.G.; Vieira, C.D.; Dos Santos-Key, S.G. Association between multidrug-resistant bacteria and outcomes in intensive care unit patients: A non-interventional study. Front. Public Health 2023, 11, 1297350. [Google Scholar] [CrossRef]
  24. Espi, M.; Koppe, L.; Fouque, D.; Thaunat, O. Chronic Kidney Disease-Associated Immune Dysfunctions: Impact of Protein-Bound Uremic Retention Solutes on Immune Cells. Toxins 2020, 12, 300. [Google Scholar] [CrossRef]
  25. Alsehemi, A.F.; Alharbi, E.A.; Alammash, B.B.; Alrais, A.I.; Elbadawy, H.M.; Alahmadi, Y.M. Assessment of risk factors associated with multidrug-resistant organism infections among patients admitted in a tertiary hospital—A retrospective study. Saudi Pharm. J. 2023, 31, 1084–1093. [Google Scholar] [CrossRef]
  26. Carrillo-Larco, R.M.; Anza-Ramírez, C.; Saal-Zapata, G.; Villarreal-Zegarra, D.; Zafra-Tanaka, J.H.; Ugarte-Gil, C.; Bernabé-Ortiz, A. Type 2 diabetes mellitus and antibiotic-resistant infections: A systematic review and meta-analysis. J. Epidemiol. Community Health 2022, 76, 75–84. [Google Scholar] [CrossRef]
  27. Yan, X.; Song, J.F.; Zhang, L.; Li, X. Analysis of risk factors for multidrug-resistant organisms in diabetic foot infection. BMC Endocr. Disord. 2022, 22, 46. [Google Scholar] [CrossRef]
  28. Dos Santos, V.P.; de Andrade Barberino, M.G.M.; Alves, C.A.S. Microbiological Species and Antibiotic Resistance in Diabetic and Nondiabetic Lower Extremity Wounds: A Comparative Cross-Sectional Study. Int. J. Low. Extrem. Wounds 2024, 23, 338–346. [Google Scholar] [CrossRef]
  29. Abdelgawad, M.A.; Bakr, R.B.; El-Gendy, A.O.; Kamel, G.M.; Azouz, A.A.; Bukhari, S.N.A. Discovery of a COX-2 selective inhibitor hit with anti-inflammatory activity and gastric ulcer protective effect. Future Med. Chem. 2017, 9, 1899–1912. [Google Scholar] [CrossRef]
  30. Cohen, J.; Cristofaro, P.; Carlet, J.; Opal, S. New method of classifying infections in critically ill patients. Crit. Care Med. 2004, 32, 1510–1526. [Google Scholar] [CrossRef]
  31. Zahar, J.R.; Timsit, J.F.; Garrouste-Orgeas, M.; Français, A.; Vesin, A.; Descorps-Declere, A.; Dubois, Y.; Souweine, B.; Haouache, H.; Goldgran-Toledano, D.; et al. Outcomes in severe sepsis and patients with septic shock: Pathogen species and infection sites are not associated with mortality. Crit. Care Med. 2011, 39, 1886–1895. [Google Scholar] [CrossRef]
  32. Kernéis, S.; Lucet, J.C.; Santoro, A.; Meschiari, M. Individual and collective impact of Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae in patients admitted to the ICU. J. Antimicrob. Chemother. 2021, 76 (Suppl. S1), i19–i26. [Google Scholar] [CrossRef]
  33. Vincent, J.L.; Sakr, Y.; Singer, M.; Martin-Loeches, I.; Machado, F.R.; Marshall, J.C.; Finfer, S.; Pelosi, P.; Brazzi, L.; Aditianingsih, D.; et al. Prevalence and Outcomes of Infection Among Patients in Intensive Care Units in 2017. JAMA 2020, 323, 1478–1487. [Google Scholar] [CrossRef]
  34. Erdem, I.; Ozgultekin, A.; Sengoz Inan, A.; Ozturk Engin, D.; Senbayrak Akcay, S.; Turan, G.; Dincer, E.; Oguzoglu, N.; Goktas, P. Bloodstream infections in a medical-surgical intensive care unit: Incidence, aetiology, antimicrobial resistance patterns of Gram-positive and Gram-negative bacteria. Clin. Microbiol. Infect. 2009, 15, 943–946. [Google Scholar] [CrossRef]
  35. Aziz, H.S.A.; Ismail, D.K.; Mohammed, N.S.A.; Elgendy, M.O.; Bassiouny, D.M. Distribution and antifungal susceptibility profiles of Candida species isolated from candidemia patients admitted to Egyptian tertiary hospitals: A cross-sectional study. BMC Infect. Dis. 2024, 24, 1177. [Google Scholar] [CrossRef]
  36. Barrasa-Villar, J.I.; Aibar-Remón, C.; Prieto-Andrés, P.; Mareca-Doñate, R.; Moliner-Lahoz, J. Impact on Morbidity, Mortality, and Length of Stay of Hospital-Acquired Infections by Resistant Microorganisms. Clin. Infect. Dis. 2017, 65, 644–652. [Google Scholar] [CrossRef]
  37. Vincent, J.L.; Sakr, Y.; Sprung, C.L.; Ranieri, V.M.; Reinhart, K.; Gerlach, H.; Moreno, R.; Carlet, J.; Le Gall, J.R.; Payen, D. Sepsis in European intensive care units: Results of the SOAP study. Crit. Care Med. 2006, 34, 344–353. [Google Scholar] [CrossRef]
  38. Spencer, R.C. Predominant pathogens found in the European Prevalence of Infection in Intensive Care Study. Eur. J. Clin. Microbiol. Infect. Dis. 1996, 15, 281–285. [Google Scholar] [CrossRef]
  39. Blanco, N.; Harris, A.D.; Rock, C.; Johnson, J.K.; Pineles, L.; Bonomo, R.A.; Srinivasan, A.; Pettigrew, M.M.; Thom, K.A. Risk Factors and Outcomes Associated with Multidrug-Resistant Acinetobacter baumannii upon Intensive Care Unit Admission. Antimicrob. Agents Chemother. 2018, 62, e01631-17. [Google Scholar] [CrossRef]
  40. Zaki, A.; Elgendy, M.O.; Abdelrahman, M.A.; Ali, H.; Khalil, E.M.; Hassan, M.; Fahmy, A.M.; Gad, R.A.; Salem, H.F. The efficacy of using different antibiotics to prevent maternal surgical site infections in COVID-19-infected cases. Eur. Chem. Bull. 2023, 6, 1342–1348. [Google Scholar]
  41. Ben-David, D.; Novikov, I.; Mermel, L.A. Are there differences in hospital cost between patients with nosocomial methicillin-resistant Staphylococcus aureus bloodstream infection and those with methicillin-susceptible S. aureus bloodstream infection? Infect. Control Hosp. Epidemiol. 2009, 30, 453–460. [Google Scholar] [CrossRef]
  42. Cosgrove, S.E. The relationship between antimicrobial resistance and patient outcomes: Mortality, length of hospital stay, and health care costs. Clin. Infect. Dis. 2006, 42 (Suppl. S2), S82–S89. [Google Scholar] [CrossRef]
  43. Alkofide, H.; Alhammad, A.M.; Alruwaili, A.; Aldemerdash, A.; Almangour, T.A.; Alsuwayegh, A.; Almoqbel, D.; Albati, A.; Alsaud, A.; Enani, M. Multidrug-Resistant and Extensively Drug-Resistant Enterobacteriaceae: Prevalence, Treatments, and Outcomes—A Retrospective Cohort Study. Infect. Drug Resist. 2020, 13, 4653–4662. [Google Scholar] [CrossRef]
  44. Ahmed, E.; El-Gendy, A.O.; Moniem Radi, N.A.; Mohamed, T. The bactericidal efficacy of femtosecond laser-based therapy on the most common infectious bacterial pathogens in chronic wounds: An in vitro study. Lasers Med. Sci. 2021, 36, 641–647. [Google Scholar] [CrossRef]
  45. Evans, L.; Rhodes, A.; Alhazzani, W.; Antonelli, M.; Coopersmith, C.M.; French, C.; Machado, F.R.; McIntyre, L.; Ostermann, M.; Prescott, H.C.; et al. Surviving sepsis campaign: International guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021, 47, 1181–1247. [Google Scholar] [CrossRef]
  46. Jernigan, J.A.; Hatfield, K.M.; Wolford, H.; Nelson, R.E.; Olubajo, B.; Reddy, S.C.; McCarthy, N.; Paul, P.; McDonald, L.C.; Kallen, A.; et al. Multidrug-Resistant Bacterial Infections in U.S. Hospitalized Patients, 2012–2017. N. Engl. J. Med. 2020, 382, 1309–1319. [Google Scholar] [CrossRef]
  47. Mauldin, P.D.; Salgado, C.D.; Hansen, I.S.; Durup, D.T.; Bosso, J.A. Attributable hospital cost and length of stay associated with health care-associated infections caused by antibiotic-resistant gram-negative bacteria. Antimicrob. Agents Chemother. 2010, 54, 109–115. [Google Scholar] [CrossRef]
  48. Elgendy, M.O.; El-Gendy, A.O.; Elgendy, S.O.; Abdelaty, L.N.; Abdelrahim, M.E.; Abdelrahman, M.A. Perceptions, Knowledge, and Experiences of Using Face Masks among Egyptian Healthcare Workers during the COVID-19 Pandemic: A Cross-Sectional Study. Healthcare 2023, 11, 838. [Google Scholar] [CrossRef]
  49. Capsoni, N.; Azin, G.M.; Scarnera, M.; Bettina, M.; Breviario, R.; Ferrari, L.; Ferrari, C.; Privitera, D.; Vismara, C.; Bielli, A.; et al. Bloodstream infections due to multi-drug resistant bacteria in the emergency department: Prevalence, risk factors and outcomes-a retrospective observational study. Intern. Emerg. Med. 2024, 20, 573–583. [Google Scholar] [CrossRef]
  50. El-Gendy, A.O.; Samir, A.; Ahmed, E.; Enwemeka, C.S.; Mohamed, T. The antimicrobial effect of 400 nm femtosecond laser and silver nanoparticles on gram-positive and gram-negative bacteria. J. Photochem. Photobiol. B Biol. 2021, 223, 112300. [Google Scholar] [CrossRef]
Medicina 61 01220 g001
Figure 1. Flow diagram of the included and excluded patients.
Figure 1. Flow diagram of the included and excluded patients.
Medicina 61 01220 g001
Table 1. Demographic data of the included patients.
Table 1. Demographic data of the included patients.
Non-MDRO-Infected Patients (n = 59)MDRO-Infected Patients (n = 47)p-Value
Age (Mean ± SD)55 ± 12.850.6 ± 170.19
SexMale [n (%)] 31 (52.54%)28 (59.57%)0.345
Female [n (%)]28 (47.46%)19 (40.43%)
MDRO: multidrug-resistant organism (s); p-value > 0.05 is considered non-significant.
Table 2. Comparison between non-MDRO-infected and MDRO-infected patients in clinical and laboratory parameters.
Table 2. Comparison between non-MDRO-infected and MDRO-infected patients in clinical and laboratory parameters.
ParametersNon-MDRO-Infected Patients (n = 59)MDRO-Infected Patients (n = 47)p-Value
Temperature (°C) (Mean ± SD)37.7 ± 0.638.0 ± 0.50.01 *
HR (Beats/min) (Mean ± SD)106 ± 19106 ± 130.92
RR (Breaths/min) (Mean ± SD)20 ± 722.7 ± 60.064
Admission SBP (mmHg) (Mean ± SD)105 ± 21102 ± 340.64
Admission DBP (mmHg) (Mean ± SD)64 ± 1365 ± 210.78
PH (Mean ± SD)7.38 ± 0.097.33 ± 0.110.028 *
PCO2 (mmHg) (Mean ± SD)40.8 ± 1635 ± 10.30.074
PaO2 (mmHg) (Mean ± SD)60 ± 2671 ± 29.30.036 *
HCO3 (mmol/dL) (Mean ± SD)24.8 ± 9.520.5 ± 6.850.008 *
Hemoglobin (g/dL) (Mean ± SD)9.9 ± 1.69.4 ± 1.80.176
Hematocrit value (%) (Mean ± SD)29.5 ± 5.527.9 ± 5.10.134
TLC (103 cell/mm3) (Mean ± SD)14.4 ± 7.716.8 ± 8.220.12
Platelets (103/mm3) (Mean ± SD)203 ± 142166 ± 1240.168
Serum creatinine (mg/dL) (Mean ± SD)1.41 ± 0.72.34 ± 1.8<0.001 *
Non-survivors [n (%)]12 (20.3%)20 (42.6%)0.013 *
ARDS [n (%)]4 (6.8%)10 (21.3%)0.029 *
Use of invasive ventilation [n (%)]14 (23.7%)20 (42.6%)0.039 *
Use of NIV [n (%)]23 (39%)17 (36.2%)0.767
Use of high doses of inotropes [n (%)]2 (3.4%)13 (27.7%)<0.001 *
Need for inotropes [n (%)]16 (27.1%)26 (55.3%)0.003 *
Days on NIV (Mean ± SD)3.27 ± 52.68 ± 50.55
Days on invasive Ventilation (Mean ± SD)1.95 ± 4.92 ± 50.91
ICU stay (days) (Mean ± SD)13 ± 9.911.6 ± 5.90.36
Hospital stay before ICU (Mean ± SD) 1.2 ± 2.41.28 ± 3.70.9
ARDS: acute respiratory distress syndrome, DBP: diastolic blood pressure, HR: heart rate, ICU: intensive care unit, MDRO: multidrug-resistant organism (s), NIV: non-invasive ventilation, PaO2: partial pressure of arterial oxygen, PCO2: partial pressure of carbon dioxide, RR: respiratory rate, SBP: systolic blood pressure, TLC: total leukocyte count; * p-value ≤ 0.05 is considered significant.
Table 3. Comparison between non-MDRO-infected and MDRO-infected patients in corrected duration analysis.
Table 3. Comparison between non-MDRO-infected and MDRO-infected patients in corrected duration analysis.
ParametersNon-MDRO-Infected Patients (n = 59)MDRO-Infected Patients (n = 47)p-Value
Days on NIV (Mean ± SD)8.42 ± 11.414.79 ± 13.80.011 *
Days on invasive ventilation (Mean ± SD)6.42 ± 12.112.79 ± 150.017 *
ICU stay (days) (Mean ± SD)15.88 ± 1119.5 ± 10.20.086
ICU: intensive care unit, MDRO: multidrug-resistant organism (s), NIV: non-invasive ventilation; * p-value ≤ 0.05 is considered significant.
Table 4. Comparison between non-MDRO-infected and MDRO-infected patients in comorbidities.
Table 4. Comparison between non-MDRO-infected and MDRO-infected patients in comorbidities.
Comorbidities Non-MDRO-Infected Patients (n = 59)MDRO-Infected Patients (n = 47)p-Value
Cerebrovascular stroke [n (%)]1 (1.7%)5 (10.6%)0.048 *
Hypertension [n (%)]25 (42.4%)20 (42.6%)0.98
Diabetes mellitus [n (%)]21 (35.6%)15 (31.9%)0.69
Renal failure [n (%)]9 (15.3%)18 (38.3%)0.007 *
Heart Failure [n (%)]3 (5.1%)2 (4.3%)0.84
Ischemic heart disease [n (%)]1 (1.7%)2 (4.3%)0.43
MDRO: multidrug-resistant organism (s); * p-value ≤ 0.05 is considered significant.
Table 5. MDROs prevalence according to the culture site.
Table 5. MDROs prevalence according to the culture site.
OrganismSputum (n = 25)Blood (n = 15)Urine (n = 10)Total (n = 50)
Klebsiella spp.15 (60%)7 (46.7%)4 (40%)26 (52%)
Pseudomonas spp.2 (8%)2 (13.3%)-4 (8%)
Acetobacter spp.4 (16%)1 (6.7%)4 (40%)9 (18%)
E. coli spp.1 (4%)2 (13.3%)1 (10%)4 (8%)
Enterobacter spp.-3 (20%)1 (10%)4 (8%)
Pseudomonas and Klebsiella2 (8%)--2 (4%)
Acinetobacter–Klebsiella1 (4%)--1 (2%)
spp.: species.
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Yassin, A.; Eid, R.A.; Mohammad, M.F.; Elgendy, M.O.; Mohammed, Z.; Abdelrahim, M.E.A.; Abdel Hamied, A.M.; Binsuwaidan, R.; Saleh, A.; Hussein, M.; et al. Microbial Multidrug-Resistant Organism (MDRO) Mapping of Intensive Care Unit Infections. Medicina 2025, 61, 1220. https://doi.org/10.3390/medicina61071220

AMA Style

Yassin A, Eid RA, Mohammad MF, Elgendy MO, Mohammed Z, Abdelrahim MEA, Abdel Hamied AM, Binsuwaidan R, Saleh A, Hussein M, et al. Microbial Multidrug-Resistant Organism (MDRO) Mapping of Intensive Care Unit Infections. Medicina. 2025; 61(7):1220. https://doi.org/10.3390/medicina61071220

Chicago/Turabian Style

Yassin, Ahmed, Ragaey Ahmad Eid, Mohammad Farouk Mohammad, Marwa O. Elgendy, Zeinab Mohammed, Mohamed E. A. Abdelrahim, Ahmed M. Abdel Hamied, Reem Binsuwaidan, Asmaa Saleh, Mona Hussein, and et al. 2025. "Microbial Multidrug-Resistant Organism (MDRO) Mapping of Intensive Care Unit Infections" Medicina 61, no. 7: 1220. https://doi.org/10.3390/medicina61071220

APA Style

Yassin, A., Eid, R. A., Mohammad, M. F., Elgendy, M. O., Mohammed, Z., Abdelrahim, M. E. A., Abdel Hamied, A. M., Binsuwaidan, R., Saleh, A., Hussein, M., & Mohamed, E. H. (2025). Microbial Multidrug-Resistant Organism (MDRO) Mapping of Intensive Care Unit Infections. Medicina, 61(7), 1220. https://doi.org/10.3390/medicina61071220

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