Evaluation of the Bacterial Infections and Antibiotic Prescribing Practices in the Intensive Care Unit of a Clinical Hospital in Romania

Academic Editor: Alberto Enrico Maraolo Received: 22 November 2024 Revised: 30 December 2024 Accepted: 8 January 2025 Published: 9 January 2025 Citation: Szabó, S.; Feier, B.; Mărginean, A.; Dumitrana, A.-E.; Costin, S.L.; Cristea, C.; Bolboacă, S.D. Evaluation of the Bacterial Infections and Antibiotic Prescribing Practices in the Intensive Care Unit of a Clinical Hospital in Romania. Antibiotics 2025, 14, 64. https://doi.org/10.3390/ antibiotics14010064 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Evaluation of the Bacterial Infections and Antibiotic Prescribing Practices in the Intensive Care Unit of a Clinical Hospital in Romania Sándor Szabó 1,†, Bogdan Feier 1,†, Alina Mărginean 2, Andra-Elena Dumitrana 2, Simona Ligia Costin 2, Cecilia Cristea 1,* and Sorana D. Bolboacă3 1Department of Analytical Chemistry, Faculty of Pharmacy, “Iuliu Hat ,ieganu” University of Medicine and Pharmacy, 4 Pasteur Street, 400349 Cluj-Napoca, Romania; [email protected] (S.S.); feier.geor[email protected] (B.F.) 2“Dr. Constantin Papilian” Military Emergency Hospital, 400132 Cluj-Napoca, Romania; [email protected] (A.M.); [email protected] (A.-E.D.); [email protected] (S.L.C.) 3Department of Medical Informatics and Biostatistics, Faculty of Medicine, “Iuliu Hat ,ieganu” University of Medicine and Pharmacy Cluj-Napoca, 400349 Cluj-Napoca, Romania; [email protected] *Correspondence: [email protected]o †These authors contributed equally to this work. Abstract: Introduction: Healthcare-associated infections (HAIs) are associated with increased mortality, antimicrobial resistance, and high antibiotic use. Methods: The characteristics of bacterial resistance and antibiotic consumption in the intensive care unit (ICU) of a clinical hospital in Romania were evaluated. Demographic data of patients, identified bacteria, antibiotics administered, and their sensitivity profiles were collected and analyzed. Results: One hundred and twenty-five patients, with a median age of 68 years, mostly male (60%), were included in the study. More than one-third of the patients died. The deceased patients were older (median age of 74 years), had longer hospitalization (median of 9 days) and bacteria detected (55.3%), and had higher antibiotic consumption than the discharged patients. The most frequent bacteria identified in our cohort were Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa in deceased patients and Klebsiella pneumoniae,Escherichia coli,Staphylococcus hemolyticus, and Enterococcus faecalis in the survived group. The top three antibiotics used were ceftriaxone, metronidazole, and meropenem. Resistance to antibiotics was observed in 44.3% of the deceased group and 37.5% of patients who were discharged (χ2= 5.5, p= 0.0628). Discussion: A positive monotonic association was observed between the number of hospitalization days and the number of antibiotic doses, with a higher correlation coefficient for deceased patients (0.6327, p< 0.0001) than in survived group (0.4749, p< 0.0001). Conclusions and Future Trends: This study provides a real picture of HAIs, the characteristics of bacteria, and the consumption of antibiotics in an ICU of a clinical hospital in Romania. The data obtained are similar to those from other international studies, but further studies are needed to reflect the real situation in Romania. Keywords: healthcare-associated infections (HAIs); bacteria; antibiotic (AB); intensive care unit (ICU); antibiotic resistance 1. Introduction Healthcare-associated infections (HAIs) are serious infections and a major public health problem [ 1 , 2 ] associated with a significant risk of morbidity, mortality, and prolonged hospital stay [ 3 – 5 ]. In Europe, approximately four million patients are infected annually Antibiotics 2025,14, 64 https://doi.org/10.3390/antibiotics14010064 Antibiotics 2025,14, 64 2 of 18 in healthcare facilities [ 3 , 6 ]. Healthcare-associated infections are associated with a 4-fold higher mortality rate and a 3-fold longer hospitalization [7]. Admission to hospitals in emerging countries such as Romania is associated with a 15% risk of developing HAI [ 1 , 3 ], but HAIs remain under-reported [ 8 ]. The risk of occurrence of HAIs in developed countries is, on average, 5% (up to 16%); however, in the Intensive Care Unit (ICU), this risk can be higher and can increase to 30% compared to other hospital wards [ 3 ]. Intensive-care infections constitute approximately half of all HAIs [ 7 ]. The most common HAIs in the ICU are ventilator-associated pneumonia (VAP), urinary tract infections (UTIs), and bloodstream infections (BSIs) [ 1 , 4 ]. The presence of HAIs in patients hospitalized in the ICU prolongs hospitalization by five days [ 9 ]. HAIs are responsible for a direct cost of €7 billion annually [ 1 ]. HAIs increase the use of antibiotics, the emergence of multi-resistant bacteria, morbidity, mortality rates, and the cost of medical care [ 3 , 4 , 7 ]. The presence of HAIs is associated with higher antibiotic consumption as it requires the use of broad-spectrum antibiotics for a long period, thereby increasing the risk of antibiotic resistance [ 10 ]. For optimal antibiotic management, the implementation of antibiotic stewardship programs is needed. El-Sokkary et al. analyzed the data from 57 ICUs in 24 countries regarding infection prevention and control programs, and antibiotic stewardship activities and showed that most centers have a surveillance program [ 11 ]. Such programs may reduce the emergence of drug-resistant bacteria. In Romania, antibioticresistant infections account for over 60% of all HAI cases, compared to approximately 5% in Finland; however, the evaluated samples were small in some cases [ 1 , 12 ]. The most common multi-drug resistant (MDR) bacteria are defined using the acronym ESKAPE: Enterococcus faecium,Staphylococcus aureus,Klebsiella pneumoniae,Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. [ 13 ]. Approximately 70% of patients in the ICUs receive antibiotic treatment [ 14 ]. The use of antimicrobials in European ICUs depends mainly on the availability of antibiotics; therefore, there are differences between countries in terms of antibiotic molecules used. Romania has implemented measures to prevent and limit HAIs and to decrease antimicrobial resistance [ 15 ]; however, data on the bacteria and consumption of antibiotics in ICUs are limited. In this study, we aimed to investigate the etiology of bacterial infections in the ICU of a clinical hospital in Romania and to describe the bacterial pattern in collected biological samples and antibiotic consumption in deceased and surviving patients. 2. Results 2.1. The Evaluated Cohort Four hundred and seventy-seven patients were hospitalized during the study period, of whom 125 met the inclusion criteria and were evaluated. More than one-third of the patients were included in the deceased group, and these patients had a longer hospitalization stay, and used a higher number of different antibiotics and antibiotic doses than those who survived (Table 1). Table 1. Characteristics of the evaluated cohort. Characteristic All (n= 125) Deceased (n= 38) Survived (n= 87) p-Value Age a 0.1794 Median [Q1 to Q3] 68 [62 to 79] 74 [63.3 to 81.8] 68 [61 to 77.5] {min to max} {39 to 94} {48 to 93} {39 to 94} Sex b 0.3825 Women 50 (40) 13 (34.2) 37 (42.5) Men 75 (60) 25 (65.8) 50 (57.5) Antibiotics 2025,14, 64 3 of 18 Table 1. Cont. Characteristic All (n= 125) Deceased (n= 38) Survived (n= 87) p-Value Days of hospital stay a 0.0031 Median [Q1 to Q3] 6 [4 to 10] 9 [5.3 to 13.8] 6 [4 to 8] {min to max} {3 to 48} {3 to 35} {3 to 48} No. of biological samples b 0.1036 0 43 (34.4) 8 (21.1) 35 (40.2) 1 40 (32) 17 (44.7) 23 (26.4) 2 19 (15.2) 7 (18.4) 12 (13.8) >2 23 (18.4) 6 (15.8) 17 (19.5) No. of bacteria b,* 0.0342 0 71 (56.8) 17 (44.7) 54 (62.1) 1 24 (19.2) 6 (15.8) 18 (20.7) 2 21 (16.8) 12 (31.6) 9 (10.3) >2 9 (7.2) 3 (7.9) 6 (6.9) No. of antibiotics b 0.0261 1 47 (37.9) 13 (34.2) 34 (39.5) 2 44 (35.5) 9 (23.7) 35 (40.7) >2 33 (26.6) 16 (42.1) 17 (19.8) No. of patients with at least one c R 46 (36.8) 18 (47.4) 28 (32.2) 0.1054 I 17 (13.6) 8 (21.1) 9 (10.3) 0.1082 S 53 (42.4) 2330 (52.6) 33 (37.9) 0.1261 Total no. of antibiotic doses a 0.0040 Median [Q1 to Q3] 15 [9 to 31] 18 [14.3 to 45] 13 [7.5 to 26.5] {min to max} {0 to 172} {4 to 137} {0 to 172} a median [Q1 to Q3], {min to max}, where Q1 is the first quartile, Q3 is the third quartile, min is then minimum, max is the maximum; comparison between groups with Mann–Whitney test. b no (%), comparison with Chisquared test or * Fisher’s exact test. c Number of cases with at least one case of R = resistance; I = intermediary; S = sensible. The top three biological samples collected were urine, bronchial secretions, and purulent/fluid secretions (Figure 1a), and the most frequent bacterium was A. baumannii (Figure 1b). Antibiotics 2025, 14, x FOR PEER REVIEW 3 of 18 Table 1. Characteristics of the evaluated cohort. Characteristic All (n = 125) Deceased (n = 38) Survived (n = 87) p-Value Age a 0.1794 Median [Q1 to Q3] 68 [62 to 79] 74 [63.3 to 81.8] 68 [61 to 77.5] {min to max} {39 to 94} {48 to 93} {39 to 94} Sex b 0.3825 Women 50 (40) 13 (34.2) 37 (42.5) Men 75 (60) 25 (65.8) 50 (57.5) Days of hospital stay a 0.0031 Median [Q1 to Q3] 6 [4 to 10] 9 [5.3 to 13.8] 6 [4 to 8] {min to max} {3 to 48} {3 to 35} {3 to 48} No. of biological samples b 0.1036 0 43 (34.4) 8 (21.1) 35 (40.2) 1 40 (32) 17 (44.7) 23 (26.4) 2 19 (15.2) 7 (18.4) 12 (13.8) >2 23 (18.4) 6 (15.8) 17 (19.5) No. of bacteria b,* 0.0342 0 71 (56.8) 17 (44.7) 54 (62.1) 1 24 (19.2) 6 (15.8) 18 (20.7) 2 21 (16.8) 12 (31.6) 9 (10.3) >2 9 (7.2) 3 (7.9) 6 (6.9) No. of antibiotics b 0.0261 1 47 (37.9) 13 (34.2) 34 (39.5) 2 44 (35.5) 9 (23.7) 35 (40.7) >2 33 (26.6) 16 (42.1) 17 (19.8) No. of patients with at least one c R 46 (36.8) 18 (47.4) 28 (32.2) 0.1054 I 17 (13.6) 8 (21.1) 9 (10.3) 0.1082 S 53 (42.4) 2330 (52.6) 33 (37.9) 0.1261 Total no. of antibiotic doses a 0.0040 Median [Q1 to Q3] 15 [9 to 31] 18 [14.3 to 45] 13 [7.5 to 26.5] {min to max} {0 to 172} {4 to 137} {0 to 172} a median [Q1 to Q3], {min to max}, where Q1 is the first quartile, Q3 is the third quartile, min is then minimum, max is the maximum; comparison between groups with Mann–Whitney test. b no (%), comparison with Chi-squared test or * Fishers exact test. c Number of cases with at least one case of R = resistance; I = intermediary; S = sensible. (a) (b) 9% 3% 15% 34% 21% 43% 3% 0% 37% 21% 18% 53% 0% 10% 20% 30% 40% 50% 60% Canulla Cerebrospinal fluid Bronchial secretion Purulent/fluid secretion Blood Urine Biological sample dead alive 3% 11% 7% 6% 1% 13% 2% 2% 0% 5% 5% 2% 7% 0% 0% 1% 26% 8% 11% 5% 3% 13% 5% 0% 3% 13% 8% 3% 3% 3% 3% 0% 0% 5% 10% 15% 20% 25% 30% Acinetobacter baumannii Escherichia coli Enterococcus faecalis Enterococcus faecium Enterobacter cloacae Klebsiella pneumoniae Proteus mirabilis Proteus penneri Providencia stuartii Pseudomonas aeruginosa Staphylococcus aureus Staphylococcus epidermidis Staphylococcus hemolyticus Staphylococcus simulans Staphylococcus hominis Staphylococcus warneri dead alive Figure 1. (a) Distribution of collected biological samples (38 deceased patients and 87 who survived); (b) distribution of bacteria per group expressed as the number of positive cases per number of eligible cases, considering that the same patient can have more than one bacterium). Antibiotics 2025,14, 64 4 of 18 2.2. Types of Bacteria and Distribution in Collected Biological Samples The most frequently identified bacteria were A. baumannii,K. pneumoniae, and P. aeruginosa in the deceased group and K. pneumoniae,Escherichia coli,S. hemolyticus, and E. faecalis in the surviving group (Figure 1b). K. pneumoniae was the only bacteria identified in the cannula samples (two cases). One cerebral fluid culture revealed the presence of K. pneumoniae. Considering the possibility of multiple biological samples being collected from patients, 41 positive cultures were identified in the deceased group and 51 were identified in the surviving group. Two bacteria with a prevalence higher than 10% were observed exclusively in the deceased group: A. baumannii and K. pneumoniae. The number of cases with positive cultures in biological samples by group are presented in Table 2. Table 2. Distribution of bacteria in biological samples by group. Bacterium Biological Sample No. Patients (Percentage, %) All, n= 125 Deceased, n= 38 Survived, n= 87 Acinetobacter baumannii Bronchial secretion 9 (7.2) 7 (18.4) 2 (2.3) Purulent/fluid secretion 4 (3.2) 3 (7.9) 1 (1.1) Enterobacter cloacae Bronchial secretion 2 (1.6) 1 (2.6) 1 (1.1) Enterococcus faecalis Blood 2 (1.6) 1 (2.6) 1 (1.1) Urine 2 (1.6) 1 (2.6) 1 (1.1) Purulent/fluid secretion 5 (4) 2 (5.3) 3 (3.4) Enterococcus faecium Blood 1 (0.8) 1 (2.6) Urine 3 (2.4) 1 (2.6) 2 (2.3) Purulent/fluid secretion 4 (3.2) 1 (2.6) 3 (3.4) Escherichia coli Blood 1 (0.8) 1 (1.1) Urine 4 (3.2) 4 (4.6) Bronchial secretion 1 (0.8) 1 (1.1) Purulent/fluid secretion 7 (5.6) 3 (7.9) 4 (4.6) Klebsiella pneumoniae Cannula 2 (1.6) 2 (2.3) Cerebrospinal fluid 1 (0.8) 1 (2.6) Blood 1 (0.8) 1 (1.1) Urine 2 (1.6) 2 (2.3) Bronchial secretion 9 (7.2) 5 (13.2) 4 (4.6) Purulent/fluid secretion 3 (2.4) 3 (3.4) Proteus mirabilis Urine 2 (1.6) 2 (2.3) Bronchial secretion 1 (0.8) 1 (2.6) Purulent/fluid secretion 1 (0.8) 1 (2.6) Proteus penneri Purulent/fluid secretion 2 (1.6) 2 (2.3) Providencia stuarti Blood 1 (0.8) 1 (2.6) Pseudomonas aeruginosa Urine 3 (2.4) 3 (7.9) Bronchial secretion 2 (1.6) 2 (5.3) Staphylococcus aureus Bronchial secretion 2 (1.6) 1 (2.6) 2 (2.3) Purulent/fluid secretion 5 (4) 2 (5.3) 1 (1.1) Urine 1 (0.8) 1 (1.1) Staphylococcus epidermidis Urine 1 (0.8) 1 (2.6) Bronchial secretion 2 (1.6) 2 (2.3) Blood 1 (0.8) 1 (1.1) Antibiotics 2025,14, 64 5 of 18 Table 2. Cont. Bacterium Biological Sample No. Patients (Percentage, %) All, n= 125 Deceased, n= 38 Survived, n= 87 Staphylococcus hemolyticus Blood 4 (3.2) 1 (2.6) 3 (3.4) Urine 1 (0.8) 1 (1.1) Purulent/fluid secretion 2 (1.6) 2 (2.3) Staphylococcus hominis Blood 1 (0.8) 1 (2.6) Staphylococcus simulans Blood 1 (0.8) 1 (2.6) Staphylococcus warneri Purulent/fluid secretion 1 (0.8) 1 (1.1) Data are expressed as number and corresponding percentage (%). 2.3. Administered Antibiotics Patients with no bacteria identified in their biological samples received up to three antibiotics (deceased vs. survived: 88:89% up to two antibiotics and 12:11% three antibiotics). Different antibiotics were administered, including antibiotics with the same or different pharmaceutical forms. The distribution of antibiotics administered to patients with multiple or no bacterial infections is presented in Table 3. Table 3. The number of antibiotics administered per number of identified bacteria stratified by group. No. of Antibiotics for No. Patients (Percentage, %) All, n= 125 Deceased, n= 38 Survived, n= 87 no bacteria 71 (56.8) 17 (44.7) 54 (62.1) 1 AB 32 (45.1) 8 (47.1) 24 (44.4) 2 ABs 31 (43.7) 7 (41.2) 24 (44.4) 3 ABs 8 (11.3) 2 (11.8) 6 (11.1) 1 bacterium 24 (19.2) 6 (15.8) 18 (20.7) 1 AB 10 (41.7) 2 (33.3) 8 (44.4) 2 ABs 8 (33.3) 1 (16.7) 7 (38.9) 3 ABs 6 (25) 3 (50) 3 (16.7) 2 bacteria 21 (16.8) 12 (31.6) 9 (10.3) 1 AB 5 (23.8) 3 (25) 2 (22.2) 2 ABs 3 (14.3) 1 (8.3) 2 (22.2) 3 ABs 8 (38.1) 6 (50) 2 (22.2) >3 ABs 5 (23.8) 2 (16.7) 3 (33.3) 3 bacteria 5 (4) 2 (5.3) 3 (3.4) no AB 1 (20) 0 (0) 1 (33.3) 2 ABs 1 (20) 0 (0) 1 (33.3) 3 ABs 1 (20) 1 (50) 0 (0) >3 ABs 2 (40) 1 (50) 1 (33.3) 4 bacteria 4 (3.2) 1 (2.6) 3 (3.4) 2 ABs 1 (25) 0 (0) 1 (33.3) 3 ABs 1 (25) 0 (0) 1 (33.3) >3 ABs 2 (50) 1 (100) 1 (33.3) Data are reported as no (%). AB = antibiotic. Table 4summarizes the antibiotics used in deceased and surviving patients. The top five antibiotics used were ceftriaxone (34.2% deceased vs. 28.7% survived, p= 0.5405), metronidazole (15.8% deceased vs. 32.2% survived, p= 0.0581), meropenem (36.8% deceased vs. 20.7% survived, p= 0.0570), vancomycin (23.7% deceased vs. 11.5% survived, p= 0.0808), and amoxicillin/clavulanic acid (26.3% deceased vs. 8.0% survived, p= 0.0061). Antibiotics 2025,14, 64 6 of 18 Table 4. The use of antibiotics by group. Antibiotic No. Patients (Percentage, %) All, n= 125 Deceased, n= 38 Survived, n= 87 Amikacin 500 mg 3 (2.4) 1 (2.6) 2 (2) Amoxicillin/Clavulanic acid 1000/200 mg 17 (13.6) 10 (26.3) 7 (7.1) Ampicillin 1 g 3 (2.4) 1 (2.6) 2 (2) Azithromycin 500 mg 2 (1.6) 1 (2.6) 1 (1) Cefazolin 1 g 1 (0.8) 0 (0) 1 (1) Cefoperazon/Sulbactam 1000/1000 mg 20 (16) 2 (5.3) 18 (18.4) Ceftazidime 1 g 3 (2.4) 2 (5.3) 1 (1) Ceftriaxone 1 g 38 (30.4) 13 (34.2) 25 (25.5) Cefuroxime 1.5 g 15 (12) 0 (0) 15 (15.3) Clindamycin 300 mg/2 mL 4 (3.2) 1 (2.6) 3 (3.1) Colistin 1MUI 13 (10.4) 6 (15.8) 7 (7.1) Doxycycline 100 mg 4 (3.2) 2 (5.3) 2 (2) Erythromycin 200 mg 4 (3.2) 1 (2.6) 3 (3.1) Ertapenem 1 g 7 (5.6) 1 (2.6) 6 (6.1) Fosfomycin 3 g p.o. 1 (0.8) 0 (0) 1 (1) Gentamicin 80 mg 2 (1.6) 0 (0) 2 (2) Linezolid 2 mg/mL 2 (1.6) 1 (2.6) 1 (1) Meropenem 1000 mg 32 (25.6) 14 (36.8) 18 (18.4) Metronidazole 250 mg 10 (8) 2 (5.3) 8 (8.2) Metronidazole 5 g/200 mL 34 (27.2) 6 (15.8) 28 (28.6) Moxifloxacin 400 mg/250 mL 2 (1.6) 1 (2.6) 1 (1) Oxacillin 1000 mg 2 (1.6) 2 (5.3) 0 (0) Penicillin G Potassium1 MUI 1 (0.8) 0 (0) 1 (1) Piperacillin/Tazobactam 2 g/0.25 g 6 (4.8) 4 (10.5) 2 (2) Rifampin 300 mg caps. 1 (0.8) 1 (2.6) 0 (0) Tigecycline 50 mg 2 (1.6) 0 (0) 2 (2) Teicoplanin 400 mg 1 (0.8) 1 (2.6) 0 (0) Trimethoprim/Sulfamethoxazole 400/80 mg 4 (3.2) 3 (7.9) 1 (1) Vancomycin 1 g 19 (15.2) 9 (23.7) 10 (10.2) Data reported as a number (%). The distribution of antibiotics by bacteria and group, considering that a patient could have more than one bacterium identified, and more than one antibiotic used, is presented in Table 5. Table 5. Distribution of administered antibiotics by bacteria and group. Bacterium Administered Antibiotic Deceased, n= 38 Survived, n= 87 Acinetobacter baumannii Amikacin 500 mg (n= 1) Amoxicillin/Clavulanic acid 1000/200 mg (n= 1) Ampicillin 1 g (n= 1) Ceftazidime 1 g (n= 2) Ceftriaxone 1 g (n= 3) Colistin 1 MUI (n= 6) Ertapenem 1 g (n= 1) Meropenem 1000 mg (n= 6) Metronidazole 5 g/200 mL (n= 3) Piperacillin/Tazobactam 2 g/0.25 g (n= 2) Rifampin 300 mg caps. (n= 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n= 2) Vancomicyn 1 g (n= 3) Ceftriaxone 1 g (n= 1) Colistin 1 MUI (n= 3) Erythromicin 200 mg (n= 1) Meropenem 1000 mg (n= 3) Metronidazole 5 g/200 mL (n= 1) Piperacillin/Tazobactam 2 g/0.25 g (n= 1) Vancomycin 1 g (n= 2) Antibiotics 2025,14, 64 7 of 18 Table 5. Cont. Bacterium Administered Antibiotic Deceased, n= 38 Survived, n= 87 Escherichia coli Colistin 1 MUI (n= 1) Ertapenem 1 g (n= 1) Meropenem 1000 mg (n= 3) Metronidazole 250 mg (n= 1) Metronidazole 5 g/200 mL (n= 1) Rifampin 300 mg caps. (n= 1) Vancomycin 1 g (n= 1) Ampicillin 1 g (n= 2) Cefazolin 1 g (n= 1) Cefoperazone/Sulbactam 1000/1000 mg (n= 1) Ceftriaxone 1 g (n= 3) Colistin 1 MUI (n= 2) Ertapenem 1 g (n= 3) Meropenem 1000 mg (n= 3) Metronidazole 250 mg (n= 1) Metronidazole 5 g/200 mL (n= 5) Vancomycin 1 g (n= 1) Enterococcus faecalis Amikacin 500 mg (n= 1) Colistin 1 MUI (n= 2) Meropenem 1000 mg (n= 4) Metronidazole 5 g/200 mL (n= 1) Teicoplanin 400 mg (n= 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n= 2) Vancomycin 1 g (n= 1) Cefazolin 1 g (n= 1) Ceftriaxone 1 g (n= 4) Doxycycline 100 mg (n= 1) Linezolid 2 mg/mL (n= 1) Meropenem 1000 mg (n= a) Metronidazole 5 g/200 mL (n= 2) Enterococcus faecium Ceftriaxone 1 g (n= 2) Colistin 1 MUI (n= 1) Meropenem 1000 mg (n= 1) Vancomycin 1 g (n= 1) Ampicillin 1 g (n= 2) Ceftriaxone 1 g (n= 3) Colistin 1 MUI (n= 2) Erythromycin 200 mg (n= 1) Ertapenem 1 g (n= 1) Meropenem 1000 mg (n= 2) Metronidazole 5 g/200 mL (n= 2) Vancomycin 1 g (n= 1) Klebsiella pneumoniae Amoxicillin/Clavulanic acid 1000/200 mg (n= 2) Ampicillin 1 g (n= 1) Ceftazidime 1 g (n= 2) Ceftriaxone 1 g (n= 1) Colistin 1 MUI (n= 2) Meropenem 1000 mg (n= 1) Metronidazole 5 g/200 mL (n= 1) Piperacillin/Tazobactam 2 g/0.25 g (n= 2) Vancomycin 1 g (n= 1) Amikacin 500 mg (n= 1) Amoxicillin/Clavulanic acid 1000/200 mg (n= 1) Ampicillin 1 g (n= 2) Cefoperazone/Sulbactam 1000/1000 mg (n= 1) Ceftriaxone 1 g (n= 3) Clindamycin 300 mg/2 mL (n= 1) Colistin 1 MUI (n= 4) Ertapenem 1 g (n= 2) Fosfomycina 3 g p.o. (n= 1) Meropenem 1000 mg (n= 8) Metronidazole 250 mg (n= 2) Metronidazole 5 g/200 mL (n= 2) Tigecycline 50 mg (n= 2) Vancomycin 1 g (n= 2) Proteus mirabilis Amoxicillin/Clavulanic acid 1000/200 mg (n= 1) Meropenem 1000 mg (n= 1) Oxacillin 1000 mg (n= 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n= 1) Cefoperazone/Sulbactam 1000/1000 mg (n= 1) Ceftriaxone 1 g (n= 1) Cefuroxime 1.5 g (n= 1) Meropenem 1000 mg (n= 1) Antibiotics 2025,14, 64 8 of 18 Table 5. Cont. Bacterium Administered Antibiotic Deceased, n= 38 Survived, n= 87 Pseudomonas aeruginosa Ceftazidime 1 g (n= 2) Ceftriaxone 1 g (n= 1) Colistin 1 MUI (n= 1) Linezolid 2 mg/mL (n= 1) Meropenem 1000 mg (n= 3) Piperacillin/Tazobactam 2 g/0.25 g (n= 2) Vancomycin 1 g (n= 2) Amikacin 500 mg (n= 1) Cefazolin 1 g (n= 1) Ceftriaxone 1 g (n= 2) Clindamycin 300 mg/2 mL (n= 1) Colistin 1 MUI (n= 2) Fosfomycin 3 g p.o. (n= 1) Meropenem 1000 mg (n= 3) Metronidazole 250 mg (n= 2) Metronidazole 5 g/200 mL (n= 2) Tigecycline 50 mg (n= 2) Vancomycin 1 g (n= 1) Staphylococcus aureus Amoxicillin/Clavulanic acid 1000/200 mg (n= 2) Ceftriaxone 1 g (n= 2) Clindamycin 300 mg/2 mL (n= 1) Oxacillin 1000 mg (n= 2) Piperacillin/Tazobactam 2 g/0.25 g (n= 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n= 1) Amoxicillin/Clavulanic acid 1000/200 mg (n= 1) Ceftriaxone 1 g (n= 2) Clindamycin 300 mg/2 mL (n= 1) Colistin 1 MUI (n= 1) Erythromycin 200 mg (n= 1) Meropenem 1000 mg (n= 1) Metronidazole 5 g/200 mL (n= 1) Penicillin G potassium 1 MUI (n= 1) Vancomycin 1 g (n= 2) Staphylococcus epidermidis Amoxicillin/Clavulanic acid 1000/200 mg (n= 1) Meropenem 1000 mg (n= 1) Vancomycin 1 g (n= 1) Ceftriaxone 1 g (n= 2) Cefuroxim 1.5 g (n= 1) Meropenem 1000 mg (n= 1) Vancomycin 1 g (n= 1) Staphylococcus hemolyticus Meropenem 1000 mg (n= 1) Metronidazole 5 g/200 mL (n= 1) Teicoplanin 400 mg (n= 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n= 1) Vancomycin 1 g (n= 1) Ceftriaxone 1 g (n= 4) Colistin 1 MUI (n= 1) Linezolid 2 mg/mL (n= 1) Meropenem 1000 mg (n= 2) Tigecycline 50 mg (n= 1) Vancomycin 1 g (n= 2) Specific bacteria were identified among deceased patients only: • Enterobacter cloacae and prescribed antibiotics to patients: amoxicillin/clavulanic acid 1000/200 mg (n= 1), meropenem 1000 mg (n= 1), and vancomycin 1 g (n= 1). • Providencia stuartii and prescribed antibiotics to patients: amoxicillin/clavulanic acid 1000/200 mg (n= 1), erythromycin 200 mg (n= 1), and vancomycin 1 g (n= 1). • Staphylococcus simulans and the prescribed antibiotics were as follows: meropenem 1000 mg (n= 1), metronidazole 5 g/200 mL (n= 1), teicoplanin 400 mg (n= 1), trimethoprim/sulfamethoxazole 400/80 mg (n= 1), and vancomycin 1 g (n= 1). • Staphylococcus hominis and prescribed antibiotics to patients: linezolid 2 mg/mL (n= 1), meropenem 1000 mg (n= 1), and vancomycin 1 g (n= 1). Antibiotics 2025,14, 64 9 of 18 Specific bacteria were exclusively observed in the surviving group: • Proteus penneri and used antibiotics: ampicillin 1 g (n= 2), ceftriaxone 1 g (n= 1), colistin 1 MUI (n= 2), meropenem 1000 mg (n= 2), metronidazole 5 g/200 mL (n= 1), and vancomycin 1 g (n= 1). • Staphylococcus warneri and used antibiotics: linezolid 2 mg/mL (n= 1) and meropenem 1000 mg (n= 1). A positive monotonic association between hospitalization length and number of antibiotic doses used was found in the investigated cohort, with a higher correlation coefficient in deceased patients ( ρ = 0.6327. p< 0.0001) than in the surviving group (ρ= 0.4749, p< 0.0001). In the analyzed cohort, the hospitalization length was significantly different among patients with a different number of collected biological samples (from 0 to 5 samples, with five samples collected from two patients) (Kruskal–Wallis test: p< 0.0001, Figure 2). The difference remained statistically significant for deceased patients (Kruskal–Wallis test: p= 0.0124) only when patients without biological samples were compared to those with three biological samples (post hoc analysis, 0 vs. 3: p= 0.0055). In the surviving group, the number of days of hospitalization was also statistically significant (Kruskal–Wallis test: p= 0.0001), with the following significant differences in post hoc analysis: p= 0.0001 for 0 vs. 4, p= 0.0028 for 1 vs. 4, and p= 0.02621 for 2 vs. 4. Antibiotics 2025, 14, x FOR PEER REVIEW 8 of 18 Staphylococcus hemolyticus Meropenem 1000 mg (n = 1) Metronidazole 5 g/200 mL (n = 1) Teicoplanin 400 mg (n = 1) Trimethoprim/Sulfamethoxazole 400/80 mg (n = 1) Vancomycin 1 g (n = 1) Ceftriaxone 1 g (n = 4) Colistin 1 MUI (n = 1) Linezolid 2 mg/mL (n = 1) Meropenem 1000 mg (n = 2) Tigecycline 50 mg (n = 1) Vancomycin 1 g (n = 2) Specific bacteria were identified among deceased patients only: • Enterobacter cloacae and prescribed antibiotics to patients: amoxicillin/clavulanic acid 1000/200 mg (n = 1), meropenem 1000 mg (n = 1), and vancomycin 1 g (n = 1). • Providencia stuartii and prescribed antibiotics to patients: amoxicillin/clavulanic acid 1000/200 mg (n = 1), erythromycin 200 mg (n = 1), and vancomycin 1 g (n = 1). • Staphylococcus simulans and the prescribed antibiotics were as follows: meropenem 1000 mg (n = 1), metronidazole 5 g/200 mL (n = 1), teicoplanin 400 mg (n = 1), trimethoprim/sulfamethoxazole 400/80 mg (n = 1), and vancomycin 1 g (n = 1). • Staphylococcus hominis and prescribed antibiotics to patients: linezolid 2 mg/mL (n = 1), meropenem 1000 mg (n = 1), and vancomycin 1 g (n = 1). Specific bacteria were exclusively observed in the surviving group: • Proteus penneri and used antibiotics: ampicillin 1 g (n = 2), ceftriaxone 1 g (n = 1), colistin 1 MUI (n = 2), meropenem 1000 mg (n = 2), metronidazole 5 g/200 mL (n = 1), and vancomycin 1 g (n = 1). • Staphylococcus warneri and used antibiotics: linezolid 2 mg/mL (n = 1) and meropenem 1000 mg (n = 1). A positive monotonic association between hospitalization length and number of antibiotic doses used was found in the investigated cohort, with a higher correlation coefficient in deceased patients (ρ = 0.6327. p < 0.0001) than in the surviving group (ρ = 0.4749, p < 0.0001). In the analyzed cohort, the hospitalization length was significantly different among patients with a different number of collected biological samples (from 0 to 5 samples, with five samples collected from two patients) (Kruskal–Wallis test: p < 0.0001, Figure 2). The difference remained statistically significant for deceased patients (Kruskal–Wallis test: p = 0.0124) only when patients without biological samples were compared to those with three biological samples (post hoc analysis, 0 vs. 3: p = 0.0055). In the surviving group, the number of days of hospitalization was also statistically significant (Kruskal–Wallis test: p = 0.0001), with the following significant differences in post hoc analysis: p = 0.0001 for 0 vs. 4, p = 0.0028 for 1 vs. 4, and p = 0.02621 for 2 vs. 4. Figure 2. Distribution of number of hospitalization days by number of biological samples (post hoc analysis: 0 vs. 3 p = 0.0007, 0 vs. 4 p < 0.0001, 1 vs. 4 p = 0.0069). Dots represent the raw data, the box Figure 2. Distribution of number of hospitalization days by number of biological samples (post hoc analysis: 0 vs. 3 p= 0.0007, 0 vs. 4 p< 0.0001, 1 vs. 4 p= 0.0069). Dots represent the raw data, the box middle line is the median, the boxes are the first, and the third quartile and the wickers are the minimum and maximum (excluding the outliers). Colors represent the distribution of the length of hospital stay for each number of biological samples. Statistically significant differences in hospitalization length for different numbers of bacteria identified in any biological sample were observed only in the survived group (Kruskal–Wallis test: p= 0.0046, post hoc analysis: 0 (n = 54) vs. 3 (n = 3), p= 0.0401) (Figure 3). Statistically significant differences were observed between antibiotic doses for different numbers of bacteria identified in any biological sample only in survived patients (Kruskal– Wallis test: p= 0.0023, post hoc analysis: 0 (n = 54) vs. 2 (n = 3), p= 0.0114) (Figure 4b). Antibiotics 2025,14, 64 16 of 18 or Fisher’s exact test according to the expected frequencies of the attribute data. The Mann– Whitney U test or Kruskal–Wallis test was used to compare quantitative data between two or more groups. Whenever the Kruskal–Wallis test showed statistically significant differences between groups, a post hoc analysis was conducted. The Kendall tau correlation coefficient was calculated to quantify the association between the number of identified bacteria and biological samples. Bacterial cultures were performed using different biological samples (e.g., cannula, cerebrospinal fluid, blood, urine, bronchial secretion, and purulent/fluid secretion). In some cases, more than one biological sample was collected from the same. In addition, more than one bacterium was identified in biological samples from the same patient. Antibiotic susceptibility tests were performed for any bacteria identified in the biological samples. Therefore, the total number of identified bacteria was higher than that of patients in the analyzed cohort. Exploratory statistical analysis was conducted using Statistica software (v.13.5, TIBCO Software Inc., Palo Alto, CA, USA). Graphical representations were created using Microsoft Excel (Microsoft Office 365, USA) or JASP (v. 0.18.3.0). All tests were two-tailed at a significance level of 5%, and p-values less than 0.05 were considered statistically significant. 5. Conclusions and Future Trends Infection with K. pneumoniae was observed in the cohort, regardless of the group, and with A. baumannii and P. aeruginosa among deceased patients, and E. coli,S. hemolyticus, and E. faecalis among discharged patients. The deceased group was older and had a longer hospitalization stay, higher bacterial load, number of antibiotics used, and higher total antibiotic doses administered. Bacteria with the highest levels of resistance to antibiotics identified in this cohort were K. pneumoniae,S. hemolyticus, and A. baumannii. Our results highlighted the main challenges recorded in one ICU of a clinical hospital in Romania in terms of HAIs, identified bacteria, and the consumption of antibiotics. Our results could be used to develop guidelines for healthcare professionals and support measures for more judicious use of antibiotics. Rapid detection methods for bacteria, as well as careful and continuous antibiotic surveillance, not only in the ICU, are needed to guide healthcare workers to provide the best patient care. Author Contributions: Conceptualization, C.C., S.S. and B.F.; methodology, S.S., A.M., A.-E.D., S.L.C. and S.D.B. validation, S.S., B.F. and S.D.B.; formal analysis, S.S., A.M., A.-E.D. and S.L.C.; investigation, S.S., A.-E.D. and S.L.C.; resources, C.C.; data curation, S.S. and B.F.; writing—original draft preparation, S.S., B.F., C.C. and S.D.B.; writing—review and editing, C.C. and S.D.B.; supervision, C.C. and S.D.B.; project administration, C.C. funding acquisition, C.C. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the European Union’s Horizon Europe research and innovation program under the grant agreement “European integration of new technologies and social-economic solutions for increasing consumer trust and engagement in seafood products (FishEuTrust), Grant Agreement: 101060712/2022. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of “Constantin Papilian” Military Emergency Hospital (protocol code A5987/04.10.2022) for studies involving humans. Informed Consent Statement: Patient consent was waived by the ethics committee due to the retrospective analysis of routinely collected data. Data Availability Statement: Data unavailable due to ethical restrictions. Conflicts of Interest: The authors declare no conflicts of interest. Antibiotics 2025,14, 64 17 of 18 References 1. 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