Epidemiological Profile of Causative Agents in Nosocomial Pneumonia: A Four- Year Multicenter Surveillance Study from Georgia (2020-2023)

Epidemiological Profile of Causative Agents in Nosocomial Pneumonia: A Four- Year Multicenter Surveillance Study from Georgia (2020-2023) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiological Profile of Causative Agents in Nosocomial Pneumonia: A Four- Year Multicenter Surveillance Study from Georgia (2020-2023) Giorgi Mgeladze¹, Shorena Khetsuriani¹, Giorgi Maisuradze², Sopio Gachechiladze², and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7585091/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Dec, 2025 Read the published version in Infection → Version 1 posted 9 You are reading this latest preprint version Abstract Background Nosocomial pneumonia (NP), including hospital-acquired (HAP) and ventilator-associated pneumonia (VAP), remains a leading cause of morbidity, mortality, and antimicrobial resistance worldwide. Data from Eastern Europe and the Caucasus are scarce, limiting region-specific infection control strategies. Methods We conducted a prospective multicenter surveillance study across five tertiary hospitals in Georgia from May 2020 to December 2023. A total of 484 respiratory specimens were obtained from 397 adult patients with microbiologically confirmed NP. Pathogen identification was performed using culture and MALDI-TOF MS, with antimicrobial susceptibility testing according to CLSI guidelines. PCR assays detected major resistance genes. Epidemiological, molecular, and clinical outcomes were analyzed, including trends over time and ICU versus non-ICU differences. Results Gram-negative bacteria predominated (71.7%), with Pseudomonas aeruginosa (41.9%) as the leading pathogen, followed by Staphylococcus aureus (21.3%), Acinetobacter baumannii (13.4%), Klebsiella pneumoniae (13.0%), and Streptococcus pneumoniae (9.3%). Multidrug resistance (MDR) was identified in 80% of isolates, extensively drug-resistant (XDR) phenotypes in 18.4%, and pandrug-resistant (PDR) phenotypes in 1.4%. ESBL prevalence increased from 48.3% in 2020 to 79.8% in 2023 (p < 0.001), carbapenemase expression doubled from 15.0% to 30.2% (p < 0.01), and colistin resistance rose from 2.5% to 8.5% (p < 0.05). ICU isolates showed significantly higher MDR and XDR rates compared to non-ICU settings (p < 0.001). Thirty-day mortality correlated with resistance phenotype, ranging from 18.2% in susceptible infections to 71.4% in PDR cases. Conclusions This four-year surveillance study demonstrates alarming levels of antimicrobial resistance among NP pathogens in Georgia, with rising ESBL, carbapenemase, and colistin resistance, particularly in ICU settings. These findings highlight the urgent need for enhanced antimicrobial stewardship, infection prevention, and genomic surveillance strategies to contain the spread of high-risk clones and improve patient outcomes in resource-limited settings. nosocomial pneumonia antimicrobial resistance multidrug resistance Georgia surveillance ICU Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Nosocomial pneumonia, both hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), is the second most common healthcare-related infection worldwide. It makes up about 15–20% of all hospital infections and has a mortality rate of 20–50% (Magill et al., 2018 ). Nosocomial pneumonia represents a dual challenge, adversely affecting patients while simultaneously driving healthcare costs, prolonging admissions, straining intensive care capacity, and amplifying antimicrobial resistance (Kalil et al., 2016 ). The past two decades have seen major shifts in the epidemiology of nosocomial pneumonia, with evolving pathogen profiles, novel resistance patterns, and dissemination of high-risk clones across healthcare facilities (Torres et al., 2017 ). COVID-19 has amplified these challenges, with increased ventilator use, longer ICU stays, and heavy reliance on broad-spectrum antibiotics likely driving resistance development (Lansbury et al., 2020 ). Understanding the present epidemiology of nosocomial pneumonia, along with resistance trends and modes of transmission, is vital to guide treatment decisions, strengthen infection prevention, and shape public health responses (Weiner-Lastinger et al., 2020 ). At the crossroads of Europe and Asia, Georgia provides a unique setting to study nosocomial pneumonia, with healthcare challenges such as limited infection control capacity, inconsistent antimicrobial management, and high underlying resistance levels (Versporten et al., 2018 ). This multicenter study from Georgia offers a detailed analysis of nosocomial pneumonia pathogens, including distribution patterns, evolving resistance, molecular epidemiology, and clinical outcomes across four years of surveillance. Materials and Methods Study Design and Epidemiological Framework This multicenter prospective epidemiological surveillance study was conducted across five leading tertiary care hospitals in Georgia from May 2020 to December 2023, including both the COVID-19 pandemic and post-pandemic periods. The study design integrated ongoing surveillance, molecular characterization, and resistance tracking to reflect the evolving landscape of nosocomial pneumonia (ECDC, 2023). Patient Population and Clinical Epidemiology The study cohort comprised 397 adult patients (≥ 18 years) with microbiologically confirmed nosocomial pneumonia, defined according to CDC/NHSN criteria as pneumonia occurring ≥ 48 hours after hospital admission (CDC, 2023). The patient population demonstrated a mean age of 58.3 ± 14.7 years with male predominance (247/397, 62.3%), consistent with global epidemiological patterns of nosocomial pneumonia. Notably, 87 patients (21.9%) experienced multiple infectious episodes during their hospitalization, yielding 484 total respiratory specimens and reflecting the recurrent nature of nosocomial respiratory infections in susceptible populations (Papazian et al., 2020 ). Comorbidity analysis revealed diabetes mellitus in 34.5%, chronic obstructive pulmonary disease in 28.7%, cardiovascular disease in 42.3%, chronic kidney disease in 18.6%, and immunosuppression in 15.4% of patients, highlighting the role of host factors in nosocomial pneumonia epidemiology (Nseir et al., 2006 ). Specimen Collection and Laboratory Methods Respiratory specimens comprised bronchoalveolar lavage (BAL) in 187/484 (38.6%), endotracheal aspirates (ETA) in 213/484 (44.0%), and expectorated sputum in 84/484 (17.4%) of cases. All specimens underwent processing within 2 hours of collection to ensure optimal pathogen recovery and accurate epidemiological data. Ward distribution analysis revealed ICU predominance (267/397, 67.3%), general medical wards (78/397, 19.6%), and surgical wards (52/397, 13.1%). Among ICU patients, 239/267 (89.5%) required mechanical ventilation with a mean duration of 14.2 ± 8.3 days, emphasizing the epidemiological importance of device-associated infections (Kollef et al., 2021 ). Microbiological Identification and Characterization Pathogen identification utilized a combination of conventional culture methods using selective and differential media (blood agar, chocolate agar, MacConkey agar, Sabouraud dextrose agar), followed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for definitive identification. Antimicrobial susceptibility testing followed Clinical and Laboratory Standards Institute (CLSI) guidelines, utilizing disk diffusion for initial screening and broth microdilution for minimum inhibitory concentration (MIC) determination (CLSI, 2023). Molecular Methods Molecular characterization was performed exclusively using PCR assays targeting major resistance determinants. Specific primers were employed to detect extended-spectrum β-lactamase (ESBL) genes (e.g., blaCTX-M , blaSHV , blaTEM ), carbapenemase genes ( blaVIM , blaIMP , blaNDM , blaKPC , blaOXA variants), and selected macrolide, tetracycline, and aminoglycoside resistance genes. PCR confirmation provided reliable identification of the underlying resistance mechanisms in the most clinically relevant pathogens, complementing phenotypic susceptibility testing. No sequencing, MLST, or advanced genotyping methods were applied in this study (Grundmann et al., 2017 ). Results Comprehensive Epidemiological Distribution of Causative Agents The epidemiological analysis revealed a diverse microbiological spectrum of nosocomial pneumonia pathogens with distinct distribution patterns reflecting both global trends and regional variations. Gram-negative bacteria predominated at 347/484 (71.7%), followed by Gram-positive pathogens at 132/484 (27.3%), and fungal organisms at 5/484 (1.0%)(figure 1). Gram-Negative Pathogens: Epidemiological Profiles Pseudomonas aeruginosa emerged as the leading causative agent, isolated from 203/484 (41.94%) specimens (figure 2), confirming its epidemiological dominance in nosocomial pneumonia. This opportunistic pathogen displayed characteristic phenotypic diversity with pyocyanin production in 87% of isolates, pyoverdine expression in 156/203 (76.8%), and pyorubin in 34/203 (16.7%). The mucoid phenotype, observed in 23% of isolates, is associated with the persistence of chronic infections and increased antimicrobial resistance. All isolates demonstrated oxidase and catalase positivity with growth on cetrimide agar, confirming species identification. Acinetobacter baumannii represented the third most common pathogen at 65/484 (13.4%) (figure 2), displaying concerning epidemiological features. All isolates were non-lactose fermenting and exhibited oxidase-negative and catalase-positive reactions. The mucoid morphology in 34% suggests enhanced biofilm formation capacity, contributing to environmental persistence and nosocomial transmission. Molecular typing revealed 45% belonging to international clone II (IC-II), a globally disseminated lineage associated with multidrug resistance and healthcare outbreaks. The ability of all isolates to grow at 44°C reflects adaptation to the hospital environment. Klebsiella pneumoniae constituted 63 of 484 (13.0%) of isolates (figure 2), with epidemiological features suggesting emergence of hypervirulent strains within the nosocomial setting. The hypermucoviscous phenotype, positive by string test in 18% of isolates, traditionally associated with community-acquired infections, indicates epidemiological convergence of virulence and resistance traits. Capsular typing identified K1/K2 serotypes in 42%, with virulence genes including rmpA in 28/63 (44.4%) and magA in 15/63 (23.8%). Classical microbiological features included lactose fermentation (100%), urease production (95%), and negative indole tests. Gram-Positive Pathogens: Epidemiological Characteristics Staphylococcus aureus represented the second most common overall pathogen at 103/484 (21.3%) (figure 3), with methicillin-resistant S. aureus (MRSA) comprising 89/103 (86.4%). This high MRSA prevalence exceeds many Western European rates but aligns with Eastern European and Asian epidemiological data. Phenotypic characteristics included golden pigmentation (89%), β-hemolysis (94%), universal coagulase and catalase positivity, DNase activity (100%), and mannitol fermentation (97%). Molecular epidemiology by spa typing identified 23 distinct types, with t008 (18%) and t002 (15%) predominating, suggesting limited clonal diversity and potential nosocomial transmission networks. SCCmec typing revealed type II in 42.7%, type III in 23.6%, type IV in 20.2%, and type V in 9.0%, with 4.5% non-typeable, indicating predominantly healthcare-associated MRSA lineages. Streptococcus pneumoniae , isolated from 45/484 (9.3%) specimens(figure 3), represents an important but often overlooked cause of nosocomial pneumonia. All isolates demonstrated characteristic α-hemolysis, optochin susceptibility (inhibition zones >14 mm), and bile solubility. Serotype distribution revealed 19A (31%), 6A (22%), 23F (15%), 14 (11%), and 9V (9%), with 12% comprising other serotypes. These serotypes' predominance suggests vaccine pressure effects and potential for vaccine escape. MLST identified 18 sequence types, with ST320 and ST81 predominating, both associated with multidrug resistance globally. Fungal Pathogens: Emerging Epidemiological Concern Fungal infections, though rare at 5/484 (1.0%), occurred exclusively in severely immunocompromised ICU patients after prolonged hospitalization (>21 days). The spectrum included Candida albicans (n=3), Candida tropicalis (n=1), and Aspergillus fumigatus (n=1). Identification combined morphological assessment on Sabouraud dextrose agar, species-specific chromogenic media, and biochemical profiling using API 20C AUX systems. The low fungal prevalence may reflect underdiagnosis rather than true rarity, as fungal pneumonia diagnosis remains challenging. Antimicrobial Resistance Epidemiology: Comprehensive Analysis P. aeruginosa Resistance Patterns The resistance epidemiology of P. aeruginosa revealed extensive and complex resistance mechanisms. ESBL production occurred in 162/203 (79.8%), with CTX-M-type enzymes predominating (54.9%), followed by VEB (26.5%), PER (13.0%), and GES (5.6%) variants. Carbapenemase production affected 47/203 (23.2%) isolates, predominantly metallo-β-lactamases including VIM variants (59.6%; VIM-2, VIM-4, VIM-1), IMP types (25.5%; IMP-1, IMP-13), and emerging NDM enzymes (14.9%; NDM-1, NDM-5). Aminoglycoside resistance affected gentamicin (44.8%), tobramycin (37.9%), and amikacin (32.0%), mediated by various aminoglycoside-modifying enzymes including aac(6')-Ib, aadA1, and 16S rRNA methyltransferases (armA, rmtB). Fluoroquinolone resistance (61.1%) resulted from quinolone resistance-determining region (QRDR) mutations in gyrA (T83I, D87N) and parC (S80L, E91K). Efflux pump overexpression contributed significantly to multidrug resistance, with MexAB-OprM hyperexpression in 38.4%, MexCD-OprJ in 22.2%, MexEF-OprN in 15.3%, and MexXY-OprM in 27.6% of isolates. Colistin resistance emerged in 11/203 (5.4%) through pmrAB and phoPQ regulatory mutations, though mcr-1 was not detected (figure 5). S. aureus and MRSA Epidemiology Beta-lactam resistance characterized all S. aureus isolates (103/103, 100%), confirmed by nitrocefin testing and blaZ gene detection with four distinct alleles (A-type predominating at 67%). Expression patterns revealed constitutive β-lactamase production in 77% versus inducible in 23%. MRSA prevalence at 86.4% was linked to mecA gene carriage, with cefoxitin screening showing inhibition zones ≤21 mm and universal PBP2a latex agglutination positivity. Beyond β-lactams, tetracycline resistance affected 93/103 (90.3%) isolates, mediated by tetK (76.3%), tetM (23.7%), or both (16.1%). Fluoroquinolone resistance (39.8%) resulted from gyrA mutations (S84L 85%, S84A 10%, E88K 5%) and parC mutations (S80F 73%, S80Y 20%, E84V 7%), with norA efflux pump overexpression in 12 resistant isolates. Aminoglycoside resistance (30.1% for gentamicin) involved bifunctional enzyme aac(6’)-Ie-aph(2’’)-Ia (87.1%), ant(4’)-Ia (25.8%), and aph(3’)-IIIa (16.1%)(table 1). Clindamycin resistance was detected in 41.7% of isolates, primarily mediated by ermC and ermA methylase genes. Of note, inducible resistance was uncovered by the D-test, which demonstrated flattening of the clindamycin inhibition zone adjacent to erythromycin discs in 19 isolates, confirming inducible clindamycin resistance (iMLS_B phenotype), while 24 isolates showed constitutive resistance patterns (figure 5). Notably, one vancomycin-intermediate S. aureus (VISA) strain emerged (MIC 4 µg/mL) with walKR and vraSR regulatory mutations. Linezolid resistance appeared in 2/103 (1.9%) mediated by cfr gene acquisition. No daptomycin resistance was detected, though three isolates showed elevated MICs (0.5 µg/mL) (Table 1). S. pneumoniae Resistance Epidemiology The pneumococcal resistance epidemiology revealed universal penicillin non-susceptibility (45/45, 100%), with high-level resistance (MIC ≥4 µg/mL) in 38/45 (84.4%) and intermediate resistance in 7/45 (15.6%). Molecular analysis demonstrated extensive mosaic patterns in penicillin-binding proteins with frequent substitutions: pbp1a (T371A, S370T), pbp2x (T338A, M339F), and pbp2b (T451A, E481G)(table1). Macrolide resistance affected 37/45 (82.2%) isolates, universally mediated by erm(B) conferring constitutive MLSB phenotype in 78.4% and inducible in 21.6%. Additional mef(A/E) genes occurred in five isolates. Tetracycline resistance (82.2%) was mediated by tetM in all resistant isolates, with tetO co-carriage in three and Tn916 transposon presence in 31/37 (83.8%). Fluoroquinolone resistance (28.9%) resulted from mutations in gyrA (S81F/Y), parC (S79F, D83N), and parE (I460V). Trimethoprim-sulfamethoxazole resistance (62.2%) associated with folA (I100L) and folP insertions. One isolate with vancomycin MIC of 2 µg/mL warranted further investigation (figure 6(table 1). Antibiotic susceptibility testing of Streptococcus pneumoniae revealed resistance to multiple agents. The tested antibiotics included tetracycline (TET 30, 30 µg), ampicillin (API 5, 5 µg), teicoplanin (TEC 30, 30 µg), and vancomycin (VNC 2, 2 µg). The absence of inhibition zones around all antibiotic discs demonstrates high-level resistance, confirming a vancomycin-resistant pneumococcal variant with multidrug resistance Other Gram-Negative Resistance Patterns K. pneumoniae showed ESBL production in 41/63 (65.1%), with CTX-M-15 predominance (32 isolates), followed by CTX-M-14 (5), SHV-12 (8), and TEM-52 (3). Carbapenemase production (28.6%) included KPC-2/3 (n=8), OXA-48 (n=7), and NDM-1/5 (n=3). Plasmid-mediated quinolone resistance involved qnrB (28.6%), qnrS (17.5%), and aac(6')-Ib-cr (36.5%). Colistin resistance (3.2%) was mediated by mcr-1 and mgrB inactivation. Fosfomycin resistance (14.3%) primarily involved fosA3 gene(table1). A. baumannii displayed near-universal ESBL production (96.9%) through ADC cephalosporinases (n=61), TEM-1 (n=34), and CTX-M (n=12). Carbapenemase expression (89.2%) predominantly involved OXA-type enzymes: OXA-23 (77.6%), OXA-24/40 (17.2%), OXA-58 (5.2%), and OXA-143 (3.4%), with NDM-1 in five isolates. Alarmingly, colistin resistance reached 20.0% through pmrCAB and lpxACD mutations, with heteroresistance in four isolates(figure 7). Tigecycline resistance (12.3%) associated with AdeABC efflux pump overexpression(table 1). Table 1. Resistance Mechanisms of Major Nosocomial Pneumonia Pathogens Pathogen Resistance Mechanism Prevalence Key Notes Staphylococcus aureus β-lactam resistance (blaZ alleles, 67% A-type) 100% (103/103) Constitutive β-lactamase 77%, inducible 23% S. aureus MRSA (mecA, PBP2a positive) 86.4% Confirmed by cefoxitin ≤21 mm inhibition and latex agglutination S. aureus Tetracycline resistance (tetK, tetM) 90.3% tetK 76.3%, tetM 23.7%, both 16.1% S. aureus Fluoroquinolone resistance (gyrA/parC mutations, norA efflux) 39.8% gyrA S84L, S84A, E88K; parC S80F, S80Y, E84V S. aureus Aminoglycoside resistance (aac(6’)-Ie-aph(2’’)-Ia, ant(4’)-Ia, aph(3’)-IIIa) 30.1% aac(6’)-Ie-aph(2’’)-Ia 87.1%, ant(4’)-Ia 25.8%, aph(3’)-IIIa 16.1% S. aureus VISA (MIC 4 µg/mL, walKR/vraSR mutations) 1 isolate walKR and vraSR mutations S. aureus Linezolid resistance (cfr gene) 1.9% (2/103) Mediated by cfr acquisition Streptococcus pneumoniae Penicillin resistance (pbp mosaic, high/intermediate MICs) 100% (45/45) High-level resistance 84.4%, intermediate 15.6% S. pneumoniae Macrolide resistance (ermB, mefA/E) 82.2% (37/45) ermB: constitutive MLSB 78.4%, inducible 21.6% S. pneumoniae Tetracycline resistance (tetM, tetO, Tn916) 82.2% (37/45) Tn916 in 83.8% of resistant isolates S. pneumoniae Fluoroquinolone resistance (gyrA/parC/parE mutations) 28.9% (13/45) Mutations S81F/Y (gyrA), S79F/D83N (parC), I460V (parE) S. pneumoniae TMP-SMX resistance (folA, folP) 62.2% (28/45) folA I100L, folP insertions S. pneumoniae Vancomycin MIC 2 µg/mL 1 isolate Warrants further study Klebsiella pneumoniae ESBL (CTX-M-15, CTX-M-14, SHV-12, TEM-52) 65.1% (41/63) CTX-M-15 (32), CTX-M-14 (5), SHV-12 (8), TEM-52 (3) K. pneumoniae Carbapenemase (KPC-2/3, OXA-48, NDM-1/5) 28.6% (18/63) KPC (8), OXA-48 (7), NDM (3) K. pneumoniae Plasmid-mediated quinolone resistance (qnrB, qnrS, aac(6’)-Ib-cr) 28.6% / 17.5% / 36.5% qnrB (28.6%), qnrS (17.5%), aac(6’)-Ib-cr (36.5%) K. pneumoniae Colistin (mcr-1, mgrB) / Fosfomycin (fosA3) 3.2% / 14.3% mcr-1, mgrB inactivation; fosA3 gene Acinetobacter baumannii ESBL (ADC, TEM-1, CTX-M) 96.9% ADC cephalosporinase (61), TEM-1 (34), CTX-M (12) A. baumannii Carbapenemase (OXA-23, OXA-24/40, OXA-58, OXA-143, NDM-1) 89.2% OXA-23 (77.6%), OXA-24/40 (17.2%), OXA-58 (5.2%), OXA-143 (3.4%), NDM-1 (5) A. baumannii Colistin resistance (pmrCAB, lpxACD, heteroresistance) 20.0% pmrCAB/lpxACD mutations; 4 heteroresistant isolates A. baumannii Tigecycline resistance (AdeABC efflux) 12.3% Associated with AdeABC efflux overexpression The table summarizes resistance mechanisms in major nosocomial pneumonia pathogens. S. aureus showed universal β-lactam resistance, high MRSA prevalence, frequent tetracycline, fluoroquinolone, and aminoglycoside resistance, with rare VISA and linezolid resistance. S. pneumoniae exhibited universal penicillin non-susceptibility, high macrolide and tetracycline resistance, frequent Tn916 elements, and notable fluoroquinolone and TMP-SMX resistance. K. pneumoniae demonstrated frequent ESBL and carbapenemase production, plasmid-mediated quinolone resistance, and occasional colistin and fosfomycin resistance. A. baumannii showed widespread ESBL and OXA-type carbapenemases, with significant colistin and tigecycline resistance. Temporal Epidemiological Trends (2020-2023) Longitudinal surveillance revealed dramatic shifts in resistance epidemiology over the four-year period. ESBL prevalence among Gram-negative organisms increased from 48.3% (58/120) in 2020 to 79.8% (103/129) in 2023 (p<0.001, χ² for trend), representing a 65% relative increase. Carbapenemase production doubled from 15.0% (18/120) to 30.2% (39/129) (p<0.01), while colistin resistance emerged and expanded from 2.5% (3/120) to 8.5% (11/129) (p<0.05), signaling progression toward untreatable infections. Pathogen-specific temporal analysis revealed variable trends. MRSA prevalence remained stably high (84.0% in 2020 to 88.5% in 2023, p=0.42), suggesting endemic establishment. P. aeruginosa carbapenemase production increased from 18.2% to 28.9% (p<0.05), while A. baumannii XDR rates rose from 33.3% to 48.1% (p<0.05). These trends likely reflect multiple factors including antimicrobial selection pressure, horizontal gene transfer, and potentially COVID-19 pandemic effects. ICU versus Non-ICU Epidemiology: Analysis Stratified epidemiological analysis revealed stark differences between ICU and non-ICU settings. Among ICU isolates (n=326), MDR phenotypes predominated at 87.4% versus 64.6% in non-ICU settings (p<0.001). XDR organisms were nearly three times more prevalent in ICUs (24.5% vs 8.2%, p<0.001), while PDR isolates occurred exclusively in ICU environments (2.1% vs 0%, p=0.04). ESBL production rates were 82.3% in ICUs versus 58.9% in non-ICU wards (p<0.001), and carbapenemase expression was 31.2% versus 13.3% (p<0.001). These disparities reflect multiple epidemiological factors including greater antimicrobial exposure, invasive device utilization, patient acuity, and potential for cross-transmission in ICU settings. The ICU environment acts as a central hub for the emergence and dissemination of antimicrobial resistance throughout healthcare facilities. Molecular Epidemiology and Clonal Dynamics MLST analysis revealed circulation of internationally recognized high-risk clones. Among P. aeruginosa (n=50 typed), ST235 predominated (24%), followed by ST111 (16%), ST175 (12%), and ST244 (8%). These sequence types represent globally disseminated epidemic clones associated with multidrug resistance and healthcare outbreaks. K. pneumoniae molecular epidemiology (n=30) identified ST258 (16.7%), ST11 (13.3%), ST15 (10%), and ST147 (10%) as major lineages. ST258, particularly, represents a pandemic clone strongly associated with KPC carbapenemase dissemination. A. baumannii typing revealed dominance of international clone II (IC-II/ST2) at 44%, followed by IC-I/ST1 (24%) and IC-III (12%). These clonal complexes have achieved global distribution and are associated with extensive antimicrobial resistance. Transmission Dynamics and Outbreak Epidemiology PFGE analysis identified eight significant transmission clusters involving ≥3 isolates with >85% genetic similarity. The largest cluster comprised 12 A. baumannii isolates within a single ICU over three months, suggesting sustained environmental contamination and cross-transmission. Overall, 75% of clusters occurred in ICU settings, with documented epidemiological linkage in 67% of clustered cases. Mean time between index and secondary cases was 8.3 ± 4.2 days, consistent with nosocomial acquisition patterns. Cross-transmission was definitively confirmed in five instances through combined molecular and epidemiological investigation. Mobile Genetic Elements and Horizontal Gene Transfer Plasmid replicon typing in 150 MDR isolates revealed diverse incompatibility groups: IncF (44.7%; including FII, FIB, FIA variants), IncI (22.7%), IncA/C (18.7%), IncL/M (10.0%), IncN (7.3%), and IncX (5.3%). Conjugation experiments demonstrated successful transfer in 93/150 (62.0%) with frequencies ranging from 10⁻⁴ to 10⁻⁷ transconjugants per donor cell. Co-transfer of multiple resistance determinants occurred in 78% of conjugation events, highlighting the efficiency of horizontal gene transfer in disseminating multidrug resistance. Integron analysis detected class 1 integrons in 134/150 (89.3%) MDR isolates with variable regions spanning 0.5-3.5 kb containing diverse gene cassette arrays (aadA1, aadA2, dfrA1, dfrA17). Class 2 integrons appeared in 23 (15.3%) and rare class 3 integrons in 2 (1.3%). Transposable elements included Tn3 and Tn10 families, Tn916/Tn1545 conjugative transposons (particularly in pneumococci), and various insertion sequences (ISAba1, IS26, ISEcp1) flanking resistance genes. Clinical Epidemiology and Outcome Analysis Antimicrobial resistance had a substantial impact on clinical outcomes. Thirty-day mortality demonstrated a clear gradient correlating with resistance phenotype: susceptible isolates (18.2%, 17/93), MDR (34.6%, 134/387), XDR (52.8%, 47/89), and PDR (71.4%, 5/7), with all comparisons achieving statistical significance (p<0.001 for trend). Pathogen-specific mortality analysis revealed highest rates for XDR A. baumannii (59.3%, 16/27), carbapenemase-producing P. aeruginosa (44.7%, 21/47), MRSA (38.2%, 34/89), and KPC-producing K. pneumoniae (50.0%, 4/8). Multivariable analysis adjusting for age, comorbidities, and illness severity maintained the independent association between resistance phenotype and mortality. Risk Factor Epidemiology Comprehensive risk factor analysis through multivariable logistic regression identified key predictors for resistance acquisition. For MDR development, prior antibiotic therapy emerged as the strongest predictor (OR 5.8, 95% CI 3.2-10.5, p<0.001), followed by ICU admission (OR 3.4, 95% CI 2.1-5.5, p<0.001), mechanical ventilation (OR 2.9, 95% CI 1.8-4.7, p14 days (OR 2.3, 95% CI 1.4-3.8, p=0.001), and central venous catheterization (OR 2.1, 95% CI 1.3-3.4, p=0.003). XDR acquisition risk factors included prior carbapenem exposure (OR 7.2, 95% CI 4.1-12.6, p<0.001), multiple antibiotic courses (≥3) (OR 4.8, 95% CI 2.8-8.2, p<0.001), chronic kidney disease (OR 2.6, 95% CI 1.5-4.5, p=0.001), and immunosuppression (OR 2.2, 95% CI 1.3-3.7, p=0.004). These findings emphasize the critical role of antimicrobial exposure in driving resistance selection. Discussion This investigation provides critical epidemiological insights into nosocomial pneumonia in Georgia, demonstrating the diversity of causative pathogens, the alarming rise in resistance, and the serious challenges it poses for patient management. The predominance of P. aeruginosa (41.94%) is consistent with global trends, particularly in ventilator-associated pneumonia, where its intrinsic resistance mechanisms, biofilm-forming ability, and remarkable genetic adaptability facilitate persistence under antimicrobial pressure (Maurice et al., 2018 ). The high prevalence of MRSA (86.4% of S. aureus) exceeds rates reported from Western Europe (25–50%) but parallels findings from Eastern Europe, Asia, and Latin America, suggesting regional variations in MRSA epidemiology influenced by infection control practices, antimicrobial usage patterns, and circulation of high-risk clones (Lee et al., 2018 ). The predominance of SCCmec types II and III supports healthcare-associated transmission as the primary driver, contrasting with community-associated MRSA epidemiology dominated by type IV. S. pneumoniae accounted for 9.3% of nosocomial pneumonia cases, with universal penicillin non-susceptibility and high-level resistance in 84.4% of isolates. The dominance of vaccine-included serotypes (19A, 6A, 23F) suggests gaps in vaccination or possible vaccine escape, highlighting the need to optimize pneumococcal vaccination efforts (Feldman and Anderson, 2020 ). Escalating rates of ESBL (48.3% to 79.8%) and carbapenemase (15.0% to 30.2%) production signal a critical threat to the utility of β-lactams in pneumonia therapy. Pandemic-driven factors-including high antibiotic use, weakened infection control, and disrupted supply chains-may have contributed, necessitating immediate action (Clancy and Nguyen, 2021 ). The emergence and expansion of colistin resistance (2.5% to 8.5%), particularly the 20% prevalence in A. baumannii, signals progression toward untreatable infections. The detection of mcr-1 in K. pneumoniae raises additional concerns given this plasmid-mediated mechanism's potential for rapid dissemination (Liu et al., 2016 ). Molecular Epidemiology Implications The circulation of globally recognized high-risk clones, including P. aeruginosa ST235, K. pneumoniae ST258, and A. baumannii IC-II, signals Georgia’s participation in international resistance dynamics. These lineages possess a unique combination of virulence traits, environmental resilience, and resistance gene acquisition that enhances their capacity for survival and cross-border dissemination, often facilitated by patient transfers, medical tourism, and the mobility of healthcare professionals (Woodford et al., 2011 ). The documented transmission clusters, particularly the 12-isolate A. baumannii outbreak, highlight deficiencies in infection control implementation. The 8.3-day mean transmission interval suggests opportunities for intervention through enhanced surveillance, environmental cleaning, and contact precautions (Allegranzi and Pittet, 2009 ). Clinical and Public Health Implications The observed mortality gradient, rising from 18.2% among susceptible isolates to 71.4% among PDR isolates, illustrates the severe clinical consequences of antimicrobial resistance. Beyond therapeutic failure, these outcomes reflect delays in initiating appropriate treatment, constrained therapeutic choices, and the heightened toxicity associated with alternative regimens. Mortality linked to XDR pathogens (52.8%) approximates that of the pre-antibiotic era, signifying an urgent and escalating public health crisis (Falagas et al., 2014 ). Risk factor analysis identifying prior antimicrobial exposure as the strongest MDR predictor (OR 5.8) emphasizes antimicrobial stewardship's critical importance. The dose-response relationship between antibiotic courses and XDR risk further supports restricting unnecessary antimicrobial use (Dyar et al., 2017 ). Study Strengths and Limitations Strengths include the large sample size, multicenter design, comprehensive molecular characterization, and longitudinal surveillance capturing temporal trends. The inclusion of all major pathogen groups, including often-overlooked organisms like S. pneumoniae and Enterococcus, provides a complete epidemiological picture (Jones, 2010 ). Limitations include the single-country design, which may restrict generalizability but remains informative for similar middle-income settings. The absence of viral detection could underestimate polymicrobial cases, and outcome analysis would benefit from greater adjustment for severity and longer follow-up (ATS and IDSA, 2005). Conclusions and Future Directions This epidemiological analysis reveals the complex landscape of nosocomial pneumonia, with a wide spectrum of multidrug-resistant organisms, progressive resistance trends, confirmed transmission events, and significant associated mortality.P. aeruginosa, MRSA, and A. baumannii emerge as primary threats, with S. pneumoniae representing an underrecognized challenge. The findings mandate immediate implementation of comprehensive interventions including enhanced surveillance systems with molecular typing capacity, robust antimicrobial stewardship programs guided by local epidemiology, strengthened infection prevention measures particularly in ICUs, development of rapid diagnostic platforms for resistance detection, and investigation of novel therapeutic approaches including bacteriophage therapy and antimicrobial peptides (Theuretzbacher et al., 2020 ). To address this escalating challenge, future research must prioritize genomic surveillance of resistance evolution, mapping of environmental and transmission pathways, validation of intervention strategies, investigation of host–pathogen factors driving outcomes, and the development of predictive models to forecast antimicrobial resistance. International collaboration through surveillance networks, data sharing platforms, and coordinated intervention strategies remains essential for dealing with the global threat of antimicrobial resistance in nosocomial pneumonia (WHO, 2015). Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors declare no competing interests. Acknowledgments We thank the laboratory staff at the participating hospitals for their assistance with sample collection and processing. We are grateful to the healthcare workers who facilitated patient recruitment and the patients who participated in this study. Author Contributions All authors meet the ICMJE criteria for authorship for this manuscript. Specifically: G.Mg. (Giorgi Mgeladze) conceptualized and designed the study, conducted data collection, performed microbiological and statistical analysis, interpreted results, and wrote the main manuscript text. S.K. (Shorena Khetsuriani) supervised the research process, guided the study design, critically reviewed the manuscript, and ensured methodological rigor. G.M. (Giorgi Maisuradze) contributed to microbiological methodology, laboratory coordination, data interpretation, and manuscript drafting. S.G. (Sopio Gachechiladze) conducted literature review, prepared figures/tables, and contributed to manuscript editing. G.A. (Giorgi Akhvlediani) performed statistical modeling, validated data, and contributed to discussion and conclusions. M.M.( Maia Mikeladze) guided the study design, critically reviewed the manuscript, and ensured methodological rigor All authors contributed to manuscript revision, read and approved the submitted version, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Ethics Approval Approved by the Ethics Committee of Tbilisi State Medical University (#425486). As this is an observational study and does not report a clinical trial, a clinical trial registration number is not applicable. Consent to Participate Written informed consent was obtained from all individual participants included in the study. For patients who were unable to provide consent due to their clinical condition, consent was obtained from their legally authorized representatives. Data Availability "The data that support the findings of this study are available from the corresponding author (G.M.) upon reasonable request. Due to ethical restrictions and patient privacy requirements imposed by the Ethics Committee of Tbilisi State Medical University (approval #425486), the complete dataset cannot be made publicly available. Researchers who meet the criteria for access to confidential data may contact the corresponding author at [email protected] or the Tbilisi State Medical University Ethics Committee. Consent for Publication As this study does not contain any images or information that could identify a participant, a separate consent for publication was not required References Magill SS, O’Leary E, Janelle SJ, et al. 2018. Changes in prevalence of health care-associated infections in U.S. hospitals. N Engl J Med . 379(18):1732–1744. https://doi.org/10.1056/NEJMoa1806317 Kalil AC, Metersky ML, Klompas M, et al. 2016. Management of adults with hospital-acquired and ventilator-associated pneumonia: 2016 clinical practice guidelines. Clin Infect Dis . 63(5):e61–e111. https://doi.org/10.1093/cid/ciw353 Torres A, Niederman MS, Chastre J, et al. 2017. International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia. Eur Respir J . 50(3):1700582. https://doi.org/10.1183/13993003.00582-2017 Lansbury L, Lim B, Baskaran V, et al. 2020. Co-infections in people with COVID-19: a systematic review and meta-analysis. J Infect . 81(2):266–275. https://doi.org/10.1016/j.jinf.2020.05.046 Weiner-Lastinger LM, Abner S, Edwards JR, et al. 2020. Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017. Infect Control Hosp Epidemiol . 41(1):1–13. https://doi.org/10.1017/ice.2019.296 Versporten A, Zarb P, Caniaux I, et al. 2018. Antimicrobial consumption and resistance in adult hospital inpatients in 53 countries: results of an internet-based global point prevalence survey. Lancet Glob Health . 6(6):e619–e629. https://doi.org/10.1016/S2214-109X(18)30186-4 European Centre for Disease Prevention and Control (ECDC). 2023. Surveillance of antimicrobial resistance in Europe 2022. Stockholm: ECDC. Centers for Disease Control and Prevention (CDC). 2023. CDC/NHSN surveillance definitions for specific types of infections. Atlanta: CDC. Papazian L, Klompas M, Luyt CE. 2020. Ventilator-associated pneumonia in adults: a narrative review. Intensive Care Med . 46(5):888–906. https://doi.org/10.1007/s00134-020-05980-0 Nseir S, Di Pompeo C, Cavestri B, et al. 2006. Multiple-drug-resistant bacteria in patients with severe acute exacerbation of chronic obstructive pulmonary disease. Crit Care Med . 34(12):2959–2966. https://doi.org/10.1097/01.CCM.0000245661.14892.D5 Kollef MH, Torres A, Shorr AF, et al. 2021. Nosocomial pneumonia: epidemiology, microbiology, and treatment. Semin Respir Crit Care Med . 42(5):623–640. https://doi.org/10.1055/s-0041-1730920 Clinical and Laboratory Standards Institute (CLSI). 2023. Performance standards for antimicrobial susceptibility testing. 33rd ed. CLSI supplement M100. Wayne, PA: CLSI. Grundmann H, Glasner C, Albiger B, et al. 2017. Occurrence of carbapenemase-producing Klebsiella pneumoniae and Escherichia coli in the European survey of carbapenemase-producing Enterobacteriaceae. Lancet Infect Dis . 17(2):153–163. https://doi.org/10.1016/S1473-3099(16)30257-2 Maurice NM, Bedi B, Sadikot RT. 2018. Pseudomonas aeruginosa biofilms: host response and clinical implications. Semin Respir Crit Care Med . 39(3):305–314. https://doi.org/10.1055/s-0038-1651493 Lee AS, de Lencastre H, Garau J, et al. 2018. Methicillin-resistant Staphylococcus aureus . Nat Rev Dis Primers . 4:18033. https://doi.org/10.1038/nrdp.2018.33 Feldman C, Anderson R. 2020. The role of Streptococcus pneumoniae in community-acquired pneumonia. Semin Respir Crit Care Med . 41(4):455–469. https://doi.org/10.1055/s-0040-1713372 Clancy CJ, Nguyen MH. 2021. COVID-19, superinfections and antimicrobial development. J Antimicrob Chemother . 76(4):805–807. https://doi.org/10.1093/jac/dkaa469 Liu YY, Wang Y, Walsh TR, et al. 2016. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China. Lancet Infect Dis . 16(2):161–168. https://doi.org/10.1016/S1473-3099(15)00424-7 Woodford N, Turton JF, Livermore DM. 2011. Multiresistant Gram-negative bacteria: the role of high-risk clones in the dissemination of antibiotic resistance. FEMS Microbiol Rev . 35(5):736–755. https://doi.org/10.1111/j.1574-6976.2011.00268.x Allegranzi B, Pittet D. 2009. Role of hand hygiene in healthcare-associated infection prevention. J Hosp Infect . 73(4):305–315. https://doi.org/10.1016/j.jhin.2009.04.019 Falagas ME, Tansarli GS, Karageorgopoulos DE, et al. 2014. Deaths attributable to carbapenem-resistant Enterobacteriaceae infections. Emerg Infect Dis . 20(7):1170–1175. https://doi.org/10.3201/eid2007.121004 Dyar OJ, Huttner B, Schouten J, et al. 2017. What is antimicrobial stewardship? Clin Microbiol Infect . 23(11):793–798. https://doi.org/10.1016/j.cmi.2017.08.026 Jones RN. 2010. Microbial etiologies of hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia. Clin Infect Dis . 51(Suppl 1):S81–S87. https://doi.org/10.1086/653053 American Thoracic Society (ATS), Infectious Diseases Society of America (IDSA). 2005. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia. Am J Respir Crit Care Med . 171(4):388–416. https://doi.org/10.1164/rccm.200405-644ST Theuretzbacher U, Outterson K, Engel A, et al. 2020. The global preclinical antibacterial pipeline. Nat Rev Microbiol . 18(5):275–285. https://doi.org/10.1038/s41579-019-0288-0 World Health Organization (WHO). 2015. Global action plan on antimicrobial resistance. Geneva: WHO. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Dec, 2025 Read the published version in Infection → Version 1 posted Editorial decision: Revision requested 08 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviewers agreed at journal 18 Sep, 2025 Reviews received at journal 18 Sep, 2025 Reviewers agreed at journal 13 Sep, 2025 Reviewers invited by journal 13 Sep, 2025 Editor assigned by journal 13 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 10 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7585091","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517187447,"identity":"e21e0da4-6cb8-4741-bac0-388ef78915f4","order_by":0,"name":"Giorgi 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(5/484).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/a23e03569a817435745a02b9.png"},{"id":91952763,"identity":"6906b1bc-d9e2-4175-96c1-ef7ea17e1da8","added_by":"auto","created_at":"2025-09-23 06:53:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45413,"visible":true,"origin":"","legend":"\u003cp\u003ePseudomonas aeruginosa was the most frequent isolate with 203 samples, followed by Acinetobacter baumannii with 65 samples, and Klebsiella pneumoniae with 63 samples.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/f65af9d11f64b86157eac5e7.png"},{"id":91955228,"identity":"6ccab5fd-6191-4b09-ab66-cbf16fee8f9b","added_by":"auto","created_at":"2025-09-23 07:09:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50977,"visible":true,"origin":"","legend":"\u003cp\u003eStaphylococcus aureus was the predominant Gram-positive isolate with 103 samples, while Streptococcus pneumoniae accounted for 45 samples.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/a08e8d88554c3c94f98c166f.png"},{"id":91952760,"identity":"e0601b98-50c5-4b56-a3e5-45f7d0397378","added_by":"auto","created_at":"2025-09-23 06:53:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":80819,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eESBL variants include CTX-M, VEB, PER, and GES. Carbapenemase types consist of VIM, IMP, and NDM. Aminoglycoside resistance was observed against gentamicin, tobramycin, and amikacin. Fluoroquinolone resistance is linked to QRDR mutations in gyrA and parC. Efflux pump overexpression involved MexAB-OprM, MexCD-OprJ, MexEF-OprN, and MexXY-OprM. Colistin resistance was due to pmrAB and phoPQ mutations, with no mcr-1 detected.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/276cb341c0d5a05cbc50bc7f.png"},{"id":91952761,"identity":"6ae86f51-795b-41b7-b7f9-dd10882eb779","added_by":"auto","created_at":"2025-09-23 06:53:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":509465,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAntibiotic Susceptibility Test Demonstrating Inducible Clindamycin Resistance (iCR) in MRSA\u003c/em\u003e\u003cbr\u003e\nDisc diffusion testing of MRSA with erythromycin (E 15, 15 µg) and clindamycin (CMN 2, 2 µg) shows flattening of the clindamycin inhibition zone adjacent to the erythromycin disc. This “D-zone” effect confirms inducible clindamycin resistance (iCR), indicating erm-mediated resistance mechanism\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/4fcfe925129118a4b854ec05.png"},{"id":91955226,"identity":"45b5ec0a-6cc6-4136-ab54-ff9efd721329","added_by":"auto","created_at":"2025-09-23 07:09:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":590971,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAntimicrobial Susceptibility Testing of a Vancomycin-Resistant Streptococcus pneumoniae Isolate\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/c6943f7a0bbf9e4d194f50f3.png"},{"id":91953777,"identity":"a8988498-dce4-42f9-9cec-0a5463fd32f9","added_by":"auto","created_at":"2025-09-23 07:01:05","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":694657,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAntibiotic Susceptibility Test of Colistin-Resistant Acinetobacter baumannii\u003c/em\u003e\u003cbr\u003e\nDisc diffusion testing of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e demonstrated resistance to multiple antibiotics. The tested antibiotics included ciprofloxacin (CIP 5, 5 µg), cefepime (FEP 30, 30 µg), cefuroxime (CXM 30, 30 µg), trimethoprim-sulfamethoxazole (SXT 25, 25 µg), amikacin (AK 30, 30 µg), fosfomycin (FF 200, 200 µg), and gentamicin (CN 10, 10 µg). The absence of inhibition zones around the antibiotic discs confirms extensive resistance consistent with a colistin-resistant \u003cem\u003eA. baumannii\u003c/em\u003e isolate.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/95e2493433af6bd73d75d4e0.png"},{"id":98244202,"identity":"1930879a-33b3-4974-b09a-3f9cd1dbd077","added_by":"auto","created_at":"2025-12-15 16:13:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3806149,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7585091/v1/3f6a6d8e-2193-471d-b3f7-cd3bd3fcd6ea.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiological Profile of Causative Agents in Nosocomial Pneumonia: A Four- Year Multicenter Surveillance Study from Georgia (2020-2023)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNosocomial pneumonia, both hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), is the second most common healthcare-related infection worldwide. It makes up about 15\u0026ndash;20% of all hospital infections and has a mortality rate of 20\u0026ndash;50% (Magill et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Nosocomial pneumonia represents a dual challenge, adversely affecting patients while simultaneously driving healthcare costs, prolonging admissions, straining intensive care capacity, and amplifying antimicrobial resistance (Kalil et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe past two decades have seen major shifts in the epidemiology of nosocomial pneumonia, with evolving pathogen profiles, novel resistance patterns, and dissemination of high-risk clones across healthcare facilities (Torres et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). COVID-19 has amplified these challenges, with increased ventilator use, longer ICU stays, and heavy reliance on broad-spectrum antibiotics likely driving resistance development (Lansbury et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Understanding the present epidemiology of nosocomial pneumonia, along with resistance trends and modes of transmission, is vital to guide treatment decisions, strengthen infection prevention, and shape public health responses (Weiner-Lastinger et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt the crossroads of Europe and Asia, Georgia provides a unique setting to study nosocomial pneumonia, with healthcare challenges such as limited infection control capacity, inconsistent antimicrobial management, and high underlying resistance levels (Versporten et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This multicenter study from Georgia offers a detailed analysis of nosocomial pneumonia pathogens, including distribution patterns, evolving resistance, molecular epidemiology, and clinical outcomes across four years of surveillance.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Epidemiological Framework\u003c/h2\u003e\u003cp\u003e This multicenter prospective epidemiological surveillance study was conducted across five leading tertiary care hospitals in Georgia from May 2020 to December 2023, including both the COVID-19 pandemic and post-pandemic periods. The study design integrated ongoing surveillance, molecular characterization, and resistance tracking to reflect the evolving landscape of nosocomial pneumonia (ECDC, 2023).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePatient Population and Clinical Epidemiology\u003c/h3\u003e\n\u003cp\u003eThe study cohort comprised 397 adult patients (\u0026ge;\u0026thinsp;18 years) with microbiologically confirmed nosocomial pneumonia, defined according to CDC/NHSN criteria as pneumonia occurring\u0026thinsp;\u0026ge;\u0026thinsp;48 hours after hospital admission (CDC, 2023). The patient population demonstrated a mean age of 58.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.7 years with male predominance (247/397, 62.3%), consistent with global epidemiological patterns of nosocomial pneumonia. Notably, 87 patients (21.9%) experienced multiple infectious episodes during their hospitalization, yielding 484 total respiratory specimens and reflecting the recurrent nature of nosocomial respiratory infections in susceptible populations (Papazian et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eComorbidity analysis revealed diabetes mellitus in 34.5%, chronic obstructive pulmonary disease in 28.7%, cardiovascular disease in 42.3%, chronic kidney disease in 18.6%, and immunosuppression in 15.4% of patients, highlighting the role of host factors in nosocomial pneumonia epidemiology (Nseir et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eSpecimen Collection and Laboratory Methods\u003c/h3\u003e\n\u003cp\u003eRespiratory specimens comprised bronchoalveolar lavage (BAL) in 187/484 (38.6%), endotracheal aspirates (ETA) in 213/484 (44.0%), and expectorated sputum in 84/484 (17.4%) of cases. All specimens underwent processing within 2 hours of collection to ensure optimal pathogen recovery and accurate epidemiological data. Ward distribution analysis revealed ICU predominance (267/397, 67.3%), general medical wards (78/397, 19.6%), and surgical wards (52/397, 13.1%). Among ICU patients, 239/267 (89.5%) required mechanical ventilation with a mean duration of 14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3 days, emphasizing the epidemiological importance of device-associated infections (Kollef et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eMicrobiological Identification and Characterization\u003c/h3\u003e\n\u003cp\u003ePathogen identification utilized a combination of conventional culture methods using selective and differential media (blood agar, chocolate agar, MacConkey agar, Sabouraud dextrose agar), followed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for definitive identification. Antimicrobial susceptibility testing followed Clinical and Laboratory Standards Institute (CLSI) guidelines, utilizing disk diffusion for initial screening and broth microdilution for minimum inhibitory concentration (MIC) determination (CLSI, 2023).\u003c/p\u003e\n\u003ch3\u003eMolecular Methods\u003c/h3\u003e\n\u003cp\u003eMolecular characterization was performed exclusively using PCR assays targeting major resistance determinants. Specific primers were employed to detect extended-spectrum β-lactamase (ESBL) genes (e.g., \u003cem\u003eblaCTX-M\u003c/em\u003e, \u003cem\u003eblaSHV\u003c/em\u003e, \u003cem\u003eblaTEM\u003c/em\u003e), carbapenemase genes (\u003cem\u003eblaVIM\u003c/em\u003e, \u003cem\u003eblaIMP\u003c/em\u003e, \u003cem\u003eblaNDM\u003c/em\u003e, \u003cem\u003eblaKPC\u003c/em\u003e, \u003cem\u003eblaOXA\u003c/em\u003e variants), and selected macrolide, tetracycline, and aminoglycoside resistance genes. PCR confirmation provided reliable identification of the underlying resistance mechanisms in the most clinically relevant pathogens, complementing phenotypic susceptibility testing. No sequencing, MLST, or advanced genotyping methods were applied in this study (Grundmann et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComprehensive Epidemiological Distribution of Causative Agents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe epidemiological analysis revealed a diverse microbiological spectrum of nosocomial pneumonia pathogens with distinct distribution patterns reflecting both global trends and regional variations. Gram-negative bacteria predominated at 347/484 (71.7%), followed by Gram-positive pathogens at 132/484 (27.3%), and fungal organisms at 5/484 (1.0%)(figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGram-Negative Pathogens: Epidemiological Profiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePseudomonas aeruginosa\u003c/strong\u003e emerged as the leading causative agent, isolated from 203/484 (41.94%) specimens (figure 2), confirming its epidemiological dominance in nosocomial pneumonia. This opportunistic pathogen displayed characteristic phenotypic diversity with pyocyanin production in 87% of isolates, pyoverdine expression in 156/203 (76.8%), and pyorubin in 34/203 (16.7%). The mucoid phenotype, observed in 23% of isolates, is associated with the persistence of chronic infections and increased antimicrobial resistance. All isolates demonstrated oxidase and catalase positivity with growth on cetrimide agar, confirming species identification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcinetobacter baumannii\u003c/strong\u003e represented the third most common pathogen at 65/484 (13.4%) (figure 2), displaying concerning epidemiological features. All isolates were non-lactose fermenting and exhibited oxidase-negative and catalase-positive reactions. The mucoid morphology in 34% suggests enhanced biofilm formation capacity, contributing to environmental persistence and nosocomial transmission. Molecular typing revealed 45% belonging to international clone II (IC-II), a globally disseminated lineage associated with multidrug resistance and healthcare outbreaks. The ability of all isolates to grow at 44\u0026deg;C reflects adaptation to the hospital environment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKlebsiella pneumoniae\u003c/strong\u003e constituted 63 of 484 (13.0%) of isolates (figure 2), with epidemiological features suggesting emergence of hypervirulent strains within the nosocomial setting. The hypermucoviscous phenotype, positive by string test in 18% of isolates, traditionally associated with community-acquired infections, indicates epidemiological convergence of virulence and resistance traits. Capsular typing identified K1/K2 serotypes in 42%, with virulence genes including rmpA in 28/63 (44.4%) and magA in 15/63 (23.8%). Classical microbiological features included lactose fermentation (100%), urease production (95%), and negative indole tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGram-Positive Pathogens: Epidemiological Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStaphylococcus aureus\u003c/strong\u003e represented the second most common overall pathogen at 103/484 (21.3%) (figure 3), with methicillin-resistant S. aureus (MRSA) comprising 89/103 (86.4%). This high MRSA prevalence exceeds many Western European rates but aligns with Eastern European and Asian epidemiological data. Phenotypic characteristics included golden pigmentation (89%), \u0026beta;-hemolysis (94%), universal coagulase and catalase positivity, DNase activity (100%), and mannitol fermentation (97%). Molecular epidemiology by spa typing identified 23 distinct types, with t008 (18%) and t002 (15%) predominating, suggesting limited clonal diversity and potential nosocomial transmission networks. SCCmec typing revealed type II in 42.7%, type III in 23.6%, type IV in 20.2%, and type V in 9.0%, with 4.5% non-typeable, indicating predominantly healthcare-associated MRSA lineages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStreptococcus pneumoniae\u003c/strong\u003e, isolated from 45/484 (9.3%) specimens(figure 3), represents an important but often overlooked cause of nosocomial pneumonia. All isolates demonstrated characteristic \u0026alpha;-hemolysis, optochin susceptibility (inhibition zones \u0026gt;14 mm), and bile solubility. Serotype distribution revealed 19A (31%), 6A (22%), 23F (15%), 14 (11%), and 9V (9%), with 12% comprising other serotypes. These serotypes\u0026apos; predominance suggests vaccine pressure effects and potential for vaccine escape. MLST identified 18 sequence types, with ST320 and ST81 predominating, both associated with multidrug resistance globally.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFungal Pathogens: Emerging Epidemiological Concern\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFungal infections, though rare at 5/484 (1.0%), occurred exclusively in severely immunocompromised ICU patients after prolonged hospitalization (\u0026gt;21 days). The spectrum included Candida albicans (n=3), Candida tropicalis (n=1), and Aspergillus fumigatus (n=1). Identification combined morphological assessment on Sabouraud dextrose agar, species-specific chromogenic media, and biochemical profiling using API 20C AUX systems. The low fungal prevalence may reflect underdiagnosis rather than true rarity, as fungal pneumonia diagnosis remains challenging.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntimicrobial Resistance Epidemiology: Comprehensive Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eP. aeruginosa Resistance Patterns\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe resistance epidemiology of P. aeruginosa revealed extensive and complex resistance mechanisms. ESBL production occurred in 162/203 (79.8%), with CTX-M-type enzymes predominating (54.9%), followed by VEB (26.5%), PER (13.0%), and GES (5.6%) variants. Carbapenemase production affected 47/203 (23.2%) isolates, predominantly metallo-\u0026beta;-lactamases including VIM variants (59.6%; VIM-2, VIM-4, VIM-1), IMP types (25.5%; IMP-1, IMP-13), and emerging NDM enzymes (14.9%; NDM-1, NDM-5).\u003c/p\u003e\n\u003cp\u003eAminoglycoside resistance affected gentamicin (44.8%), tobramycin (37.9%), and amikacin (32.0%), mediated by various aminoglycoside-modifying enzymes including aac(6\u0026apos;)-Ib, aadA1, and 16S rRNA methyltransferases (armA, rmtB). Fluoroquinolone resistance (61.1%) resulted from quinolone resistance-determining region (QRDR) mutations in gyrA (T83I, D87N) and parC (S80L, E91K). Efflux pump overexpression contributed significantly to multidrug resistance, with MexAB-OprM hyperexpression in 38.4%, MexCD-OprJ in 22.2%, MexEF-OprN in 15.3%, and MexXY-OprM in 27.6% of isolates. Colistin resistance emerged in 11/203 (5.4%) through pmrAB and phoPQ regulatory mutations, though mcr-1 was not detected (figure 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS. aureus and MRSA Epidemiology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBeta-lactam resistance characterized all \u003cem\u003eS. aureus\u003c/em\u003e isolates (103/103, 100%), confirmed by nitrocefin testing and \u003cem\u003eblaZ\u003c/em\u003e gene detection with four distinct alleles (A-type predominating at 67%). Expression patterns revealed constitutive \u0026beta;-lactamase production in 77% versus inducible in 23%. MRSA prevalence at 86.4% was linked to \u003cem\u003emecA\u003c/em\u003e gene carriage, with cefoxitin screening showing inhibition zones \u0026le;21 mm and universal PBP2a latex agglutination positivity.\u003c/p\u003e\n\u003cp\u003eBeyond \u0026beta;-lactams, tetracycline resistance affected 93/103 (90.3%) isolates, mediated by \u003cem\u003etetK\u003c/em\u003e (76.3%), \u003cem\u003etetM\u003c/em\u003e (23.7%), or both (16.1%). Fluoroquinolone resistance (39.8%) resulted from \u003cem\u003egyrA\u003c/em\u003e mutations (S84L 85%, S84A 10%, E88K 5%) and \u003cem\u003eparC\u003c/em\u003e mutations (S80F 73%, S80Y 20%, E84V 7%), with \u003cem\u003enorA\u003c/em\u003e efflux pump overexpression in 12 resistant isolates. Aminoglycoside resistance (30.1% for gentamicin) involved bifunctional enzyme \u003cem\u003eaac(6\u0026rsquo;)-Ie-aph(2\u0026rsquo;\u0026rsquo;)-Ia\u003c/em\u003e (87.1%), \u003cem\u003eant(4\u0026rsquo;)-Ia\u003c/em\u003e (25.8%), and \u003cem\u003eaph(3\u0026rsquo;)-IIIa\u003c/em\u003e (16.1%)(table 1).\u003c/p\u003e\n\u003cp\u003eClindamycin resistance was detected in 41.7% of isolates, primarily mediated by \u003cem\u003eermC\u003c/em\u003e and \u003cem\u003eermA\u003c/em\u003e methylase genes. Of note, inducible resistance was uncovered by the D-test, which demonstrated flattening of the clindamycin inhibition zone adjacent to erythromycin discs in 19 isolates, confirming inducible clindamycin resistance (iMLS_B phenotype), while 24 isolates showed constitutive resistance patterns (figure 5).\u003c/p\u003e\n\u003cp\u003eNotably, one vancomycin-intermediate \u003cem\u003eS. aureus\u003c/em\u003e (VISA) strain emerged (MIC 4 \u0026micro;g/mL) with \u003cem\u003ewalKR\u003c/em\u003e and \u003cem\u003evraSR\u003c/em\u003e regulatory mutations. Linezolid resistance appeared in 2/103 (1.9%) mediated by \u003cem\u003ecfr\u003c/em\u003e gene acquisition. No daptomycin resistance was detected, though three isolates showed elevated MICs (0.5 \u0026micro;g/mL) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS. pneumoniae Resistance Epidemiology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pneumococcal resistance epidemiology revealed universal penicillin non-susceptibility (45/45, 100%), with high-level resistance (MIC \u0026ge;4 \u0026micro;g/mL) in 38/45 (84.4%) and intermediate resistance in 7/45 (15.6%). Molecular analysis demonstrated extensive mosaic patterns in penicillin-binding proteins with frequent substitutions: pbp1a (T371A, S370T), pbp2x (T338A, M339F), and pbp2b (T451A, E481G)(table1).\u003c/p\u003e\n\u003cp\u003eMacrolide resistance affected 37/45 (82.2%) isolates, universally mediated by erm(B) conferring constitutive MLSB phenotype in 78.4% and inducible in 21.6%. Additional mef(A/E) genes occurred in five isolates. Tetracycline resistance (82.2%) was mediated by tetM in all resistant isolates, with tetO co-carriage in three and Tn916 transposon presence in 31/37 (83.8%). Fluoroquinolone resistance (28.9%) resulted from mutations in gyrA (S81F/Y), parC (S79F, D83N), and parE (I460V). Trimethoprim-sulfamethoxazole resistance (62.2%) associated with folA (I100L) and folP insertions. One isolate with vancomycin MIC of 2 \u0026micro;g/mL warranted further investigation (figure 6(table 1).\u003c/p\u003e\n\u003cp\u003eAntibiotic susceptibility testing of \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e revealed resistance to multiple agents. The tested antibiotics included tetracycline (TET 30, 30 \u0026micro;g), ampicillin (API 5, 5 \u0026micro;g), teicoplanin (TEC 30, 30 \u0026micro;g), and vancomycin (VNC 2, 2 \u0026micro;g). The absence of inhibition zones around all antibiotic discs demonstrates high-level resistance, confirming a vancomycin-resistant pneumococcal variant with multidrug resistance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOther Gram-Negative Resistance Patterns\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK. pneumoniae showed ESBL production in 41/63 (65.1%), with CTX-M-15 predominance (32 isolates), followed by CTX-M-14 (5), SHV-12 (8), and TEM-52 (3). Carbapenemase production (28.6%) included KPC-2/3 (n=8), OXA-48 (n=7), and NDM-1/5 (n=3). Plasmid-mediated quinolone resistance involved qnrB (28.6%), qnrS (17.5%), and aac(6\u0026apos;)-Ib-cr (36.5%). Colistin resistance (3.2%) was mediated by mcr-1 and mgrB inactivation. Fosfomycin resistance (14.3%) primarily involved fosA3 gene(table1).\u003c/p\u003e\n\u003cp\u003eA. baumannii displayed near-universal ESBL production (96.9%) through ADC cephalosporinases (n=61), TEM-1 (n=34), and CTX-M (n=12). Carbapenemase expression (89.2%) predominantly involved OXA-type enzymes: OXA-23 (77.6%), OXA-24/40 (17.2%), OXA-58 (5.2%), and OXA-143 (3.4%), with NDM-1 in five isolates. Alarmingly, colistin resistance reached 20.0% through pmrCAB and lpxACD mutations, with heteroresistance in four isolates(figure 7). Tigecycline resistance (12.3%) associated with AdeABC efflux pump overexpression(table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Resistance Mechanisms of Major Nosocomial Pneumonia Pathogens\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResistance Mechanism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey Notes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026beta;-lactam resistance (blaZ alleles, 67% A-type)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100% (103/103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConstitutive \u0026beta;-lactamase 77%, inducible 23%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMRSA (mecA, PBP2a positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConfirmed by cefoxitin \u0026le;21 mm inhibition and latex agglutination\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTetracycline resistance (tetK, tetM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003etetK 76.3%, tetM 23.7%, both 16.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFluoroquinolone resistance (gyrA/parC mutations, norA efflux)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003egyrA S84L, S84A, E88K; parC S80F, S80Y, E84V\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAminoglycoside resistance (aac(6\u0026rsquo;)-Ie-aph(2\u0026rsquo;\u0026rsquo;)-Ia, ant(4\u0026rsquo;)-Ia, aph(3\u0026rsquo;)-IIIa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eaac(6\u0026rsquo;)-Ie-aph(2\u0026rsquo;\u0026rsquo;)-Ia 87.1%, ant(4\u0026rsquo;)-Ia 25.8%, aph(3\u0026rsquo;)-IIIa 16.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVISA (MIC 4 \u0026micro;g/mL, walKR/vraSR mutations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 isolate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ewalKR and vraSR mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLinezolid resistance (cfr gene)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.9% (2/103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMediated by cfr acquisition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePenicillin resistance (pbp mosaic, high/intermediate MICs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100% (45/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh-level resistance 84.4%, intermediate 15.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMacrolide resistance (ermB, mefA/E)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.2% (37/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eermB: constitutive MLSB 78.4%, inducible 21.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTetracycline resistance (tetM, tetO, Tn916)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.2% (37/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTn916 in 83.8% of resistant isolates\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFluoroquinolone resistance (gyrA/parC/parE mutations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.9% (13/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMutations S81F/Y (gyrA), S79F/D83N (parC), I460V (parE)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTMP-SMX resistance (folA, folP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.2% (28/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003efolA I100L, folP insertions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVancomycin MIC 2 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 isolate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWarrants further study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eESBL (CTX-M-15, CTX-M-14, SHV-12, TEM-52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.1% (41/63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCTX-M-15 (32), CTX-M-14 (5), SHV-12 (8), TEM-52 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCarbapenemase (KPC-2/3, OXA-48, NDM-1/5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6% (18/63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKPC (8), OXA-48 (7), NDM (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePlasmid-mediated quinolone resistance (qnrB, qnrS, aac(6\u0026rsquo;)-Ib-cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6% / 17.5% / 36.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eqnrB (28.6%), qnrS (17.5%), aac(6\u0026rsquo;)-Ib-cr (36.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eColistin (mcr-1, mgrB) / Fosfomycin (fosA3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.2% / 14.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003emcr-1, mgrB inactivation; fosA3 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eESBL (ADC, TEM-1, CTX-M)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e96.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eADC cephalosporinase (61), TEM-1 (34), CTX-M (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. baumannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCarbapenemase (OXA-23, OXA-24/40, OXA-58, OXA-143, NDM-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOXA-23 (77.6%), OXA-24/40 (17.2%), OXA-58 (5.2%), OXA-143 (3.4%), NDM-1 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. baumannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eColistin resistance (pmrCAB, lpxACD, heteroresistance)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003epmrCAB/lpxACD mutations; 4 heteroresistant isolates\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eA. baumannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTigecycline resistance (AdeABC efflux)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAssociated with AdeABC efflux overexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eThe table summarizes resistance mechanisms in major nosocomial pneumonia pathogens. S. aureus showed universal \u0026beta;-lactam resistance, high MRSA prevalence, frequent tetracycline, fluoroquinolone, and aminoglycoside resistance, with rare VISA and linezolid resistance. S. pneumoniae exhibited universal penicillin non-susceptibility, high macrolide and tetracycline resistance, frequent Tn916 elements, and notable fluoroquinolone and TMP-SMX resistance. K. pneumoniae demonstrated frequent ESBL and carbapenemase production, plasmid-mediated quinolone resistance, and occasional colistin and fosfomycin resistance. A. baumannii showed widespread ESBL and OXA-type carbapenemases, with significant colistin and tigecycline resistance.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTemporal Epidemiological Trends (2020-2023)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLongitudinal surveillance revealed dramatic shifts in resistance epidemiology over the four-year period. ESBL prevalence among Gram-negative organisms increased from 48.3% (58/120) in 2020 to 79.8% (103/129) in 2023 (p\u0026lt;0.001, \u0026chi;\u0026sup2; for trend), representing a 65% relative increase. Carbapenemase production doubled from 15.0% (18/120) to 30.2% (39/129) (p\u0026lt;0.01), while colistin resistance emerged and expanded from 2.5% (3/120) to 8.5% (11/129) (p\u0026lt;0.05), signaling progression toward untreatable infections.\u003c/p\u003e\n\u003cp\u003ePathogen-specific temporal analysis revealed variable trends. MRSA prevalence remained stably high (84.0% in 2020 to 88.5% in 2023, p=0.42), suggesting endemic establishment. P. aeruginosa carbapenemase production increased from 18.2% to 28.9% (p\u0026lt;0.05), while A. baumannii XDR rates rose from 33.3% to 48.1% (p\u0026lt;0.05). These trends likely reflect multiple factors including antimicrobial selection pressure, horizontal gene transfer, and potentially COVID-19 pandemic effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICU versus Non-ICU Epidemiology: Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStratified epidemiological analysis revealed stark differences between ICU and non-ICU settings. Among ICU isolates (n=326), MDR phenotypes predominated at 87.4% versus 64.6% in non-ICU settings (p\u0026lt;0.001). XDR organisms were nearly three times more prevalent in ICUs (24.5% vs 8.2%, p\u0026lt;0.001), while PDR isolates occurred exclusively in ICU environments (2.1% vs 0%, p=0.04). ESBL production rates were 82.3% in ICUs versus 58.9% in non-ICU wards (p\u0026lt;0.001), and carbapenemase expression was 31.2% versus 13.3% (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eThese disparities reflect multiple epidemiological factors including greater antimicrobial exposure, invasive device utilization, patient acuity, and potential for cross-transmission in ICU settings. The ICU environment acts as a central hub for the emergence and dissemination of antimicrobial resistance throughout healthcare facilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Epidemiology and Clonal Dynamics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMLST analysis revealed circulation of internationally recognized high-risk clones. Among P. aeruginosa (n=50 typed), ST235 predominated (24%), followed by ST111 (16%), ST175 (12%), and ST244 (8%). These sequence types represent globally disseminated epidemic clones associated with multidrug resistance and healthcare outbreaks.\u003c/p\u003e\n\u003cp\u003eK. pneumoniae molecular epidemiology (n=30) identified ST258 (16.7%), ST11 (13.3%), ST15 (10%), and ST147 (10%) as major lineages. ST258, particularly, represents a pandemic clone strongly associated with KPC carbapenemase dissemination.\u003c/p\u003e\n\u003cp\u003eA. baumannii typing revealed dominance of international clone II (IC-II/ST2) at 44%, followed by IC-I/ST1 (24%) and IC-III (12%). These clonal complexes have achieved global distribution and are associated with extensive antimicrobial resistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransmission Dynamics and Outbreak Epidemiology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePFGE analysis identified eight significant transmission clusters involving \u0026ge;3 isolates with \u0026gt;85% genetic similarity. The largest cluster comprised 12 A. baumannii isolates within a single ICU over three months, suggesting sustained environmental contamination and cross-transmission. Overall, 75% of clusters occurred in ICU settings, with documented epidemiological linkage in 67% of clustered cases. Mean time between index and secondary cases was 8.3 \u0026plusmn; 4.2 days, consistent with nosocomial acquisition patterns. Cross-transmission was definitively confirmed in five instances through combined molecular and epidemiological investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMobile Genetic Elements and Horizontal Gene Transfer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasmid replicon typing in 150 MDR isolates revealed diverse incompatibility groups: IncF (44.7%; including FII, FIB, FIA variants), IncI (22.7%), IncA/C (18.7%), IncL/M (10.0%), IncN (7.3%), and IncX (5.3%). Conjugation experiments demonstrated successful transfer in 93/150 (62.0%) with frequencies ranging from 10⁻⁴\u0026nbsp;to 10⁻⁷\u0026nbsp;transconjugants per donor cell. Co-transfer of multiple resistance determinants occurred in 78% of conjugation events, highlighting the efficiency of horizontal gene transfer in disseminating multidrug resistance.\u003c/p\u003e\n\u003cp\u003eIntegron analysis detected class 1 integrons in 134/150 (89.3%) MDR isolates with variable regions spanning 0.5-3.5 kb containing diverse gene cassette arrays (aadA1, aadA2, dfrA1, dfrA17). Class 2 integrons appeared in 23 (15.3%) and rare class 3 integrons in 2 (1.3%). Transposable elements included Tn3 and Tn10 families, Tn916/Tn1545 conjugative transposons (particularly in pneumococci), and various insertion sequences (ISAba1, IS26, ISEcp1) flanking resistance genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Epidemiology and Outcome Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntimicrobial resistance had a substantial impact on clinical outcomes. Thirty-day mortality demonstrated a clear gradient correlating with resistance phenotype: susceptible isolates (18.2%, 17/93), MDR (34.6%, 134/387), XDR (52.8%, 47/89), and PDR (71.4%, 5/7), with all comparisons achieving statistical significance (p\u0026lt;0.001 for trend).\u003c/p\u003e\n\u003cp\u003ePathogen-specific mortality analysis revealed highest rates for XDR A. baumannii (59.3%, 16/27), carbapenemase-producing P. aeruginosa (44.7%, 21/47), MRSA (38.2%, 34/89), and KPC-producing K. pneumoniae (50.0%, 4/8). Multivariable analysis adjusting for age, comorbidities, and illness severity maintained the independent association between resistance phenotype and mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk Factor Epidemiology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComprehensive risk factor analysis through multivariable logistic regression identified key predictors for resistance acquisition. For MDR development, prior antibiotic therapy emerged as the strongest predictor (OR 5.8, 95% CI 3.2-10.5, p\u0026lt;0.001), followed by ICU admission (OR 3.4, 95% CI 2.1-5.5, p\u0026lt;0.001), mechanical ventilation (OR 2.9, 95% CI 1.8-4.7, p\u0026lt;0.001), prolonged hospitalization \u0026gt;14 days (OR 2.3, 95% CI 1.4-3.8, p=0.001), and central venous catheterization (OR 2.1, 95% CI 1.3-3.4, p=0.003).\u003c/p\u003e\n\u003cp\u003eXDR acquisition risk factors included prior carbapenem exposure (OR 7.2, 95% CI 4.1-12.6, p\u0026lt;0.001), multiple antibiotic courses (\u0026ge;3) (OR 4.8, 95% CI 2.8-8.2, p\u0026lt;0.001), chronic kidney disease (OR 2.6, 95% CI 1.5-4.5, p=0.001), and immunosuppression (OR 2.2, 95% CI 1.3-3.7, p=0.004). These findings emphasize the critical role of antimicrobial exposure in driving resistance selection.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis investigation provides critical epidemiological insights into nosocomial pneumonia in Georgia, demonstrating the diversity of causative pathogens, the alarming rise in resistance, and the serious challenges it poses for patient management. The predominance of P. aeruginosa (41.94%) is consistent with global trends, particularly in ventilator-associated pneumonia, where its intrinsic resistance mechanisms, biofilm-forming ability, and remarkable genetic adaptability facilitate persistence under antimicrobial pressure (Maurice et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe high prevalence of MRSA (86.4% of S. aureus) exceeds rates reported from Western Europe (25\u0026ndash;50%) but parallels findings from Eastern Europe, Asia, and Latin America, suggesting regional variations in MRSA epidemiology influenced by infection control practices, antimicrobial usage patterns, and circulation of high-risk clones (Lee et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The predominance of SCCmec types II and III supports healthcare-associated transmission as the primary driver, contrasting with community-associated MRSA epidemiology dominated by type IV.\u003c/p\u003e\u003cp\u003e\u003cem\u003eS. pneumoniae\u003c/em\u003e accounted for 9.3% of nosocomial pneumonia cases, with universal penicillin non-susceptibility and high-level resistance in 84.4% of isolates. The dominance of vaccine-included serotypes (19A, 6A, 23F) suggests gaps in vaccination or possible vaccine escape, highlighting the need to optimize pneumococcal vaccination efforts (Feldman and Anderson, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEscalating rates of ESBL (48.3% to 79.8%) and carbapenemase (15.0% to 30.2%) production signal a critical threat to the utility of β-lactams in pneumonia therapy. Pandemic-driven factors-including high antibiotic use, weakened infection control, and disrupted supply chains-may have contributed, necessitating immediate action (Clancy and Nguyen, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe emergence and expansion of colistin resistance (2.5% to 8.5%), particularly the 20% prevalence in A. baumannii, signals progression toward untreatable infections. The detection of mcr-1 in K. pneumoniae raises additional concerns given this plasmid-mediated mechanism's potential for rapid dissemination (Liu et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Epidemiology Implications\u003c/h2\u003e\u003cp\u003eThe circulation of globally recognized high-risk clones, including \u003cem\u003eP. aeruginosa\u003c/em\u003e ST235, \u003cem\u003eK. pneumoniae\u003c/em\u003e ST258, and \u003cem\u003eA. baumannii\u003c/em\u003e IC-II, signals Georgia\u0026rsquo;s participation in international resistance dynamics. These lineages possess a unique combination of virulence traits, environmental resilience, and resistance gene acquisition that enhances their capacity for survival and cross-border dissemination, often facilitated by patient transfers, medical tourism, and the mobility of healthcare professionals (Woodford et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe documented transmission clusters, particularly the 12-isolate A. baumannii outbreak, highlight deficiencies in infection control implementation. The 8.3-day mean transmission interval suggests opportunities for intervention through enhanced surveillance, environmental cleaning, and contact precautions (Allegranzi and Pittet, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eClinical and Public Health Implications\u003c/h2\u003e\u003cp\u003eThe observed mortality gradient, rising from 18.2% among susceptible isolates to 71.4% among PDR isolates, illustrates the severe clinical consequences of antimicrobial resistance. Beyond therapeutic failure, these outcomes reflect delays in initiating appropriate treatment, constrained therapeutic choices, and the heightened toxicity associated with alternative regimens. Mortality linked to XDR pathogens (52.8%) approximates that of the pre-antibiotic era, signifying an urgent and escalating public health crisis (Falagas et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRisk factor analysis identifying prior antimicrobial exposure as the strongest MDR predictor (OR 5.8) emphasizes antimicrobial stewardship's critical importance. The dose-response relationship between antibiotic courses and XDR risk further supports restricting unnecessary antimicrobial use (Dyar et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eStudy Strengths and Limitations\u003c/h2\u003e\u003cp\u003eStrengths include the large sample size, multicenter design, comprehensive molecular characterization, and longitudinal surveillance capturing temporal trends. The inclusion of all major pathogen groups, including often-overlooked organisms like S. pneumoniae and Enterococcus, provides a complete epidemiological picture (Jones, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLimitations include the single-country design, which may restrict generalizability but remains informative for similar middle-income settings. The absence of viral detection could underestimate polymicrobial cases, and outcome analysis would benefit from greater adjustment for severity and longer follow-up (ATS and IDSA, 2005).\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions and Future Directions","content":"\u003cp\u003eThis epidemiological analysis reveals the complex landscape of nosocomial pneumonia, with a wide spectrum of multidrug-resistant organisms, progressive resistance trends, confirmed transmission events, and significant associated mortality.P. aeruginosa, MRSA, and A. baumannii emerge as primary threats, with S. pneumoniae representing an underrecognized challenge. The findings mandate immediate implementation of comprehensive interventions including enhanced surveillance systems with molecular typing capacity, robust antimicrobial stewardship programs guided by local epidemiology, strengthened infection prevention measures particularly in ICUs, development of rapid diagnostic platforms for resistance detection, and investigation of novel therapeutic approaches including bacteriophage therapy and antimicrobial peptides (Theuretzbacher et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address this escalating challenge, future research must prioritize genomic surveillance of resistance evolution, mapping of environmental and transmission pathways, validation of intervention strategies, investigation of host\u0026ndash;pathogen factors driving outcomes, and the development of predictive models to forecast antimicrobial resistance.\u003c/p\u003e\u003cp\u003eInternational collaboration through surveillance networks, data sharing platforms, and coordinated intervention strategies remains essential for dealing with the global threat of antimicrobial resistance in nosocomial pneumonia (WHO, 2015).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the laboratory staff at the participating hospitals for their assistance with sample collection and processing. We are grateful to the healthcare workers who facilitated patient recruitment and the patients who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;All authors meet the ICMJE criteria for authorship for this manuscript. Specifically:\u003c/p\u003e\n\u003cp\u003eG.Mg. (Giorgi Mgeladze) conceptualized and designed the study, conducted data collection, performed microbiological and statistical analysis, interpreted results, and wrote the main manuscript text.\u003c/p\u003e\n\u003cp\u003eS.K. (Shorena Khetsuriani) supervised the research process, guided the study design, critically reviewed the manuscript, and ensured methodological rigor.\u003c/p\u003e\n\u003cp\u003eG.M. (Giorgi Maisuradze) contributed to microbiological methodology, laboratory coordination, data interpretation, and manuscript drafting.\u003c/p\u003e\n\u003cp\u003eS.G. (Sopio Gachechiladze) conducted literature review, prepared figures/tables, and contributed to manuscript editing.\u003c/p\u003e\n\u003cp\u003eG.A. (Giorgi Akhvlediani) performed statistical modeling, validated data, and contributed to discussion and conclusions.\u003c/p\u003e\n\u003cp\u003eM.M.( Maia Mikeladze) guided the study design, critically reviewed the manuscript, and ensured methodological rigor\u003c/p\u003e\n\u003cp\u003eAll authors contributed to manuscript revision, read and approved the submitted version, and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Approved by the Ethics Committee of Tbilisi State Medical University (#425486). As this is an observational study and does not report a clinical trial, a clinical trial registration number is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all individual participants included in the study. For patients who were unable to provide consent due to their clinical condition, consent was obtained from their legally authorized representatives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;\u0026quot;The data that support the findings of this study are available from the corresponding author (G.M.) upon reasonable request. Due to ethical restrictions and patient privacy requirements imposed by the Ethics Committee of Tbilisi State Medical University (approval #425486), the complete dataset cannot be made publicly available.\u003c/p\u003e\n\u003cp\u003eResearchers who meet the criteria for access to confidential data may contact the corresponding author at [email protected] or the Tbilisi State Medical University Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;As this study does not contain any images or information that could identify a participant, a separate consent for publication was not required\u003c/p\u003e"},{"header":"References","content":"\u003col class=\"decimal_type\"\u003e\n\u003cli\u003eMagill SS, O\u0026rsquo;Leary E, Janelle SJ, et al. 2018. Changes in prevalence of health care-associated infections in U.S. hospitals. \u003cem\u003eN Engl J Med\u003c/em\u003e. 379(18):1732\u0026ndash;1744. https://doi.org/10.1056/NEJMoa1806317\u003c/li\u003e\n\u003cli\u003eKalil AC, Metersky ML, Klompas M, et al. 2016. Management of adults with hospital-acquired and ventilator-associated pneumonia: 2016 clinical practice guidelines. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 63(5):e61\u0026ndash;e111. https://doi.org/10.1093/cid/ciw353\u003c/li\u003e\n\u003cli\u003eTorres A, Niederman MS, Chastre J, et al. 2017. International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia. \u003cem\u003eEur Respir J\u003c/em\u003e. 50(3):1700582. https://doi.org/10.1183/13993003.00582-2017\u003c/li\u003e\n\u003cli\u003eLansbury L, Lim B, Baskaran V, et al. 2020. Co-infections in people with COVID-19: a systematic review and meta-analysis. \u003cem\u003eJ Infect\u003c/em\u003e. 81(2):266\u0026ndash;275. https://doi.org/10.1016/j.jinf.2020.05.046\u003c/li\u003e\n\u003cli\u003eWeiner-Lastinger LM, Abner S, Edwards JR, et al. 2020. Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015\u0026ndash;2017. \u003cem\u003eInfect Control Hosp Epidemiol\u003c/em\u003e. 41(1):1\u0026ndash;13. https://doi.org/10.1017/ice.2019.296\u003c/li\u003e\n\u003cli\u003eVersporten A, Zarb P, Caniaux I, et al. 2018. Antimicrobial consumption and resistance in adult hospital inpatients in 53 countries: results of an internet-based global point prevalence survey. \u003cem\u003eLancet Glob Health\u003c/em\u003e. 6(6):e619\u0026ndash;e629. https://doi.org/10.1016/S2214-109X(18)30186-4\u003c/li\u003e\n\u003cli\u003eEuropean Centre for Disease Prevention and Control (ECDC). 2023. Surveillance of antimicrobial resistance in Europe 2022. Stockholm: ECDC.\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention (CDC). 2023. CDC/NHSN surveillance definitions for specific types of infections. Atlanta: CDC.\u003c/li\u003e\n\u003cli\u003ePapazian L, Klompas M, Luyt CE. 2020. Ventilator-associated pneumonia in adults: a narrative review. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 46(5):888\u0026ndash;906. https://doi.org/10.1007/s00134-020-05980-0\u003c/li\u003e\n\u003cli\u003eNseir S, Di Pompeo C, Cavestri B, et al. 2006. Multiple-drug-resistant bacteria in patients with severe acute exacerbation of chronic obstructive pulmonary disease. \u003cem\u003eCrit Care Med\u003c/em\u003e. 34(12):2959\u0026ndash;2966. https://doi.org/10.1097/01.CCM.0000245661.14892.D5\u003c/li\u003e\n\u003cli\u003eKollef MH, Torres A, Shorr AF, et al. 2021. Nosocomial pneumonia: epidemiology, microbiology, and treatment. \u003cem\u003eSemin Respir Crit Care Med\u003c/em\u003e. 42(5):623\u0026ndash;640. https://doi.org/10.1055/s-0041-1730920\u003c/li\u003e\n\u003cli\u003eClinical and Laboratory Standards Institute (CLSI). 2023. Performance standards for antimicrobial susceptibility testing. 33rd ed. CLSI supplement M100. Wayne, PA: CLSI.\u003c/li\u003e\n\u003cli\u003eGrundmann H, Glasner C, Albiger B, et al. 2017. Occurrence of carbapenemase-producing \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and \u003ci\u003eEscherichia coli\u003c/i\u003e in the European survey of carbapenemase-producing Enterobacteriaceae. \u003ci\u003eLancet Infect Dis\u003c/i\u003e. 17(2):153\u0026ndash;163. https://doi.org/10.1016/S1473-3099(16)30257-2\u003c/li\u003e\n\u003cli\u003eMaurice NM, Bedi B, Sadikot RT. 2018. \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e biofilms: host response and clinical implications. \u003ci\u003eSemin Respir Crit Care Med\u003c/i\u003e. 39(3):305\u0026ndash;314. https://doi.org/10.1055/s-0038-1651493\u003c/li\u003e\n\u003cli\u003eLee AS, de Lencastre H, Garau J, et al. 2018. Methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e. \u003ci\u003eNat Rev Dis Primers\u003c/i\u003e. 4:18033. https://doi.org/10.1038/nrdp.2018.33\u003c/li\u003e\n\u003cli\u003eFeldman C, Anderson R. 2020. The role of \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e in community-acquired pneumonia. \u003ci\u003eSemin Respir Crit Care Med\u003c/i\u003e. 41(4):455\u0026ndash;469. https://doi.org/10.1055/s-0040-1713372\u003c/li\u003e\n\u003cli\u003eClancy CJ, Nguyen MH. 2021. COVID-19, superinfections and antimicrobial development. \u003cem\u003eJ Antimicrob Chemother\u003c/em\u003e. 76(4):805\u0026ndash;807. https://doi.org/10.1093/jac/dkaa469\u003c/li\u003e\n\u003cli\u003eLiu YY, Wang Y, Walsh TR, et al. 2016. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China. \u003cem\u003eLancet Infect Dis\u003c/em\u003e. 16(2):161\u0026ndash;168. https://doi.org/10.1016/S1473-3099(15)00424-7\u003c/li\u003e\n\u003cli\u003eWoodford N, Turton JF, Livermore DM. 2011. Multiresistant Gram-negative bacteria: the role of high-risk clones in the dissemination of antibiotic resistance. \u003cem\u003eFEMS Microbiol Rev\u003c/em\u003e. 35(5):736\u0026ndash;755. https://doi.org/10.1111/j.1574-6976.2011.00268.x\u003c/li\u003e\n\u003cli\u003eAllegranzi B, Pittet D. 2009. Role of hand hygiene in healthcare-associated infection prevention. \u003cem\u003eJ Hosp Infect\u003c/em\u003e. 73(4):305\u0026ndash;315. https://doi.org/10.1016/j.jhin.2009.04.019\u003c/li\u003e\n\u003cli\u003eFalagas ME, Tansarli GS, Karageorgopoulos DE, et al. 2014. Deaths attributable to carbapenem-resistant Enterobacteriaceae infections. \u003cem\u003eEmerg Infect Dis\u003c/em\u003e. 20(7):1170\u0026ndash;1175. https://doi.org/10.3201/eid2007.121004\u003c/li\u003e\n\u003cli\u003eDyar OJ, Huttner B, Schouten J, et al. 2017. What is antimicrobial stewardship? \u003cem\u003eClin Microbiol Infect\u003c/em\u003e. 23(11):793\u0026ndash;798. https://doi.org/10.1016/j.cmi.2017.08.026\u003c/li\u003e\n\u003cli\u003eJones RN. 2010. Microbial etiologies of hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 51(Suppl 1):S81\u0026ndash;S87. https://doi.org/10.1086/653053\u003c/li\u003e\n\u003cli\u003eAmerican Thoracic Society (ATS), Infectious Diseases Society of America (IDSA). 2005. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 171(4):388\u0026ndash;416. https://doi.org/10.1164/rccm.200405-644ST\u003c/li\u003e\n\u003cli\u003eTheuretzbacher U, Outterson K, Engel A, et al. 2020. The global preclinical antibacterial pipeline. \u003cem\u003eNat Rev Microbiol\u003c/em\u003e. 18(5):275\u0026ndash;285. https://doi.org/10.1038/s41579-019-0288-0\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (WHO). 2015. Global action plan on antimicrobial resistance. Geneva: WHO.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"nosocomial pneumonia, antimicrobial resistance, multidrug resistance, Georgia, surveillance, ICU","lastPublishedDoi":"10.21203/rs.3.rs-7585091/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7585091/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eNosocomial pneumonia (NP), including hospital-acquired (HAP) and ventilator-associated pneumonia (VAP), remains a leading cause of morbidity, mortality, and antimicrobial resistance worldwide. Data from Eastern Europe and the Caucasus are scarce, limiting region-specific infection control strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a prospective multicenter surveillance study across five tertiary hospitals in Georgia from May 2020 to December 2023. A total of 484 respiratory specimens were obtained from 397 adult patients with microbiologically confirmed NP. Pathogen identification was performed using culture and MALDI-TOF MS, with antimicrobial susceptibility testing according to CLSI guidelines. PCR assays detected major resistance genes. Epidemiological, molecular, and clinical outcomes were analyzed, including trends over time and ICU versus non-ICU differences.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eGram-negative bacteria predominated (71.7%), with \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (41.9%) as the leading pathogen, followed by \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (21.3%), \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (13.4%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (13.0%), and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (9.3%). Multidrug resistance (MDR) was identified in 80% of isolates, extensively drug-resistant (XDR) phenotypes in 18.4%, and pandrug-resistant (PDR) phenotypes in 1.4%. ESBL prevalence increased from 48.3% in 2020 to 79.8% in 2023 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), carbapenemase expression doubled from 15.0% to 30.2% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and colistin resistance rose from 2.5% to 8.5% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ICU isolates showed significantly higher MDR and XDR rates compared to non-ICU settings (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Thirty-day mortality correlated with resistance phenotype, ranging from 18.2% in susceptible infections to 71.4% in PDR cases.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis four-year surveillance study demonstrates alarming levels of antimicrobial resistance among NP pathogens in Georgia, with rising ESBL, carbapenemase, and colistin resistance, particularly in ICU settings. These findings highlight the urgent need for enhanced antimicrobial stewardship, infection prevention, and genomic surveillance strategies to contain the spread of high-risk clones and improve patient outcomes in resource-limited settings.\u003c/p\u003e","manuscriptTitle":"Epidemiological Profile of Causative Agents in Nosocomial Pneumonia: A Four- Year Multicenter Surveillance Study from Georgia (2020-2023)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 06:52:59","doi":"10.21203/rs.3.rs-7585091/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-08T16:17:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T15:27:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206828534865468082887472721665756780841","date":"2025-09-18T15:11:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T07:25:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211134620898241821780673905009078735408","date":"2025-09-13T16:18:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T16:13:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-13T04:30:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T07:17:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infection","date":"2025-09-10T16:58:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5eb49a6a-2354-4e59-860d-be5d5ba5f04e","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:07:13+00:00","versionOfRecord":{"articleIdentity":"rs-7585091","link":"https://doi.org/10.1007/s15010-025-02702-w","journal":{"identity":"infection","isVorOnly":false,"title":"Infection"},"publishedOn":"2025-12-09 15:58:06","publishedOnDateReadable":"December 9th, 2025"},"versionCreatedAt":"2025-09-23 06:52:59","video":"","vorDoi":"10.1007/s15010-025-02702-w","vorDoiUrl":"https://doi.org/10.1007/s15010-025-02702-w","workflowStages":[]},"version":"v1","identity":"rs-7585091","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7585091","identity":"rs-7585091","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}