Burden and Antimicrobial Resistance Trends of Catheter-Associated and Non-Catheter UTIs in Trauma Care: A Retrospective Analysis (2017–2024)

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In this study we characterize the epidemiology, microbiological profile, antimicrobial resistance patterns, and clinical outcomes of CAUTIs and non-CAUTI urinary tract infections (UTIs) at a Level 1 Trauma Centre in India from 2017 to 2024, using a modified CDC-NHSN definition and digital surveillance. Methods: A retrospective analysis of 723 UTI events was conducted using Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC-NHSN) definitions, modified to include Candida spp. at ≥10 5 CFU/mL. Surveillance was performed by dedicated Hospital Infection Control Nurses (HICNs) using a digital system. Microbiological identification and antimicrobial susceptibility testing (AST) were conducted via the conventional manual methods and automated systems. Results: of 723 UTI events, 608 (84.0%) were CAUTIs. The cohort had a median age of 34 years (IQR:22-45) and was 76% male. Pseudomonas aeruginosa (18%), Klebsiella pneumoniae (17.9%), and Escherichia coli (15%) were predominant pathogens. Antimicrobial resistance was high, with 100% resistance to ceftazidime in Acinetobacter baumannii and 93.6-94.1% resistance to ciprofloxacin in Klebsiella spp. and Enterococcus spp. Mortality was 25.5% (28.2% in CAUTI, 12.9% in non-CAUTI). Conclusion: This large-scale, trauma specific study with modified fungal criteria and digital surveillance highlights the importance of CAUTI burden and the high resistance in pathogens causing this infection. Introduction Catheter-associated urinary tract infections (CAUTIs) are a leading cause of healthcare-associated infections (HAIs), particularly in trauma care and intensive care unit (ICU) settings where indwelling urinary catheters are frequently used [ 1 , 2 ]. These infections contribute to prolonged hospital stays, increased healthcare costs, morbidity, and mortality, with global incidence rates of 1.7–3.2 per 1000 catheter-days [ 3 , 4 ]. The rise of antimicrobial resistance, especially among Gram-negative bacteria and emerging fungal pathogens, poses significant challenges, particularly in resource-constrained environments [ 5 , 6 , 7 ]. Trauma centers face unique pressures due to high patient volumes, complex injuries, and limited infection control infrastructure, amplifying the CAUTI burden [ 8 , 9 , 10 ]. Recent studies have documented regional variations in CAUTI epidemiology, with Gram-negative pathogens like Pseudomonas aeruginosa , Klebsiella pneumoniae , and Escherichia coli predominating in Asian and Indian settings [ 11 , 12 ]. A recent study highlighted the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) organisms, alongside fungal pathogens such as Candida auris , emphasizing the need for enhanced surveillance [ 5 ]. Another study noted shifts in HAI patterns during the COVID-19 pandemic, with changes in pathogen distribution and resistance profiles [ 13 ]. However, longitudinal studies using standardized, digitally supported surveillance and modified definitions to capture fungal CAUTIs remain scarce. This study addresses these gaps by analyzing 782 UTI events from May 2017 to April 2024 at a Level-1 Trauma Center in India, employing a modified CDC-NHSN definition that includes Candida spp. at ≥ 10⁵ CFU/mL to enhance fungal detection along with clinical systems with UTI. [ 14 ]. We provide a large-scale, trauma-specific dataset with detailed microbiological, resistance, and outcome data. Methodology The study was conducted at a Level-1 Trauma Center in India, receiving patients from across the country. This centre is part of a large tertiary care, academic hospital with a capacity of 2,500 beds. The Trauma Centre comprises 284 beds, including 32 beds in the intensive care unit (ICU) and 30 beds in a high-dependency unit (HDU) designated for polytrauma patients. Infection surveillance activities are supported by a dedicated team consisting of ten full-time Hospital Infection Control Nurses (HICNs) and one data entry operator assigned exclusively for surveillance documentation. Healthcare-associated infections (HAIs) were identified based on the most recent definitions provided by the Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC-NHSN). A slight modification was made to the urinary tract infection (UTI) definition, isolation of at least one organism growing at ≥ 10⁵ CFU/mL which included Candida spp. (NHSN excludes Candida, Moulds, and dimorphic fungi in UTI case definition) along with clinical symptoms of UTI [ 14 ]. All surveillance definitions and updates were implemented in real-time. Surveillance for CAUTIs was initiated in patients who remained in the intensive care unit (ICU) for more than two consecutive calendar days. A standardized proforma was used to document vital signs, relevant clinical parameters, and catheter-related information for each ICU patient, including the dates of catheter insertion, replacement, and removal. These records were subsequently transferred to the microbiology department, where the data was systematically entered on a digital platform HAIS India ( www.haisindia.com ). All clinical specimens for diagnosis were collected by the treating physicians based on clinical judgment and predefined diagnostic criteria. Microbiological processing of the samples was carried out following standard laboratory methods [ 15 ]. Microorganism identification was performed using the automated systems and antimicrobial susceptibility testing (AST) was conducted according to the latest CLSI guidelines. manufacturer’s guidelines. Results Cohort Demographics and Clinical Characteristics : A retrospective analysis of 723 urinary tract infection (UTI) events included 608 catheter-associated urinary tract infections (CAUTI) and 115 non-CAUTI cases. The cohort had a median age of 34 years (interquartile range: 22–45), with 76% males (72.7% in CAUTI, 93.9% in non-CAUTI). Median duration of stay in the unit was 34 days (interquartile range: 20–64) for CAUTI and 27 days (interquartile range: 15–57) for non-CAUTI cases. Median time from admission to outcome was 7 days (interquartile range: 4–14) for CAUTI and 8 days (interquartile range: 5–12) for non-CAUTI cases. The demographic and clinical characteristics are summarized in Table 1 . Table 1 Cohort Demographics and Clinical Characteristics Characteristic Overall (N = 723) CAUTI (N = 608) Non-CAUTI (N = 115) Male, n (%) 550 (76.0) 442 (72.7) 108 (93.9) Age, median (IQR), years 34 (22–45) 34 (22–45) 32 (22–45) Duration of Stay, median (IQR), days 33 (19–63) 34 (20–64) 27 (15–57) Time to Outcome, median (IQR), days 7 (4–13) 7 (4–14) 8 (5–12) Temporal Distribution of CAUTI and Non-CAUTI Cases Across the study period (2017–2024), CAUTI constituted the majority of reported events; however, their proportional representation declined over time. In the pre-COVID era (2017–2020), CAUTIs accounted for 87.8% of cases, whereas in the post-COVID period (2021–2024), this declined to 76.7%. A corresponding increase in non-CAUTI events was observed, This Temporal distribution is presented in Table 2 Table 2 Temporal Distribution of CAUTI and Non-CAUTI Cases Year/Period Total Events, n CAUTI, n (%) Non-CAUTI, n (%) 2017–18 86 79 (91.9) 7 (8.1) 2018–19 199 176 (88.4) 23 (11.6) 2019–20 189 161 (85.2) 28 (14.8) 2020–21 4 4 (100) 0 (0) 2021–22 20 18 (90.0) 2 (10.0) 2022–23 99 79 (79.8) 20 (20.2) 2023–24 126 91 (72.2) 35 (27.8) Table 3 Pathogen Distribution by CAUTI and Non-CAUTI Status Pathogen Group Organism Overall, n (%) 782 CAUTI, n (%) 656 Non-CAUTI, n (%) 126 Gram-Negative Enterobacteriaceae Klebsiella pneumoniae 140 (17.9) 115 (17.5) 25 (19.8) Escherichia coli 117 (15.0) 97 (14.8) 20 (15.9) Proteus mirabilis 25 (3.2) 20 (3.0) 5 (4.0) Providencia rettgeri 25 (3.2) 21 (3.2) 4 (3.2) Providencia stuartii 16 (2.0) 12 (1.8) 4 (3.2) Enterobacter cloacae 13 (1.7) 9 (1.4) 4 (3.2) Gram-Negative Non-Enterobacteriaceae Pseudomonas aeruginosa 141 (18.0) 111 (16.9) 30 (23.8) Acinetobacter baumannii 57 (7.3) 45 (5.8) 12 (1.5) Gram-Positive Enterococcus faecium 43 (5.5) 37 (5.6) 6 (4.8) Fungal Candida spp. 83 (10.6) 78 (11.9) 5 (4.0) Candida tropicalis 59 (7.5) 54 (8.2) 5 (4.0) Candida albicans 15 (1.9) 14 (2.1) 1 (0.8) Microbiological Profile A total of 782 isolates were identified, which included Pseudomonas aeruginosa 141 (18%), Klebsiella pneumoniae 140 (18%), and Escherichia coli 117 (15%) being the most commonly isolated organisms overall. Higher proportion of Acinetobacter baumannii and Proteus mirabilis observed. Fungal pathogens such as Candida spp. were notably more frequent in CAUTI cases 78 (12%) than in non-CAUTI cases 5 (4%), particularly Candida tropicalis . Rare isolates including Candida auris , Stenotrophomonas maltophilia , and Trichosporon asahii were observed in small numbers. Time to Infection and Length of Stay Time to infection (TTI) included 370 cases developing in ≤ 7 days, 186 cases in 8–14 days, 88 cases in 15–21 days, and 79 cases in > 21 days. Length of stay (LOS) included 7 cases having LOS ≤ 7 days, 112 cases had 8–14 days, 101 cases had 15–21 days, and 503 cases had > 21 days. Detailed distribution of TTI and LOS are presented in Table 4 . Table 4 Time to Infection and Length of Stay by CAUTI and Non-CAUTI Status Metric Category Overall, n (%) 723 CAUTI, n (%) 608 Non-CAUTI, n (%) 115 Time to Infection (days) ≤ 7 370 (51.2) 314 (84.9) 56 (15.1) 8–14 186 (25.7) 154 (82.8) 32 (17.2) 15–21 88 (12.2) 78 (88.6) 10 (11.4) > 21 79 (10.9) 62 (78.5) 17 (21.5) Length of Stay (days) ≤ 7 7 (1.0) 5 (71.4) 2 (28.6) 8–14 112 (15.5) 89 (79.5) 23 (20.5) 15–21 101 (14.0) 82 (81.2) 19 (18.8) > 21 503 (69.6) 432 (85.9) 71 (14.1) The Final outcomes included 481 cases (71.7%) who were discharged (393 CAUTI, 70.2%; 88 non-CAUTI, 87.1%), 171 cases (25.5%) who died (158 CAUTI, 28.2%; 13 non-CAUTI, 12.9%). Outcomes: 14 days outcome & final outcomes is tabulated in Table 5 Table 5 Clinical Outcomes by CAUTI and Non-CAUTI Status Outcome Category Overall, n (%) 723 CAUTI, n (%) 608 Non-CAUTI, n (%) 115 14-Day Outcome Died 90 (12.4) 79 (13.0) 11 (9.6) Discharged 182 (25.2) 138 (22.7) 44 (38.2) Other* 451 (62.4) 391 (64.3) 60 (52.2) Final Outcome Died 171 (25.5) 158 (26.0) 13 (11.3) Discharged 481 (71.7) 393 (64.6) 88 (76.5) Other* 71 (10.6) 57 (9.4) 14 (12.2) * Transferred to another hospital Left against medical advice Table 6 Antimicrobial Resistance Patterns of number (%) of common Urinary Pathogens Pathogen Group Organism Antibiotic/Antifungal Resistance, n/N (%) Susceptibility, n/N (%) Gram-Negative Enterobacteriaceae Escherichia coli Ampicillin 63/63 (100) 0/63 (0) Colistin 1/56 (1.8) 55/56 (98.2) Klebsiella spp. Ciprofloxacin 132/141(93.6) 9/141 (6.4) Colistin 11/63 (17.5) 52/63 (82.5) Gram-Negative Non-Enterobacteriaceae Acinetobacter baumannii Ceftazidime 56/56 (100) 0/56 (0) Colistin 0/25 (0) 25/25 (100) Pseudomonas spp. Ciprofloxacin 129/145 (89.0) 16/145 (11.0) Colistin 1/67 (1.5) 66/67 (98.5) Gram-Positive Enterococcus spp. Ciprofloxacin 48/51 (94.1) 3/51 (5.9) Linezolid 3/48 (6.3) 45/48 (93.8) Fungal Candida spp. Voriconazole 2/92 (2.2) 90/92 (97.8) Fluconazole 10/99 (10.0) 89/99 (89.9) Antimicrobial Resistance Patterns Antimicrobial resistance patterns for Acinetobacter baumannii (n = 57) showed 100% resistance to ceftazidime (56/56), 97.3% to cefepime (36/37), and 98.2% to ciprofloxacin (54/55), with 100% susceptibility to colistin (25/25) and 62.2% to minocycline (28/45). Escherichia coli (n = 117) had 100% resistance to ampicillin (63/63) and cefazolin (20/20), with 98.2% susceptibility to colistin (55/56) and 50.6% to ertapenem (42/83). Klebsiella spp. (n = 142) showed 93.6% resistance to ciprofloxacin (132/141) and 94.4% to cefepime (101/107), with 82.5% susceptibility to colistin (52/63). Pseudomonas spp . (n = 146) had 100% resistance to minocycline (9/9) and 89.0% to ciprofloxacin (129/145), with 98.5% susceptibility to colistin (66/67). Enterococcus spp . (n = 52) showed 97.5% resistance to erythromycin (39/40) and 94.1% to ciprofloxacin (48/51), with 93.8% susceptibility to linezolid (45/48) and 73.5% to vancomycin (36/49). Candida spp. (n = 169) showed 97.8% susceptibility to voriconazole (90/92), 94.7% to micafungin (90/95), and 89.9% to fluconazole (89/99), with resistance rates of 2.2%, 5.3%, and 10.0%, respectively. Discussion This study provides a comprehensive analysis of catheter-associated urinary tract infections (CAUTIs) and non-CAUTI analysed 723 UTI events. The high CAUTI burden, distinct microbiological profiles, and alarming antimicrobial resistance patterns align with global trends, offering a replicable model for HAI monitoring in resource-limited settings [ 1 , 2 , 5 ]. CAUTI Burden and Temporal Trends The predominance of CAUTIs (84.1% of 723 UTI events) aligns with findings from high-risk settings. Recent studies reported CAUTI incidence rates of 1.7–3.2 per 1000 catheter-days across 235 ICUs in eight Asian countries, highlighting the challenge in resource-constrained settings [ 3 , 4 ]. A recent study documented a sustained CAUTI burden over a decade at another Indian trauma center, with rates comparable to our CAUTI events [ 8 ]. Our unique temporal analysis across pre-COVID (87.8% CAUTI), COVID (100% CAUTI), and post-COVID (76.7% CAUTI) periods reveals a decline in CAUTI proportion post-COVID, mirroring a recent study that noted shifts in HAI patterns due to altered patient demographics and enhanced infection control during the pandemic [ 13 ]. The digital system and daily HICN surveillance ensured accurate data capture, surpassing the scope of manual or shorter-term surveillance in similar studies [ 8 , 9 ]. Microbiological Profile and Regional Comparisons Pseudomonas aeruginosa (18.0%), Klebsiella pneumoniae (17.9%), and Escherichia coli (15.0%), predominantly reflects patterns in recent studies from India and globally [ 8 , 11 , 12 ]. A recent study reported E. coli as a leading cause of community-acquired UTIs in India, with increasing resistance during the COVID-19 period [ 11 ], while another identified Gram-negative dominance in CAUTIs at a trauma center [ 8 ]. Our modified CDC-NHSN definition, including Candida spp. at ≥ 10⁵ CFU/mL, enhanced detection of fungal CAUTIs (10.6% overall, 11.9% in CAUTI), particularly Candida tropicalis (7.5%), addressing a gap noted in a recent study on emerging fungal pathogens like Candida auris [ 5 ]. The higher prevalence of P. aeruginosa in non-CAUTI cases (23.8% vs. 16.9% in CAUTI) aligns with a recent study reporting non-fermenters in non-CAUTI settings [ 2 ]. The VITEK-2 system ensured standardized microbial identification and AST, corroborating a recent study on MDR pathogens in Indian ICUs [ 7 ]. Antimicrobial Resistance Patterns The high antimicrobial resistance rates underscore the global crisis in trauma settings. Acinetobacter baumannii exhibited 100% resistance to ceftazidime and 98.2% to ciprofloxacin, consistent with a recent study on MDR Acinetobacter spp. in Indian ICUs [ 7 ]. E. coli and Klebsiella spp. showed near universal resistance to ampicillin (100%) and ciprofloxacin (93.6–94.1%), consistent with findings reported in recent literature from inpatient and community healthcare settings. [ 1 , 11 ]. Candida spp. showed favourable susceptibility to voriconazole (97.8%) and micafungin (94.7%), consistent with a recent study on C. auris [ 5 ], but 10.0% fluconazole resistance suggests cautious antifungal stewardship, as noted in a recent study on catheter technologies [ 10 ]. Clinical Outcomes and Risk Factors The 25.5% mortality rate (28.2% in CAUTI, 12.9% in non-CAUTI) exceeds that reported in a recent study on elderly CAUTI patients (14.7%), likely due to trauma severity [ 16 ]. Prolonged LOS (69.6% >21 days) and early TTI (51.2% ≤7 days) in CAUTI cases align with a recent study identifying prolonged catheterization as a risk factor [ 6 ]. Extended monitoring post-ICU discharge enhanced outcome accuracy. Higher discharge rates in non-CAUTI cases (87.1% vs. 70.2% in CAUTI) reflect less severe courses, consistent with a recent study [ 17 ]. Male predominance (76.0%, 93.9% in non-CAUTI) reflects trauma center demographics, as noted in a recent study [ 12 ]. Implications for Infection Control Our findings support targeted CAUTI prevention, as advocated in a recent study on catheter removal protocols [ 18 ]. High resistance rates necessitate susceptibility-guided therapy, as recommended in a recent study Conclusion This study’s large-scale, trauma-specific analysis with modified fungal criteria and digital surveillance highlights the CAUTI burden and resistance patterns. It offers a replicable model for HAI monitoring, addressing gaps in fungal detection and longitudinal data, and supports enhanced infection control and stewardship in resource-limited settings. Abbreviations CAUTIs Catheter-associated urinary tract infections HAI Healthcare-associated infection UTIs Urinary tract infections CDC-NHSN Centre for Disease Control and Prevention’s National Healthcare Safety Network HICNs Hospital Infection Control Nurses MDR Multidrug-resistant ICU Intensive care unit AST Antimicrobial Susceptibility Testing Declarations Ethics approval -The study protocol received approval from the Institutional Ethics Committee AIIMS, New Delhi (IEC 633/03-09-2021) Our study adhered to the Declaration of Helsinki. The Institutional Ethics Committee AIIMS, New Delhi has agreed to waive the consent of the participants. Consent to participate -Nor applicable. Clinical trial number : Not Applicable Consent for publication -Not Applicable Availability of data and materials - Data is provided within the manuscript. Competing interests -The authors declare no competing interests. Fundings- Not Applicable Authors contributions- PS, MNA and PM wrote the main manuscript text and AKT, MK, BCD, VT, RP prepared figures. All authors reviewed the manuscript Acknowledgements - I am thankful to all my research, lab staff and data entry operators for all the help and support. References Giuliano G, Hankache G, Sambo M, Cusi MG, Lazzerini PE, Gennari L, … et al. Urinary tract infections caused by Gram-negative bacteria in elderly hospitalized patients: epidemiology, clinical features and outcomes in the era of antimicrobial resistance. J Glob Antimicrob Resist . 2025 Jun 11:S2213-7165(25)00138-9. doi: 10.1016/j.jgar.2025.06.006 Hassuna NA, Kotb DN, Lami M, Abdelrahim SS. Characterization of antimicrobial resistance among Proteus mirabilis isolates from catheter-associated urinary tract infections and non-catheter-associated urinary tract infections in Egypt. BMC Infect Dis . 2025 May 27;25(1):767. doi: 10.1186/s12879-025-11118-8. 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Bacterial species and antimicrobial resistance differ between catheter and non-catheter-associated urinary tract infections: Data from a national surveillance network. Antimicrob Steward Healthc Epidemiol . 2023 Mar 20;3(1):e55. doi: 10.1017/ash.2022.340. Rosenthal VD, Memish ZA, Nicastri E, Leone S, Bearman G. Preventing catheter-associated urinary tract infections: A position paper of the International Society for Infectious Diseases, 2024 update. Int J Infect Dis . 2025 Feb;151:107304. doi: 10.1016/j.ijid.2024.107304. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviews received at journal 28 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers invited by journal 15 Aug, 2025 Editor assigned by journal 07 Aug, 2025 Submission checks completed at journal 06 Aug, 2025 First submitted to journal 06 Aug, 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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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Subodh","middleName":"","lastName":"Kumar","suffix":""},{"id":503234040,"identity":"a11f1c20-c579-481f-87a0-e5234fe344cf","order_by":8,"name":"Sushma Sagar","email":"","orcid":"","institution":"All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sushma","middleName":"","lastName":"Sagar","suffix":""},{"id":503234041,"identity":"bf8e39c0-1176-4b44-ace5-c795f73bd5fa","order_by":9,"name":"Kapil Dev Soni","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kapil","middleName":"Dev","lastName":"Soni","suffix":""},{"id":503234042,"identity":"ddf40ad4-7837-487e-be60-90acb9295ac7","order_by":10,"name":"Richa Aggarwal","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Richa","middleName":"","lastName":"Aggarwal","suffix":""},{"id":503234043,"identity":"f0650ac6-1f32-43ed-bc56-90f4219ca51c","order_by":11,"name":"Ashish Bindra","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ashish","middleName":"","lastName":"Bindra","suffix":""},{"id":503234044,"identity":"fd5fd8c7-2ecf-4f4b-964e-0c389065ecc7","order_by":12,"name":"Keshav Goyal","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Keshav","middleName":"","lastName":"Goyal","suffix":""},{"id":503234045,"identity":"0ba24f23-a2ea-4899-adb0-61150ae22ff4","order_by":13,"name":"Gyanendra Pal Singh","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gyanendra","middleName":"Pal","lastName":"Singh","suffix":""},{"id":503234046,"identity":"f16a2128-8c89-41b1-b1bf-c49b09eae284","order_by":14,"name":"Navdeep Sokhal","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Navdeep","middleName":"","lastName":"Sokhal","suffix":""},{"id":503234047,"identity":"8ed7e725-69e7-4842-8af1-d94c0813b0ed","order_by":15,"name":"Kamran Farooque","email":"","orcid":"","institution":"Trauma Centre, All India Institute of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kamran","middleName":"","lastName":"Farooque","suffix":""},{"id":503234048,"identity":"4862fe43-219d-442b-ae3d-d7e2e4fe132a","order_by":16,"name":"Purva Mathur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIie3RvQrCMBSGYUPAqda5eBOKILh4I44FJ49zxL/jEhfdHaS9hbp0bgmkS9RZXLwMR9MKOkhb3QTzQso35BlKKhWT6ReLnsvSh+lDKX5IqilRKSHfEMLTVULsy0E2xrzXr/sbPbxZv77S5MbCXOIcRwPnwF3YSluPMIGtIEjW6pJLmsrqOKgooNRjGUpATSjhpWQBfkZ2EvzPCBMQZASnEJQRR9luF1kCezlsd1FGsNckLvoXW9XiMzYn4AnVOuN0Dt5JxNcbyyePR38lsm9UcP+NzIsvm0wm0192BxQmXHopt3GGAAAAAElFTkSuQmCC","orcid":"","institution":"All India Institute of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Purva","middleName":"","lastName":"Mathur","suffix":""}],"badges":[],"createdAt":"2025-07-28 10:53:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7233045/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7233045/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-025-12028-5","type":"published","date":"2025-12-30T15:57:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99545417,"identity":"4d869091-e790-4e8f-ae3c-05563b312d28","added_by":"auto","created_at":"2026-01-05 16:07:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1112260,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7233045/v1/63625d0a-38e9-473f-ae35-2f64ae6ea7f0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden and Antimicrobial Resistance Trends of Catheter-Associated and Non-Catheter UTIs in Trauma Care: A Retrospective Analysis (2017–2024)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCatheter-associated urinary tract infections (CAUTIs) are a leading cause of healthcare-associated infections (HAIs), particularly in trauma care and intensive care unit (ICU) settings where indwelling urinary catheters are frequently used [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These infections contribute to prolonged hospital stays, increased healthcare costs, morbidity, and mortality, with global incidence rates of 1.7\u0026ndash;3.2 per 1000 catheter-days [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The rise of antimicrobial resistance, especially among Gram-negative bacteria and emerging fungal pathogens, poses significant challenges, particularly in resource-constrained environments [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Trauma centers face unique pressures due to high patient volumes, complex injuries, and limited infection control infrastructure, amplifying the CAUTI burden [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies have documented regional variations in CAUTI epidemiology, with Gram-negative pathogens like \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, and \u003cem\u003eEscherichia coli\u003c/em\u003e predominating in Asian and Indian settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A recent study highlighted the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) organisms, alongside fungal pathogens such as \u003cem\u003eCandida auris\u003c/em\u003e, emphasizing the need for enhanced surveillance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Another study noted shifts in HAI patterns during the COVID-19 pandemic, with changes in pathogen distribution and resistance profiles [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, longitudinal studies using standardized, digitally supported surveillance and modified definitions to capture fungal CAUTIs remain scarce.\u003c/p\u003e\u003cp\u003eThis study addresses these gaps by analyzing 782 UTI events from May 2017 to April 2024 at a Level-1 Trauma Center in India, employing a modified CDC-NHSN definition that includes \u003cem\u003eCandida\u003c/em\u003e spp. at \u0026ge;\u0026thinsp;10⁵ CFU/mL to enhance fungal detection along with clinical systems with UTI. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. We provide a large-scale, trauma-specific dataset with detailed microbiological, resistance, and outcome data.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThe study was conducted at a Level-1 Trauma Center in India, receiving patients from across the country. This centre is part of a large tertiary care, academic hospital with a capacity of 2,500 beds. The Trauma Centre comprises 284 beds, including 32 beds in the intensive care unit (ICU) and 30 beds in a high-dependency unit (HDU) designated for polytrauma patients. Infection surveillance activities are supported by a dedicated team consisting of ten full-time Hospital Infection Control Nurses (HICNs) and one data entry operator assigned exclusively for surveillance documentation.\u003c/p\u003e\u003cp\u003eHealthcare-associated infections (HAIs) were identified based on the most recent definitions provided by the Centers for Disease Control and Prevention\u0026rsquo;s National Healthcare Safety Network (CDC-NHSN). A slight modification was made to the urinary tract infection (UTI) definition, isolation of at least one organism growing at \u0026ge;\u0026thinsp;10⁵ CFU/mL which included \u003cem\u003eCandida\u003c/em\u003e spp. (NHSN excludes Candida, Moulds, and dimorphic fungi in UTI case definition) along with clinical symptoms of UTI [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. All surveillance definitions and updates were implemented in real-time.\u003c/p\u003e\u003cp\u003eSurveillance for CAUTIs was initiated in patients who remained in the intensive care unit (ICU) for more than two consecutive calendar days. A standardized proforma was used to document vital signs, relevant clinical parameters, and catheter-related information for each ICU patient, including the dates of catheter insertion, replacement, and removal. These records were subsequently transferred to the microbiology department, where the data was systematically entered on a digital platform HAIS India (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.haisindia.com\u003c/span\u003e\u003c/span\u003e). All clinical specimens for diagnosis were collected by the treating physicians based on clinical judgment and predefined diagnostic criteria. Microbiological processing of the samples was carried out following standard laboratory methods [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Microorganism identification was performed using the automated systems and antimicrobial susceptibility testing (AST) was conducted according to the latest CLSI guidelines. manufacturer\u0026rsquo;s guidelines.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eCohort Demographics and Clinical Characteristics\u003c/b\u003e: A retrospective analysis of 723 urinary tract infection (UTI) events included 608 catheter-associated urinary tract infections (CAUTI) and 115 non-CAUTI cases. The cohort had a median age of 34 years (interquartile range: 22\u0026ndash;45), with 76% males (72.7% in CAUTI, 93.9% in non-CAUTI). Median duration of stay in the unit was 34 days (interquartile range: 20\u0026ndash;64) for CAUTI and 27 days (interquartile range: 15\u0026ndash;57) for non-CAUTI cases. Median time from admission to outcome was 7 days (interquartile range: 4\u0026ndash;14) for CAUTI and 8 days (interquartile range: 5\u0026ndash;12) for non-CAUTI cases. The demographic and clinical characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCohort Demographics and Clinical Characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;723)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCAUTI (N\u0026thinsp;=\u0026thinsp;608)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-CAUTI (N\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e550 (76.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e442 (72.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e108 (93.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, median (IQR), years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (22\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (22\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (22\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of Stay, median (IQR), days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (19\u0026ndash;63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (20\u0026ndash;64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (15\u0026ndash;57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime to Outcome, median (IQR), days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (4\u0026ndash;13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (4\u0026ndash;14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (5\u0026ndash;12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTemporal Distribution of CAUTI and Non-CAUTI Cases\u003c/strong\u003e\u003cp\u003eAcross the study period (2017\u0026ndash;2024), CAUTI constituted the majority of reported events; however, their proportional representation declined over time. In the pre-COVID era (2017\u0026ndash;2020), CAUTIs accounted for 87.8% of cases, whereas in the post-COVID period (2021\u0026ndash;2024), this declined to 76.7%. A corresponding increase in non-CAUTI events was observed, This Temporal distribution is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTemporal Distribution of CAUTI and Non-CAUTI Cases\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear/Period\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Events, n\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCAUTI, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-CAUTI, n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u0026ndash;18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (91.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (8.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u0026ndash;19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e176 (88.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (11.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e161 (85.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (14.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u0026ndash;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u0026ndash;22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (90.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (10.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u0026ndash;23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (79.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (20.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (72.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (27.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePathogen Distribution by CAUTI and Non-CAUTI Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathogen Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganism\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall,\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003cp\u003e782\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCAUTI,\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003cp\u003e656\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNon-CAUTI,\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003cp\u003e126\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eGram-Negative Enterobacteriaceae\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e140 (17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e115 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25 (19.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e117 (15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e97 (14.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20 (15.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eProteus mirabilis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5 (4.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eProvidencia rettgeri\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eProvidencia stuartii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12 (1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13 (1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4 (3.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGram-Negative\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNon-Enterobacteriaceae\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e141 (18.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e111 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e30 (23.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57 (7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45 (5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12 (1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGram-Positive\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eEnterococcus faecium\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43 (5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6 (4.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eFungal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eCandida\u003c/em\u003e spp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83 (10.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e78 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5 (4.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eCandida tropicalis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59 (7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54 (8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5 (4.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1 (0.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cstrong\u003eMicrobiological Profile\u003c/strong\u003e\u003cp\u003eA total of 782 isolates were identified, which included \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e 141 (18%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e 140 (18%), and \u003cem\u003eEscherichia coli\u003c/em\u003e 117 (15%) being the most commonly isolated organisms overall. Higher proportion of \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e and \u003cem\u003eProteus mirabilis\u003c/em\u003e observed.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eFungal pathogens such as \u003cem\u003eCandida spp.\u003c/em\u003e were notably more frequent in CAUTI cases 78 (12%) than in non-CAUTI cases 5 (4%), particularly \u003cem\u003eCandida tropicalis\u003c/em\u003e. Rare isolates including \u003cem\u003eCandida auris\u003c/em\u003e, \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e, and \u003cem\u003eTrichosporon asahii\u003c/em\u003e were observed in small numbers.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTime to Infection and Length of Stay\u003c/strong\u003e\u003cp\u003eTime to infection (TTI) included 370 cases developing in \u0026le;\u0026thinsp;7 days, 186 cases in 8\u0026ndash;14 days, 88 cases in 15\u0026ndash;21 days, and 79 cases in \u0026gt;\u0026thinsp;21 days.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eLength of stay (LOS) included 7 cases having LOS\u0026thinsp;\u0026le;\u0026thinsp;7 days, 112 cases had 8\u0026ndash;14 days, 101 cases had 15\u0026ndash;21 days, and 503 cases had\u0026thinsp;\u0026gt;\u0026thinsp;21 days. Detailed distribution of TTI and LOS are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTime to Infection and Length of Stay by CAUTI and Non-CAUTI Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetric\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall, n (%)\u003c/p\u003e\u003cp\u003e723\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCAUTI, n (%)\u003c/p\u003e\u003cp\u003e608\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNon-CAUTI, n (%)\u003c/p\u003e\u003cp\u003e115\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eTime to Infection (days)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e370 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e314 (84.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e56 (15.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e186 (25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e154 (82.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32 (17.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88 (12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e78 (88.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10 (11.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79 (10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e62 (78.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17 (21.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eLength of Stay (days)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5 (71.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2 (28.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112 (15.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e89 (79.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e23 (20.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e101 (14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e82 (81.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19 (18.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e503 (69.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e432 (85.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e71 (14.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe Final outcomes included 481 cases (71.7%) who were discharged (393 CAUTI, 70.2%; 88 non-CAUTI, 87.1%), 171 cases (25.5%) who died (158 CAUTI, 28.2%; 13 non-CAUTI, 12.9%). Outcomes: 14 days outcome \u0026amp; final outcomes is tabulated in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Outcomes by CAUTI and Non-CAUTI Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall, n (%)\u003c/p\u003e\u003cp\u003e723\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCAUTI, n (%)\u003c/p\u003e\u003cp\u003e608\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNon-CAUTI, n (%)\u003c/p\u003e\u003cp\u003e115\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003e14-Day Outcome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDied\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90 (12.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79 (13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11 (9.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDischarged\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e182 (25.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e138 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e44 (38.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e451 (62.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e391 (64.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60 (52.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eFinal Outcome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDied\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e171 (25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e158 (26.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13 (11.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDischarged\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e481 (71.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e393 (64.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e88 (76.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71 (10.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14 (12.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Transferred to another hospital Left against medical advice\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAntimicrobial Resistance Patterns of number (%) of common Urinary Pathogens\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathogen Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganism\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAntibiotic/Antifungal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResistance, n/N (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSusceptibility, n/N (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eGram-Negative Enterobacteriaceae\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAmpicillin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63/63 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0/63 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColistin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1/56 (1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55/56 (98.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eKlebsiella\u003c/em\u003e\u003c/p\u003e\u003cp\u003espp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCiprofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132/141(93.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9/141 (6.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColistin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11/63 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52/63 (82.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eGram-Negative\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNon-Enterobacteriaceae\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCeftazidime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56/56 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0/56 (0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColistin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0/25 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25/25 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ePseudomonas\u003c/em\u003e\u003c/p\u003e\u003cp\u003espp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCiprofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129/145 (89.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16/145 (11.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColistin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1/67 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66/67 (98.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGram-Positive\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eEnterococcus\u003c/em\u003e\u003c/p\u003e\u003cp\u003espp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCiprofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48/51 (94.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/51 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLinezolid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3/48 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45/48 (93.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eFungal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eCandida\u003c/em\u003e\u003c/p\u003e\u003cp\u003espp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVoriconazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2/92 (2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90/92 (97.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFluconazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10/99 (10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e89/99 (89.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eAntimicrobial Resistance Patterns\u003c/h3\u003e\n\u003cp\u003eAntimicrobial resistance patterns for \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;57) showed 100% resistance to ceftazidime (56/56), 97.3% to cefepime (36/37), and 98.2% to ciprofloxacin (54/55), with 100% susceptibility to colistin (25/25) and 62.2% to minocycline (28/45). \u003cem\u003eEscherichia coli\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;117) had 100% resistance to ampicillin (63/63) and cefazolin (20/20), with 98.2% susceptibility to colistin (55/56) and 50.6% to ertapenem (42/83). \u003cem\u003eKlebsiella\u003c/em\u003e spp. (n\u0026thinsp;=\u0026thinsp;142) showed 93.6% resistance to ciprofloxacin (132/141) and 94.4% to cefepime (101/107), with 82.5% susceptibility to colistin (52/63). \u003cem\u003ePseudomonas spp\u003c/em\u003e. (n\u0026thinsp;=\u0026thinsp;146) had 100% resistance to minocycline (9/9) and 89.0% to ciprofloxacin (129/145), with 98.5% susceptibility to colistin (66/67). \u003cem\u003eEnterococcus spp\u003c/em\u003e. (n\u0026thinsp;=\u0026thinsp;52) showed 97.5% resistance to erythromycin (39/40) and 94.1% to ciprofloxacin (48/51), with 93.8% susceptibility to linezolid (45/48) and 73.5% to vancomycin (36/49). \u003cem\u003eCandida\u003c/em\u003e spp. (n\u0026thinsp;=\u0026thinsp;169) showed 97.8% susceptibility to voriconazole (90/92), 94.7% to micafungin (90/95), and 89.9% to fluconazole (89/99), with resistance rates of 2.2%, 5.3%, and 10.0%, respectively.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a comprehensive analysis of catheter-associated urinary tract infections (CAUTIs) and non-CAUTI analysed 723 UTI events. The high CAUTI burden, distinct microbiological profiles, and alarming antimicrobial resistance patterns align with global trends, offering a replicable model for HAI monitoring in resource-limited settings [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCAUTI Burden and Temporal Trends\u003c/strong\u003e\u003cp\u003eThe predominance of CAUTIs (84.1% of 723 UTI events) aligns with findings from high-risk settings. Recent studies reported CAUTI incidence rates of 1.7\u0026ndash;3.2 per 1000 catheter-days across 235 ICUs in eight Asian countries, highlighting the challenge in resource-constrained settings [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A recent study documented a sustained CAUTI burden over a decade at another Indian trauma center, with rates comparable to our CAUTI events [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Our unique temporal analysis across pre-COVID (87.8% CAUTI), COVID (100% CAUTI), and post-COVID (76.7% CAUTI) periods reveals a decline in CAUTI proportion post-COVID, mirroring a recent study that noted shifts in HAI patterns due to altered patient demographics and enhanced infection control during the pandemic [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The digital system and daily HICN surveillance ensured accurate data capture, surpassing the scope of manual or shorter-term surveillance in similar studies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMicrobiological Profile and Regional Comparisons\u003c/strong\u003e\u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (18.0%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (17.9%), and \u003cem\u003eEscherichia coli\u003c/em\u003e (15.0%), predominantly reflects patterns in recent studies from India and globally [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A recent study reported \u003cem\u003eE. coli\u003c/em\u003e as a leading cause of community-acquired UTIs in India, with increasing resistance during the COVID-19 period [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], while another identified Gram-negative dominance in CAUTIs at a trauma center [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Our modified CDC-NHSN definition, including \u003cem\u003eCandida\u003c/em\u003e spp. at \u0026ge;\u0026thinsp;10⁵ CFU/mL, enhanced detection of fungal CAUTIs (10.6% overall, 11.9% in CAUTI), particularly \u003cem\u003eCandida tropicalis\u003c/em\u003e (7.5%), addressing a gap noted in a recent study on emerging fungal pathogens like \u003cem\u003eCandida auris\u003c/em\u003e [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The higher prevalence of \u003cem\u003eP. aeruginosa\u003c/em\u003e in non-CAUTI cases (23.8% vs. 16.9% in CAUTI) aligns with a recent study reporting non-fermenters in non-CAUTI settings [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The VITEK-2 system ensured standardized microbial identification and AST, corroborating a recent study on MDR pathogens in Indian ICUs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAntimicrobial Resistance Patterns\u003c/strong\u003e\u003cp\u003eThe high antimicrobial resistance rates underscore the global crisis in trauma settings. \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e exhibited 100% resistance to ceftazidime and 98.2% to ciprofloxacin, consistent with a recent study on MDR \u003cem\u003eAcinetobacter\u003c/em\u003e spp. in Indian ICUs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eKlebsiella\u003c/em\u003e spp. showed near universal resistance to ampicillin (100%) and ciprofloxacin (93.6\u0026ndash;94.1%), consistent with findings reported in recent literature from inpatient and community healthcare settings. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. \u003cem\u003eCandida\u003c/em\u003e spp. showed favourable susceptibility to voriconazole (97.8%) and micafungin (94.7%), consistent with a recent study on \u003cem\u003eC. auris\u003c/em\u003e [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], but 10.0% fluconazole resistance suggests cautious antifungal stewardship, as noted in a recent study on catheter technologies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eClinical Outcomes and Risk Factors\u003c/strong\u003e\u003cp\u003eThe 25.5% mortality rate (28.2% in CAUTI, 12.9% in non-CAUTI) exceeds that reported in a recent study on elderly CAUTI patients (14.7%), likely due to trauma severity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Prolonged LOS (69.6% \u0026gt;21 days) and early TTI (51.2% \u0026le;7 days) in CAUTI cases align with a recent study identifying prolonged catheterization as a risk factor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Extended monitoring post-ICU discharge enhanced outcome accuracy. Higher discharge rates in non-CAUTI cases (87.1% vs. 70.2% in CAUTI) reflect less severe courses, consistent with a recent study [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Male predominance (76.0%, 93.9% in non-CAUTI) reflects trauma center demographics, as noted in a recent study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eImplications for Infection Control\u003c/strong\u003e\u003cp\u003eOur findings support targeted CAUTI prevention, as advocated in a recent study on catheter removal protocols [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. High resistance rates necessitate susceptibility-guided therapy, as recommended in a recent study\u003c/p\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study\u0026rsquo;s large-scale, trauma-specific analysis with modified fungal criteria and digital surveillance highlights the CAUTI burden and resistance patterns. It offers a replicable model for HAI monitoring, addressing gaps in fungal detection and longitudinal data, and supports enhanced infection control and stewardship in resource-limited settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCAUTIs Catheter-associated urinary tract infections\u003c/p\u003e\n\u003cp\u003eHAI Healthcare-associated infection \u003c/p\u003e\n\u003cp\u003eUTIs Urinary tract infections \u003c/p\u003e\n\u003cp\u003eCDC-NHSN Centre for Disease Control and Prevention\u0026rsquo;s National Healthcare Safety Network \u003c/p\u003e\n\u003cp\u003eHICNs Hospital Infection Control Nurses \u003c/p\u003e\n\u003cp\u003eMDR Multidrug-resistant \u003c/p\u003e\n\u003cp\u003eICU Intensive care unit \u003c/p\u003e\n\u003cp\u003eAST Antimicrobial Susceptibility Testing \u003cbr\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e-The study protocol received approval from the Institutional Ethics Committee AIIMS, New Delhi (IEC 633/03-09-2021) Our study adhered to the Declaration of Helsinki. The Institutional Ethics Committee AIIMS, New Delhi has agreed to waive the consent of the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e-Nor applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e-Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e-\u0026nbsp;Data is provided within the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e -The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings-\u0026nbsp;\u003c/strong\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions-\u003c/strong\u003e PS, MNA and PM wrote the main manuscript text and AKT, MK, BCD, VT, RP prepared figures. All authors reviewed the manuscript\u003cbr\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e- I am thankful to all my research, lab staff and data entry operators for all the help and support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGiuliano G, Hankache G, Sambo M, Cusi MG, Lazzerini PE, Gennari L, \u0026hellip; et al. Urinary tract infections caused by Gram-negative bacteria in elderly hospitalized patients: epidemiology, clinical features and outcomes in the era of antimicrobial resistance. \u003cem\u003eJ Glob Antimicrob Resist\u003c/em\u003e. 2025 Jun 11:S2213-7165(25)00138-9. doi: 10.1016/j.jgar.2025.06.006\u003c/li\u003e\n\u003cli\u003eHassuna NA, Kotb DN, Lami M, Abdelrahim SS. 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A Comprehensive Review of Progress in Preventing Urinary Infections Associated with the Use of Urinary Catheters: A Dual Analysis of Publications and Patents. \u003cem\u003eInfect Dis Rep\u003c/em\u003e. 2025 Jun 4;17(3):64. doi: 10.3390/idr17030064.\u003c/li\u003e\n\u003cli\u003eVenugopal S, Chunchanur S, Panigrahy R, Tak V, Yadav M, Chauhan A,\u0026hellip; et al. Changes in antimicrobial resistance of \u003cem\u003eEscherichia coli\u003c/em\u003e isolated from community-associated urinary tract infection before and during the COVID-19 pandemic in India. \u003cem\u003eJ Glob Antimicrob Resist\u003c/em\u003e. 2024 Jun;37:165-167. doi: 10.1016/j.jgar.2024.02.022.\u003c/li\u003e\n\u003cli\u003eParihar S, Sharma R, Kinimi SV, Choudhary S. An Observational Study from Northern India to Evaluate Catheter-associated Urinary Tract Infection in Medical Intensive Care Unit at a Tertiary Care Center. \u003cem\u003eIndian J Crit Care Med\u003c/em\u003e. 2023 Sep;27(9):642-646. doi: 10.5005/jp-journals-10071-24519.\u003c/li\u003e\n\u003cli\u003eSleziak J, Błażejewska M, Duszyńska W. Catheter-associated urinary tract infections in the intensive care unit during and after the COVID-19 pandemic. \u003cem\u003eBMC Infect Dis\u003c/em\u003e. 2025 Apr 24;25(1):595. doi: 10.1186/s12879-025-10996-2.\u003c/li\u003e\n\u003cli\u003eMathur P, Malpiedi P, Walia K, Srikantiah P, Gupta S, Lohiya A,\u0026hellip; et al. Health-care-associated bloodstream and urinary tract infections in a network of hospitals in India: a multicentre, hospital-based, prospective surveillance study. Lancet Glob Health. 2022 Sep;10(9):e1317-e1325. doi: 10.1016/S2214-109X(22)00274-1.\u003c/li\u003e\n\u003cli\u003eCollee JG, Mackie TJ, McCartney JE. Mackie \u0026amp; McCartney practical medical microbiology. fourteenth ed. New York: Churchill Livingstone; 1996\u003c/li\u003e\n\u003cli\u003eShen L, Fu T, Huang L, Sun H, Wang Y, Sun L,\u0026hellip; et al. 7295 elderly hospitalized patients with catheter-associated urinary tract infection: a case-control study. \u003cem\u003eBMC Infect Dis\u003c/em\u003e. 2023 Nov 24;23(1):825. doi: 10.1186/s12879-023-08711-0.\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Incau S, Atkinson A, Leitner L, Kronenberg A, Kessler TM, Marschall J. Bacterial species and antimicrobial resistance differ between catheter and non-catheter-associated urinary tract infections: Data from a national surveillance network. \u003cem\u003eAntimicrob Steward Healthc Epidemiol\u003c/em\u003e. 2023 Mar 20;3(1):e55. doi: 10.1017/ash.2022.340.\u003c/li\u003e\n\u003cli\u003eRosenthal VD, Memish ZA, Nicastri E, Leone S, Bearman G. Preventing catheter-associated urinary tract infections: A position paper of the International Society for Infectious Diseases, 2024 update. \u003cem\u003eInt J Infect Dis\u003c/em\u003e. 2025 Feb;151:107304. doi: 10.1016/j.ijid.2024.107304.\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":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7233045/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7233045/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e:Catheter-associated\u0026nbsp;urinary\u0026nbsp;tract\u0026nbsp;infections\u0026nbsp;(CAUTIs)\u0026nbsp;are\u0026nbsp;a\u0026nbsp;major\u0026nbsp;healthcare-associated\u0026nbsp;infection (HAI)\u0026nbsp;in\u0026nbsp;trauma\u0026nbsp;care\u0026nbsp;settings,\u0026nbsp;contributing\u0026nbsp;to\u0026nbsp;morbidity,\u0026nbsp;mortality and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eantimicrobial\u0026nbsp;resistance. In this study we characterize the epidemiology, microbiological profile, antimicrobial resistance patterns, and clinical outcomes of CAUTIs and non-CAUTI urinary tract infections (UTIs) at a Level 1 Trauma Centre in India from 2017 to 2024, using a modified CDC-NHSN definition and digital surveillance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A retrospective analysis of 723 UTI events was conducted using Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC-NHSN) definitions, modified to include \u003cem\u003eCandida \u003c/em\u003espp. at ≥10\u003csup\u003e5 \u003c/sup\u003eCFU/mL. Surveillance was performed by dedicated Hospital Infection Control Nurses (HICNs) using a digital system. Microbiological identification and antimicrobial susceptibility testing (AST) were conducted via the conventional manual methods and automated systems.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eof 723 UTI events, 608 (84.0%) were CAUTIs. The cohort had a median age of 34 years (IQR:22-45) and was 76% male. \u003cem\u003ePseudomonas aeruginosa \u003c/em\u003e(18%), \u003cem\u003eKlebsiella pneumoniae \u003c/em\u003e(17.9%), and \u003cem\u003eEscherichia coli \u003c/em\u003e(15%) were predominant pathogens. Antimicrobial resistance was high, with 100% resistance to ceftazidime in \u003cem\u003eAcinetobacter baumannii \u003c/em\u003eand 93.6-94.1% resistance to ciprofloxacin in \u003cem\u003eKlebsiella \u003c/em\u003espp. and \u003cem\u003eEnterococcus \u003c/em\u003espp. Mortality was 25.5% (28.2% in CAUTI, 12.9% in non-CAUTI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis large-scale, trauma specific study with modified fungal criteria and digital surveillance highlights the importance of CAUTI burden and the high resistance in pathogens causing this infection.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Burden and Antimicrobial Resistance Trends of Catheter-Associated and Non-Catheter UTIs in Trauma Care: A Retrospective Analysis (2017–2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 13:39:22","doi":"10.21203/rs.3.rs-7233045/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-09-08T08:36:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29529632333486564139371727088689785644","date":"2025-08-29T11:21:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-28T22:54:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71933540801030903894109659401533851274","date":"2025-08-17T20:35:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-15T08:40:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-07T22:13:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-06T09:32:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-08-06T09:29:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cd985e2d-6ddd-49e3-92fc-02ed0d2613ee","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:03:23+00:00","versionOfRecord":{"articleIdentity":"rs-7233045","link":"https://doi.org/10.1186/s12879-025-12028-5","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-12-30 15:57:54","publishedOnDateReadable":"December 30th, 2025"},"versionCreatedAt":"2025-08-22 13:39:22","video":"","vorDoi":"10.1186/s12879-025-12028-5","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12028-5","workflowStages":[]},"version":"v1","identity":"rs-7233045","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7233045","identity":"rs-7233045","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}