Hospital-acquired infection in adult ICU incidence, antimicrobial resistance pattern, mortality rates, and risk factors detecting in Tripoli University Hospital- Libya: Longitudinal study

Hospital-acquired infection in adult ICU incidence, antimicrobial resistance pattern, mortality rates, and risk factors detecting in Tripoli University Hospital- Libya: Longitudinal study | 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 Hospital-acquired infection in adult ICU incidence, antimicrobial resistance pattern, mortality rates, and risk factors detecting in Tripoli University Hospital- Libya: Longitudinal study Maha Saeid, Maheebah Saeid, Mohamed Benlamin, Amina Hilal, Suhaib Ben Khaled, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7629170/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Frequency of Intensive Care Unit-Acquired Infections (ICU-AI) and antimicrobial resistance rates remain higher in developing countries than in developed countries. There is limited information regarding ICU-AI in public hospitals in Libya. Methods This longitudinal study conducted in Tripoli University Hospital, Libya, including all patients diagnosed with HAI in the ICU from March 2023 to September 2023. Included patients aged 18 years and older who stayed more than 48 hours in the ICU. Results Of the 66 included cases, 18 were infected (27.27% of all patients), and ICU-AI incidence density was 24.97 per 1000 patient days. The most frequent ICU-AI was pneumonia (71.4%) followed by UTI (19%), Blood Stream Infection, and skin infection (4.8%) for each. For Device-Associated Infection (DAI) density; 34.48 per 1000 Mechanical Ventilation (MV) days for the Ventilator Associated Infection (VAP), 7.59 per 1000 catheter days for Catheter Associated UTI (CAUTI), and 2.33 per 1000 central line days for Central Line Associated Blood Stream Infection (CLABSI). Klebsiella pneumonia was the commonest (41.7% of isolates). Mortality rate among infected patients was 55.56%. Conclusion High bacterial resistance emerges and high mortality rate among infected patients in medical ICU require immediate action to implement urgent infection prevention and control programs. Hospital Acquired Infection ICU VAP CAUTI CLABSI MDR INTRODUCTION Hospital Acquired Infections (HAIs) and patient mortality rates remain higher in developing countries compared to developed countries. The frequency of ICU-AI and antimicrobial resistance rates are at least three to five times higher in these countries ( 1 – 3 ). Previous studies revealed a high prevalence of HAI rates and high device-associated infections in low and middle-income countries (LMICs) compared to high-income countries ( 4 – 7 ). In Libya, one of LMICs, which has been plagued by civil war since 2011, significant healthcare-associated problems have also been observed within its hospitals. Consequently, despite the scarcity of studies on the subject, Libyan ICUs continue to experience a higher incidence of HAIs compared to other hospital wards ( 8 – 11 ). Due to limited information about HAIs and their effect on mortality rate in public hospital ICUs in Libya, this study aimed to investigate the rate of ICU-AI, assess the patterns of antimicrobial resistance, identify risk factors for acquisition, and determine the mortality rate due to HAIs. METHODS This prospective longitudinal study was conducted at Tripoli University Hospital, a public tertiary hospital with 1200 beds, of which 500 are staffed, 16 are in medical ICU, but only five of 16 are operational. Study was carried out for six months, from March 2023 to September 2023. The study included patients who were aged over 18 years and acquired an infection after 48 hours of ICU admission. Data collection: Data was collected daily by the research team. Self-designed data collection sheet was used, including demographic and clinical characteristics such as gender, age, date of admission, primary diagnosis which was the cause of admission, and patient referral source (i.e. referred from medical wards, emergency, and trauma department, gynaecological department, surgical departments, or other ICUs). For descriptive purposes, the outcome of the patients was documented as (i.e. discharged, discharged against medical advice (DAMA), or deceased), for analysis of mortality, the outcomes were divided into “survived” including DAMA, and “died”. The duration of admission was calculated as the number of days from first day of ICU admission (day one) until date of patient’s outcome. Follow-up of patient’s data included calculating and documenting SOFA score in the first three days of admission and Charlson comorbidity index (CCI)). Invasive procedures, such as mechanical ventilation, central and peripheral venous lines, urinary catheters, and nasogastric tubes before infection were also documented. Potential risk factors, such as blood transfusion during admission, sepsis, steroid use, and immunosuppression (on immunosuppressants or having AIDS) were also recorded. Antimicrobial use before and after ICU admission, type of the causative organism, culture, and sensitivity results were recorded. Statistical Analysis: Variables with missed data more than 30% were excluded from the analysis. Descriptive analysis of categorical variables was performed using frequencies and percentages, while for numerical variables, mean and standard deviation were used in normally distributed data, and median and interquartile range were used in case the data was not normally distributed. Univariate and multivariate logistic regression analyses were conducted to investigate potential risk factors associated with acquiring of ICU-AI. Univariate analysis results with P values of less than or equal to 0.1 were entered into the multivariate model. A confidence interval (CI) of 95% and a significance level of < 0.05 were used for logistic regression analysis. Calculations The incidence of HAI was calculated by dividing number of infected patients by total number of included patients in the study, multiplied by 100. The incidence density of HAI per 1000 patient-days was calculated by dividing number of infected patients by total patient-days multiplied by 1000, where patient-days equals the total sum of days of admission spent by each patient admitted during the study period. Device-associated infection per 1000 device-days was calculated by dividing number of DAI by total device-days multiplied by 1000. Definitions Hospital-acquired pneumonia is identified by using a combination of clinical, imaging, and laboratory criteria of lung infection that develops after 48 hours of admission, while VAP is pneumonia developed in patients on mechanical ventilation for at least two consecutive days, in which day one is the day of ventilator placement ( 12 ). Catheter Associated UTI (CAUTI): it’s a UTI occurs when an Indwelling Urinary Catheter (IUC) placed for more than two consecutive days, considering day one is the day of IUC placement; in contrast, Non-CAUTI defined as patients must meet all three criteria including symptoms; urine cultures and patient has an indwelling catheter less than two consecutive days ( 13 ). Central Line Associated Blood Stream Infection (CLABSI): is a laboratory-confirmed blood infection where an eligible causative organism and central line are present on the day of event or the day before( 14 ). Charlson Comorbidity Index: It’s a weighted score used to predict short and long-term outcomes such as function and mortality; it depends on number and severity of 19 predefined comorbid conditions ( 15 ). Results Descriptive Features of ICU Patients: From March 1 to September 1, 2023, 73 patients were admitted to the medical ICU, with 66 meeting inclusion criteria (721 patient-days). Exclusions included patients under 18, those with stays under 48 hours, and one with an exceptionally long stay (about one year). The included patients (ages 18 to 93, mean age 50.62 ± 19.3) comprised 41 females (62.1%) and 25 males (37.9%). Primary admission reasons were neurological (27.3%), infectious (18.2%), and oncological (10.6%). Common procedures included indwelling urethral catheterization (92.4%), peripheral venous catheterization (86.4%), and central venous catheterization (62.1%). Major comorbidities were diabetes, renal disease, and cerebrovascular accidents. Table 1 provides a detailed overview of patient characteristics. Table 1 Demographic and Clinical Profile of Intensive Care Unit Admissions Demographic and clinical characters Total (N = 66) ICU-AI patients (N = 18) No ICU-AI patients (N = 48) Age (years) Mean ± SD 50.62 ± 19.3 53.94 ± 19.98 49.38 ± 19.1 Gender : Male n (%) 25 (37.9) 6 (33.3) 19 (39.6) Female n (%) 41 (62.1) 12 (66.7) 29 (60.4) Length of ICU stay Median (IQR) 6 (3-13.25) 17 (12-30.5) 4.5 ( 3 – 7 ) Referred from : Medical ward 56 (84.8%) 16 (88.9%) 40 (83.3%) Emergency 5 (7.6%) 2 (11.1%) 3 (6.3%) Gynecological 2 (3.0%) 0 2 (4.2%) Surgical 2 (3.0%) 0 2 (4.2%) CCU 1 (1.5%) 0 1 (2.1%) The main cause of ICU admission Neurological 18 (27.3%) 6 (33.3%) 12 (25%) Infectious 12 (18.2%) 5 (27.8%) 7 (14.6%) Oncological 7 (10.6%) 1 (5.6%) 6 (12.5%) Metabolic* 6 (9.1%) 1 (5.6%) 5 (10.4%) Renal 6 (9.1%) 1 (5.6%) 5 (10.4%) Cardiovascular 4 (6.1%) 2 (11.1%) 2 (4.2%) Respiratory 4 (6.1%) 0 4 (8.3%) Gastrointestinal 4 (6.1%) 2 (11.1%) 2 (4.2%) Blood/Immune 3 (4.5%) 0 3 (6.3%) Rheumatologic 1 (1.5%) 0 1 (2.1%) Surgical 1 (1.5%) 0 1 (2.1%) Invasive Procedures n (%) : Urinary catheter 61 (92.4%) 18 (100%) 43 (89.6%) Peripheral venous catheter 57 (86.4%) 16 (88.9%) 41 (85.4%) Central venous line 41 (62.1%) 17 (94.4%) 24 (50%) Inserted NGT 34 (51.5%) 13 (72.2%) 21 (43.8%) Mechanical ventilation > 48hr 25 (37.9%) 12 (66.7%) 13 (27.1%) Blood transfusion during admission 22 (33.3%) 10 (55.6%) 12 (25%) Tracheostomy 4 (6%) 2 (11.1%) 2 (4.2%) Comorbidities : Diabetes mellitus 27 (40.9%) 9 (50%) 18 (37.5%) Renal disease 23 (34.8%) 7 (38.9%) 16 (33.3%) Cardiovascular disease 15 (22.7%) 5 (27.8%) 10 (20.8%) Sepsis 10 (15.2%) 6 (33.3%) 4 (8.3%) Respiratory disease 8 (12.1%) 2 (11.1%) 6 (12.5%) Immunosuppression 8 (12.1%) 3 (16.7%) 5 (10.4%) Liver disease 3 (4.5%) 0 3 (6.3%) SOFA score: Median (IQR) 4 (3-7.25) 6 (3.5–8.5) 4 (2.5-6) Charlson comorbidity index: Midian (IQR) 2 (0–5) 3.5 (0.75–6.25) 2 (0–4.75) Antimicrobial use before ICU admission: n (%) Yes 29 (43.9%) 10 (55.6%) 19 (39.6%) No 6 (9.1%) 2 (11.1%) 4 (8.3%) Unknown 31 (47%) 6 (33.3%) 25 (52.1%) Antibiotic use 48 hrs. after ICU admission : 61 (92.4%) 18 (100%) 43 (89.6%) The outcome of admitted cases : Discharged 40 (60.6%) 6 (33.4%) 34 (70.8%) DAMA 4 (6.1%) 2 (11.1%) 2 (4.2%) Died 22 (33.3%) 10 (55.6%) 12 (25%) ICU-AI = Intensive Care Unit Acquired Infection, SD = Standard Deviation, IQR = Interquartile Range, CCU = Cardiac Care Unit, SOFA = Sequential Organ Failure Assessment, DAMA = Discharged Against Medical Advice. * Metabolic causes of admission included Diabetic Ketoacidosis and Hyperglycemic Hyperosmolar Nonketotic Syndrome. Table 1 : Demographic and Clinical Profile of Intensive Care Unit Admissions Incidence and Types of ICU-Acquired Infections (ICU-AIs): During ICU admission, 18 patients (27.27%) experienced hospital-acquired infections, with an overall rate of 24.97 per 1,000 patient-days. Among these, three had two different infections (totaling 21 infections). The most common was Ventilator-Associated Pneumonia (VAP) in 9 cases (60% of ICU-acquired pneumonia), followed by non-ventilator associated pneumonia (non-VAP) in 6 cases (40% of all ICU-acquired pneumonia). Together, these accounted for 15 cases (71.4% of ICU-AIs ). Urinary tract infections (all catheter-associated) occurred in four patients (19%). The remaining infections included one case each of bloodstream infection (BSI) and skin infection (4.8%). For device-associated infection density per 1000 device-days, the rates were 34.48 per 1000 Mechanical Ventilation (MV) days for VAP, 7.59 per 1000 catheter-days for CAUTI, and 2.33 per 1000 central line-days for CLABSI. Potential Risk Factors of ICU-AIs: Univariate analysis identified several significant risk factors for ICU-AIs: longer ICU stays (OR = 1.283, 95% CI = 1.126–1.462, p < 0.001), presence of a central venous line (OR = 17, 95% CI = 2.093-138.084, p = 0.008), nasogastric tube insertion (OR = 3.343, 95% CI = 1.029–10.863, p = 0.045), sepsis (OR = 5.5, 95% CI = 1.333–22.687, p = 0.018), and mechanical ventilation > 48h (OR = 5.385, 95% CI = 1.674–17.325, p = 0.008). After adjusting for other variables, only the duration of ICU stays (OR = 1.299, 95% CI = 1.118–1.510, p = 0.001) remained independently associated with ICU-acquired infections. Table 2 presents these regression analysis results. The multivariate model, was significant (χ² ( 6 ) = 48.454, p < 0.001), explaining 75.4% of the variance and classifying 89.4% of cases correctly (sensitivity = 83.3%, specificity = 91.7%). Table 2 Univariate and Multivariate Logistic Regression for Potential Risk Factors for Acquisition of ICU-Acquired Infections Risk factor Univariate analysis Multivariate regression OR CI 95% P value OR CI 95% P value Age 1.013 0.984–1.042 0.390 Gender Male (ref) 1.00 0.642 Female 1.31 0.420–4.089 Length of ICU stay 1.283 1.126–1.462 < 0.001 1.299 1.118–1.510 0.001 Central venous line 17 2.093- 138.084 0.008 31.524 0.698-1424.043 0.076 Peripheral venous catheter 1.366 0.256–7.287 0.715 Inserted NGT 3.343 1.029–10.863 0.045 0.059 0.001–3.017 0.159 Mechanical ventilation > 48hr 5.385 1.674–17.325 0.005 5.100 0.131- 197.804 0.383 Tracheostomy 2.875 0.374–22.129 0.310 Diabetes mellitus 1.667 0.559–4.973 0.360 Renal disease 1.273 0.415–3.907 0.673 Sepsis 5.5 1.333–22.687 0.018 6.074 0.575–64.128 0.134 COPD 1.353 0.115–15.901 0.810 Immunosuppression 1.720 0.366–8.082 0.492 Steroid 0.375 0.075–1.873 0.203 SOFA score 1.078 0.915–1.271 0.369 Charlson comorbidity Index 1.182 0.974–1.435 0.091 1.201 0.871–1.656 0.264 OR = odds ratio, CI = confidence interval, NGT = nasogastric tube, COPD = chronic obstructive lung disease, SOFA score = sequential organ failure assessment score. Table 2 : Univariate and Multivariate Logistic Regression for Potential Risk Factors for Acquisition of ICU-Acquired Infections Mortality Rates and Risk Factors: Of the admitted patients, 33.3% died in the ICU, with a fatality rate of 55.56% for ICU-AIs. Non-infected patients had a 25% mortality rate, resulting in an excess mortality of 30.56%. A significant association was found between ICU-AIs and mortality (χ² (1, N = 66) = 5.500, p = 0.019). In assessing risk factors for mortality among infected patients, no statistically significant associations were identified, likely due to the small sample size (8 survivors vs. 10 non-survivors). Despite the lack of statistical significance, we included a (Table 3 ) to compare the two groups. Table 3 Description and comparison of mortality within ICU-acquired infection group Risk factor Survived ICU-AI Died ICU-AI Univariate analysis (n = 8) (n = 10) OR CI 95% p-value Age Mean ± SD 53 ± 22.47 54.7 ± 18.97 1.005 0.957–1.054 0.854 Gender Male (ref) Female 3 (37.5%) 5 (62.5%) 3 (30%) 7 (70%) 1.00 1.400 0.195–10.032 0.738 Length of ICU stay(days) Median (IQR) 23 (13.75- 35) 15 (11.5–25.5) 1.031 0.982–1.083 0.219 SOFA score (Mean ± SD) 6 ± 3.1 6.29 ± 3.73 1.029 0.729–1.451 0.872 Charlson comorbidity index Median (IQR) 2 (0–6) 4.5 (1.75–7) 0.969 0.832–1.129 0.689 More than 1 ICU-AI 1 (12.5%) 2 (20%) 1.750 0.129–23.703 0.674 Inserted NGT 6 (75%) 7 (70%) 0.778 0.096–6.322 0.778 Mechanical ventilation > 48hr 5 (62.5%) 7 (70%) 1.400 0.195–10.032 0.738 Tracheostomy 1 (12.5%) 1 (10%) 0.778 0.041–14.750 0.867 Diabetes mellitus 5 (62.5%) 4 (40%) 0.400 0.059–2.702 0.347 Renal disease 3 (37.5%) 4 (40%) 1.111 0.164–7.506 0.914 Sepsis 1 (12.5%) 5 (50%) 7.000 0.613–79.871 0.117 Immunosuppression 1 (12.5%) 2 (20%) 1.750 0129-23.703 0.674 ICU-AI = intensive-care-unit-acquired infection, OR = odds ratio, CI = confidence interval, NGT = nasogastric tube, SOFA score = sequential organ failure assessment score, SD = standard deviation, IQR = interquartile range. Table 3 : Description and comparison of mortality within ICU-acquired infection group Antimicrobial use: A total of 150 antimicrobials were used for 61 patients (92.4%). Detailed Antimicrobial use and distribution are shown in Table 4 Table 4 Antimicrobial Use in the Adult Medical ICU at Tripoli University Hospital (March-September 2023) Types and numbers of antibiotics N % Number of Antimicrobials used by each patient (total = 61 patients) Non 5 7.6 One Antimicrobial 17 25.8 Two antimicrobials 20 30.3 Tree or more antimicrobials 24 36.4 Distribution of types used antimicrobials (total = 150) Cephalosporins : 35 23.3 Ceftriaxone (J01DD04) 17 11.3 Ceftazidime (J01DD02) 9 6 Cefepime (J01DE01) 9 6 Carbapenems : 31 20.7 Tienem (J01DH02) 11 7.3 Meropenem (J01DH02) 11 7.3 Imipenem/cilastatin (J01DH51) 4 2.7 Unspecified carbapenem 5 3.3 Fluoroquinolones : 25 16.7 Levofloxacin (J01MA12) 11 7.3 Ciprofloxacin (J01MA02) 8 5.3 moxifloxacin (J01MA14) 6 4 Metronidazole (J01XD01) 21 14 Aminoglycoside : 15 10 Gentamycin (J01GB03) 8 5.3 Amikacin (J01GB06) 7 4.7 Penicillins : 4 2.7 Amoxicillin/clavulanic acid (J01CR02) 2 1.3 Amoxicillin (J01CA04) 1 0.7 Tazocin (Piperacillin/tazobactam) (J01CR05) 1 0.7 Lincosamide : Clindamycin (J01FF01) 6 4 Vancomycin (J01XA01) 7 4.7 Macrolides: Clarithromycin (J01FA09) 1 0.7 Sulfamethoxazole/trimethoprim (J01EE01) 1 0.7 Other antimicrobials : 4 2.7 Antifungal 2 1.3 Anti-tuberculosis 1 0.7 Antiviral 1 0.7 Table 4 : Antimicrobial Use in the Adult Medical ICU at Tripoli University Hospital (March-September 2023) Microbial Etiology and Antimicrobial Resistance: Microbiological results were available for 7 of the 18 infected patients. Identifying a total of 12 isolates. Klebsiella species were the most common pathogens, accounting for 5 isolates (41.7%), followed by Pseudomonas aeruginosa and Candida albicans (2 isolates each, 16.7%), and 1 isolate each of Proteus spp., non-coagulase positive Staphylococci , and Acinetobacter calcoaceticus (8.3%). Antimicrobial resistance patterns were limited due to incomplete bacterial culture data resulting from laboratory service shortages; however, susceptibility results were available for 8 of the 10 bacterial isolates. Overall, the resistance rate among all isolated bacteria was 77.1%. Specifically, 90.7% of K.pneumoniae isolates were resistant, 26.3% of pseudomonas isolates were resistant, and the single acinetobacter isolate was resistant to all tested antibiotics. Applying CDC definitions, 50% of pseudomonas were classified as multidrug-resistant (MDR), 50% of klebsiella as carbapenem-resistant enterobacteriaceae (CRE), and 75% as extended-spectrum beta-lactamases (ESBL). The single acinetobacter isolate showed a carbapenem-resistant acinetobacter (CRA) pattern. Resistance to specific antibiotics was observed, with both amoxicillin and augmentin showing 100% resistance in klebsiella and pseudomonas. Gentamicin resistance was found in the single acinetobacter isolate and 50% of klebsiella isolates. Carbapenems revealed 50% resistance in pseudomonas and 83.3% resistance in klebsiella. Antimicrobial resistance patterns are shown in the Supplementary Table A1. DISCUSSION To our knowledge; this is the first study in the country describing epidemiological features of HAI in adult medical ICU in governmental hospitals; in which HAI rate, risk factor for infection acquisition, mortality rate, and etiological microorganisms with antimicrobial resistance patterns were analysed. Our results revealed ICU-AI rate 27.27% which is higher than 25.2%, 12.6%, 9.3% in Tunisia, Egyptian, and Italian medical ICUs respectively ( 16 – 18 ). In contrast, is lower than 32.7% in Serbia ( 19 ), and 35.7% in Slovenia ( 20 ). To measure the infection per 1000 patient days. In our study; ICU-AI density was 24.97 per 1000 patients days; which is considered to be lower than what WHO declared that HAI in adult ICUs in developing countries about 47.9 per 1000 patients days ( 21 ), and lower than 66.4 episodes per 1000 days in Tunisia ( 22 ). The low density observed in our study can be attributed to a high number of patient-days (long duration of admission). This is primarily due to absence of a long-term care facility, which necessitates patients to remain in ICU for an extended period until they discharged. The underlying causes behind these variations in HAI rates among different ICUs are due to variation in study designs, sample size, guidelines of HAI detection, disparities in infection control protocols across hospitals, and variations in medical staff’s experience and training, furthermore, shortage of medical services should be considered. During these 6 months, the most frequent ICU-AI was pneumonia, accounting for 71.4% of all acquired infections. This included 60% VAP and 40% non-VAP. The incidence of pneumonia in our study was higher than 59% in Tunisia( 16 ), 28.8% in Kuwait ( 23 ), 3.9% by ECDC ( 24 ), And 62% in India ( 25 ). In contrast, incidence of infection per 1,000 mechanical ventilation (MV) days in our study was 34.48 per 1,000 MV days, is higher than 30 in Egypt, 26.6 in India, 7.8 by ECDC, and 4.21 in Kuwait per 1,000 MV days ( 23 – 26 ). This significantly high density of VAP in our results indicates a greater burden of ventilator-associated infections in our patients. In contrast to most studies that have revealed A.baumanni as predominant bacteria among pneumatic patients; our study found K.pneumonia the most frequent pathogen consistently with Egyptian, ECDC, and Libyan reports ( 17 , 24 , 27 ). High frequency of pneumonia in this study can be attributed to several factors. Firstly, 100% of the patients received proton pump inhibitors upon admission, which has been identified as a potential risk factor for pneumonia in critically ill patients( 28 , 29 ). Additionally, 92.5% of the patients received prophylactic antibiotics, which enhance oral colonization and contribute to development of pneumonia ( 25 , 30 ). Moreover, patient-to-nurse ratio in our ICU reached 2:1 and 3:1. It is essential for medical staff to strictly adhere to guidelines for VAP prevention. After pneumonia, CAUTI constituted 19% of all acquired infections; which is equal to 19% in Abusalim Trauma Hospital in Tripoli, and higher than 3%,15% in Egypt and Tunisia respectively ( 16 , 26 , 27 ), while it’s lower than 27.59% and 36.3% in both India and Serbia; respectively( 19 , 25 ). For incidence of CA UTI per 1000 catheter days in our study was 7.59 which is higher than 2.8 by ECDC, 2.9 in Egypt, 1.96 in Kuwait and 7.44 in India ( 23 – 26 ). It’s evident among studies that most common organism for UTI was E.coli while in our study C.albicans spp was the commonest consistent with Egyptian study ( 31 ). Bloodstream infections (BSIs) were the least common, representing only 4.8% of cases. This rate is lower than 10% in Abusalim Trauma Hospital, 9.3% in Tunisia, 6.7% in Kuwait, 10.34% in India, and 19.6% in Serbia ( 16 , 19 , 23 , 25 , 27 ), while it is higher than 3.2% by the ECDC( 24 ). In our study, the incidence of CLABSIs per 1,000 central line-days was 2.3, which is lower than 2.9 in Egypt, 2.46 in India, and 3.4 by ECDC ( 24 – 26 ). Consistently with ECDC and Indian studies, the most commonly identified microorganisms in BSIs were coagulase-negative staphylococci. The suggested cause behind low incidence of (BSIs) is routine administration of antibiotics to admitted patients upon admission, which results in negative blood culture results when samples are taken. Our study found that the length of stay in ICU is a significant predictor for HAI acquisition. Unlike prior studies, we identified prolonged hospital stay as the sole significant independent risk factor for HAI acquisition, while exposures to invasive devices and chronic comorbidities that were significant in univariate testing did not remain predictive in the adjusted model. This is because of small size of study population. When it comes to mortality rate in our study it was found to be 55.56% among infected patients, it's higher than 39.4%, 17.2%, 42.5%, and 53.6% in Serbia, India, Poland and Kenya respectively ( 19 , 25 , 32 , 33 ). While non-infected individuals had a mortality rate of 25%, resulting in an excess mortality rate of 30.56%. when comparing mortality among both groups, p-value = 0.019; meaning there is a significantly increasing risk of death for infected patients; conversely to other studies, which their p-value didn’t reach statistical significance ( 25 , 32 ). high mortality rate observed in our ICU can be attributed to spread of bacterial resistance among infected individuals. This elevated rate of mortality, highlights the necessity for further investigation to explore the underlying causes. Our study results indicate no evidence of Clostridium difficile infection (CDI) among infected patients, despite it being recognized as a significant concern in healthcare facilities, particularly in ICUs ( 34 ). ( 19 ). Our ICU has not reported any cases or symptoms of diarrhoea associated with CDI in at least the past 5 years, despite the overuse of antibiotics. However, it is important to note that there is a lack of studies supporting this observation and exploring the underlying reasons behind this phenomenon. Besides to prevalence of K.Pneumonia among other bacteria, resistance rate to different antibiotics reached 90.7%, which is higher than 68.3% in South Africa ( 35 ) and 54% in India ( 36 ) and 53.75% in Ethiopia ( 37 ) and lower than 97.7% in Equatorial Guinea ( 38 ). Approximately 75% of Klebsiella showed ESBL, it’s lower than 88% of ESBL in Abusalim Trauma Hospital in Libya ( 38 ); while it’s higher than 71% of ESBL in Egypt ( 31 ) and 48% in Morocco ( 39 ). For Carbapenem resistance in Klebsiella; our results showed 75% resistance for imipenem and 100% for Meropenem, 100% Amikacin which all being higher than 17% Imipenem, 25% Amikacin, 50% Meropenem in Abusalim Trauma Hospital. The cause behind these high rates of resistance especially Carbapenem was attributed to overselection of carbapenem in our ICU and absence of facility-specific antibiogram data. As previous results indicated high VAP and high mortality rate compared to neighbouring countries on the same continent; these results which obtained from four- beds medical ICU of university hospital; may arise from inadequate implementation of infection prevention protocols and lack of a consistent surveillance system for analyzing HAIs and outbreaks. despite being an upper middle income country as World Bank rank; Libya still faces significant challenges, including political conflict, and economic instability. It’s worth paying attention to prevalence of ICU-AI in these countries This study has several limitations First; the sample size was small due to a limited number of available ICU beds, and slow bed turnover times caused by the absence of long-term care facilities. These factors resulted in fewer admitted patients. Secondly, the study faced crucial challenges related to the shortage of medical laboratory services and lack of financial support. As a result, out of the 18 identified cases of ICU-AIs, only 7 were able to receive microbiological test results. A third limitation was the common practice of administering antibiotics to patients upon admission and before collecting samples from infection site. This led to false-negative results. Future studies with larger sample sizes, more robust laboratory support, and practice of collecting blood samples before administering antibiotics will be crucial to better characterize the burden of HAIs and antimicrobial resistance. CONCLUSIONS In this first longitudinal study in TUH, the incidence of acquired infection in medical ICU was 27.27%, high incidence of pneumonia which was remarkably high, in addition to high bacterial resistance pattern, and alarming high mortality rate among infected patients; all of these findings reinforce the need to urgently implement of HAI surveillance system, and infection control program. The emerge of bacterial resistance, especially against Carbapenem drugs the 2nd most used antibiotic in our ICU; reflects challenges in treating highly vulnerable infected patients and challenges in healthcare practitioner compliance to evidence-based and local antibiogram data-based treatment guidelines and stewardship program. Declarations Funding: This work was not supported by any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors did not receive any funding for this research. Competing Interests: The authors declare that they have no competing interests. They have no financial, personal, or professional interests that could be construed as influencing the work reported in this paper. Ethics Approval: This research was conducted following the ethical principles outlined in the Declaration of Helsinki. The study protocol was approved by the Scientific Research and Ethics Committee at the University of Tripoli, No: SREC/010/35. Data Availability: The data that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgments: Author Contribution Maha: Conceptualization, methodology, investigation and writing original draft. Maheebah: methodology, Formal analysis, Visualization (Tables), writing original draft, review and editing. Mohamed: editing -review and supervision. Amina,Suhaib,Dow, Batool: Investigation and review. , Essra: Investigation, review Abubaker: Supervision Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References Rosenthal VD, Maki DG, Graves N. The International Nosocomial Infection Control Consortium (INICC): goals and objectives, description of surveillance methods, and operational activities. American journal of infection control. 2008;36(9):e1-e12. Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care–associated infection and criteria for specific types of infections in the acute care setting. American journal of infection control. 2008;36(5):309–32. Alp E, Damani N. Healthcare-associated infections in intensive care units: epidemiology and infection control in low-to-middle income countries. Journal of infection in developing countries. 2015;9(10). 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National Healthcare Safety Network, January 2024. Available at: https://www.cdc.gov/nhsn/pdfs/pscmanual/7psccauticurrent.pdf (last accessed: October 18, 2024). Bloodstream Infection Event (Central Line-Associated Bloodstream Infection and Non-central Line Associated Bloodstream Infection). National Healthcare Safety Network, January 2024. Available at: https://www.cdc.gov/nhsn/pdfs/pscmanual/4psc_clabscurrent.pdf (last accessed: October 18, 2024). Charlson ME, Pompei P, Ales KL, MacKenzie CR: A New Method of Classifying Prognostic Comorbidity in Longitudinal Studies: Development and Validation. Journal of Chronic Diseases 40:373–383, 1987. Jamoussi A, Ayed S, Ben Ismail K, Chtara K, Bouaziz M, Mokline A. The prevalence of healthcare-associated infection in medical intensive care units in Tunisia. Results of the multi-centre nosorea1 study. Tunis Med. 2018;96(10–11):731–6. Hassan R, El-Gilany A-H, El-Mashad N, Azim DA. An overview of healthcare-associated infections in a tertiary care hospital in Egypt. Infection prevention in practice. 2020;2(3):100059. Chelazzi C, Pettini E, Villa G, De Gaudio AR. Epidemiology, associated factors and outcomes of ICU-acquired infections caused by Gram-negative bacteria in critically ill patients: an observational, retrospective study. BMC anesthesiology. 2015;15:1–7. Despotovic A, Milosevic B, Milosevic I, Mitrovic N, Cirkovic A, Jovanovic S, et al. Hospital-acquired infections in the adult intensive care unit—Epidemiology, antimicrobial resistance patterns, and risk factors for acquisition and mortality. American journal of infection control. 2020;48(10):1211–5. Klavs I, Kolman J, Zupanc TL, Kevorkijan BK, Korošec A, Serdt M. The prevalence of and risk factors for healthcare-associated infections in Slovenia: results of the second national survey. Slovenian Journal of Public Health. 2016;55(4):239–47. Agaba P, Tumukunde J, Tindimwebwa J, Kwizera A. Nosocomial bacterial infections and their antimicrobial susceptibility patterns among patients in Ugandan intensive care units: a cross sectional study. BMC research notes. 2017;10:1–12. Trifi A, Abdellatif S, Oueslati M, Zribi M, Daly F, Nasri R, et al. Infections nosocomiales: état des lieux dans un service de réanimation nosocomial infections: current situation in a resuscitation-unit. Tunis Med. 2017;95(3). Alfouzan W, Dhar R, Abdo NM, Alali WQ, Rabaan AA. Epidemiology and microbiological profile of common healthcare associated infections among patients in the intensive care unit of a general hospital in Kuwait: a retrospective observational study. Journal of epidemiology and global health. 2021;11(3):302–9. European Centre for Disease Prevention and Control. Annual Epidemiological Report for 2019 – Healthcare-associated infections acquired in intensive care units. In: ECDC. Annual epidemiological report for 2018. Stockholm: ECDC; 2023. Available at: https://www.ecdc.europa.eu/sites/default/files/documents/healthcare-associated-infections-intensive-care-units-annual-epidemiological-report-2019.pdf (last accessed: October 18, 2024) Dasgupta S, Das S, Chawan NS, Hazra A. Nosocomial infections in the intensive care unit: Incidence, risk factors, outcome and associated pathogens in a public tertiary teaching hospital of Eastern India. Indian journal of critical care medicine: peer-reviewed, official publication of Indian Society of Critical Care Medicine. 2015;19(1):14. El-Kholy A, Saied T, Gaber M, Younan MA, Haleim MM, El-Sayed H, et al. Device-associated nosocomial infection rates in intensive care units at Cairo University hospitals: first step toward initiating surveillance programs in a resource-limited country. American journal of infection control. 2012;40(6):e216-e20. Zorgani A, Abofayed A, Glia A, Albarbar A, Hanish S. Prevalence of device-associated nosocomial infections caused by gram-negative bacteria in a trauma intensive care unit in Libya. Oman medical journal. 2015;30(4):270. Mao X, Yang Z. Association between hospital-acquired pneumonia and proton pump inhibitor prophylaxis in patients treated with glucocorticoids: a retrospective cohort study based on 307,622 admissions in China. Journal of Thoracic Disease. 2022;14(6). Maret-Ouda J, Panula J, Santoni G, Xie S, Lagergren J. Proton pump inhibitor use and risk of pneumonia: a self-controlled case series study. Journal of gastroenterology. 2023;58(8):734–40. Agodi A, Auxilia F, Barchitta M, Brusaferro S, D'Alessandro D, Grillo OC, et al. Trends, risk factors and outcomes of healthcare-associated infections within the Italian network SPIN-UTI. Journal of Hospital Infection. 2013;84(1):52–8. See I, Lessa FC, ElAta OA, Hafez S, Samy K, El-Kholy A, et al. Incidence and pathogen distribution of healthcare-associated infections in pilot hospitals in Egypt. Infection Control & Hospital Epidemiology. 2013;34(12):1281–8. Kołpa M, Wałaszek M, Gniadek A, Wolak Z, Dobroś W. Incidence, microbiological profile and risk factors of healthcare-associated infections in intensive care units: a 10 year observation in a provincial hospital in Southern Poland. International journal of environmental research and public health. 2018;15(1):112. Melaku EE, Urgie BM, Dessie F, Seid A, Abebe Z, Tefera AS. Determinants of Mortality of Patients Admitted to the Intensive Care Unit at Debre Berhan Comprehensive Specialized Hospital: A Retrospective Cohort Study. Patient Related Outcome Measures. 2024:61–70. Scott Fridkin M, Baggs J, MD SM, MD PM, Rubin PMA, MD MHS, et al. Vital signs: improving antibiotic use among hospitalized patients. Morbidity and mortality weekly report. 2014;69(9):194–200. Perovic O, Singh-Moodley A, Dusé A, Bamford C, Elliott G, Swe-Han KS, et al. National sentinel site surveillance for antimicrobial resistance in Klebsiella pneumoniae isolates in South Africa, 2010–2012. South African Medical Journal. 2014;104(8):563–8. Perween N, Prakash SK, Siddiqui O. Multi drug resistant Klebsiella isolates in burn patients: a comparative study. Journal of clinical and diagnostic research: JCDR. 2015;9(9):DC14. Gebremeskel L, Teklu T, Kasahun GG, Tuem KB. Antimicrobial resistance pattern of Klebsiella isolated from various clinical samples in Ethiopia: a systematic review and meta-analysis. BMC Infectious Diseases. 2023;23(1):643. Shatalov A. Prevalence and antibiotic resistance pattern of Escherichia coli and Klebsiella pneumoniae in urine tract infections at the La Paz Medical center, Malabo, Equatorial Guinea. Open Journal of Medical Microbiology. 2015;5(4):177–83. Zahlane K, Ouafi AT, Barakate M. The clinical and epidemiological risk factors of infections due to multi-drug resistant bacteria in an adult intensive care unit of University Hospital Center in Marrakesh-Morocco. Journal of infection and public health. 2020;13(4):637–43. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7629170","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554629000,"identity":"f4811150-ee01-4632-91f2-8f6a4b775c92","order_by":0,"name":"Maha Saeid","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYNACA2Y5CIONgYGPWC3GDAzMEC1sRFrDnNhAtBbdBvaHHz4UWKdvON5/gOFD2WEGNokE/FrMDvAYS84wSM/dcOYwA+OMc8RpYZDmMTicu+FGMgMzbxtRWtgf//5jcDjdAKTlL3FaGMykGQwOJ4C1MBKl5TCPmWWPQbrhzDOHDQ72nEvnYeN5QEDL8fbHN378sZbnO9748MGPMms5fnYCtoBjAwYOADEPgwAhLZiA/wDJWkbBKBgFo2B4AwAk/j6gmemDcgAAAABJRU5ErkJggg==","orcid":"","institution":"tripoli university hospital","correspondingAuthor":true,"prefix":"","firstName":"Maha","middleName":"","lastName":"Saeid","suffix":""},{"id":554629001,"identity":"a5fef921-e02d-4fdf-9a8e-fd6104f98cda","order_by":1,"name":"Maheebah Saeid","email":"","orcid":"","institution":"University of Tripoli","correspondingAuthor":false,"prefix":"","firstName":"Maheebah","middleName":"","lastName":"Saeid","suffix":""},{"id":554629002,"identity":"194637d7-6563-4108-9f64-d5ae93647d4a","order_by":2,"name":"Mohamed 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The frequency of ICU-AI and antimicrobial resistance rates are at least three to five times higher in these countries (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Previous studies revealed a high prevalence of HAI rates and high device-associated infections in low and middle-income countries (LMICs) compared to high-income countries (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In Libya, one of LMICs, which has been plagued by civil war since 2011, significant healthcare-associated problems have also been observed within its hospitals. Consequently, despite the scarcity of studies on the subject, Libyan ICUs continue to experience a higher incidence of HAIs compared to other hospital wards (\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Due to limited information about HAIs and their effect on mortality rate in public hospital ICUs in Libya, this study aimed to investigate the rate of ICU-AI, assess the patterns of antimicrobial resistance, identify risk factors for acquisition, and determine the mortality rate due to HAIs.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis prospective longitudinal study was conducted at Tripoli University Hospital, a public tertiary hospital with 1200 beds, of which 500 are staffed, 16 are in medical ICU, but only five of 16 are operational. Study was carried out for six months, from March 2023 to September 2023. The study included patients who were aged over 18 years and acquired an infection after 48 hours of ICU admission.\u003c/p\u003e\u003cp\u003eData collection:\u003c/p\u003e\u003cp\u003eData was collected daily by the research team. Self-designed data collection sheet was used, including demographic and clinical characteristics such as gender, age, date of admission, primary diagnosis which was the cause of admission, and patient referral source (i.e. referred from medical wards, emergency, and trauma department, gynaecological department, surgical departments, or other ICUs). For descriptive purposes, the outcome of the patients was documented as (i.e. discharged, discharged against medical advice (DAMA), or deceased), for analysis of mortality, the outcomes were divided into \u0026ldquo;survived\u0026rdquo; including DAMA, and \u0026ldquo;died\u0026rdquo;. The duration of admission was calculated as the number of days from first day of ICU admission (day one) until date of patient\u0026rsquo;s outcome. Follow-up of patient\u0026rsquo;s data included calculating and documenting SOFA score in the first three days of admission and Charlson comorbidity index (CCI)). Invasive procedures, such as mechanical ventilation, central and peripheral venous lines, urinary catheters, and nasogastric tubes before infection were also documented. Potential risk factors, such as blood transfusion during admission, sepsis, steroid use, and immunosuppression (on immunosuppressants or having AIDS) were also recorded. Antimicrobial use before and after ICU admission, type of the causative organism, culture, and sensitivity results were recorded.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis:\u003c/h2\u003e\u003cp\u003eVariables with missed data more than 30% were excluded from the analysis. Descriptive analysis of categorical variables was performed using frequencies and percentages, while for numerical variables, mean and standard deviation were used in normally distributed data, and median and interquartile range were used in case the data was not normally distributed. Univariate and multivariate logistic regression analyses were conducted to investigate potential risk factors associated with acquiring of ICU-AI. Univariate analysis results with P values of less than or equal to 0.1 were entered into the multivariate model. A confidence interval (CI) of 95% and a significance level of \u0026lt;\u0026thinsp;0.05 were used for logistic regression analysis.\u003c/p\u003e\u003cp\u003eCalculations\u003c/p\u003e\u003cp\u003eThe incidence of HAI was calculated by dividing number of infected patients by total number of included patients in the study, multiplied by 100. The incidence density of HAI per 1000 patient-days was calculated by dividing number of infected patients by total patient-days multiplied by 1000, where patient-days equals the total sum of days of admission spent by each patient admitted during the study period. Device-associated infection per 1000 device-days was calculated by dividing number of DAI by total device-days multiplied by 1000.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDefinitions\u003c/strong\u003e\u003cp\u003eHospital-acquired pneumonia is identified by using a combination of clinical, imaging, and laboratory criteria of lung infection that develops after 48 hours of admission, while VAP is pneumonia developed in patients on mechanical ventilation for at least two consecutive days, in which day one is the day of ventilator placement (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Catheter Associated UTI (CAUTI): it\u0026rsquo;s a UTI occurs when an Indwelling Urinary Catheter (IUC) placed for more than two consecutive days, considering day one is the day of IUC placement; in contrast, Non-CAUTI defined as patients must meet all three criteria including symptoms; urine cultures and patient has an indwelling catheter less than two consecutive days (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Central Line Associated Blood Stream Infection (CLABSI): is a laboratory-confirmed blood infection where an eligible causative organism and central line are present on the day of event or the day before(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Charlson Comorbidity Index: It\u0026rsquo;s a weighted score used to predict short and long-term outcomes such as function and mortality; it depends on number and severity of 19 predefined comorbid conditions (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptive Features of ICU Patients:\u003c/p\u003e\u003cp\u003eFrom March 1 to September 1, 2023, 73 patients were admitted to the medical ICU, with 66 meeting inclusion criteria (721 patient-days). Exclusions included patients under 18, those with stays under 48 hours, and one with an exceptionally long stay (about one year). The included patients (ages 18 to 93, mean age 50.62\u0026thinsp;\u0026plusmn;\u0026thinsp;19.3) comprised 41 females (62.1%) and 25 males (37.9%). Primary admission reasons were neurological (27.3%), infectious (18.2%), and oncological (10.6%). Common procedures included indwelling urethral catheterization (92.4%), peripheral venous catheterization (86.4%), and central venous catheterization (62.1%). Major comorbidities were diabetes, renal disease, and cerebrovascular accidents. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a detailed overview of patient characteristics.\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\u003eDemographic and Clinical Profile of Intensive Care Unit Admissions\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eDemographic and clinical characters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;66) \u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eICU-AI patients\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo ICU-AI patients\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.62\u0026thinsp;\u0026plusmn;\u0026thinsp;19.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53.94\u0026thinsp;\u0026plusmn;\u0026thinsp;19.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e49.38\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMale n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (37.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19 (39.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eFemale n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (62.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29 (60.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLength of ICU stay Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (3-13.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (12-30.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.5 (\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReferred from\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMedical ward\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (84.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (88.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40 (83.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eEmergency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eGynecological\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSurgical\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eCCU\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eThe main cause of ICU admission\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eNeurological\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (27.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12 (25%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eInfectious\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (18.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (27.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (14.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eOncological\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (10.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eMetabolic*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (9.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (10.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eRenal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (9.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (10.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eCardiovascular\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eRespiratory\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (8.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGastrointestinal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eBlood/Immune\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eRheumatologic\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSurgical\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (2.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInvasive Procedures n (%)\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eUrinary catheter\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61 (92.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e43 (89.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003ePeripheral venous catheter\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (86.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (88.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41 (85.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eCentral venous line\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (62.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (94.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24 (50%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eInserted NGT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (51.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (72.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21 (43.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMechanical ventilation\u0026thinsp;\u0026gt;\u0026thinsp;48hr\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (37.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13 (27.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eBlood transfusion during admission\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (55.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12 (25%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eTracheostomy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (40.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eRenal disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (34.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (38.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eCardiovascular disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (22.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (27.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10 (20.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSepsis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (15.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (8.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eRespiratory disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (12.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eImmunosuppression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (12.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (16.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (10.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eLiver disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSOFA score: Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (3-7.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (3.5\u0026ndash;8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (2.5-6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharlson comorbidity index: Midian (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0\u0026ndash;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.5 (0.75\u0026ndash;6.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (0\u0026ndash;4.75)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAntimicrobial use before ICU admission: n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (43.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (55.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19 (39.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (9.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (8.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eUnknown\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25 (52.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAntibiotic use 48 hrs. after ICU admission\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61 (92.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e43 (89.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eThe outcome of admitted cases\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDischarged\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (60.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (33.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34 (70.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDAMA\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (11.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (4.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eDied\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (55.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12 (25%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eICU-AI\u0026thinsp;=\u0026thinsp;Intensive Care Unit Acquired Infection, SD\u0026thinsp;=\u0026thinsp;Standard Deviation, IQR\u0026thinsp;=\u0026thinsp;Interquartile Range, CCU\u0026thinsp;=\u0026thinsp;Cardiac Care Unit, SOFA\u0026thinsp;=\u0026thinsp;Sequential Organ Failure Assessment, DAMA\u0026thinsp;=\u0026thinsp;Discharged Against Medical Advice.\u003c/p\u003e\u003cp\u003e* Metabolic causes of admission included Diabetic Ketoacidosis and Hyperglycemic Hyperosmolar Nonketotic Syndrome.\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: Demographic and Clinical Profile of Intensive Care Unit Admissions\u003c/p\u003e\u003cp\u003eIncidence and Types of ICU-Acquired Infections (ICU-AIs):\u003c/p\u003e\u003cp\u003eDuring ICU admission, 18 patients (27.27%) experienced hospital-acquired infections, with an overall rate of 24.97 per 1,000 patient-days. Among these, three had two different infections (totaling 21 infections). The most common was Ventilator-Associated Pneumonia (VAP) in 9 cases (60% of ICU-acquired pneumonia), followed by non-ventilator associated pneumonia (non-VAP) in 6 cases (40% of all ICU-acquired pneumonia). Together, these accounted for 15 cases (71.4% of ICU-AIs ). Urinary tract infections (all catheter-associated) occurred in four patients (19%). The remaining infections included one case each of bloodstream infection (BSI) and skin infection (4.8%). For device-associated infection density per 1000 device-days, the rates were 34.48 per 1000 Mechanical Ventilation (MV) days for VAP, 7.59 per 1000 catheter-days for CAUTI, and 2.33 per 1000 central line-days for CLABSI.\u003c/p\u003e\u003cp\u003ePotential Risk Factors of ICU-AIs:\u003c/p\u003e\u003cp\u003eUnivariate analysis identified several significant risk factors for ICU-AIs: longer ICU stays (OR\u0026thinsp;=\u0026thinsp;1.283, 95% CI\u0026thinsp;=\u0026thinsp;1.126\u0026ndash;1.462, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of a central venous line (OR\u0026thinsp;=\u0026thinsp;17, 95% CI\u0026thinsp;=\u0026thinsp;2.093-138.084, p\u0026thinsp;=\u0026thinsp;0.008), nasogastric tube insertion (OR\u0026thinsp;=\u0026thinsp;3.343, 95% CI\u0026thinsp;=\u0026thinsp;1.029\u0026ndash;10.863, p\u0026thinsp;=\u0026thinsp;0.045), sepsis (OR\u0026thinsp;=\u0026thinsp;5.5, 95% CI\u0026thinsp;=\u0026thinsp;1.333\u0026ndash;22.687, p\u0026thinsp;=\u0026thinsp;0.018), and mechanical ventilation\u0026thinsp;\u0026gt;\u0026thinsp;48h (OR\u0026thinsp;=\u0026thinsp;5.385, 95% CI\u0026thinsp;=\u0026thinsp;1.674\u0026ndash;17.325, p\u0026thinsp;=\u0026thinsp;0.008). After adjusting for other variables, only the duration of ICU stays (OR\u0026thinsp;=\u0026thinsp;1.299, 95% CI\u0026thinsp;=\u0026thinsp;1.118\u0026ndash;1.510, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) remained independently associated with ICU-acquired infections. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents these regression analysis results. The multivariate model, was significant (χ\u0026sup2; (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;48.454, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), explaining 75.4% of the variance and classifying 89.4% of cases correctly (sensitivity\u0026thinsp;=\u0026thinsp;83.3%, specificity\u0026thinsp;=\u0026thinsp;91.7%).\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\u003eUnivariate and Multivariate Logistic Regression for Potential Risk Factors for Acquisition of ICU-Acquired Infections\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRisk factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eMultivariate regression\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCI 95%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCI 95%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.984\u0026ndash;1.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMale (ref)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.420\u0026ndash;4.089\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLength of ICU stay\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.126\u0026ndash;1.462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.118\u0026ndash;1.510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCentral venous line\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.093- 138.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.698-1424.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePeripheral venous catheter\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.256\u0026ndash;7.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.715\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInserted NGT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.029\u0026ndash;10.863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u0026ndash;3.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.159\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMechanical ventilation\u0026thinsp;\u0026gt;\u0026thinsp;48hr\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.674\u0026ndash;17.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.131- 197.804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.383\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTracheostomy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.875\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.374\u0026ndash;22.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.559\u0026ndash;4.973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.360\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenal disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.415\u0026ndash;3.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.673\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSepsis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.333\u0026ndash;22.687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.575\u0026ndash;64.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCOPD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.115\u0026ndash;15.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImmunosuppression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.366\u0026ndash;8.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.492\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSteroid\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.075\u0026ndash;1.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSOFA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.915\u0026ndash;1.271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharlson comorbidity Index\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.974\u0026ndash;1.435\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.091\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.871\u0026ndash;1.656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eOR\u0026thinsp;=\u0026thinsp;odds ratio, CI\u0026thinsp;=\u0026thinsp;confidence interval, NGT\u0026thinsp;=\u0026thinsp;nasogastric tube, COPD\u0026thinsp;=\u0026thinsp;chronic obstructive lung disease, SOFA score\u0026thinsp;=\u0026thinsp;sequential organ failure assessment score.\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: Univariate and Multivariate Logistic Regression for Potential Risk Factors for Acquisition of ICU-Acquired Infections\u003c/p\u003e\u003cp\u003eMortality Rates and Risk Factors:\u003c/p\u003e\u003cp\u003eOf the admitted patients, 33.3% died in the ICU, with a fatality rate of 55.56% for ICU-AIs. Non-infected patients had a 25% mortality rate, resulting in an excess mortality of 30.56%. A significant association was found between ICU-AIs and mortality (χ\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;66)\u0026thinsp;=\u0026thinsp;5.500, p\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e\u003cp\u003eIn assessing risk factors for mortality among infected patients, no statistically significant associations were identified, likely due to the small sample size (8 survivors vs. 10 non-survivors). Despite the lack of statistical significance, we included a (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) to compare the two groups.\u003c/p\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\u003eDescription and comparison of mortality within ICU-acquired infection group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRisk factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSurvived ICU-AI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDied\u003c/p\u003e\u003cp\u003eICU-AI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCI 95%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;22.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54.7\u0026thinsp;\u0026plusmn;\u0026thinsp;18.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.957\u0026ndash;1.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.854\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMale (ref)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (37.5%)\u003c/p\u003e\u003cp\u003e5 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (30%)\u003c/p\u003e\u003cp\u003e7 (70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003cp\u003e1.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.195\u0026ndash;10.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.738\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLength of ICU stay(days)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (13.75- 35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (11.5\u0026ndash;25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.982\u0026ndash;1.083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.219\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSOFA score (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.729\u0026ndash;1.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.872\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharlson comorbidity index Median (IQR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5 (1.75\u0026ndash;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.832\u0026ndash;1.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.689\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMore than 1 ICU-AI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.129\u0026ndash;23.703\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.674\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInserted NGT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (75%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.096\u0026ndash;6.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMechanical ventilation\u0026thinsp;\u0026gt;\u0026thinsp;48hr\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.195\u0026ndash;10.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.738\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTracheostomy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.041\u0026ndash;14.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.867\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.059\u0026ndash;2.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenal disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.164\u0026ndash;7.506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSepsis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.613\u0026ndash;79.871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.117\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImmunosuppression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0129-23.703\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.674\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eICU-AI\u0026thinsp;=\u0026thinsp;intensive-care-unit-acquired infection, OR\u0026thinsp;=\u0026thinsp;odds ratio, CI\u0026thinsp;=\u0026thinsp;confidence interval, NGT\u0026thinsp;=\u0026thinsp;nasogastric tube, SOFA score\u0026thinsp;=\u0026thinsp;sequential organ failure assessment score, SD\u0026thinsp;=\u0026thinsp;standard deviation, IQR\u0026thinsp;=\u0026thinsp;interquartile range.\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: Description and comparison of mortality within ICU-acquired infection group\u003c/p\u003e\u003cp\u003eAntimicrobial use:\u003c/p\u003e\u003cp\u003eA total of 150 antimicrobials were used for 61 patients (92.4%). Detailed Antimicrobial use and distribution are shown 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\u003eAntimicrobial Use in the Adult Medical ICU at Tripoli University Hospital (March-September 2023)\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\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eTypes and numbers of antibiotics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eNumber of Antimicrobials used by each patient (total\u0026thinsp;=\u0026thinsp;61 patients)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOne Antimicrobial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTwo antimicrobials\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTree or more antimicrobials\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDistribution of types used antimicrobials (total\u0026thinsp;=\u0026thinsp;150)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCephalosporins\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e35\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e23.3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCeftriaxone (J01DD04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCeftazidime (J01DD02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCefepime (J01DE01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCarbapenems\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e31\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e20.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eTienem (J01DH02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMeropenem (J01DH02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eImipenem/cilastatin (J01DH51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnspecified carbapenem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFluoroquinolones\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e16.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eLevofloxacin (J01MA12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCiprofloxacin (J01MA02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003emoxifloxacin (J01MA14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMetronidazole (J01XD01)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAminoglycoside\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eGentamycin (J01GB03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAmikacin (J01GB06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePenicillins\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e2.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAmoxicillin/clavulanic acid (J01CR02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAmoxicillin (J01CA04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eTazocin (Piperacillin/tazobactam) (J01CR05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLincosamide\u003c/b\u003e: \u003cb\u003eClindamycin (J01FF01)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVancomycin (J01XA01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMacrolides: Clarithromycin (J01FA09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSulfamethoxazole/trimethoprim (J01EE01)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOther antimicrobials\u003c/b\u003e:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e2.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAntifungal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAnti-tuberculosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAntiviral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: Antimicrobial Use in the Adult Medical ICU at Tripoli University Hospital (March-September 2023)\u003c/p\u003e\u003cp\u003eMicrobial Etiology and Antimicrobial Resistance:\u003c/p\u003e\u003cp\u003eMicrobiological results were available for 7 of the 18 infected patients. Identifying a total of 12 isolates. \u003cem\u003eKlebsiella\u003c/em\u003e species were the most common pathogens, accounting for 5 isolates (41.7%), followed by \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003eCandida albicans\u003c/em\u003e (2 isolates each, 16.7%), and 1 isolate each of \u003cem\u003eProteus\u003c/em\u003e spp., non-coagulase positive \u003cem\u003eStaphylococci\u003c/em\u003e, and \u003cem\u003eAcinetobacter calcoaceticus\u003c/em\u003e (8.3%). Antimicrobial resistance patterns were limited due to incomplete bacterial culture data resulting from laboratory service shortages; however, susceptibility results were available for 8 of the 10 bacterial isolates. Overall, the resistance rate among all isolated bacteria was 77.1%. Specifically, 90.7% of \u003cem\u003eK.pneumoniae\u003c/em\u003e isolates were resistant, 26.3% of pseudomonas isolates were resistant, and the single acinetobacter isolate was resistant to all tested antibiotics. Applying CDC definitions, 50% of pseudomonas were classified as multidrug-resistant (MDR), 50% of klebsiella as carbapenem-resistant enterobacteriaceae (CRE), and 75% as extended-spectrum beta-lactamases (ESBL). The single acinetobacter isolate showed a carbapenem-resistant acinetobacter (CRA) pattern. Resistance to specific antibiotics was observed, with both amoxicillin and augmentin showing 100% resistance in klebsiella and pseudomonas. Gentamicin resistance was found in the single acinetobacter isolate and 50% of klebsiella isolates. Carbapenems revealed 50% resistance in pseudomonas and 83.3% resistance in klebsiella. Antimicrobial resistance patterns are shown in the Supplementary Table A1.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eTo our knowledge; this is the first study in the country describing epidemiological features of HAI in adult medical ICU in governmental hospitals; in which HAI rate, risk factor for infection acquisition, mortality rate, and etiological microorganisms with antimicrobial resistance patterns were analysed.\u003c/p\u003e\u003cp\u003eOur results revealed ICU-AI rate 27.27% which is higher than 25.2%, 12.6%, 9.3% in Tunisia, Egyptian, and Italian medical ICUs respectively (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In contrast, is lower than 32.7% in Serbia (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and 35.7% in Slovenia (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo measure the infection per 1000 patient days. In our study; ICU-AI density was 24.97 per 1000 patients days; which is considered to be lower than what WHO declared that HAI in adult ICUs in developing countries about 47.9 per 1000 patients days (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), and lower than 66.4 episodes per 1000 days in Tunisia (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The low density observed in our study can be attributed to a high number of patient-days (long duration of admission). This is primarily due to absence of a long-term care facility, which necessitates patients to remain in ICU for an extended period until they discharged.\u003c/p\u003e\u003cp\u003e The underlying causes behind these variations in HAI rates among different ICUs are due to variation in study designs, sample size, guidelines of HAI detection, disparities in infection control protocols across hospitals, and variations in medical staff\u0026rsquo;s experience and training, furthermore, shortage of medical services should be considered. During these 6 months, the most frequent ICU-AI was pneumonia, accounting for 71.4% of all acquired infections. This included 60% VAP and 40% non-VAP. The incidence of pneumonia in our study was higher than 59% in Tunisia(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), 28.8% in Kuwait (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), 3.9% by ECDC (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), And 62% in India (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In contrast, incidence of infection per 1,000 mechanical ventilation (MV) days in our study was 34.48 per 1,000 MV days, is higher than 30 in Egypt, 26.6 in India, 7.8 by ECDC, and 4.21 in Kuwait per 1,000 MV days (\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This significantly high density of VAP in our results indicates a greater burden of ventilator-associated infections in our patients.\u003c/p\u003e\u003cp\u003eIn contrast to most studies that have revealed \u003cem\u003eA.baumanni\u003c/em\u003e as predominant bacteria among pneumatic patients; our study found \u003cem\u003eK.pneumonia\u003c/em\u003e the most frequent pathogen consistently with Egyptian, ECDC, and Libyan reports (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHigh frequency of pneumonia in this study can be attributed to several factors. Firstly, 100% of the patients received proton pump inhibitors upon admission, which has been identified as a potential risk factor for pneumonia in critically ill patients(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Additionally, 92.5% of the patients received prophylactic antibiotics, which enhance oral colonization and contribute to development of pneumonia (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Moreover, patient-to-nurse ratio in our ICU reached 2:1 and 3:1. It is essential for medical staff to strictly adhere to guidelines for VAP prevention.\u003c/p\u003e\u003cp\u003eAfter pneumonia, CAUTI constituted 19% of all acquired infections; which is equal to 19% in Abusalim Trauma Hospital in Tripoli, and higher than 3%,15% in Egypt and Tunisia respectively (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), while it\u0026rsquo;s lower than 27.59% and 36.3% in both India and Serbia; respectively(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). For incidence of CA UTI per 1000 catheter days in our study was 7.59 which is higher than 2.8 by ECDC, 2.9 in Egypt, 1.96 in Kuwait and 7.44 in India (\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). It\u0026rsquo;s evident among studies that most common organism for UTI was \u003cem\u003eE.coli\u003c/em\u003e while in our study \u003cem\u003eC.albicans\u003c/em\u003e spp was the commonest consistent with Egyptian study (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBloodstream infections (BSIs) were the least common, representing only 4.8% of cases. This rate is lower than 10% in Abusalim Trauma Hospital, 9.3% in Tunisia, 6.7% in Kuwait, 10.34% in India, and 19.6% in Serbia (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), while it is higher than 3.2% by the ECDC(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In our study, the incidence of CLABSIs per 1,000 central line-days was 2.3, which is lower than 2.9 in Egypt, 2.46 in India, and 3.4 by ECDC (\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Consistently with ECDC and Indian studies, the most commonly identified microorganisms in BSIs were coagulase-negative staphylococci. The suggested cause behind low incidence of (BSIs) is routine administration of antibiotics to admitted patients upon admission, which results in negative blood culture results when samples are taken.\u003c/p\u003e\u003cp\u003eOur study found that the length of stay in ICU is a significant predictor for HAI acquisition. Unlike prior studies, we identified prolonged hospital stay as the sole significant independent risk factor for HAI acquisition, while exposures to invasive devices and chronic comorbidities that were significant in univariate testing did not remain predictive in the adjusted model. This is because of small size of study population.\u003c/p\u003e\u003cp\u003eWhen it comes to mortality rate in our study it was found to be 55.56% among infected patients, it's higher than 39.4%, 17.2%, 42.5%, and 53.6% in Serbia, India, Poland and Kenya respectively (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). While non-infected individuals had a mortality rate of 25%, resulting in an excess mortality rate of 30.56%. when comparing mortality among both groups, p-value\u0026thinsp;=\u0026thinsp;0.019; meaning there is a significantly increasing risk of death for infected patients; conversely to other studies, which their p-value didn\u0026rsquo;t reach statistical significance (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). high mortality rate observed in our ICU can be attributed to spread of bacterial resistance among infected individuals. This elevated rate of mortality, highlights the necessity for further investigation to explore the underlying causes.\u003c/p\u003e\u003cp\u003eOur study results indicate no evidence of \u003cem\u003eClostridium difficile\u003c/em\u003e infection (CDI) among infected patients, despite it being recognized as a significant concern in healthcare facilities, particularly in ICUs (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Our ICU has not reported any cases or symptoms of diarrhoea associated with CDI in at least the past 5 years, despite the overuse of antibiotics. However, it is important to note that there is a lack of studies supporting this observation and exploring the underlying reasons behind this phenomenon.\u003c/p\u003e\u003cp\u003eBesides to prevalence \u003cem\u003eof K.Pneumonia\u003c/em\u003e among other bacteria, resistance rate to different antibiotics reached 90.7%, which is higher than 68.3% in South Africa (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and 54% in India (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and 53.75% in Ethiopia (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) and lower than 97.7% in Equatorial Guinea (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Approximately 75% of Klebsiella showed ESBL, it\u0026rsquo;s lower than 88% of ESBL in Abusalim Trauma Hospital in Libya (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e); while it\u0026rsquo;s higher than 71% of ESBL in Egypt (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) and 48% in Morocco (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). For Carbapenem resistance in Klebsiella; our results showed 75% resistance for imipenem and 100% for Meropenem, 100% Amikacin which all being higher than 17% Imipenem, 25% Amikacin, 50% Meropenem in Abusalim Trauma Hospital. The cause behind these high rates of resistance especially Carbapenem was attributed to overselection of carbapenem in our ICU and absence of facility-specific antibiogram data.\u003c/p\u003e\u003cp\u003eAs previous results indicated high VAP and high mortality rate compared to neighbouring countries on the same continent; these results which obtained from four- beds medical ICU of university hospital; may arise from inadequate implementation of infection prevention protocols and lack of a consistent surveillance system for analyzing HAIs and outbreaks. despite being an upper middle income country as World Bank rank; Libya still faces significant challenges, including political conflict, and economic instability. It\u0026rsquo;s worth paying attention to prevalence of ICU-AI in these countries\u003c/p\u003e\u003cp\u003eThis study has several limitations First; the sample size was small due to a limited number of available ICU beds, and slow bed turnover times caused by the absence of long-term care facilities. These factors resulted in fewer admitted patients.\u003c/p\u003e\u003cp\u003eSecondly, the study faced crucial challenges related to the shortage of medical laboratory services and lack of financial support. As a result, out of the 18 identified cases of ICU-AIs, only 7 were able to receive microbiological test results.\u003c/p\u003e\u003cp\u003eA third limitation was the common practice of administering antibiotics to patients upon admission and before collecting samples from infection site. This led to false-negative results.\u003c/p\u003e\u003cp\u003eFuture studies with larger sample sizes, more robust laboratory support, and practice of collecting blood samples before administering antibiotics will be crucial to better characterize the burden of HAIs and antimicrobial resistance.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn this first longitudinal study in TUH, the incidence of acquired infection in medical ICU was 27.27%, high incidence of pneumonia which was remarkably high, in addition to high bacterial resistance pattern, and alarming high mortality rate among infected patients; all of these findings reinforce the need to urgently implement of HAI surveillance system, and infection control program. The emerge of bacterial resistance, especially against Carbapenem drugs the 2nd most used antibiotic in our ICU; reflects challenges in treating highly vulnerable infected patients and challenges in healthcare practitioner compliance to evidence-based and local antibiogram data-based treatment guidelines and stewardship program.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis work was not supported by any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors did not receive any funding for this research.\u003c/p\u003e\u003cp\u003eCompeting Interests: The authors declare that they have no competing interests. They have no financial, personal, or professional interests that could be construed as influencing the work reported in this paper.\u003c/p\u003e\u003cp\u003e Ethics Approval: This research was conducted following the ethical principles outlined in the Declaration of Helsinki. The study protocol was approved by the Scientific Research and Ethics Committee at the University of Tripoli, No: SREC/010/35.\u003c/p\u003e\u003cp\u003eData Availability: The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003cp\u003eAcknowledgments:\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMaha: Conceptualization, methodology, investigation and writing original draft. Maheebah: methodology, Formal analysis, Visualization (Tables), writing original draft, review and editing. Mohamed: editing -review and supervision. Amina,Suhaib,Dow, Batool: Investigation and review. , Essra: Investigation, review Abubaker: Supervision\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRosenthal VD, Maki DG, Graves N. The International Nosocomial Infection Control Consortium (INICC): goals and objectives, description of surveillance methods, and operational activities. American journal of infection control. 2008;36(9):e1-e12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoran TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care\u0026ndash;associated infection and criteria for specific types of infections in the acute care setting. 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Journal of infection and public health. 2020;13(4):637\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hospital Acquired Infection, ICU, VAP, CAUTI, CLABSI, MDR","lastPublishedDoi":"10.21203/rs.3.rs-7629170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7629170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eFrequency of Intensive Care Unit-Acquired Infections (ICU-AI) and antimicrobial resistance rates remain higher in developing countries than in developed countries. There is limited information regarding ICU-AI in public hospitals in Libya.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis longitudinal study conducted in Tripoli University Hospital, Libya, including all patients diagnosed with HAI in the ICU from March 2023 to September 2023. Included patients aged 18 years and older who stayed more than 48 hours in the ICU.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf the 66 included cases, 18 were infected (27.27% of all patients), and ICU-AI incidence density was 24.97 per 1000 patient days. The most frequent ICU-AI was pneumonia (71.4%) followed by UTI (19%), Blood Stream Infection, and skin infection (4.8%) for each. For Device-Associated Infection (DAI) density; 34.48 per 1000 Mechanical Ventilation (MV) days for the Ventilator Associated Infection (VAP), 7.59 per 1000 catheter days for Catheter Associated UTI (CAUTI), and 2.33 per 1000 central line days for Central Line Associated Blood Stream Infection (CLABSI). \u003cem\u003eKlebsiella pneumonia\u003c/em\u003e was the commonest (41.7% of isolates). Mortality rate among infected patients was 55.56%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eHigh bacterial resistance emerges and high mortality rate among infected patients in medical ICU require immediate action to implement urgent infection prevention and control programs.\u003c/p\u003e","manuscriptTitle":"Hospital-acquired infection in adult ICU incidence, antimicrobial resistance pattern, mortality rates, and risk factors detecting in Tripoli University Hospital- Libya: Longitudinal study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-05 16:49:25","doi":"10.21203/rs.3.rs-7629170/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7c040e77-c80d-454f-b4ab-5cf9f5c789e2","owner":[],"postedDate":"December 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-23T22:23:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-05 16:49:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7629170","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7629170","identity":"rs-7629170","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}