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Background: Reporting on the International Nosocomial Infection Control Consortium study results from 2015 to 2020, conducted in 630 intensive care units across 123 cities in 45 countries spanning Africa, Asia, Eastern Europe, Latin America, and the Middle East., Methods: Prospective intensive care unit patient data collected via International Nosocomial Infection Control Consortium Surveillance Online System. Centers for Disease Control and Prevention/National Health Care Safety Network definitions applied for device-associated health care-associated infections (DA-HAI)., Results: We gathered data from 204,770 patients, 1,480,620 patient days, 936,976 central line (CL)-days, 637,850 mechanical ventilators (MV)-days, and 1,005,589 urinary catheter (UC)-days. Our results showed 4,270 CL-associated bloodstream infections, 7,635 ventilator-associated pneumonia, and 3,005 UC-associated urinary tract infections. The combined rates of DA-HAIs were 7.28%, and 10.07 DA-HAIs per 1,000 patient days. CL-associated bloodstream infections occurred at 4.55 per 1,000 CL-days, ventilator-associated pneumonias at 11.96 per 1,000 MV-days, and UC-associated urinary tract infections at 2.91 per 1,000 UC days. In terms of resistance, Pseudomonas aeruginosa showed 50.73% resistance to imipenem, 44.99% to ceftazidime, 37.95% to ciprofloxacin, and 34.05% to amikacin. Meanwhile, Klebsiella spp had resistance rates of 48.29% to imipenem, 72.03% to ceftazidime, 61.78% to ciprofloxacin, and 40.32% to amikacin. Coagulase-negative Staphylococci and Staphylococcus aureus displayed oxacillin resistance in 81.33% and 53.83% of cases, respectively., Conclusions: The high rates of DA-HAI and bacterial resistance emphasize the ongoing need for continued efforts to control them., (Copyright © 2024 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Central line (CL)-associated bloodstream infections (CLABSIs) occurring in the intensive care unit (ICU) are common and associated with a high burden., Methods: We implemented a multidimensional approach, incorporating an 11-element bundle, education, surveillance of CLABSI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CLABSI rates and clinical outcomes, and performance feedback in 316 ICUs across 30 low- and middle-income countries. Our dependent variables were CLABSI per 1,000-CL-days and in-ICU all-cause mortality rates. These variables were measured at baseline and during the intervention, specifically during the second month, third month, 4 to 16 months, and 17 to 29 months. Comparisons were conducted using a two-sample t test. To explore the exposure-outcome relationship, we used a generalized linear mixed model with a Poisson distribution to model the number of CLABSIs., Results: During 1,837,750 patient-days, 283,087 patients, used 1,218,882 CL-days. CLABSI per 1,000 CL-days rates decreased from 15.34 at the baseline period to 7.97 in the 2nd month (relative risk (RR) = 0.52; 95% confidence interval [CI] = 0.48-0.56; P < .001), 5.34 in the 3rd month (RR = 0.35; 95% CI = 0.32-0.38; P < .001), and 2.23 in the 17 to 29 months (RR = 0.15; 95% CI = 0.13-0.17; P < .001). In-ICU all-cause mortality rate decreased from 16.17% at baseline to 13.68% (RR = 0.84; P = .0013) at 17 to 29 months., Conclusions: The implemented approach was effective, and a similar intervention could be applied in other ICUs of low- and middle-income countries to reduce CLABSI and in-ICU all-cause mortality rates., (Copyright © 2023 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Objective: To identify urinary catheter (UC)-associated urinary tract infection (CAUTI) incidence and risk factors., Design: A prospective cohort study., Setting: The study was conducted across 623 ICUs of 224 hospitals in 114 cities in 37 African, Asian, Eastern European, Latin American, and Middle Eastern countries., Participants: The study included 169,036 patients, hospitalized for 1,166,593 patient days., Methods: Data collection took place from January 1, 2014, to February 12, 2022. We identified CAUTI rates per 1,000 UC days and UC device utilization (DU) ratios stratified by country, by ICU type, by facility ownership type, by World Bank country classification by income level, and by UC type. To estimate CAUTI risk factors, we analyzed 11 variables using multiple logistic regression., Results: Participant patients acquired 2,010 CAUTIs. The pooled CAUTI rate was 2.83 per 1,000 UC days. The highest CAUTI rate was associated with the use of suprapubic catheters (3.93 CAUTIs per 1,000 UC days); with patients hospitalized in Eastern Europe (14.03) and in Asia (6.28); with patients hospitalized in trauma (7.97), neurologic (6.28), and neurosurgical ICUs (4.95); with patients hospitalized in lower-middle-income countries (3.05); and with patients in public hospitals (5.89).The following variables were independently associated with CAUTI: Age (adjusted odds ratio [aOR], 1.01; P < .0001), female sex (aOR, 1.39; P < .0001), length of stay (LOS) before CAUTI-acquisition (aOR, 1.05; P < .0001), UC DU ratio (aOR, 1.09; P < .0001), public facilities (aOR, 2.24; P < .0001), and neurologic ICUs (aOR, 11.49; P < .0001)., Conclusions: CAUTI rates are higher in patients with suprapubic catheters, in middle-income countries, in public hospitals, in trauma and neurologic ICUs, and in Eastern European and Asian facilities.Based on findings regarding risk factors for CAUTI, focus on reducing LOS and UC utilization is warranted, as well as implementing evidence-based CAUTI-prevention recommendations.

Purpose: Identify urinary catheter (UC)-associated urinary tract infections (CAUTI) incidence and risk factors (RF) in Latin American Countries., Methods: From 01/01/2014 to 02/10/2022, we conducted a prospective cohort study in 145 ICUs of 67 hospitals in 35 cities in nine Latin American countries: Argentina, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, and Peru. To estimate CAUTI incidence, we used the number of UC-days as the denominator, and the number of CAUTIs as numerator. To estimate CAUTI RFs, we analyzed the following 10 variables using multiple logistic regression: gender, age, length of stay (LOS) before CAUTI acquisition, UC-days before CAUTI acquisition, UC-device utilization (DU) ratio, UC-type, hospitalizationtype, ICU type, facility ownership, and time period., Results: 31,631 patients, hospitalized for 214,669 patient-days, acquired 305 CAUTIs. The pooled CAUTI rate per 1000 UC-days was 2.58, for those using suprapubic catheters, it was 2.99, and for those with indwelling catheters, it was 2.21. The following variables were independently associated with CAUTI: age, rising risk 1% yearly (aOR = 1.01; 95% CI 1.01-1.02; p < 0.0001 female gender (aOR = 1.28; 95% CI 1.01-1.61; p = 0.04), LOS before CAUTI acquisition, rising risk 7% daily (aOR = 1.07; 95% CI 1.06-1.08; p < 0.0001, UC/DU ratio (aOR = 1.14; 95% CI 1.08-1.21; p < 0.0001, public facilities (aOR = 2.89; 95% CI 1.75-4.49; p < 0.0001. The periods 2014-2016 and 2017-2019 had significantly higher risks than the period 2020-2022. Suprapubic catheters showed similar risks as indwelling catheters., Conclusion: The following CAUTI RFs are unlikely to change: age, gender, hospitalization type, and facility ownership. Based on these findings, it is suggested to focus on reducing LOS, UC/DU ratio, and implementing evidence-based CAUTI prevention recommendations., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Our objective was to identify central line (CL)-associated bloodstream infections (CLABSI) rates and risk factors in Latin-America., Methods: From January 1, 2014 to February 10, 2022, we conducted a multinational multicenter prospective cohort study in 58 ICUs of 34 hospitals in 21 cities in 8 Latin American countries (Argentina, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama). We applied multiple-logistic regression. Outcomes are shown as adjusted-odds ratios (aOR)., Results: About 29,385 patients were hospitalized during 92,956 days, acquired 400 CLABSIs, and pooled CLABSI rate was 4.30 CLABSIs per 1,000 CL-days. We analyzed following 10 variables: Gender, age, length of stay (LOS) before CLABSI acquisition, CL-days before CLABSI acquisition, CL-device utilization (DU) ratio, CL-type, tracheostomy use, hospitalization type, intensive care unit (ICU) type, and facility ownership, Following variables were independently associated with CLABSI: LOS before CLABSI acquisition, rising risk 3% daily (aOR=1.03;95%CI=1.02-1.04; P < .0001); number of CL-days before CLABSI acquisition, rising risk 4% per CL-day (aOR=1.04;95%CI=1.03-1.05; P < .0001); publicly-owned facility (aOR=2.33;95%CI=1.79-3.02; P < .0001). ICU with highest risk was medical-surgical (aOR=2.61;95%CI=1.41-4.81; P < .0001). CL with the highest risk were femoral (aOR=2.71;95%CI=1.61-4.55; P < .0001), and internal-jugular (aOR=2.62;95%CI=1.82-3.79; P < .0001). PICC (aOR=1.25;95%CI=0.63-2.51; P = .52) was not associated with CLABSI risk., Conclusions: Based on these findings it is suggested to focus on reducing LOS, CL-days, using PICC instead of femoral or internal-jugular; and implementing evidence-based CLABSI prevention recommendations., (Copyright © 2023 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: The International Nosocomial Infection Control Consortium has found a high ICU mortality rate. Our aim was to identify all-cause mortality risk factors in ICU-patients., Methods: Multinational, multicenter, prospective cohort study at 786 ICUs of 312 hospitals in 147 cities in 37 Latin American, Asian, African, Middle Eastern, and European countries., Results: Between 07/01/1998 and 02/12/2022, 300,827 patients, followed during 2,167,397 patient-days, acquired 21,371 HAIs. Following mortality risk factors were identified in multiple logistic regression: Central line-associated bloodstream infection (aOR:1.84; P<.0001); ventilator-associated pneumonia (aOR:1.48; P<.0001); catheter-associated urinary tract infection (aOR:1.18;P<.0001); medical hospitalization (aOR:1.81; P<.0001); length of stay (LOS), risk rises 1% per day (aOR:1.01; P<.0001); female gender (aOR:1.09; P<.0001); age (aOR:1.012; P<.0001); central line-days, risk rises 2% per day (aOR:1.02; P<.0001); and mechanical ventilator (MV)-utilization ratio (aOR:10.46; P<.0001). Coronary ICU showed the lowest risk for mortality (aOR: 0.34;P<.0001)., Conclusion: Some identified risk factors are unlikely to change, such as country income-level, facility ownership, hospitalization type, gender, and age. Some can be modified; Central line-associated bloodstream infection, ventilator-associated pneumonia, catheter-associated urinary tract infection, LOS, and MV-utilization. So, to lower the risk of death in ICUs, we recommend focusing on strategies to shorten the LOS, reduce MV-utilization, and use evidence-based recommendations to prevent HAIs., (Copyright © 2022 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Objective: To identify central-line (CL)-associated bloodstream infection (CLABSI) incidence and risk factors in low- and middle-income countries (LMICs)., Design: From July 1, 1998, to February 12, 2022, we conducted a multinational multicenter prospective cohort study using online standardized surveillance system and unified forms., Setting: The study included 728 ICUs of 286 hospitals in 147 cities in 41 African, Asian, Eastern European, Latin American, and Middle Eastern countries., Patients: In total, 278,241 patients followed during 1,815,043 patient days acquired 3,537 CLABSIs., Methods: For the CLABSI rate, we used CL days as the denominator and the number of CLABSIs as the numerator. Using multiple logistic regression, outcomes are shown as adjusted odds ratios (aORs)., Results: The pooled CLABSI rate was 4.82 CLABSIs per 1,000 CL days, which is significantly higher than that reported by the Centers for Disease Control and Prevention National Healthcare Safety Network (CDC NHSN). We analyzed 11 variables, and the following variables were independently and significantly associated with CLABSI: length of stay (LOS), risk increasing 3% daily (aOR, 1.03; 95% CI, 1.03-1.04; P < .0001), number of CL days, risk increasing 4% per CL day (aOR, 1.04; 95% CI, 1.03-1.04; P < .0001), surgical hospitalization (aOR, 1.12; 95% CI, 1.03-1.21; P < .0001), tracheostomy use (aOR, 1.52; 95% CI, 1.23-1.88; P < .0001), hospitalization at a publicly owned facility (aOR, 3.04; 95% CI, 2.31-4.01; P <.0001) or at a teaching hospital (aOR, 2.91; 95% CI, 2.22-3.83; P < .0001), hospitalization in a middle-income country (aOR, 2.41; 95% CI, 2.09-2.77; P < .0001). The ICU type with highest risk was adult oncology (aOR, 4.35; 95% CI, 3.11-6.09; P < .0001), followed by pediatric oncology (aOR, 2.51;95% CI, 1.57-3.99; P < .0001), and pediatric (aOR, 2.34; 95% CI, 1.81-3.01; P < .0001). The CL type with the highest risk was internal-jugular (aOR, 3.01; 95% CI, 2.71-3.33; P < .0001), followed by femoral (aOR, 2.29; 95% CI, 1.96-2.68; P < .0001). Peripherally inserted central catheter (PICC) was the CL with the lowest CLABSI risk (aOR, 1.48; 95% CI, 1.02-2.18; P = .04)., Conclusions: The following CLABSI risk factors are unlikely to change: country income level, facility ownership, hospitalization type, and ICU type. These findings suggest a focus on reducing LOS, CL days, and tracheostomy; using PICC instead of internal-jugular or femoral CL; and implementing evidence-based CLABSI prevention recommendations.

Competing Interests: Declaration of Competing Interest All authors report no conflicts of interest related to this article. The Institutional Review Board of each hospital agreed to the study protocol, and patient confidentiality was protected by codifying the recorded information, making it only identifiable to the infection control team.

Objective: Rates of ventilator-associated pneumonia (VAP) in low- and middle-income countries (LMIC) are several times above those of high-income countries. The objective of this study was to identify risk factors (RFs) for VAP cases in ICUs of LMICs., Design: Prospective cohort study., Setting: This study was conducted across 743 ICUs of 282 hospitals in 144 cities in 42 Asian, African, European, Latin American, and Middle Eastern countries., Participants: The study included patients admitted to ICUs across 24 years., Results: In total, 289,643 patients were followed during 1,951,405 patient days and acquired 8,236 VAPs. We analyzed 10 independent variables. Multiple logistic regression identified the following independent VAP RFs: male sex (adjusted odds ratio [aOR], 1.22; 95% confidence interval [CI], 1.16-1.28; P < .0001); longer length of stay (LOS), which increased the risk 7% per day (aOR, 1.07; 95% CI, 1.07-1.08; P < .0001); mechanical ventilation (MV) utilization ratio (aOR, 1.27; 95% CI, 1.23-1.31; P < .0001); continuous positive airway pressure (CPAP), which was associated with the highest risk (aOR, 13.38; 95% CI, 11.57-15.48; P < .0001); tracheostomy connected to a MV, which was associated with the next-highest risk (aOR, 8.31; 95% CI, 7.21-9.58; P < .0001); endotracheal tube connected to a MV (aOR, 6.76; 95% CI, 6.34-7.21; P < .0001); surgical hospitalization (aOR, 1.23; 95% CI, 1.17-1.29; P < .0001); admission to a public hospital (aOR, 1.59; 95% CI, 1.35-1.86; P < .0001); middle-income country (aOR, 1.22; 95% CI, 15-1.29; P < .0001); admission to an adult-oncology ICU, which was associated with the highest risk (aOR, 4.05; 95% CI, 3.22-5.09; P < .0001), admission to a neurologic ICU, which was associated with the next-highest risk (aOR, 2.48; 95% CI, 1.78-3.45; P < .0001); and admission to a respiratory ICU (aOR, 2.35; 95% CI, 1.79-3.07; P < .0001). Admission to a coronary ICU showed the lowest risk (aOR, 0.63; 95% CI, 0.51-0.77; P < .0001)., Conclusions: Some identified VAP RFs are unlikely to change: sex, hospitalization type, ICU type, facility ownership, and country income level. Based on our results, we recommend focusing on strategies to reduce LOS, to reduce the MV utilization ratio, to limit CPAP use and implementing a set of evidence-based VAP prevention recommendations., (© The Author(s) 2023.)

Background: The International Nosocomial Infection Control Consortium (INICC) has found a high ICU mortality rate in Latin America., Methods: A prospective cohort study in 198 ICUs of 96 hospitals in 46 cities in 12 Latin American countries to identify mortality risk factors (RF), and data were analyzed using multiple logistic regression., Results: Between 07/01/1998 and 02/12/2022, 71,685 patients, followed during 652,167 patient-days, acquired 4700 HAIs, and 10,890 died. We prospectively collected data of 16 variables. Following 11 independent mortality RFs were identified in multiple logistic regression: ventilator-associated pneumonia (VAP) acquisition (adjusted odds ratio [aOR] = 1.17; 95% CI: 1.06-1.30; p < 0.0001); catheter-associated urinary tract infection (CAUTI) acquisition (aOR = 1.34; 95% CI: 1.15-1.56; p < 0.0001); older age, rising risk 2% yearly (aOR = 1.02; 95% CI: 1.01-1.02; p < 0.0001); longer indwelling central line(CL)-days, rising risk 3% daily (aOR = 1.03; 95% CI: 1.02-1.03; p < 0.0001); longer indwelling urinary catheter(UC)-days, rising risk 1% daily (aOR = 1.01; 95% CI: 1.01-1.26; p < 0.0001); higher mechanical ventilation (MV) (aOR = 6.47; 95% CI: 5.96-7.03; p < 0.0001) and urinary catheter-utilization ratio (aOR = 1.19; 95% CI: 1.11-1.27; p < 0.0001); lower-middle level income country (aOR = 2.94; 95% CI: 2.10-4.12; p < 0.0001); private (aOR = 1.50; 95% CI: 1.27-1.77; p < 0.0001) or public hospital (aOR = 1.47; 95% CI: 1.24-1.74; p < 0.0001) compared with university hospitals; medical hospitalization instead of surgical (aOR = 1.67; 95% CI: 1.59-1.75; p < 0.0001); neurologic ICU (aOR = 4.48; 95% CI: 2.68-7.50; p < 0.0001); adult oncology ICU (aOR = 3.48; 95% CI: 2.14-5.65; p < 0.0001); and others., Conclusion: Some of the identified mortality RFs are unlikely to change, such as the income level of the country, facility ownership, hospitalization type, ICU type, and age. But some of the mortality RFs we found can be changed, and efforts should be made to reduce CL-days, UC-days, MV-utilization ratio, UC-utilization ratio, and lower VAPs and CAUTI rates., (© 2022. The Author(s).)