Victor Daniel Rosenthal, Zhilin Jin, Ziad A. Memish, Camilla Rodrigues, Sheila Nainan Myatra, Mohit Kharbanda, Sandra Liliana Valderrama-Beltran, Yatin Mehta, Mohammad Abdellatif Daboor, Subhash Kumar Todi, Guadalupe Aguirre-Avalos, Ertugrul Guclu, Chin Seng Gan, Luisa Fernanda Jiménez Alvarez, Rajesh Chawla, Sona Hlinkova, Rajalakshmi Arjun, Hala Mounir Agha, Maria Adelia Zuniga Chavarria, Narangarav Davaadagva, Mat Nor Mohd Basri, Katherine Gomez, Daisy Aguilar De Moros, Chian-Wern Tai, Alejandro Sassoe Gonzalez, Lina Alejandra Aguilar Moreno, Kavita Sandhu, Jarosław Janc, Mary Cruz Aleman Bocanegra, Dincer Yildizdas, Yuliana Andrea Cano Medina, Maria Isabel Villegas Mota, Abeer Aly Omar, Wieslawa Duszynska, Souad BelKebir, Amani Ali El-Kholy, Safaa Abdulaziz Alkhawaja, George Horhat Florin, Eduardo Alexandrino Medeiros, Lili Tao, Nellie Tumu, May Gamar Elanbya, Reshma Dongol, Vesna Mioljević, Lul Raka, Lourdes Dueñas, Nilton Yhuri Carreazo, Tarek Dendane, Aamer Ikram, Souha S. Kanj, Michael M. Petrov, Asma Bouziri, Nguyen Viet Hung, Vladislav Belskiy, Naheed Elahi, María Marcela Bovera, and Ruijie Yin
Abstract 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.