Yin, Ruijie
Jin, Zhilin
Lee, Brandon Hochahn
Alvarez, Gustavo Andres
Stagnaro, Juan Pablo
Valderrama-Beltran, Sandra Liliana
Gualtero, Sandra Milena
Jiménez-Alvarez, Luisa Fernanda
Reyes, Lidia Patricia
Henao Rodas, Claudia Milena
Gomez, Katherine
Alarcon, Johana
Aguilar Moreno, Lina Alejandra
Bravo Ojeda, Juan Sebastian
Cano Medina, Yuliana Andrea
Chapeta Parada, Edwin Giovannny
Zuniga Chavarria, Maria Adelia
Quesada Mora, Ana Marcela
Aguirre-Avalos, Guadalupe
Mijangos-Méndez, Julio Cesar
Sassoe-Gonzalez, Alejandro
Millán-Castillo, Claudia Marisol
Aleman-Bocanegra, Mary Cruz
Echazarreta-Martínez, Clara Veronica
Hernandez-Chena, Blanca Estela
Jarad, Rajab Mohamed Abu
Villegas-Mota, Maria Isabel
Montoya-Malváez, Mildred
Aguilar-de-Moros, Daisy
Castaño-Guerra, Elizabeth
Córdoba, Judith
Castañeda-Sabogal, Alex
Medeiros, Eduardo Alexandrino
Fram, Dayana
Dueñas, Lourdes
Carreazo, Nilton Yhuri
Salgado, Estuardo
Rosenthal, Victor Daniel http://orcid.org/0000-0001-9138-4801
Article History
Received: 4 May 2023
Accepted: 16 September 2023
First Online: 12 October 2023
Declarations
:
: All authors declare that they do not have any financial or personal relationships with other people or organizations that could inappropriately influence (bias) their work. All authors declare that they have no potential competing interests, such as employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications or registrations, and grants or other funding. Submission of this article implies that the work described has not been published previously, that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically, without the written consent of the copyright holder.
: This project involved the analysis of big data collected prospectively using standardized forms. There was not any recruitment involved. The study sample reflects the demographics of the hospitalized patients in intensive care units (ICUs) in Latin America, which are 50/50 male and female. The hospital team's ICU surveillance of catheter-related urinary tract infections (CAUTI) rates was based on U.S. CDC/NHSN methodology, without patient identifiers or any patient detail, and collected only "urinary catheter” and "acquisition of a CAUTI." Our IPPs obtained CAUTI surveillance data from ICU records of surveillance without being in contact with patients. To determine the rates of CAUTI, IPPs visited all ICUs and checked ICU records from Monday to Friday for 60 min each time. On Mondays, weekend data were collected. This gold standard approach to CR-BSI and MDRO surveillance is a well-documented method that adheres to the legal and ethical framework of the US CDC NHSN.
: This is a surveillance study without any intervention, and for that reason, informed consent was not required. The research team maintained the highest level of confidentiality with the data of hospitalized patients. Individually identifiable information was not collected or shared with anyone. Any potential data and identifiers were removed at data entry. These data were kept in separate, locked file drawers and on a password-protected computer. The computerized data were kept on a non-networked computer. Only de-identified datasets were kept on a computer that resides inside the university network and is protected by multiple firewalls. VD Rosenthal, Z Jin, and R Yin had access to the collected data. This research did not collect any information on the participants, thus no personal identifier information.