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Antibiotic resistance patterns in infections associated with health care in a Third Level Center with hospital reconversion in the COVID-19 pandemic
Almeida Villegas, Jorge Angel; Gutiérrez Gutiérrez, José Alfonso; León Quirino, Silvia; Albarrán Calzonzín, Patricia; Acosta Ramírez, Alejandro; Rubén Castillo Nava, Carlos Alberto; Guzmán Márquez, María del Carmen.
Affiliation
  • Almeida Villegas, Jorge Angel; University of Ixtlahuaca CUI. Ixtlahuaca. México
  • Gutiérrez Gutiérrez, José Alfonso; University of Ixtlahuaca CUI. Ixtlahuaca. México
  • León Quirino, Silvia; Autonomous Mexico State University. Faculty of Chemistry. México
  • Albarrán Calzonzín, Patricia; Autonomous Mexico State University. Faculty of Chemistry. México
  • Acosta Ramírez, Alejandro; Autonomous Mexico State University. Faculty of Chemistry. México
  • Rubén Castillo Nava, Carlos Alberto; University of Ixtlahuaca CUI. Ixtlahuaca. México
  • Guzmán Márquez, María del Carmen; Microbiology Laboratory Medical Center. Toluca. México
An. R. Acad. Nac. Farm. (Internet) ; 88(2): 123-130, abr-jun 2022. tab
Article in English | IBECS | ID: ibc-206552
Responsible library: ES1.1
Localization: ES15.1 - BNCS
ABSTRACT
Objetive Description of the different isolated microorganisms and their prevalence in infections associated with health care, in addition to determining their patterns of resistance to antibiotics in patients admitted with a confirmed or suspected diagnosis of COVID-19 in the Intensive Care Unit, during a third-level medical center with hospital reconversion.

Method:

Patient demographic data was obtained from the clinical record, with defined criteria. Antibiotic resistance patterns were evaluated as well as the identification of isolated bacteria in cultures of expectoration, pleural fluid, catheter tips. For bacterial identification and resistance mechanisms, automated equipment and phenotypic tests were used, following the CLSI (Clinical & Laboratory Standards Institute) criteria.

Results:

A total of 100 patients with bacterial infection added to the main COVID-19 picture were obtained, representing pneumonia, urinary tract infection, catheter infections and bacteremia. A total of 100 strains were isolated, of which 84 are Extremely Drug Resistant, 12 Multidrug Resistant and only 4 variable sensitivity. The bacteria with the highest prevalence is Staphylococcus aureus with, followed by Pseudonomas aeruginosa and Stenotrophomonas maltophilia. 100% of the patients admitted to the ICU (Intensive Care Unit) had death.

Conclusion:

The increase in resistance to antibiotics in the COVID-19 pandemic has set off alarms due to the complication that this brings, and the improper use of drugs as prophylaxis or attempted treatment only generates selective pressure that leads to an increase in resistance as observed in the isolated strains in this study, where the vast majority present enzymes as well as other resistance mechanisms that confer them to be XDR (Extremely Drug Resistant).(AU)
RESUMEN

Objetivo:

Descripción de los diferentes microorganismos aislados y su prevalencia en infecciones asociadas a la atención de la salud, además de determinar sus patrones de resistencia a antibióticos en pacientes ingresados con diagnóstico confirmado o sospechado de COVID-19 en la Unidad de Cuidados Intensivos, en Centro médico de tercer nivel con reconversión hospitalaria.

Método:

Los datos demográficos de los pacientes se obtuvieron de la historia clínica, con criterios definidos. Se evaluaron patrones de resistencia a antibióticos, así como la identificación de bacterias aisladas en cultivos de expectoración, líquido pleural, puntas de catéter. Para la identificación bacteriana y los mecanismos de resistencia se utilizaron equipos automatizados y pruebas fenotípicas, siguiendo los criterios del CLSI (Clinical & Laboratory Standards Institute).

Resultados:

Se estudió un total de 100 pacientes con infección bacteriana sumado al cuadro principal de COVID-19, de los cuales representó neumonía, infección de vías urinarias, infecciones de catéter y bacteriemia. Se aislaron un total de 100 cepas, de las cuales 84 son Extremadamente Resistentes, 12 Multirresistentes y solo 4 de sensibilidad variable. La bacteria con mayor prevalencia es Staphylococcus aureus, seguida de Pseudonomas aeruginosa y Stenotrophomonas maltophilia. El 100% de los pacientes ingresados en UCI (Unidad de Cuidados Intensivos) tuvieron muerte.

Conclusión:

El aumento de las resistencias a los antibióticos en la pandemia de COVID-19 ha hecho saltar las alarmas por la complicación que esto trae consigo, y el uso inadecuado de fármacos como profilaxis o intento de tratamiento solo genera una presión selectiva que conduce a un aumento de las resistencias como se observa en las cepas aisladas en este estudio, donde la gran mayoría presenta enzimas así como otros mecanismos de resistencia que les confieren ser XDR (Extremadamente Resistente).(AU)
Subject(s)

Full text: Available Collection: National databases / Spain Database: IBECS Main subject: Drug Resistance, Microbial / Cross Infection / Coronavirus Limits: Humans Language: English Journal: An. R. Acad. Nac. Farm. (Internet) Year: 2022 Document type: Article Institution/Affiliation country: Autonomous Mexico State University/México / Microbiology Laboratory Medical Center/México / University of Ixtlahuaca CUI/México
Full text: Available Collection: National databases / Spain Database: IBECS Main subject: Drug Resistance, Microbial / Cross Infection / Coronavirus Limits: Humans Language: English Journal: An. R. Acad. Nac. Farm. (Internet) Year: 2022 Document type: Article Institution/Affiliation country: Autonomous Mexico State University/México / Microbiology Laboratory Medical Center/México / University of Ixtlahuaca CUI/México
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