Antimicrobial resistance profile of Pseudomonas aeruginosa clinical isolates from healthcare-associated infections in Ethiopia: A systematic review and meta-analysis
Authors: Asmare Zelalem , Reta Melese Abate , Gashaw Yalewayker , Getachew Ermias , Sisay Assefa , Gashaw Muluken , Tamrat Ephrem , Kidie Atitegeb Abera , Abebe Wagaw , Misganaw Tadesse , Ashagre Agenagnew , Dejazmach Zelalem , Kumie Getinet , Nigatie Marye , Ayana Sisay , Jemal Abdu , Gedfie Solomon , Kassahun Woldeteklehaymanot , Kassa Mulat Awoke , Tadesse Selamyhun , Abate Biruk Beletew 
Published: August 2024

Background
Antimicrobial-resistant (AMR) bacterial infection is a significant global threat to the healthcare systems. Pseudomonas aeruginosa, the leading infectious agent in the healthcare setting is now one of the major threats due to AMR. A comprehensive understanding of the magnitude of AMR, particularly highly public health important pathogens such as P. aeruginosa, is necessary for the management of infections based on local information.

Objective
This systematic review and meta-analysis aimed to determine the country-wide AMR of P. aeruginosa.

Methods
Systematic searches were performed to retrieve articles from PubMed, Scopus, Web of Science, ScienceDirect electronic databases, Google Scholar search engine, and repository registrars from 2015 to 31st December 2023. Twenty-three studies that provided important data on AMR in P. aeruginosa were systematically reviewed and analyzed to determine the country-wide magnitude of P. aeruginosa AMR profile from healthcare-associated infections. AMR of P. aeruginosa to 10 different antibiotics were extracted separately into Microsoft Excel and analyzed using STATA 17.0. Cohen’s kappa was computed to determine the agreement between reviewers, the Inverse of variance (I2) was used to evaluate heterogeneity across studies, and Egger’s test to identify publication bias. A random effect model was used to determine the pooled resistance to each antibiotic. Subgroup analysis was performed by infection type and year of publication.

Results
This systematic review and meta-analysis revealed that the pooled prevalence of P. aeruginosa in clinical specimens associated with HAI was 4.38%(95%CI: 3.00–5.76). The pooled prevalence of AMR in P. aeruginosa for different antibiotics varies, ranging from 20.9% (95%CI: 6.2–35.8) for amikacin to 98.72% (95%CI: 96.39–101.4) for ceftriaxone. The pooled resistance was higher for ceftriaxone (98.72%), Trimethoprim-sulfamethoxazole (75.41), and amoxicillin-clavulanic acid (91.2). In contrast relatively lower AMR were observed for amikacin (20.9%) and meropenem (28.64%). The pooled multi-drug resistance (MDR) in P. aeruginosa was 80.5% (95%CI: 66.25–93.84). Upon subgroup analysis by infection types and year of publication, P. aeruginosa isolated from healthcare-associated infections exhibited higher resistance to ceftazidime (94.72%) compared to isolates from mixed types of healthcare-associated infections (70.84%) and surgical site infections (57.84%). Antimicrobial resistance in gentamicin was higher during the periods of 2018–2020 (73.96%), while comparatively lower during 2021–2023 (42.69%) and 2015–2017 (29.82%)

Conclusions
Significantly high AMR and MDR were observed from this systematic review and meta-analysis. AMR obtained from this systematic review and meta-analysis urges the need for improved infection control, antimicrobial stewardship practices, and strengthened surveillance systems to control the spread of AMR and ensure effective treatment of P. aeruginosa infections.

Protocol registration
This systematic review and meta-analysis was registered on PROSPERO (Registration ID: CRD42024518145).