Antimicrobial susceptibility testing data analysis over 3 years at the Yaoundé General Hospital, Cameroon

• Published in: JAC-antimicrobial resistance Vol. 6; no. 2; p. dlae043
• Main Authors: Ngogang, Marie Paule, Nkoth, Abel Fils, Ngaleu, Welysiane, Mfouapon, Heroine, Ekoume, Priscille, Nibeye, Yannick, Medi Sike, Christiane, Voundi, Esther Voundi, Mouliom Mouiche, Mohammed Moctar, Fonkoua, Marie Christine, Toukam, Michel, Mbopi-Keou, Francois-Xavier
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01-04-2024
• Subjects: Original
• DOI: 10.1093/jacamr/dlae043
• EISSN: 2632-1823

Antimicrobial resistance (AMR) is a major health concern with high rates in low-income countries. Bacteriology laboratories sustain the fight against AMR by providing antibiotic susceptibility testing (AST) results to ensure appropriate therapies. These laboratories generate a lot of data, which are usually used for prospective interventions. Our study conducted in a lower-middle-income hospital setting aimed to describe the profile of bacteria isolated from the specimens received over 3 years, assess their susceptibility profile and identify potential gaps or area of improvement from the analysis of our data.
Monthly data were retrieved from registers for all specimens received between January 2020 until December 2022. Data were compiled and analysed using the R and WHONET software.
Out of 3582 specimens received, 797 were culture positive (22.3%).
and
were frequently isolated (30.5% and 24.2%, respectively). AST results analysis showed high resistance of Gram-negative bacteria to penams and cephems, whereas low resistance was observed to carbapenems. Susceptibility to antibiotics based on the AWaRe antibiotic classification was variable. The bacteriological profile in the various types of specimen was established and rational information to design a therapeutic protocol adapted to our hospital setting was obtained.
AST results may not only be used for prospective guidance for treatment, but rather cumulative data analysis can contribute to design effective antibiotic prescriptions and improve general practices at the laboratory. This is, however, dependent on a good record-keeping, standardization of practices and collaboration between clinicians and laboratory scientists.