Genetic relationship between bacteria isolated from intraoperative air samples and surgical site infections at a major teaching hospital in Ghana

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Background: In low- and middle-income countries (LMICs) the rate of surgical site infections (SSI) is high, leading to negative patient outcomes and excess healthcare costs. A causal relationship between airborne bacteria in the operating room and SSI has not been established, at a molecular or genetic level. We studied the relationship between intraoperative airborne bacteria and bacteria causing SSI in an LMIC. Methods: Active air sampling using a portable impactor was performed during clean or clean-contaminated elective surgical procedures. Active patient follow-up consisting of phone calls and clinical examinations was performed 3, 14 and 30 days after surgery. Bacterial isolates recovered from SSI and air samples were compared by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) identification, ribotyping, whole genome sequencing (WGS), and metagenomic analysis. Results: Of 128 included patients, 116 (91%) completed follow-up and 11 (9%) developed SSI. Known pathogenic bacteria were isolated from intraoperative air samples in all cases with SSI. A match between air and SSI isolates was found by MALDI-TOF in eight cases. Matching ribotypes were found in six cases and in one case both WGS and metagenomic analysis showed identity between air- and SSI-isolates. Conclusion: The study showed high levels of intraoperative airborne bacteria, an SSI-rate of 9% and a genetic link between intraoperative airborne bacteria and bacteria isolated from SSIs. This indicates the need for awareness of intraoperative air quality in LMICs.

Original languageEnglish
JournalJournal of Hospital Infection
Volume104
Issue number3
Pages (from-to)309-320
Number of pages12
ISSN0195-6701
DOIs
Publication statusPublished - 2020

    Research areas

  • Airborne bacteria, Low- and middle-income countries, Metagenomic, Staphylococcus aureus, Surgical site infections, Whole genome sequencing

ID: 235591727