Orthopaedic surgical site infections: Prevalence, bacterial etiology, and antimicrobial resistance
Data files
Dec 28, 2023 version files 97.66 KB
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Data.xlsx
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README.md
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README.md.txt
Abstract
Background: Surgical site infections (SSIs), the second most dreaded post-operative hospital-acquired infection, play an important role in the emergence of multi-drug-resistant (MDR) bacteria owing to the practice of prophylactic antibiotic use. Even in the most advanced hospitals, SSIs are becoming more common, yet limited literature exists on the bacteriological profile and antimicrobial resistance. This cross-sectional study assessed the prevalence of orthopaedic SSIs in traumatically operated patients’ one-month post-operation in correlation to antibiotic resistance in bacteria-causing SSIs.
Method: The demographic and surgical records of orthopaedic patients suffering post-operative SSI (clean or clean-contaminated wound) and examined in the Department of Microbiology, National Trauma Center, for aerobic bacteriological culture and susceptibility testing during three years (2020-2022) were analyzed with SPSS version 17.0.
Results: Among the total patients (n=1,438), 448 (median age: 35 years; males: 341) developed SSIs, with knee/joint infections (141/448) being predominant. SSIs occurred every seven days on average. Staphylococcus aureus (216/448) was the predominant bacteria. Overall, 61.88% (250/404) of isolates were penicillin-resistant, whereas 51.31% (450/877) were cephalosporin-resistant. Streptococcus spp. and Enterobacter spp. were equally predominant MDR (50%) and extensively drug-resistant (XDR) isolates (25%), while S. aureus was the predominant pan-drug-resistant isolate (0.46%). Fluoroquinolone resistance rates in non-MDR (n=272), MDR (n=153), and XDR (n=22) were 15.88%, 60.59%, and 22.94%, respectively, while aminoglycoside resistance rates were 13.27%, 59.29%, and 24.49%. Acinetobacter calcoaceticus baumanii complex exhibited the highest multiple antibiotic resistance index (0.58).
Conclusion: SSIs following orthopaedic procedures were highly prevalent, particularly due to S. aureus and MDR strains. Antibiotic resistance was more pronounced in MDR strains, encompassing XDR strains, than in non-MDR strains.
README: Orthopaedic surgical site infections: prevalence, bacterial etiology, and antimicrobial resistance
https://doi.org/10.5061/dryad.h18931zt2
The dataset is of orthopaedic surgical site infections (SSIs) in traumatically operated patients’ one-month post-operation along with antibiotic susceptibility profiles of bacteria-causing SSIs.
Dataset comprises single sheet. The sheet details for demographic information, such as age and gender of the orthopaedic patients; clinical information, including fractures; microbiological findings comprising bacterial genera, antimicrobial resistance patterns, multi-drug-resistant or non-multi-drug-resistant, extesnsively-drug-resistant or non-extesnsively-drug-resistant. Exact age is removed and is categorized as age group in order to anonymize the data.
Data were anonymized with the code. Orthopaedic patients with bacterial infections were coded with serial number (1, 23, etc.).
Units of the study variables were standard and as follows:
(a) Age group Years
(b) Post operative time for infections Days
Antimicrobial susceptibility testing was done with Kirby Bauer Disc Diffusion method.
Except for values of post operative days for infections, the data were qualitative and were calculated as frequency (percentage) in SPSS version 17.0. Qualitative variables were tested using chi-square test at 95% confidence interval.
S.N represents serial number, ACB complex represnts Acinetobacter calcoaceticus-baumannii complex, CoNS represents Coagulase-negative Staphylococcus, spp. represents species, n/a represents not available.
Readers may access the data from the Dryad repository or with a request email to the corresponding author, Pramod Joshi (researchdev108@gmail.com), of the article.
Methods
Patient-related information (age and gender) and surgical-related information [sites and types of fracture, length (days) to develop postoperative infections, type of wound (clean, clean-contaminated, contaminated, or dirty-contaminated), bacterial strain, and antibiotic susceptibility pattern] were collected between January 20th and February 27th, 2023, from the hospital's electronic database. Collected data were assessed for statistical analyses between March 6th and March 28th, 2023.
The Statistical Package for Social Sciences, version 17.0 (SPSS Inc., Chicago, IL, USA), was used to import the exported data from Midas into Microsoft Excel version 10.0. The categorical variables were analyzed using frequencies and percentages in descriptive analysis. The median and interquartile ranges of patients' ages and lengths of postoperative infections were calculated. For two groups, the independent student t-test and chi-squared test were used to compare the strength of the associations between the quantitative (age) and qualitative (gender, year, season, month, surgical site, bacteria, antibiotic, and resistance) variables, respectively. P-values <0.05 were considered significant.