Prevalence, resistance profiles and factors associated with skin and soft-tissue infections at Jinja regional referral hospital: A retrospective study

Published Jun 06, 2024 on Dryad. https://doi.org/10.5061/dryad.rjdfn2zkh

Data files

Jun 06, 2024 version files 142.59 KB

Abstract

Skin and soft-tissue infections (SSTI) are common cases of hospital-acquired infections with aetiologic agents exhibiting antimicrobial resistance (AMR). We determined the prevalence, proportion of laboratory-investigated cases, AMR-profiles, and factors associated with SSTI and multi-drug resistance (MDR). This study was based on archived data of patients suspected of SSTI from 2019-2021 at Jinja Regional Referral Hospital. The analysis involved 268 randomly selected patient reports. Prevalence of SSTI was 66.4%. Laboratory-investigated cases were 14.11%. Staphylococcus aureus (n=51) was the most isolated organism. MDR pathogens explained 47% of infections. Methicillin-resistant S. aureus was up to 44%. In addition, 61% of Gram-negatives had the potential to produce extended-spectrum beta-lactamases, while 27% were non-susceptible to carbapenems. Ward of admission was significantly associated with infection (aPR=1.78, 95% CI: 1.003-3.18, p-value=0.04). Age category (19-35) was an independent predictor for MDR infections (aPR=2.30, 95%CI:1.02-5.23, p-value=0.04). The prevalence is relatively high with MDR pathogens responsible for almost half of the infections. Routine use of culture and sensitivity testing should be done for proper infection management. Gentamicin and ciprofloxacin can be considered for empirical management of emergency SSTI suspected of S. aureus. Recognizing SSTI under the Global Antimicrobial resistance Surveillance System (GLASS) would lead to improved preparedness and response to AMR.

https://doi.org/10.5061/dryad.rjdfn2zkh

The original dataset (SSTI Dataset-JRRH.xls) and the WHONET version (SSTI Dataset-JRRH.dbf) have both been uploaded.

Description of the data and file structure

This dataset is mainly made up of rows and columns appropriately titled. Each row corresponds to one individual and respective data. This includes multiple variables including;

Year Case-Year in which the patient sought medical care and their case recorded at the facility.
Ward- Special medical unit for patient care
Sex- Biological characteristics of males or females
Age- Time spent on earth since birth (in years)
Age group- Categories of the age
Hospitalized≥48Hrs- Whether a patient was admitted at the hospital for at least two days or not. N/A in this case and elsewhere indicates that the data was not readily available during collection.
Surgery- Whether any of the patients underwent surgery
Surgical Type-If the patient underwent surgery, what type (Elective or Emergency)
Theatre- The theatre where the surgery was conducted (Main or Orthopedic)
On Antibiotics- Whether a patient was having antibiotics before undergoing microbiological testing.
Infection-Whether a patient was found to have a pathogenic microorganism capable of causing the skin and soft tissue infection,
MDR Pathogen- Whether the microorganism found in the patient’s sample was resistant to more than two antibiotics of different classes.
Organism- The species of microorganism found in the patient’s sample.
The rest of the column titles were the antibiotics tested against the different microorganism. The observations corresponding to them (R,I,S) were the outcomes of the test between the antibiotic and microorganism. Only one of the three applies to every antibiotic-microorganism combination tested.

Usage notes

Microsoft Excel can effectively open SSTI Dataset-JRRH.xls

Any version of the World Health Organization Network (WHONET) desktop application can be used to open SSTI Dataset-JRRH.dbf.

Sharing/Access information

Data was derived from the following sources:

Detailed information about this dataset can be obtained from Jinja Regional Referral Hospital(JRRH) with authorization from the JRRH Research and Ethics Committee (JREC)

Code/Software

The version of SSTI Dataset-JRRH.xls can be converted into SSTI Dataset-JRRH.dbf using the interface application called Baclink which is associated with WHONET application.