Dataset Information

Characterisation of Bacterial Isolates from Infected Post-Operative Patients in a Malaysian Tertiary Heart Care Centre.

ABSTRACT: Several bacterial species cause post-operative infections, which has been a critical health concern among hospital patients. Our study in this direction is a much-needed exploratory study that was carried out at the National Heart Institute (IJN) of Malaysia to examine the virulence properties of causative bacteria obtained from postoperative patients. The bacterial isolates and data were provided by the IJN. Antibiotic resistance gene patterns, and the ability to form biofilm were investigated for 127 isolates. Klebsiella pneumoniae (36.2%) was the most common isolate collected, which was followed by Pseudomonas aeruginosa (26%), Staphylococcus aureus (23.6%), Streptococcus spp. (8.7%) and Acinetobacter baumannii (5.5%). There were 49 isolates that showed the presence of multidrug resistance genes. The mecA gene was surprisingly found in methicillin-susceptible S. aureus (MSSA), which also carried the ermA gene from those erythromycin-susceptible strains. The phenotypic antibiotic resistance profiles varied greatly between isolates. Findings from the biofilm assay revealed that 44 of the 127 isolates demonstrated the ability to produce biofilms. Our findings provide insights into the possibility of some of these bacteria surviving under antibiotic stress, and some antibiotic resistance genes being silenced.

SUBMITTER: Yong YK

PROVIDER: S-EPMC8471342 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundDe novo genic and copy number variants are enriched in patients with congenital heart disease, particularly those with extra-cardiac anomalies. The impact of de novo damaging variants on outcomes following cardiac repair is unknown.MethodsWe studied 2517 patients with congenital heart disease who had undergone whole-exome sequencing as part of the CHD GENES study (Congenital Heart Disease Genetic Network).ResultsTwo hundred ninety-four patients (11.7%) had clinically significant de novo variants. Patients with de novo damaging variants were 2.4 times more likely to have extra-cardiac anomalies (P=5.63×10-12). In 1268 patients (50.4%) who had surgical data available and underwent open-heart surgery exclusive of heart transplantation as their first operation, we analyzed transplant-free survival following the first operation. Median follow-up was 2.65 years. De novo variants were associated with worse transplant-free survival (hazard ratio, 3.51; P=5.33×10-04) and longer times to final extubation (hazard ratio, 0.74; P=0.005). As de novo variants had a significant interaction with extra-cardiac anomalies for transplant-free survival (P=0.003), de novo variants conveyed no additional risk for transplant-free survival for patients with these anomalies (adjusted hazard ratio, 1.96; P=0.06). By contrast, de novo variants in patients without extra-cardiac anomalies were associated with worse transplant-free survival during follow-up (hazard ratio, 11.21; P=1.61×10-05) than that of patients with no de novo variants. Using agnostic machine-learning algorithms, we identified de novo copy number variants at 15q25.2 and 15q11.2 as being associated with worse transplant-free survival and 15q25.2, 22q11.21, and 3p25.2 as being associated with prolonged time to final extubation.ConclusionsIn patients with congenital heart disease undergoing open-heart surgery, de novo variants were associated with worse transplant-free survival and longer times on the ventilator. De novo variants were most strongly associated with adverse outcomes among patients without extra-cardiac anomalies, suggesting a benefit for preoperative genetic testing even when genetic abnormalities are not suspected during routine clinical practice. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01196182.

Dataset Information

Characterisation of Bacterial Isolates from Infected Post-Operative Patients in a Malaysian Tertiary Heart Care Centre.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets