Related Experiment Videos
Clinical index to predict bacteraemia caused by staphylococci
L Leibovici1, W R Gransden, S J Eykyn
1Department of Medicine B, Beilinson Medical Centre, Petah Tiqva, Israel.
Journal of Internal Medicine
|July 1, 1993
Summary
This study identified key risk factors for Staphylococcus aureus and coagulase-negative staphylococci bloodstream infections. These findings help define patient groups requiring prompt empiric anti-staphylococcal antibiotic treatment.
Area of Science:
- Infectious Diseases
- Clinical Microbiology
- Epidemiology
Background:
- Bacteraemia caused by Staphylococcus aureus and coagulase-negative staphylococci poses a significant clinical challenge.
- Identifying patients at high risk is crucial for timely and effective treatment.
Purpose of the Study:
- To define risk factors associated with Staphylococcus aureus (S. aureus) and coagulase-negative staphylococci (CoNS) bacteraemia.
- To develop models for identifying patients who would benefit from empiric anti-staphylococcal antibiotic therapy.
Main Methods:
- Observational, prospective study for derivation set (n=1410) and retrospective analysis for validation set (n=1040).
- Logistic regression models were used to identify risk factors and stratify patients.
- Data collected from two university hospitals in Israel and the UK.
Main Results:
- For S. aureus bacteraemia, risk factors included infection focus, haemodialysis, intravenous drug abuse, and orthopaedic ward acquisition.
- For CoNS bacteraemia, risk factors included central/peripheral intravenous catheter, preterm neonate, low temperature, and low white blood cell count.
- Models effectively stratified patients into low, intermediate, and high-risk groups for both types of staphylococcal bacteraemia (P < 0.0001).
Conclusions:
- The study successfully defined distinct risk factor profiles for S. aureus and CoNS bacteraemia.
- Empiric anti-staphylococcal antibiotic treatment is recommended for patients identified in high-risk groups.
- These findings can guide clinical decision-making for empiric antibiotic selection in suspected staphylococcal bloodstream infections.