Identification of Inducible Clindamycin Resistance in Staphylococcus aureus using Automated Vitek-2 Compact System and D test

Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most common pathogen causing serious and life-threatening clinical infections. Detecting inducible resistance to clindamycin (ICR) in S. aureus is challenging with routine testing methods, potentially leading to treatment failure. Hence, use of both automated systems like VITEK-2 and conventional methods for detecting ICR in routine microbiology laboratories will be helpful in accurate diagnosis. Aim and Objectives: To identify S. aureus in clinical samples and assess the reliability of VITEK-2 for detecting inducible clindamycin resistance as compared to routine D-test. Materials and methods: A total of 80 isolates of S. aureus were identified from clinical samples by routine conventional microbiological methods and antibiotic susceptibility testing was performed using both automated VITEK-2 and conventional technique. Results: The sensitivity of the Vitek-2 test for detecting ICR was 91.18% and specificity was 100% as compared to D-test. The PPV and NPV were 100% and 94.23% respectively. However, 3 isolates which showed ICR by D-test could not be detected in VITEK-2 system. Conclusion: Use of both automated systems and routine conventional techniques together in detecting ICR in Staphylococcus aureus will accurately give the diagnosis and accelerate the treatment. Keywords: VITEK-2, D-test, Resistance, Staphylococcus aureus, Inducible clindamycin resistance (ICR)

Authors

Publication Details

Journal
Journal of Medical Sciences and Health
Published
2024-08-15
DOI
https://doi.org/10.46347/jmsh.v10.i2.24.26
Citations
1
Primary Topic
Antimicrobial Resistance in Staphylococcus
Type
article
Field-Weighted Citation Impact
0.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of Inducible Clindamycin Resistance in Staphylococcus aureus using Automated Vitek-2 Compact System and D test

Rupali Satyen Mantri, Nazneen I Malak, Sharmila Raut, UA Premjith Lal et al.
1 citations
Journal of Medical Sciences and Health
Antimicrobial Resistance in Staphylococcus
0.39
article

Identification of Inducible Clindamycin Resistance in Staphylococcus aureus using Automated Vitek-2 Compact System and D test

Rupali Satyen Mantri, Nazneen I Malak, Sharmila Raut, UA Premjith Lal, Nitin Ambhore, Poojashri Sharma
article en
1 citations

Abstract

Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most common pathogen causing serious and life-threatening clinical infections. Detecting inducible resistance to clindamycin (ICR) in S. aureus is challenging with routine testing methods, potentially leading to treatment failure. Hence, use of both automated systems like VITEK-2 and conventional methods for detecting ICR in routine microbiology laboratories will be helpful in accurate diagnosis. Aim and Objectives: To identify S. aureus in clinical samples and assess the reliability of VITEK-2 for detecting inducible clindamycin resistance as compared to routine D-test. Materials and methods: A total of 80 isolates of S. aureus were identified from clinical samples by routine conventional microbiological methods and antibiotic susceptibility testing was performed using both automated VITEK-2 and conventional technique. Results: The sensitivity of the Vitek-2 test for detecting ICR was 91.18% and specificity was 100% as compared to D-test. The PPV and NPV were 100% and 94.23% respectively. However, 3 isolates which showed ICR by D-test could not be detected in VITEK-2 system. Conclusion: Use of both automated systems and routine conventional techniques together in detecting ICR in Staphylococcus aureus will accurately give the diagnosis and accelerate the treatment. Keywords: VITEK-2, D-test, Resistance, Staphylococcus aureus, Inducible clindamycin resistance (ICR)

Journal of Medical Sciences and HealthVol. 10(2)
Openalex Percentile: Top 36%
Antimicrobial Resistance in Staphylococcus
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.