Changing Trends in Antimicrobial Susceptibility Patterns of Bloodstream Infection (BSI) in Secondary Care Hospitals of India

Abstract

IntroductionBloodstream infection (BSI) and subsequent sepsis are life-threatening medical conditions. The onset of antimicrobial resistance and subsequent multi-drug resistant organisms (MDRO) significantly increase healthcare-associated expenditure with adverse clinical outcomes. The present study was undertaken to identify the trends of BSI in community settings in secondary care hospitals (smaller private hospitals and district hospitals) in the state of Madhya Pradesh in Central India with the support of the

Emerging trends in antimicrobial resistance in bloodstream infections: multicentric longitudinal study in India (2017–2022)

“…Although we do not have the consumption data, this may indicate a decrease in the use of these antibiotics. Our results are generally consistent with Karuna et al.’s 16 findings on 693 BSI-positive patients from 10 secondary care centres and Mathur et al.’s 25 findings on 2622 HA-BSIs from tertiary care centres on the relative prevalence of pathogens in Bloodstream infections in India.…”

“…The AMR prevalence in our study aligns with smaller, single-centric studies from India, thus affirming the validity of our findings and highlighting the need for ongoing, comprehensive monitoring of AMR at a national level. 15 , 16 , 17 , 24 , 25 Our study estimated national AMR trends using a linear regression model, adjusting for data clustering by tertiary care centres. This model accounted for variations in resistance levels and changes over time within each hospital, adjusting for both the potential heteroskedasticity and auto-correlation within hospital clusters through cluster-robust p values.…”

“… 15 Although multiple studies have noted resistance to critical antibiotics, a gap remains in longitudinal, nationwide data on trends and associations of AMR in BSIs. 16 , 17 This study aims to fill a critical gap in nationwide AMR surveillance by constructing time series and machine learning models for utilising a six-year dataset from the Indian Council of Medical Research AMR Surveillance Network (IAMRSN). We hypothesised that temporal patterns in IAMRSN data can provide data-driven, actionable evidence and early warning signals for proactive surveillance of AMR.…”

Antimicrobial Resistance in Gram Negative Bacilli Isolated From Blood Culture

“…Blood is a clean, sterile fluid. When microorganisms enter the bloodstream, it is a major factor in causing infectious diseases [1].…”