Blog | Friday, April 4, 2014

What we talk about when we talk about MDR-GNR

I titled a talk at SHEA 2014 “Lab Identification and Surveillance for Multidrug-Resistant Organisms” (that title is a real barn-burner, right?). I dashed off material on methicillan-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus pretty quickly, but got bogged down fast when I hit the category of “multidrug-resistant Gram-negative rods (MDR-GNR)”. Why? Two major reasons:
1. MDR-GNRs encompass a vast array of different species, each with its own bag of tricks, and 2. Most labs are underprepared to accurately detect and characterize the most fearsome of the MDR-GNRs (e.g. carbapenemase-producing Enterobacteriaceae [CRE]).

Therefore, it is a major challenge to even define what we are talking about when we talk about MDR-GNRs.

An article in a special issue of Infection Control and Hospital Epidemiology drives this point home nicely. In a survey of hospitals in the SHEA Research Network, Marci Drees and colleagues tallied 14 unique definitions for MDR-Acinetobacter, 18 for MDR-Pseudomonas, and 22 for MDR-Enterobacteriaceae (that’s a lot of definitions for just 66 responding hospitals!). There was similar variation in what these hospitals did when MDR-GNRs were identified (isolation practices, cohorting, etc.), and in how equipped laboratories were to find the organisms of greatest interest (e.g. CRE).

This isn’t an indictment of the hospitals or their labs, it simply reflects the fact that drug-resistance among Gram-negative organisms is extraordinarily complex, and the molecular methods needed to rapidly characterize the most troublesome organisms are beyond the reach of most clinical labs.

In the absence of affordable commercial methods for detection of common MDR-GNR resistance mechanisms, we desperately need to develop a network of specialized regional referral labs that can quickly characterize pathogens submitted from clinical laboratories. Whole-genome sequencing could be introduced in such labs as a first step to wider adoption and development of automated data interpretation software. Let’s hope that the $30 million CDC budget allocation for responding to antibiotic resistance will move us in that direction.

Daniel J. Diekema, MD, FACP, practices infectious diseases, clinical microbiology, and hospital epidemiology in Iowa City, Iowa, splitting time between seeing patients with infectious diseases, diagnosing infections in the microbiology laboratory, and trying to prevent infections in the hospital. This post originally appeared at the blog Controversies in Hospital Infection Prevention.