Public Health Efforts Can Impact Adoption of Current Susceptibility Breakpoints, but Closer Attention from Regulatory Bodies Is Needed.

Microbiological testing, including interpretation of antimicrobial susceptibility testing results using current breakpoints, is crucial for clinical care and infection control. Continued use of obsolete Enterobacteriaceae carbapenem breakpoints is common in clinical laboratories. The purposes of this study were (i) to determine why laboratories failed to update breakpoints and (ii) to provide support for breakpoint updates. The Los Angeles County Department of Public Health conducted a 1-year outreach program for 41 hospitals in Los Angeles County that had reported, in a prior survey of California laboratories, using obsolete Enterobacteriaceae carbapenem breakpoints. In-person interviews with hospital stakeholders and customized expert guidance and resources were provided to aid laboratories in updating breakpoints, including support from technical representatives from antimicrobial susceptibility testing device manufacturers. Forty-one hospitals were targeted, 7 of which had updated breakpoints since the prior survey. Of the 34 remaining hospitals, 27 (79%) assumed that their instruments applied current breakpoints, 17 (50%) were uncertain how to change breakpoints, and 10 (29%) lacked resources to perform a validation study for off-label use of the breakpoints on their systems. Only 7 hospitals (21%) were familiar with the FDA/CDC Antibiotic Resistance Isolate Bank. All hospitals launched a breakpoint update process; 16 (47%) successfully updated breakpoints, 12 (35%) received isolates from the CDC in order to validate breakpoints on their systems, and 6 (18%) were planning to update within 1 year. The public health intervention was moderately successful in identifying and overcoming barriers to updating Enterobacteriaceae carbapenem breakpoints in Los Angeles hospitals. However, the majority of targeted hospitals continued to use obsolete breakpoints despite 1 year of effort. These findings have important implications for the quality of patient care and patient safety. Other public health jurisdictions may want to utilize similar resources to bridge the patient safety gap, while manufacturers, the FDA, and others determine how best to address this growing public health issue.

A hybrid classifier for characterizing motor unit action potentials in diagnosing neuromuscular disorders.

BACKGROUND: The time and frequency features of motor unit action potentials (MUAPs) extracted from electromyographic (EMG) signal provide discriminative information for diagnosis and treatment of neuromuscular disorders. However, the results of conventional automatic diagnosis methods using MUAP features is not convincing yet. OBJECTIVE: The main goal in designing a MUAP characterization system is obtaining high classification accuracy to be used in clinical decision system. For this aim, in this study, a robust classifier is proposed to improve MUAP classification performance in estimating the class label (myopathic, neuropathic and normal) of a given MUAP. METHOD: The proposed scheme employs both time and time-frequency features of a MUAP along with an ensemble of support vector machines (SVMs) classifiers in hybrid serial/parallel architecture. Time domain features includes phase, turn, peak to peak amplitude, area, and duration of the MUAP. Time-frequency features are discrete wavelet transform coefficients of the MUAP. RESULTS: Evaluation results of the developed system using EMG signals of 23 subjects (7 with myopathic, 8 with neuropathic and 8 with no diseases)  showed that the system estimated the class label of MUAPs extracted from these signals with average of accuracy of 91% which is at least 5% higher than the accuracy of two previously presented methods. CONCLUSION: Using different optimized subsets of features along with the presented hybrid classifier results in a classification accuracy that is encouraging to be used in clinical applications for MUAP characterization.