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Article ; Online: The prescription drug monitoring program in a multifactorial approach to the opioid crisis: PDMP data, Pennsylvania, 2016-2020.

Adalbert, Jenna R / Syal, Amit / Varshney, Karan / George, Brandon / Hom, Jeffrey / Ilyas, Asif M

2023 Volume 23, Issue 1, Page(s) 364

Abstract: Background: Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription ... ...

Abstract	Background: Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription drug monitoring programs (PDMPs), aim to reduce opioid morbidity and mortality through enhanced tracking and reporting of prescription data. The primary objective of our study was to describe the opioid prescribing trends in the state of Pennsylvania (PA) as recorded by the PA PDMP following legislative changes in reporting guidelines, and discuss the PDMP's role in a multifactorial approach to opioid harm reduction. Methods: State-level opioid prescription data summaries recorded by the PA PDMP for each calendar quarter from August 2016 through March 2020 were collected from the PA Department of Health. Data for oxycodone, hydrocodone, and morphine were analyzed by quarter for total prescription numbers and refills. Prescription lengths, pill quantities, and average morphine milliequivalents (MMEs) were analyzed by quarter for all 14 opioid prescription variants recorded by the PA PDMP. Linear regression was conducted for each group of variables to identify significant differences in prescribing trends. Results: For total prescriptions dispensed, the number of oxycodone, hydrocodone, and morphine prescriptions decreased by 34.4, 44.6, and 22.3% respectively (p < 0.0001). Refills fluctuated less consistently with general peaks in Q3 of 2017 and Q3 of 2018 (p = 0.2878). The rate of prescribing for all opioid prescription lengths decreased, ranging in frequency from 22 to 30 days (47.5% of prescriptions) to 31+ days of opioids (0.8% of prescriptions) (p < 0.0001). Similarly, decreased prescribing was observed for all prescription amounts, ranging in frequency from 22 to 60 pills (36.6% of prescriptions) to 60-90 pills (14.2% of prescriptions) (p < 0.0001). Overall, the average MME per opioid prescription decreased by 18.9%. Conclusions: Per the PA PDMP database, opioid prescribing has decreased significantly in PA from 2016 to 2020. The PDMP database is an important tool for tracking opioid prescribing trends in PA, and PDMPs structured similarly in other states may enhance our ability to understand and influence the trajectory of the U.S. opioid crisis. Further research is needed to determine optimal PDMP policies and practices nationwide.
MeSH term(s)	Humans ; United States ; Prescription Drug Monitoring Programs ; Analgesics, Opioid/therapeutic use ; Pennsylvania/epidemiology ; Hydrocodone/therapeutic use ; Oxycodone/therapeutic use ; Opioid Epidemic ; Practice Patterns, Physicians'
Chemical Substances	Analgesics, Opioid ; Hydrocodone (6YKS4Y3WQ7) ; Oxycodone (CD35PMG570) ; RV 538 (73257-80-4)
Language	English
Publishing date	2023-04-13
Publishing country	England
Document type	Journal Article
ZDB-ID	2050434-2
ISSN	1472-6963 ; 1472-6963
ISSN (online)	1472-6963
ISSN	1472-6963
DOI	10.1186/s12913-023-09272-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The prescription drug monitoring program in a multifactorial approach to the opioid crisis

Jenna R. Adalbert / Amit Syal / Karan Varshney / Brandon George / Jeffrey Hom / Asif M. Ilyas

BMC Health Services Research, Vol 23, Iss 1, Pp 1-

PDMP data, Pennsylvania, 2016–2020

2023 Volume 13

Abstract: Abstract Background Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state ... ...

Abstract	Abstract Background Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription drug monitoring programs (PDMPs), aim to reduce opioid morbidity and mortality through enhanced tracking and reporting of prescription data. The primary objective of our study was to describe the opioid prescribing trends in the state of Pennsylvania (PA) as recorded by the PA PDMP following legislative changes in reporting guidelines, and discuss the PDMP’s role in a multifactorial approach to opioid harm reduction. Methods State-level opioid prescription data summaries recorded by the PA PDMP for each calendar quarter from August 2016 through March 2020 were collected from the PA Department of Health. Data for oxycodone, hydrocodone, and morphine were analyzed by quarter for total prescription numbers and refills. Prescription lengths, pill quantities, and average morphine milliequivalents (MMEs) were analyzed by quarter for all 14 opioid prescription variants recorded by the PA PDMP. Linear regression was conducted for each group of variables to identify significant differences in prescribing trends. Results For total prescriptions dispensed, the number of oxycodone, hydrocodone, and morphine prescriptions decreased by 34.4, 44.6, and 22.3% respectively (p < 0.0001). Refills fluctuated less consistently with general peaks in Q3 of 2017 and Q3 of 2018 (p = 0.2878). The rate of prescribing for all opioid prescription lengths decreased, ranging in frequency from 22 to 30 days (47.5% of prescriptions) to 31+ days of opioids (0.8% of prescriptions) (p < 0.0001). Similarly, decreased prescribing was observed for all prescription amounts, ranging in frequency from 22 to 60 pills (36.6% of prescriptions) to 60–90 pills (14.2% of prescriptions) (p < 0.0001). Overall, the average MME per opioid prescription decreased by 18.9%. Conclusions Per the PA PDMP ...
Keywords	Opioids ; Opioid epidemic ; Opioid policy ; PDMP ; Prescription opioids ; Public health ; Public aspects of medicine ; RA1-1270
Subject code	333
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Rapid antibiotic susceptibility testing based on bacterial motion patterns with long short-term memory neural networks.

Iriya, Rafael / Jing, Wenwen / Syal, Karan / Mo, Manni / Chen, Chao / Yu, Hui / Haydel, Shelley E / Wang, Shaopeng / Tao, Nongjian

IEEE sensors journal

2020 Volume 20, Issue 9, Page(s) 4940–4950

Abstract: Antibiotic resistance is an increasing public health threat. To combat it, a fast method to determine the antibiotic susceptibility of infecting pathogens is required. Here we present an optical imaging-based method to track the motion of single ... ...

Abstract	Antibiotic resistance is an increasing public health threat. To combat it, a fast method to determine the antibiotic susceptibility of infecting pathogens is required. Here we present an optical imaging-based method to track the motion of single bacterial cells and generate a model to classify active and inactive cells based on the motion patterns of the individual cells. The model includes an image-processing algorithm to segment individual bacterial cells and track the motion of the cells over time, and a deep learning algorithm (Long Short-Term Memory network) to learn and determine if a bacterial cell is active or inactive. By applying the model to human urine specimens spiked with an Escherichia coli lab strain, we show that the method can accurately perform antibiotic susceptibility testing as fast as 30 minutes for five commonly used antibiotics.
Language	English
Publishing date	2020-01-17
Publishing country	United States
Document type	Journal Article
ISSN	1530-437X
ISSN	1530-437X
DOI	10.1109/JSEN.2020.2967058
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Article ; Online: Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

Shen, Simon / Syal, Karan / Tao, Nongjian / Wang, Shaopeng

The Review of scientific instruments

2015 Volume 86, Issue 12, Page(s) 126104

Abstract: We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In ...

Abstract	We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.
MeSH term(s)	Bacterial Adhesion/physiology ; Cell Tracking/methods ; Escherichia coli O157/cytology ; Escherichia coli O157/physiology ; Image Interpretation, Computer-Assisted/methods ; Machine Learning ; Microscopy/methods ; Pattern Recognition, Automated/methods ; Reproducibility of Results ; Sensitivity and Specificity ; Subtraction Technique
Language	English
Publishing date	2015-12
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	209865-9
ISSN	1089-7623 ; 0034-6748
ISSN (online)	1089-7623
ISSN	0034-6748
DOI	10.1063/1.4937479
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Article ; Online: Rapid Antibiotic Susceptibility Testing of Uropathogenic E. coli by Tracking Submicron Scale Motion of Single Bacterial Cells.

Syal, Karan / Shen, Simon / Yang, Yunze / Wang, Shaopeng / Haydel, Shelley E / Tao, Nongjian

ACS sensors

2017 Volume 2, Issue 8, Page(s) 1231–1239

Abstract: To combat antibiotic resistance, a rapid antibiotic susceptibility testing (AST) technology that can identify resistant infections at disease onset is required. Current clinical AST technologies take 1-3 days, which is often too slow for accurate ... ...

Abstract	To combat antibiotic resistance, a rapid antibiotic susceptibility testing (AST) technology that can identify resistant infections at disease onset is required. Current clinical AST technologies take 1-3 days, which is often too slow for accurate treatment. Here we demonstrate a rapid AST method by tracking sub-μm scale bacterial motion with an optical imaging and tracking technique. We apply the method to clinically relevant bacterial pathogens, Escherichia coli O157: H7 and uropathogenic E. coli (UPEC) loosely tethered to a glass surface. By analyzing dose-dependent sub-μm motion changes in a population of bacterial cells, we obtain the minimum bactericidal concentration within 2 h using human urine samples spiked with UPEC. We validate the AST method using the standard culture-based AST methods. In addition to population studies, the method allows single cell analysis, which can identify subpopulations of resistance strains within a sample.
Language	English
Publishing date	2017-08-25
Publishing country	United States
Document type	Journal Article
ISSN	2379-3694
ISSN (online)	2379-3694
DOI	10.1021/acssensors.7b00392
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Article ; Online: Real-time detection of antibiotic activity by measuring nanometer-scale bacterial deformation.

Iriya, Rafael / Syal, Karan / Jing, Wenwen / Mo, Manni / Yu, Hui / Haydel, Shelley E / Wang, Shaopeng / Tao, Nongjian

Journal of biomedical optics

2018 Volume 22, Issue 12, Page(s) 1–9

Abstract: Diagnosing antibiotic-resistant bacteria currently requires sensitive detection of phenotypic changes associated with antibiotic action on bacteria. Here, we present an optical imaging-based approach to quantify bacterial membrane deformation as a ... ...

Abstract	Diagnosing antibiotic-resistant bacteria currently requires sensitive detection of phenotypic changes associated with antibiotic action on bacteria. Here, we present an optical imaging-based approach to quantify bacterial membrane deformation as a phenotypic feature in real-time with a nanometer scale (∼9 nm) detection limit. Using this approach, we found two types of antibiotic-induced membrane deformations in different bacterial strains: polymyxin B induced relatively uniform spatial deformation of Escherichia coli O157:H7 cells leading to change in cellular volume and ampicillin-induced localized spatial deformation leading to the formation of bulges or protrusions on uropathogenic E. coli CFT073 cells. We anticipate that the approach will contribute to understanding of antibiotic phenotypic effects on bacteria with a potential for applications in rapid antibiotic susceptibility testing.
MeSH term(s)	Anti-Bacterial Agents/pharmacology ; Cell Membrane/drug effects ; Computer Systems ; Escherichia coli/drug effects ; Escherichia coli O157/drug effects ; Optical Imaging ; Time Factors
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2018-02-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	1309154-2
ISSN	1560-2281 ; 1083-3668
ISSN (online)	1560-2281
ISSN	1083-3668
DOI	10.1117/1.JBO.22.12.126002
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Article ; Online: Correction to "Phenotypic Antimicrobial Susceptibility Testing with Deep Learning Video Microscope".

Yu, Hui / Jing, Wenwen / Iriya, Rafael / Yang, Yunze / Syal, Karan / Mo, Manni / Grys, Thomas E / Haydel, Shelley E / Wang, Shaopeng / Tao, Nongjian

Analytical chemistry

2018 Volume 90, Issue 12, Page(s) 7784

Language	English
Publishing date	2018-05-30
Publishing country	United States
Document type	Journal Article ; Published Erratum
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.8b02212
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Article: Plasmonic imaging of protein interactions with single bacterial cells

Syal, Karan / Hong-Yuan Chen / Nongjian Tao / Shaopeng Wang / Wei Wang / Xiaonan Shan

Biosensors & bioelectronics. 2015 Jan. 15, v. 63

2015

Abstract: Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial ... ...

Abstract	Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.
Keywords	antibiotic resistance ; antibodies ; bacteria ; biosensors ; Escherichia coli O157 ; image analysis ; immune evasion ; ligands ; pathogenesis ; statistical analysis
Language	English
Dates of publication	2015-0115
Size	p. 131-137.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2014.06.069
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Article ; Online: Plasmonic imaging of protein interactions with single bacterial cells.

Syal, Karan / Wang, Wei / Shan, Xiaonan / Wang, Shaopeng / Chen, Hong-Yuan / Tao, Nongjian

Biosensors & bioelectronics

2015 Volume 63, Page(s) 131–137

Abstract	Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.
MeSH term(s)	Antibodies/chemistry ; Antibodies/immunology ; Biosensing Techniques/methods ; Escherichia coli O157/chemistry ; Escherichia coli O157/pathogenicity ; Escherichia coli Proteins/chemistry ; Escherichia coli Proteins/metabolism ; Kinetics ; Ligands ; Protein Interaction Mapping/methods ; Single-Cell Analysis/methods ; Surface Plasmon Resonance
Chemical Substances	Antibodies ; Escherichia coli Proteins ; Ligands
Language	English
Publishing date	2015-01-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1011023-9
ISSN	1873-4235 ; 0956-5663
ISSN (online)	1873-4235
ISSN	0956-5663
DOI	10.1016/j.bios.2014.06.069
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Article ; Online: Antimicrobial Susceptibility Test with Plasmonic Imaging and Tracking of Single Bacterial Motions on Nanometer Scale.

Syal, Karan / Iriya, Rafael / Yang, Yunze / Yu, Hui / Wang, Shaopeng / Haydel, Shelley E / Chen, Hong-Yuan / Tao, Nongjian

ACS nano

2016 Volume 10, Issue 1, Page(s) 845–852

Abstract: Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Currently, most ASTs performed in clinical microbiology laboratories are based on bacterial ... ...

Abstract	Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Currently, most ASTs performed in clinical microbiology laboratories are based on bacterial culturing, which take days to complete for slowly growing microorganisms. A faster AST will reduce morbidity and mortality rates and help healthcare providers administer narrow spectrum antibiotics at the earliest possible treatment stage. We report the development of a nonculture-based AST using a plasmonic imaging and tracking (PIT) technology. We track the motion of individual bacterial cells tethered to a surface with nanometer (nm) precision and correlate the phenotypic motion with bacterial metabolism and antibiotic action. We show that antibiotic action significantly slows down bacterial motion, which can be quantified for development of a rapid phenotypic-based AST.
MeSH term(s)	Anti-Bacterial Agents/pharmacology ; Cells, Immobilized/drug effects ; Cells, Immobilized/physiology ; Escherichia coli/drug effects ; Escherichia coli/physiology ; Microbial Sensitivity Tests/instrumentation ; Microbial Sensitivity Tests/methods ; Motion ; Optical Imaging/instrumentation ; Optical Imaging/methods ; Surface Plasmon Resonance ; Surface Properties
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2016-01-26
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	1936-086X
ISSN (online)	1936-086X
DOI	10.1021/acsnano.5b05944
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