Tag Archives: @nyugrossman

Prescription Opioids for Pain Relief in Youth Decreased in Recent Years

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PainRelief.com Interview with:

Madeline H. Renny, MD
Postdoctoral Fellow, Department of Population Health
Clinical Instructor, Department of Emergency Medicine and Pediatrics
New York University Grossman School of Medicine
New York, New York

Dr. Renny

PainRelief.com:  What is the background for this study?

Response: Prescription opioids are involved in over half of opioid overdoses among youth.  Additionally, prescription opioid use is associated with risks of future misuse, adverse events, and unintentional exposures by young children.  While there are several studies on opioid prescribing in adults, few studies have focused on the pediatric and adolescent population.  In the last year, postoperative guidelines for opioid prescribing for children and adolescents were released, but there remain no national guidelines on general opioid prescribing for youth. 

To our knowledge, no prior national studies have examined trends in important opioid prescribing practices, including amount prescribed, duration, high-dosage, and extended-release/long-acting (ER/LA) opioid prescriptions, in this subset of the population; a necessary step in understanding the opioid epidemic and in developing targeted interventions for youth. 

Therefore, we performed a cross-sectional analysis of U.S. opioid prescription data to investigate temporal trends in several key opioid prescribing practices in children, adolescents, and younger adults in the U.S. from 2006-2018.

PainRelief.com: What are the main findings?

Response: We found that opioid dispensing rates declined significantly for children, adolescents, and younger adults since 2013. When examining trends in opioid prescribing practices, there were differences based on age group. For adolescents and young adults, rates of long-duration and high-dosage opioid prescriptions decreased during the study period, whereas there were increases in these rates for younger children.  

PainRelief.com: What should readers take away from your report?

Response: Dispensed opioid prescriptions for youth have significantly decreased in recent years.  These findings are consistent with prior studies in children and adults, suggesting that opioid prescribing practices may be improving. Additionally, the decrease in rates of high-dosage and long-duration prescriptions in adolescents and young adults is encouraging in the context of research showing associations with these prescribing practices and opioid use disorder and overdose. However, opioids remain commonly dispensed to youth and potential high-risk prescribing practices (long-duration, high-dosage, and ER/LA prescriptions) appear to be common, especially in younger children.  

PainRelief.com: What recommendations do you have for future research as a result of this work?

Response: The increase in rates of potential high-risk prescribing practices in young children was an unexpected finding and warrants future study. Due to the limitations of our database (no clinical information, including diagnoses or indications for prescription), we were unable to determine the appropriateness of opioid prescribing practices (e.g., whether a prescription was for a child with cancer or for a child with an acute injury).  Our two sensitivity analyses were performed to try to identify a subset of patients with chronic illness and both showed no differences in trends.  However, it will be important to further investigate these opioid prescribing practices using a database with clinical information to better understand these findings in young children.

Further research investigating specific opioid prescribing practices may inform targeted interventions, including pediatric and adolescent-specific opioid prescribing guidelines, to ensure appropriate opioid prescribing in this population. 

No disclosures

Citation:

Renny MH, Yin HS, Jent V, Hadland SE, Cerdá M. Temporal Trends in Opioid Prescribing Practices in Children, Adolescents, and Younger Adults in the US From 2006 to 2018. JAMA Pediatr. Published online June 28, 2021. doi:10.1001/jamapediatrics.2021.1832

The information on PainRelief.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.

Brain Implant Targets Chronic Pain

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PainRelief.com Interview with:
Jing Wang MD PhD
Department of Anesthesiology, Perioperative Care and Pain
Department of Neuroscience & Physiology
NYU Langone
Neuroscience Institute, New York University School of Medicine
New York, NY

PainRelief.com:  What is the background for this study?  What are the main findings?

Response: The motivation for this study is three fold.

First, there are no objective ways to measure pain in preclinical models that could facilitate study of pain mechanisms and analgesic screening.

Secondly, while pain is assessed by patient report, a lack of alternative pain measures in humans hinders clinical treatment of pain in patients whom we cannot assess pain readily, such as patients who suffer from dementia or very young children.

Thirdly, chronic pain patients often complain of spontaneously occurring pain episodes which are unpredictable, and we currently do have a way to target specific pain episodes, and so we treat pain with scheduled drugs, leading to under- or over-treatment. We designed a prototype closed-loop neural interface, employing computerized brain implants, to address these challenges. We found that this interface quite effectively relieves short-term and chronic pain in rodents. In this study, we designed a computerized brain implant to detect and relieve bursts of pain in real time. We implanted electrodes in a region of the brain called anterior cingulate cortex, an important area for the processing the emotional component of pain. We used these implanted electrodes to measure neural activity in this brain region, and then applied machine learning algorithm to detect a change in neural activity in this region which signals the onset of pain experience. The detected pain signal then triggered stimulation of another brain region, called prefrontal cortex, which is known to suppress pain. In this way, our device automatically detected and treated pain with minimal delay, as shown by a number of pain behavior assays in rats. The device is also the first of its kind to target chronic pain, which often occurs without being prompted by a known trigger.

PainRelief.com: What should readers take away from your report?

Response: Our experiments offer a blueprint for the development of brain implants to treat pain syndromes and other brain-based disorders, such as anxiety, depression, and panic attacks. The advantage of our approach is that it targets symptoms in a time-sensitive manner. Our approach can detect pain as it occurs in real time. In its current form, it already becomes a powerful tool to screen drugs. In our current system, pain detection is coupled with neurostimulation treatment. But it can also be coupled with drug delivery. In this way, our system can be used to screen new analgesic drugs. It can also be used to screen other neurostimulation techniques.

PainRelief.com: What recommendations do you have for future research as a result of this work?

Response: We are already working on modifications of our system to move it closer to translation to the bedside.

First, we would like to improve pain decoding accuracy. We are doing that be recording from multiple brain regions.

Second, the current treatment requires injection of viral vectors and foreign proteins, which are not realistic in human use, and thus we are working to use more clinically feasible approaches to treat pain in our closed-loop device.

Finally, we are working on making the device non-invasive – free of brain implants.

Citation:

Zhang, Q., Hu, S., Talay, R. et al. A prototype closed-loop brain–machine interface for the study and treatment of pain. Nat Biomed Eng (2021). https://doi.org/10.1038/s41551-021-00736-7

The information on PainRelief.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.