scholarly journals Oral and Topical Treatment of Painful Diabetic Polyneuropathy: Practice Guideline Update Summary

Neurology ◽  
2021 ◽  
Vol 98 (1) ◽  
pp. 31-43
Author(s):  
Raymond Price ◽  
Don Smith ◽  
Gary Franklin ◽  
Gary Gronseth ◽  
Michael Pignone ◽  
...  

ObjectiveTo update the 2011 American Academy of Neurology (AAN) guideline on the treatment of painful diabetic neuropathy (PDN) with a focus on topical and oral medications and medical class effects.MethodsThe authors systematically searched the literature from January 2008 to April 2020 using a structured review process to classify the evidence and develop practice recommendations using the AAN 2017 Clinical Practice Guideline Process Manual.ResultsGabapentinoids (standardized mean difference [SMD] 0.44; 95% confidence interval [CI], 0.21–0.67), serotonin-norepinephrine reuptake inhibitors (SNRIs) (SMD 0.47; 95% CI, 0.34–0.60), sodium channel blockers (SMD 0.56; 95% CI, 0.25–0.87), and SNRI/opioid dual mechanism agents (SMD 0.62; 95% CI, 0.38–0.86) all have comparable effect sizes just above or just below our cutoff for a medium effect size (SMD 0.5). Tricyclic antidepressants (TCAs) (SMD 0.95; 95% CI, 0.15–1.8) have a large effect size, but this result is tempered by a low confidence in the estimate.Recommendations SummaryClinicians should assess patients with diabetes for PDN (Level B) and those with PDN for concurrent mood and sleep disorders (Level B). In patients with PDN, clinicians should offer TCAs, SNRIs, gabapentinoids, and/or sodium channel blockers to reduce pain (Level B) and consider factors other than efficacy (Level B). Clinicians should offer patients a trial of medication from a different effective class when they do not achieve meaningful improvement or experience significant adverse effects with the initial therapeutic class (Level B) and not use opioids for the treatment of PDN (Level B).

Author(s):  
Emanuele Cerulli Irelli ◽  
Alessandra Morano ◽  
Martina Fanella ◽  
Biagio Orlando ◽  
Enrico M Salamone ◽  
...  

Author(s):  
Andrew Pilny ◽  
C. Joseph Huber

Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing to the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one condition each. They were prompted to anonymously provide contacts and populated places visited from the past four days depending on what condition they were given. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely to recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to the development of innovative social network data collection methods for contract tracing survey instruments.


ChemInform ◽  
2010 ◽  
Vol 41 (52) ◽  
pp. no-no
Author(s):  
Sriram Tyagarajan ◽  
et al. et al.

2013 ◽  
Vol 73 ◽  
pp. 48-55 ◽  
Author(s):  
Lihong Diao ◽  
Jennifer L. Hellier ◽  
Jessica Uskert-Newsom ◽  
Philip A. Williams ◽  
Kevin J. Staley ◽  
...  

2021 ◽  
Author(s):  
Xiaochun Han ◽  
Yoni K. Ashar ◽  
Philip Kragel ◽  
Bogdan Petre ◽  
Victoria Schelkun ◽  
...  

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49, average r = 0.20). The NPS showed excellent short-term (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with ≥60 trials required for excellent test-retest reliability. Reliability was comparable in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicates that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports, but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions.


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