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QST - pro

QST - pro. David Yarnitsky MD Neurology, Rambam Med Ctr Technion Faculty of Medicine Haifa ISRAEL. Why would a clinical neurophysiologist want to conduct a QST test on his patient?. Quantify pathology Support diagnosis Follow-up natural history/treatment Predict future pain

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QST - pro

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  1. QST - pro David Yarnitsky MD Neurology, Rambam Med Ctr Technion Faculty of Medicine Haifa ISRAEL

  2. Why would a clinical neurophysiologist want to conduct a QST test on his patient? • Quantify pathology • Support diagnosis • Follow-up natural history/treatment • Predict future pain • Predict response to therapy

  3. Quantification of pathology

  4. Quantification of pathology

  5. Quantification of pathology

  6. German network data presentation for the individual patient Pfau et al 2012

  7. 2. Supporting diagnosis • 23 C6-7 Radic, 8 NS neck-arm pain, 22 FM & 31 ctrls • Wide QST battery at painful and contralateral sites

  8. Cervical radiculopathyvs.Non specific neck-arm painvs.Fibromyalgia Tampin et al, 2012

  9. Side to side differences

  10. 41 studies included • PPT found most common QST • 7 studies assessed session to session repeatability, found quite good • Estimated that 45 patients are needed to distinct OA and ctrl groups for affected joint PPT

  11. PPT (pressure pain thresholds) in OA • Staד Standardized Mean Differences compared to controls Suokas et al, 2012

  12. Pooled SMD (95% Conf.Int.) Suokas et al, 2012

  13. 3. Follow-up on natural history • Sequential QST on face for 10 wks • 40 patients undergoing oral surgery • No post surgical sensory complaints

  14. Cold Detection Thresholds Said-Yekta et al, 2012

  15. Heat pain thresholds Said-Yekta et al, 2012

  16. The dynamic QST paradigms Temporal summation (TS) & Conditioned pain modulation (CPM, DNIC-like)

  17. Temporal Summation (TS) • Psychophysical response to repetitive stimuli expressed by • increased pain rating along stimulation • Equivalent to ‘wind-up’ in spinal WDR neurons Pain rating Stimulus intensity time

  18. Temporal summation (TS) in TMD Sarlani & Greenspan, 2005

  19. CPM (conditioned pain modulation, the DNIC like phenomenon) CPM = ∆ VAS (VAS Post – VAS Pre) VAS Rt Lt Rt Temp Conditioned - pre Conditioned - post Conditioning

  20. CPM (DNIC) Distribution 122 pre-operative patients Efficient Less efficient

  21. CPM in IBS and TMD Nachmias et al 2009

  22. 4. Prediction of chronic pain:Thoracotomy study • Thoracotomy patients were: • Assessed for pain processing before surgery, at pain-free time: • Pain thresholds • Pain60 • CPM (DNIC), TS • Undergone thoracotomy • Reported acute post-op pain (days 2 and 5) during: • Cough • Arm elevation • Reported chronic post-op pain (6-12 month) • During the week previous to clinic visit

  23. Negative Correlation Between CPM (DNIC) and CPTP

  24. Odds ratio to develop CPTP (Logistic regression)

  25. Rationale for therapeutic study • If pain modulation is involved in the generation of pain, it could also be involved in its alleviation • then • If less efficient CPM leads to development of pain, improving CPM in pain patients could lead to alleviation of pain

  26. 5. Prediction of analgesic efficacy • Pain assessed weekly, along: • 1 baseline week • 1 placebo week • 1 week of 30 mg duloxetine • 4 weeks of 60 mg duloxetine • CPM, TS and other pain psychophysics at beginning and end.

  27. CPM predicts efficacy of duloxetine in painful diabetic neuropathy Less efficient CPM GAIN !!! Efficient CPM NO GAIN!!! Yarnitsky et al, 2012

  28. Predictors of drug efficacy a linear regression model

  29. TS does not predict efficacy of duloxetine in painful diabetic NP

  30. CPM changes in parallel to change in pain

  31. Thus, QST paradigms can: • Quantify sensory changes – positive and negative (vs. EMG) • Discern neuropathic from non neuropathic pain states • Be used for follow-up on changes in sensory state, such as after surgery • Predict post operative pain • Predict efficacy of pain alleviating agents

  32. Yonathan Crispel Alon Sinai Irit Weismann Fogel Michal Granot Iris Amor David Yarnitsky Ruth Moont Yelena Granovsky Erica Dolnikov Liat Honigman Hadas AverbuchNachman And Lab staff: Elliot Sprecher Dorit Pud Beth Murrinson Rony Nir Rina Lev Collaborators: Elon Eisenberg Ruth Defrin Stefan Lautenbacher Eli Eliav Bob Coghill Lars Arendt-Nielsen Oliver Wilder-Smith Rami Burstein

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