Transcript Qst pro

Quantify pathology
2. Support diagnosis
3. Follow-up natural history/treatment
4. Predict future pain
5. Predict response to therapy
1.
1.Quantifying sensory function
Static pain parameters
Non painful modalities
Hypo (-)
Hypo (-)
Painful modalities
Hyper (+)
Thresholds
Quantifying sensory function
Static pain
parameters
Non painful
modalities
Hypo (-)
Hypo (-)
Painful modalities
Hyper
(+)
Non painful
neuropathy
Neuropathic
pain
Non
neuropathic
pain
Quantifying sensory function
Thresholds
Non painful
modalities
Hypo (-)
Hypo (-)
Painful modalities
Hyper
(+)
Non painful
Neuropathy
Neuropathic
pain
Non
neuropathic
pain
Pfau et al 2012
2. Supporting diagnosis
23 C6-7 Radic, 8 NS neck-arm pain, 22 FM
& 31 ctrls
 Wide QST battery at painful and
contralateral sites

Tampin et al, 2012
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

‫ד‬Sta 
Standardized Mean Differences
compared to controls
Suokas et al, 2012
Pooled SMD (95% Conf.Int.)
Suokas et al, 2012
Sequential QST on face for 10 wks
 40 patients undergoing oral surgery
 No post surgical sensory complaints

Said-Yekta et al, 2012
Said-Yekta et al, 2012
Temporal summation (TS)
&
Conditioned pain modulation
(CPM, DNIC-like)
• Psychophysical response to repetitive stimuli expressed by
increased pain rating along stimulation
• Equivalent to ‘wind-up’ in spinal WDR neurons
Stimulus intensity
Pain rating
time
Sarlani & Greenspan, 2005
Temp
VAS
CPM = ∆ VAS
(VAS Post – VAS Pre)
Rt
Rt
Lt
Conditioned - pre
Conditioned - post
Conditioning
40
122 pre-operative patients
30
20
CPM score
10
0
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
-10
-20
-30
-40
-50
number of subjects
-60
Efficient
Less efficient
CPM in IBS and TMD
Nachmias et al 2009

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
Term
95% upper and
lower OR
CPM (DNIC)
Odds Ratio
(OR)
0.50
Baseline test-pain
0.89
0.54-1.47
Acute pain
1.86
1.29-2.98
Pain threshold
0.79
0.75-1.19
Surgery type [no rib #]
0.62
0.28-1.30
Gender [female]
0.62
0.26-1.35
Age
0.99
0.93-1.04
0.28-0.79

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






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.
CPM predicts efficacy of duloxetine
in painful diabetic neuropathy
60
50
40 R² = 0.3956
30
20
10
CPM 0
20%
-10 0%
-20
-30
-40
-50
-60
40%
60%
80%
100%
Drug efficacy
Yarnitsky et al, 2012
Predictors
B
coefficients
Beta
t
P
Pre treatment
depression
1.08
0.27
1.45
0.171
Initial
spontaneous pain
0.29
0.24
1.03
0.321
Foot MDT
5.53
0.16
0.74
0.475
Foot WDT
-2.03
-0.24
-1.27
0.227
Placebo Effect
-0.23
-0.14
-0.63
0.559
Pre treatment
CPM
1.16
0.822
4.20
0.001
1.
2.
3.
4.
5.
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
Yonathan Crispel
And
Lab staff:
Irit Weismann Fogel
Alon Sinai
Michal Granot
Iris Amor
David Yarnitsky
Ruth Moont
Yelena Granovsky
Erica Dolnikov
Liat Honigman Hadas AverbuchNachman
Elliot Sprecher
Dorit Pud
Beth Murrinson
Rony Nir
Rina Lev
Collaborators:
Elon Eisenberg
Ruth Defrin
Stefan
Lautenbacher
Eli Eliav
Bob Coghill
Lars ArendtNielsen
Oliver WilderSmith
Rami Burstein