Title: Classifications of Spine Injuries
1Analysis of Learning Curve for Minimally Invasive
Transforaminal Lumbar Interbody Fusion
Byung-Joon Shin, Jae Chul Lee, Hae-Dong
Chang, Su-Jin Yun, Yon-Il Kim
Spine Center Department of Orthopaedic Surgery
Soonchunhyang University Hospital Seoul, Korea
2Introduction
- Minimally Invasive TLIF
- Advantages
- Decreased soft tissue injury
- Unilateral exposure less muscle dissection
- Preservation of contralateral structure
- Decreased operative bleeding
- Disadvantages
- Technically demanding
- Increased operative time
Steep learning curve
Peng et al., Spine, 2009 Scheufler et al.,
Neurosurg, 2007 Schizas, Int Orthop, 2008
3Introduction
- New vs. Gold standard procedure
- False negative result
- Too early assessment
- Indifferent result
- Positive result
When?
New
Old
(Gold standard)
Learning curve for MIS TLIF?
Ramsay CR et al Statistical assessment of the
learning curves of health technologies. Health
Technol Assess 5179, 2001
4Materials
- Prospective analysis of
- The first 41 cases of MIS TLIF procedure
- Degenerative lumbar disease treated by
- Decompression thru tubular retractor
- Obliquely inserted a PEEK cage
- Percutaneous pedicle screw fixation and fusion
- F/U gt minimum 1yr
5Materials
- Patients characteristics
- Average age 57 yrs (36-76)
- Average F/U 21 m
- Etiology
- Spinal stenosis 24 cases
- Spondylolisthsis 12 cases
- HIVD 3 cases
- IDD 1 case
- Seg. Instability 1 case
6Materials
- Procedure (41 patients)
- No. of operated levels
- 1 level TLIF 31 cases
- 1 level TLIF 1 level decomp 8 cases
- 2 level TLIF 2 cases
- Laminectomy
- Unilateral 37 cases
- Bilateral 4 cases
- Contralateral decompression
- 16 cases
7Methods
- Assessing parameters of learning curve
- Length of operative time
- Amount of bleeding
- Intraoperative bleeding
- H-vac drain
- Total perioperative bleeding
- Starting day of ambulation
- Transfusion incidence
- Occurrence of complications
- Clinical outcome
- Oswestry disability index
- Visual analogue scale
- Low back pain
- Radiating pain to legs
Learning curve
8Statistical analysis
- Regression analysis for learning curve
- Bivariate analysis
- Case vs. parameters (operative time, bleeding)
- Logarithmic curve-fit
- Former 20 vs. Latter 21 cases
- Student T-test
- Operative time, Blood loss, Start of ambulation
- Chi-square test
- Transfusion need, Occurrence of complications
- SPSS (ver.13.0)
- plt0.05
9Results
- Operative time (F/U gt 1yr n41)
Min
p0.000
Case
10Results
- Operative time (Whole series 72 cases)
Min
Asymptote
Case
11Results
Mean Op. Time
Case 1-20 249
Case 21-41 198
p0.000
12Results
Mean Op. Time
Case 1-20 250
Case 21-41 198
Case 42-72 185
198
185
P lt 0.05
P gt 0.05
13Results
Amount of Bleeding
ml
p0.005
Case
14Results
Amount of Bleeding
- Postoperative H-vac Drain
ml
p0.547
Case
15Results
Amount of Bleeding
- Perioperative Blood Loss (Intraop Drain)
ml
p0.004
Case
16Results
p0.000
p0.190
17Results
PO Day
X 1
Ambulation
Case 1-20 2.80.6
Case 21-41 2.00.5
X 13
X 2
X 6
X 17
X 2
p0.000
Case 1-20
Case 21-41
18Results
Yes No
Case 1-20 6 14
Case 21-41 0 21
p0.009
19Results
- Occurrence of Complications
Yes
Case 10 Deep infection 24 Bone graft frag.
extrusion from the cage 25 Screw
malposition 41 Minimal dural tear
No
20Results
- Oswestry Disability Index
ODI
PreOp. 24
Final 7
21Results
LBP
PreOp. 5.1
Final 1.7
22Results
- VAS for Radiating Pain to Legs
RP
PreOp. 6.9
Final 0.8
23Results
- Case 1-20 versus Case 21-41
Plt0.05
24Summary and Conclusions
- Learning curve for minimally invasive TLIF was
steep, but acceptable. Asymptote of the curve was
approximately 35-40 cases. - Operative time was significantly decreased with a
surgeons experience.
Mean Op. time
Case 1-20 249 min
Case 21-41 198 min
25Summary and Conclusions
- Amount of bleeding and needs for transfusion
also significantly decreased with a learning
curve. - Minimally invasive TLIF can be an effective
method treating degenerative lumbar diseases,
provided appropriate training is obtained.
Intraop.Bleeding Perioperative B
Case 1-20 506 ml 689 ml
Case 21-41 272 ml 382 ml
26Thank you very much.