scholarly journals The Triad of Nerve Root Enhancement, Thickening, and Displacement in Patients with Sciatica and Recurrent Disk Herniation in the Postoperative Lumbar Spine May Prompt Further Surgical Treatment in Patients with Failed-Back Surgical Syndrome

2009 ◽  
Vol 30 (5) ◽  
pp. 1068-1069
Author(s):  
G. Chaljub ◽  
R.D. Sullivan ◽  
J.T. Patterson
Spine ◽  
1983 ◽  
Vol 8 (3) ◽  
pp. 261-265 ◽  
Author(s):  
ANTONIO SAN MARTINO ◽  
FRANCESCO M. DʼANDRIA ◽  
CORRADO SAN MARTINO

2002 ◽  
Vol 7 (4) ◽  
pp. 8-10
Author(s):  
Christopher R. Brigham ◽  
Leon H. Ensalada

Abstract Recurrent radiculopathy is evaluated by a different approach in the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), Fifth Edition, compared to that in the Fourth Edition. The AMA Guides, Fifth Edition, specifies several occasions on which the range-of-motion (ROM), not the Diagnosis-related estimates (DRE) method, is used to rate spinal impairments. For example, the AMA Guides, Fifth Edition, clarifies that ROM is used only for radiculopathy caused by a recurrent injury, including when there is new (recurrent) disk herniation or a recurrent injury in the same spinal region. In the AMA Guides, Fourth Edition, radiculopathy was rated using the Injury Model, which is termed the DRE method in the Fifth Edition. Also, in the Fourth Edition, for the lumbar spine all radiculopathies resulted in the same impairment (10% whole person permanent impairment), based on that edition's philosophy that radiculopathy is not quantifiable and, once present, is permanent. A rating of recurrent radiculopathy suggests the presence of a previous impairment rating and may require apportionment, which is the process of allocating causation among two or more factors that caused or significantly contributed to an injury and resulting impairment. A case example shows the divergent results following evaluation using the Injury Model (Fourth Edition) and the ROM Method (Fifth Edition) and concludes that revisions to the latter for rating permanent impairments of the spine often will lead to different results compared to using the Fourth Edition.


Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 902
Author(s):  
Nils Christian Lehnen ◽  
Robert Haase ◽  
Jennifer Faber ◽  
Theodor Rüber ◽  
Hartmut Vatter ◽  
...  

Our objective was to evaluate the diagnostic performance of a convolutional neural network (CNN) trained on multiple MR imaging features of the lumbar spine, to detect a variety of different degenerative changes of the lumbar spine. One hundred and forty-six consecutive patients underwent routine clinical MRI of the lumbar spine including T2-weighted imaging and were retrospectively analyzed using a CNN for detection and labeling of vertebrae, disc segments, as well as presence of disc herniation, disc bulging, spinal canal stenosis, nerve root compression, and spondylolisthesis. The assessment of a radiologist served as the diagnostic reference standard. We assessed the CNN’s diagnostic accuracy and consistency using confusion matrices and McNemar’s test. In our data, 77 disc herniations (thereof 46 further classified as extrusions), 133 disc bulgings, 35 spinal canal stenoses, 59 nerve root compressions, and 20 segments with spondylolisthesis were present in a total of 888 lumbar spine segments. The CNN yielded a perfect accuracy score for intervertebral disc detection and labeling (100%), and moderate to high diagnostic accuracy for the detection of disc herniations (87%; 95% CI: 0.84, 0.89), extrusions (86%; 95% CI: 0.84, 0.89), bulgings (76%; 95% CI: 0.73, 0.78), spinal canal stenoses (98%; 95% CI: 0.97, 0.99), nerve root compressions (91%; 95% CI: 0.89, 0.92), and spondylolisthesis (87.61%; 95% CI: 85.26, 89.21), respectively. Our data suggest that automatic diagnosis of multiple different degenerative changes of the lumbar spine is feasible using a single comprehensive CNN. The CNN provides high diagnostic accuracy for intervertebral disc labeling and detection of clinically relevant degenerative changes such as spinal canal stenosis and disc extrusion of the lumbar spine.


2021 ◽  
pp. 219256822199112
Author(s):  
Maike H. J. Schepens ◽  
Miranda L. van Hooff ◽  
Judith A. van Erkelens ◽  
Ronald Bartels ◽  
Eric Hoebink ◽  
...  

Study Design: Retrospective cohort study. Objective: There is only limited data on the outcome of primary surgery of lumbar disk herniation (LDH) in Dutch patients. The objective of this study is to describe undesirable outcomes after primary LDH. Methods: The National Claims Database (Vektis) was searched for primary LDH operations performed from July 2015 until June 2016, for reoperations within 18 months, prescription of opioids between 6 to 12 months and nerve root block within 1 year. A combined outcome measure was also made. Group comparisons were analyzed with the Student’s t-test. Results: Primary LDH surgery was performed in 6895 patients in 70 hospitals. Weighted mean of reoperations was 7.3%, nerve root block 6.7% and opioid use 15.6%. In total, 23.0% of patients had one or more undesirable outcomes after surgery. The 95% CI interval exceeded the 50% incidence line for 14 out of 26 hospitals with less than 50 surgical interventions per year. Although the data suggested a volume effect on undesired outcomes, the t-tests between hospitals with volume thresholds of 100, 150 and 200 interventions per year did not support this ( P values 0.078, 0.129, 0.114). Conclusion: This unique nationwide claims-based study provides insight into patient-relevant undesirable outcomes such as reoperation, nerve root block and opioid use after LDH surgery. About a quarter of the patients had a serious complication in the first follow up year that prompted further medical treatment. There is a wide variation in complication rates between hospitals with a trend that supports concentration of LDH care.


2021 ◽  
Vol 28 (6) ◽  
pp. 1167
Author(s):  
Ismail Yuce ◽  
Okan Kahyaoglu ◽  
Muzeyyen Ataseven ◽  
Halit Cavusoglu ◽  
Yunus Aydin

Orthopedics ◽  
2015 ◽  
Vol 38 (9) ◽  
pp. e794-e798 ◽  
Author(s):  
Qing-shan Zhuang ◽  
Deng-xing Lun ◽  
Zhao-wan Xu ◽  
Wei-hua Dai ◽  
Da-yong Liu

Sign in / Sign up

Export Citation Format

Share Document