Foot drop due to lumbar degenerative conditions: mechanism and prognostic factors in herniated nucleus pulposus and lumbar spinal stenosis

Iizuka, Yoichi; Iizuka, Haku; Tsutsumi, Satoshi; Nakagawa, Yumi; Nakajima, Takashi; Sorimachi, Yasunori; Ara, Tsuyoshi; Nishinome, Masahiro; Seki, Takayuki; Shida, Kosuke; Takagishi, Kenji

doi:10.3171/2008.12.spine08500

Cited by 64 publications

(57 citation statements)

References 13 publications

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“…The former corresponds to pretibialis anterior muscle strength in the current study. Other predictors are age at surgery [6,7,16], herniated soft disc [7,12,13], and involvement of a single level [7]. In the current study, the two main predictors (pretibialis anterior strength and the duration of drop foot before surgery) were confirmed by the Bayesian network models as direct predictors.…”

Section: Discussionsupporting

confidence: 56%

“…Predictors for residual drop foot in previous studies are varied, but the two main predictors have been preoperative motor weakness [1,3,6,12,16,17,21] and the duration of drop foot before surgery [2,3,7,16,17]. The former corresponds to pretibialis anterior muscle strength in the current study.…”

Section: Discussionmentioning

confidence: 67%

“…Prior work using traditional analytic approaches (such as multivariate analyses) have suggested that duration of drop foot before surgery and preoperative motor weakness [1,3,16,17] may be associated with recovery of active dorsiflexion after decompressive lumbar spine surgery; however, this is somewhat controversial, since other studies did not identify one or either of these factors as important in anticipating a patient's neurologic recovery [2,6,7,12,13,21]. We believe that those analytic approaches may not be ideal for this purpose because they are difficult to describe layered correlations among predictors, and we believe that Bayesian network analysis, which is graphic and intuitive to the clinician, may be better suited to the task because this approach readily describes the layered correlation among predictors.…”

Section: Discussionmentioning

confidence: 99%

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Prediction of Postoperative Clinical Recovery of Drop Foot Attributable to Lumbar Degenerative Diseases, via a Bayesian Network

Takenaka

Aono

2017

Clinical Orthopaedics &Amp; Related Research

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Background Drop foot resulting from degenerative lumbar diseases can impair activities of daily living. Therefore, predictors of recovery of this symptom have been investigated using univariate or/and multivariate analyses. However, the conclusions have been somewhat controversial. Bayesian network models, which are graphic and intuitive to the clinician, may facilitate understanding of the prognosis of drop foot resulting from degenerative lumbar diseases. Questions/purposes (1) To show a layered correlation among predictors of recovery from drop foot resulting from degenerative lumbar diseases; and (2) to develop support tools for clinical decisions to treat drop foot resulting from lumbar degenerative diseases.Methods Between 1993 and 2013, we treated 141 patients with decompressive lumbar spine surgery who presented with drop foot attributable to degenerative diseases. Of those, 102 (72%) were included in this retrospective study because they had drop foot of recent development and had no diseases develop that affect evaluation of drop foot after surgery. Specifically, 28 (20%) patients could not be analyzed because their records were not available at a minimum of 2 years followup after surgery and 11 (8%) were lost owing to postoperative conditions that affect the muscle strength evaluation. Eight candidate variables were sex, age, herniated soft disc, duration of the neurologic injury (duration), preoperative tibialis anterior muscle strength (pretibialis anterior), leg pain, cauda equina syndrome, and number of involved levels. Manual muscle testing was used to assess the tibialis anterior muscle strength. Drop foot was defined as a tibialis anterior muscle strength score of less than 3 of 5 (5 = movement against gravity and full resistance, 4 = movement against gravity and moderate resistance, 3 = movement against gravity through full ROM, 3À = movement against gravity through partial ROM, 2 = movement with gravity eliminated through full ROM, 1 = slight contraction but no movement, and 0 = no contraction). The two outcomes of interest were postoperative tibialis anterior muscle strength (posttibialis anterior) of 3 or greater and posttibialis anterior strength of 4 or greater at 2 years after surgery. We developed two separate Bayesian network models with outcomes of interest for posttibialis anterior strength of 3 or greater and posttibialis anterior strength of 4 or greater. The two outcomes correspond to ''good'' and ''excellent'' results based on previous reports, respectively. Direct predictors are defined as variables that have the tail of the arrow connecting the outcome of interest, whereas indirect predictors are defined as variables that have the tail of the arrow Each author certifies that neither he, nor any member of his immediate family, have funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article. All ICMJE Conflict of Interest Forms for ...

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Section: Discussionsupporting

confidence: 56%

Section: Discussionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 99%

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Prediction of Postoperative Clinical Recovery of Drop Foot Attributable to Lumbar Degenerative Diseases, via a Bayesian Network

Takenaka

Aono

2017

Clinical Orthopaedics &Amp; Related Research

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“…On the other hand, Aono et al [11] reported that preoperative strength was a factor that most affected drop foot recovery following surgical intervention for patients with lumbar spinal degeneration. Similarly, Iizuka et al [12] demonstrated a significant association between prognosis and preoperative strength in drop foot patients with lumbar spinal stenosis. We thought that it was disadvantageous for recovery after surgery when the patient exhibited weaker muscle strength because this meant more severe damage to the spinal cord or nerve root.…”

Section: Discussionmentioning

confidence: 85%

Appropriate timing of surgical intervention for the proximal type of cervical spondylotic amyotrophy

Tauchi

Imagama

Inoh

et al. 2014

Eur J Orthop Surg Traumatol

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“…Patients with signs of visceral involvement (e.g., bowel or bladder dysfunction), signs of severe radicular pain, acute motor axonal neuropathy, or chronic one but moderate-severe motor deficit, with spinal instability at dynamic flexedextended lumbar, x-rays were excluded [13][14][15].…”

Section: Methodsmentioning

confidence: 99%

Lumbar Spinal Stenosis Minimally Invasive Treatment with Bilateral Transpedicular Facet Augmentation System

Masala

Tarantino

Nano

et al. 2012

Cardiovasc Intervent Radiol

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Foot drop due to lumbar degenerative conditions: mechanism and prognostic factors in herniated nucleus pulposus and lumbar spinal stenosis

Cited by 64 publications

References 13 publications

Prediction of Postoperative Clinical Recovery of Drop Foot Attributable to Lumbar Degenerative Diseases, via a Bayesian Network

Prediction of Postoperative Clinical Recovery of Drop Foot Attributable to Lumbar Degenerative Diseases, via a Bayesian Network

Appropriate timing of surgical intervention for the proximal type of cervical spondylotic amyotrophy

Lumbar Spinal Stenosis Minimally Invasive Treatment with Bilateral Transpedicular Facet Augmentation System

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