A novel, objective, quantitative method of evaluation of the back pain component using comparative computerized multi-parametric tactile mapping before/after spinal cord stimulation and database analysis: The “Neuro-Pain’t” software
One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as the...
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| Vydané v: | Neuro-chirurgie Ročník 61; s. S99 - S108 |
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| Hlavní autori: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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France
Elsevier Masson SAS
01.03.2015
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| ISSN: | 0028-3770, 1773-0619, 1773-0619 |
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| Abstract | One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation.
We developed a touch screen interface, in Poitiers University Hospital and N3Lab, called the “Neuro-Pain’T”, to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain’T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called “RFG Index”.
This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices.
The Neuro-Pain’T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques.
Un des challenges majeurs de la neurostimulation concerne actuellement sa capacité à couvrir et à soulager la composante lombaire chez les patients souffrant de lombo-radiculalgies chroniques. En réponse au foisonnement récent des techniques de neurostimulation et des outils disponibles, les implanteurs, les patients et parfois même les industriels de la neurostimulation ont tendance à rester confus lorsqu’ils doivent choisir les outils les plus adaptés aux « bons » patients et aux bonnes indications. Afin d’être capable d’évaluer et de comparer le plus objectivement possible le devenir des patients en fonction du matériel qui leur a été implanté, il apparaît essentiel de promouvoir une approche quantitative et rationnelle d’évaluation de la douleur avant/après implantation.
Nous avons développé au CHU de Poitiers et au sein du laboratoire de neuro-informatique N3Lab, une interface tactile appelée « Neuro-Pain’T » pour : (1) analyser, enregistrer et quantifier des changements de surface et d’intensité douloureuse chez des patients implantés, (2) analyser le lien existant entre la couverture paresthésiante et l’effet antalgique potentiel, mesuré par la réduction de la surface douloureuse et de l’intensité douloureuse rapportée à la surface concernée, et par l’évolution locale des différentes composantes neuropathique/nociceptive, grâce à tel ou tel type de stimulation implantée, (3) tenter de corréler ces paramètres cliniques à des données patient plus globales, par l’intermédiaire d’une base de données en réseau (Neuro-Database), dans le but de fournir une mesure simple mais objective de l’efficacité d’un dispositif de neurostimulation implantée, se résumant à un index appelé « Index RFG ».
Le logiciel Neuro-Pain’T a été utilisé sur plus de 190 patients depuis 2012, ce qui nous a progressivement conduit à identifier 3 paramètres cliniques, définissant la composante clinique de l’index RFG. Celui-ci pourrait non seulement permettre d’évaluer l’efficacité antalgique d’une neurostimulation mais également de comparer les dispositifs entre eux à l’aide de critères standardisés et fiables.
Le logiciel « Neuro-Pain’T » a été créé pour caractériser de manière objective la réduction d’une surface douloureuse chez un individu donné, en termes d’intensité, de surface et de changement possible de répartition/prédominance des composantes nociceptives/neuropathique de la douleur, en réponse à un traitement donné ou une stimulation implantée. C’est parce que la douleur est une sensation physique qui intègre une dimension psychologique, que son évaluation justifie l’utilisation d’échelles multi-dimensionnelles. En revanche, dans le contexte de la neurostimulation implantée et d’études cliniques comparatives réalisées pour tester l’efficacité technique pure d’un dispositif donné, un outil d’évaluation simple, objectif et quantifiable pourrait permettre d’aider les choix des options thérapeutiques de demain, en remplaçant les convictions personnelles de chaque implanteur par un rationnel scientifique plus robuste, reposant sur des bases de données et sur le recours aux techniques d’analyse statistique de type data mining. |
|---|---|
| AbstractList | One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation.
We developed a touch screen interface, in Poitiers University Hospital and N3Lab, called the “Neuro-Pain’T”, to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain’T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called “RFG Index”.
This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices.
The Neuro-Pain’T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques.
Un des challenges majeurs de la neurostimulation concerne actuellement sa capacité à couvrir et à soulager la composante lombaire chez les patients souffrant de lombo-radiculalgies chroniques. En réponse au foisonnement récent des techniques de neurostimulation et des outils disponibles, les implanteurs, les patients et parfois même les industriels de la neurostimulation ont tendance à rester confus lorsqu’ils doivent choisir les outils les plus adaptés aux « bons » patients et aux bonnes indications. Afin d’être capable d’évaluer et de comparer le plus objectivement possible le devenir des patients en fonction du matériel qui leur a été implanté, il apparaît essentiel de promouvoir une approche quantitative et rationnelle d’évaluation de la douleur avant/après implantation.
Nous avons développé au CHU de Poitiers et au sein du laboratoire de neuro-informatique N3Lab, une interface tactile appelée « Neuro-Pain’T » pour : (1) analyser, enregistrer et quantifier des changements de surface et d’intensité douloureuse chez des patients implantés, (2) analyser le lien existant entre la couverture paresthésiante et l’effet antalgique potentiel, mesuré par la réduction de la surface douloureuse et de l’intensité douloureuse rapportée à la surface concernée, et par l’évolution locale des différentes composantes neuropathique/nociceptive, grâce à tel ou tel type de stimulation implantée, (3) tenter de corréler ces paramètres cliniques à des données patient plus globales, par l’intermédiaire d’une base de données en réseau (Neuro-Database), dans le but de fournir une mesure simple mais objective de l’efficacité d’un dispositif de neurostimulation implantée, se résumant à un index appelé « Index RFG ».
Le logiciel Neuro-Pain’T a été utilisé sur plus de 190 patients depuis 2012, ce qui nous a progressivement conduit à identifier 3 paramètres cliniques, définissant la composante clinique de l’index RFG. Celui-ci pourrait non seulement permettre d’évaluer l’efficacité antalgique d’une neurostimulation mais également de comparer les dispositifs entre eux à l’aide de critères standardisés et fiables.
Le logiciel « Neuro-Pain’T » a été créé pour caractériser de manière objective la réduction d’une surface douloureuse chez un individu donné, en termes d’intensité, de surface et de changement possible de répartition/prédominance des composantes nociceptives/neuropathique de la douleur, en réponse à un traitement donné ou une stimulation implantée. C’est parce que la douleur est une sensation physique qui intègre une dimension psychologique, que son évaluation justifie l’utilisation d’échelles multi-dimensionnelles. En revanche, dans le contexte de la neurostimulation implantée et d’études cliniques comparatives réalisées pour tester l’efficacité technique pure d’un dispositif donné, un outil d’évaluation simple, objectif et quantifiable pourrait permettre d’aider les choix des options thérapeutiques de demain, en remplaçant les convictions personnelles de chaque implanteur par un rationnel scientifique plus robuste, reposant sur des bases de données et sur le recours aux techniques d’analyse statistique de type data mining. One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation. We developed a touch screen interface, in Poitiers University Hospital and N(3)Lab, called the "Neuro-Pain'T", to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain'T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called "RFG Index". This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices. The Neuro-Pain'T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques. One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation.INTRODUCTIONOne of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation.We developed a touch screen interface, in Poitiers University Hospital and N(3)Lab, called the "Neuro-Pain'T", to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain'T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called "RFG Index".OBJECTIVES, MATERIAL AND METHODSWe developed a touch screen interface, in Poitiers University Hospital and N(3)Lab, called the "Neuro-Pain'T", to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain'T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called "RFG Index".This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices.RESULTS AND DISCUSSIONThis software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices.The Neuro-Pain'T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques.CONCLUSIONThe Neuro-Pain'T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques. Abstract Introduction One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain. Facing a tremendous expansion of neurostimulation techniques and available devices, implanters and patients can still remain confused as they need to select the right tool for the right indication. To be able to evaluate and compare objectively patient outcomes, depending on therapeutical strategies, it appears essential to develop a rational and quantitative approach to pain assessment for those who undergo neurostimulation implantation. Objectives, material and methods We developed a touch screen interface, in Poitiers University Hospital and N3 Lab, called the “Neuro-Pain’T”, to detect, record and quantify the painful area surface and intensity changes in an implanted patient within time. The second aim of this software is to analyse the link between a paraesthesia coverage generated by a type of neurostimulation and a potential analgesic effect, measured by pain surface reduction, pain intensity reduction within the painful surface and local change in pain characteristics distribution. The third aim of Neuro-Pain’T is to correlate these clinical parameters to global patient data and functional outcome analysis, via a network database (Neuro-Database), to be able to provide a concise but objective approach of the neurostimulation efficacy, summarized by an index called “RFG Index”. Results and discussion This software has been used in more than 190 patients since 2012, leading us to define three clinical parameters grouped as a clinical component of the RFG Index, which might be helpful to assess neurostimulation efficacy and compare implanted devices. Conclusion The Neuro-Pain’T is an original software designed to objectively and quantitatively characterize reduction of a painful area in a given individual, in terms of intensity, surface and pain typology, in response to a treatment strategy or implantation of an analgesic device. Because pain is a physical sensation, which integrates a psychological dimension, its assessment justifies the use of multidimensional and global evaluation scales. However, in the context of neurostimulation and comparative clinical trials designed to test the technical efficacy of a given device, a simple, objective and quantitative evaluation tool could help to guide tomorrow's treatment options by transforming personal convictions into a more robust scientific rationale based on data collection and data mining techniques. |
| Author | Rigoard, P. Lorgeoux, B. Guetarni, F. Roulaud, M. Nivole, K. Bataille, B. Blouin, P. Monlezun, O. |
| Author_xml | – sequence: 1 givenname: P. surname: Rigoard fullname: Rigoard, P. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 2 givenname: K. surname: Nivole fullname: Nivole, K. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 3 givenname: P. surname: Blouin fullname: Blouin, P. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 4 givenname: O. surname: Monlezun fullname: Monlezun, O. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 5 givenname: M. surname: Roulaud fullname: Roulaud, M. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 6 givenname: B. surname: Lorgeoux fullname: Lorgeoux, B. organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France – sequence: 7 givenname: B. surname: Bataille fullname: Bataille, B. organization: Department of Neurosurgery, Poitiers University Hospital, 86000 Poitiers, France – sequence: 8 givenname: F. surname: Guetarni fullname: Guetarni, F. email: f.guetarni@chu-poitiers.fr organization: N3Lab (Neuromodulation & Neural Networks), Poitiers University Hospital, 86000 Poitiers, France |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25484344$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1177/230949900901700214 10.1016/j.pain.2010.11.027 10.1111/papr.12095 10.1016/j.ncl.2007.01.004 10.1136/jech.46.3.227 10.1186/1471-2474-7-65 10.1016/j.spinee.2010.02.002 10.1016/j.neuchi.2014.11.001 10.1227/NEU.0b013e318236a57c |
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| Keywords | Pain mapping Surface coverage Stimulation médullaire épidurale Spinal cord stimulation Mesure Spécificité Data mining Back Pain Surface de couverture Lombo-radiculalgies postopératoires Cartographie de la douleur Efficacité Douleur lombaire Efficacy/Specificity |
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| References | Andersen, Christensen, Høy, Helmig, Niedermann, Hansen (bib0050) 2010; 10 Taylor, Desai, Rigoard, Taylor (bib0025) 2014; 14 Blond, Mertens, David, Rigoard (bib0010) 2015 Rigoard, Blond, David, Mertens (bib0015) 2014 Rigoard, Slavin (bib0030) 2014 Bouhassira, Attal (bib0005) 2011; 152 Rigoard, Delmotte, D’Houtaud, Misbert, Diallo, Roy-Moreau (bib0020) 2012; 70 Grunnesjö, Bogefeldt, Blomberg, Delaney, Svärdsudd (bib0035) 2006; 7 Rubin (bib0040) 2007; 25 Pande, Khurjekar, Kanikdaley (bib0055) 2009; 17 Walsh, Cruddas, Coggon (bib0045) 1992; 46 Guetarni, Blouin, Rigoard (bib0060) 2014 Rigoard (10.1016/j.neuchi.2014.09.003_bib0015) 2014 Rigoard (10.1016/j.neuchi.2014.09.003_bib0020) 2012; 70 Andersen (10.1016/j.neuchi.2014.09.003_bib0050) 2010; 10 Blond (10.1016/j.neuchi.2014.09.003_bib0010) 2015 Guetarni (10.1016/j.neuchi.2014.09.003_bib0060) 2014 Grunnesjö (10.1016/j.neuchi.2014.09.003_bib0035) 2006; 7 Rigoard (10.1016/j.neuchi.2014.09.003_bib0030) 2014 Bouhassira (10.1016/j.neuchi.2014.09.003_bib0005) 2011; 152 Taylor (10.1016/j.neuchi.2014.09.003_bib0025) 2014; 14 Rubin (10.1016/j.neuchi.2014.09.003_bib0040) 2007; 25 Walsh (10.1016/j.neuchi.2014.09.003_bib0045) 1992; 46 Pande (10.1016/j.neuchi.2014.09.003_bib0055) 2009; 17 |
| References_xml | – year: 2014 ident: bib0060 article-title: The “Neuro-Mapping Locator” software. A real-time intraoperative objective paresthesia mapping tool to evaluate paraesthesia coverage of the painful zone in patients undergoing spinal cord stimulation lead implantation publication-title: Neurochirurgie – volume: 70 start-page: 584 year: 2012 end-page: 585 ident: bib0020 article-title: Back pain: a real target for spinal cord stimulation? publication-title: Neurosurgery – year: 2014 ident: bib0015 article-title: Pathophysiological characterisation of back pain generators in failed back surgery syndrome (Part B) publication-title: Neurochirurgie – volume: 10 start-page: 372 year: 2010 end-page: 379 ident: bib0050 article-title: The predictive value of pain drawings in lumbar spinal fusion surgery publication-title: Spine – volume: 25 start-page: 353 year: 2007 end-page: 371 ident: bib0040 article-title: Epidemiology and risk factors for spine pain publication-title: Neurol Clin – volume: 17 start-page: 190 year: 2009 end-page: 193 ident: bib0055 article-title: Correlation of low back pain to a high-intensity zone of the lumbar disc in Indian patients publication-title: J Orthop Surg – volume: 7 start-page: 65 year: 2006 ident: bib0035 article-title: The course of pain drawings during a 10-week treatment period in patients with acute and sub-acute low back pain publication-title: BMC Musculoskelet Disord – volume: 46 start-page: 227 year: 1992 end-page: 230 ident: bib0045 article-title: Low back pain in eight areas of Britain publication-title: J Epidemiol Community Health – year: 2014 ident: bib0030 article-title: Neurostimulation options for failed back surgery syndrome. 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A real-time intraoperative objective paresthesia mapping tool to evaluate paraesthesia coverage of the painful zone in patients undergoing spinal cord stimulation lead implantation publication-title: Neurochirurgie – year: 2015 ident: 10.1016/j.neuchi.2014.09.003_bib0010 article-title: From “mechanical” to “neuropathic” back pain in FBSS patients. Factors leading to the chronification of pain. (PartC) publication-title: Neurochirurgie doi: 10.1016/j.neuchi.2014.11.001 – year: 2014 ident: 10.1016/j.neuchi.2014.09.003_bib0015 article-title: Pathophysiological characterisation of back pain generators in failed back surgery syndrome (Part B) publication-title: Neurochirurgie – volume: 70 start-page: 584 issue: 3 year: 2012 ident: 10.1016/j.neuchi.2014.09.003_bib0020 article-title: Back pain: a real target for spinal cord stimulation? publication-title: Neurosurgery doi: 10.1227/NEU.0b013e318236a57c – year: 2014 ident: 10.1016/j.neuchi.2014.09.003_bib0030 article-title: Neurostimulation options for failed back surgery syndrome. The need for rational and objective measurements. Proposal of an international clinical network using an integrated database and health economic analysis: the PROBACK network publication-title: Neurochirurgie |
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| Snippet | One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain.... Abstract Introduction One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory... |
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| SubjectTerms | Analgesia Back Pain Cartographie de la douleur Data mining Databases, Factual Douleur lombaire Efficacité Efficacy/Specificity Humans Lombo-radiculalgies postopératoires Low Back Pain - therapy Mesure Neural Pathways - anatomy & histology Neurosurgery Pain Management - methods Pain mapping Pain Measurement - methods Paresthesia - diagnosis Peripheral Nervous System Diseases - diagnosis Peripheral Nervous System Diseases - therapy Reproducibility of Results Software Spinal cord stimulation Spinal Cord Stimulation - methods Spécificité Stimulation médullaire épidurale Surface coverage Surface de couverture Surgery Treatment Outcome User-Computer Interface |
| Title | A novel, objective, quantitative method of evaluation of the back pain component using comparative computerized multi-parametric tactile mapping before/after spinal cord stimulation and database analysis: The “Neuro-Pain’t” software |
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