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Record W6996580031

Second edition of SIMPAR’s “Feed Your Destiny” workshop: the role of lifestyle in improving pain management

2018· review· en· W6996580031 on OpenAlexaboutno aff

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2018
Typereview
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
Fundersnot available
KeywordsMultidisciplinary approachPublic healthPain managementHealth professionalsMultidisciplinary teamHealth care
DOInot available

Abstract

fetched live from OpenAlex

Manuela De Gregori,1–3 Inna Belfer,2,4 Roberto De Giorgio,5 Maurizio Marchesini,2,3,6 Carolina Muscoli,7 Mariangela Rondanelli,2,8 Daniela Martini,9 Pedro Mena,9 Laura Isabel Arranz,2,10 Silvia Lorente-Cebrián,2,11 Simone Perna,8 Anna Villarini,12 Maurizio Salamone,2,13,14 Massimo Allegri,2,15 Michael 
E Schatman2,16,17 1 Pain Therapy Service, Fondazione IRCCS Polclinico San Matteo, Pavia, Italy; 2Study in Multidisciplinary Pain Research Group, Parma, Italy; 3Young Against Pain Group, Parma, Italy; 4Faculty of Dentistry, McGill University, Montreal, QC, Canada; 5Department of Clinical Sciences, Nuovo Arcispedale S. Anna, University of Ferrara, Ferrara, Italy; 6Anesthesia, Intensive Care and Pain Therapy Service, Azienda Ospedaliero, Universitaria of Parma, Parma, Italy; 7Department of Health Sciences, Institute of Research for Food Safety and Health, University “Magna Graecia” of Catanzaro, Parma, Italy; 8Department of Public Health, Section of Human Nutrition and Dietetics, Azienda di Servizi alla Persona di Pavia, University of Pavia, Pavia, Italy; 9Human Nutrition Unit, Department of Food & Drugs, University of Parma, Parma, Italy; 10Department of Nutrition, Food Sciences and Gastronomy, University of Barcelona, Barcelona, Spain; 11Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy, Center for Nutrition Research, University of Navarra, Pamplona, Spain; 12Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; 13Science department, Metagenics Italia srl, Milano, Italy; 14Società internazionale di Neuropsicocardiologia, Trapani, Italy; 15Anesthesia and Intensive Care Service – IRCCS MultiMedica Hospital, Sesto San Giovanni, Milano, Italy; 16Research and Network Development, Boston Pain Care, Waltham, MA, USA; 17Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA Abstract: This review is aimed to summarize the latest data regarding pain and nutrition, which have emerged during the second edition of Feed Your Destiny (FYD). Theme presentations and interactive discussions were held at a workshop on March 30, 2017, in Florence, Italy, during the 9th Annual Meeting of Study in Multidisciplinary Pain Research, where an international faculty, including recognized experts in nutrition and pain, reported the scientific evidence on this topic from various perspectives. Presentations were divided into two sections. In the initial sessions, we analyzed the outcome variables and methods of measurement for health claims pertaining to pain proposed under Regulation EC No 1924/2006 of the European Parliament and of the Council of 20 December 2006 on nutrition and health claims made on foods. Moreover, we evaluated how the Mediterranean diet can have a potential impact on pain, gastrointestinal disorders, obesity, cancer, and aging. Second, we discussed the evidence regarding vitamin D as a nutraceutical that may contribute to pain control, evaluating the interindividual variability of pain nature and nurture, and the role of micro-RNAs (miRNAs), polyunsaturated omega 3 fatty acids, and phenolic compounds, with a final revision of the clinical role of nutrition in tailoring pain therapy. The key take-home message provided by the FYD workshop was that a balanced, personalized nutritional regimen might play a role as a synergic strategy that can improve management of chronic pain through a precision medicine approach. Keywords: chronic pain, multidisciplinary pain management, personalized nutrition, nutritional supplements

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.313
Threshold uncertainty score0.980

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.3130.178

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.316
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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