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Record W4307994170 · doi:10.1007/s00586-022-07432-3

SPINE20 recommendations 2022: spine care—working together to recover stronger

2022· review· en· W4307994170 on OpenAlexaff
Bambang Darwono, Koji Tamai, Pierre Côté, Sami Aleissa, Agus Hadian Rahim, Paulo Pereira, Hana Alsobayel, Harvinder Singh Chhabra, Giuseppe Costanzo, Manabu Ito, Frank Kandziora, Donna Lahey, Cristiano Magalhães Menezes, Sohail Bajammal, William J. Sullivan, Peter Vajkoczy, Alaa Ahmad, M. Arand, Saiful Asmiragani, Thomas R. Blattert, Jamiu O. Busari, Edward J. Dohring, Bernardo Misaggi, Eric J. Muehlbauer, Raghava D. Mulukutla, Everard Munting, Michael Piccirillo, Carlo Ruosi, Ahmed Alturkistany, Marco Campello, Patrick C. Hsieh, Marco Teli, Jeffrey C. Wang, Margareta Nordin

Bibliographic record

VenueEuropean Spine Journal · 2022
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsMedicineHealth careWorkforceLife expectancyPopulationNursingEconomic growthEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE: Globally, spine disorders are the leading cause of disability, affecting more than half a billion individuals. However, less than 50% of G20 countries specifically identify spine health within their public policy priorities. Therefore, it is crucial to raise awareness among policy makers of the disabling effect of spine disorders and their impact on the economic welfare of G20 nations. In 2019, SPINE20 was established as the leading advocacy group to bring global attention to spine disorders. METHODS: Recommendations were developed through two Delphi methods with international and multi-professional panels. RESULTS: In 2022, seven recommendations were delivered to the leaders of G20 countries, urging them to: Develop action plans to provide universal access to evidence-based spine care that incorporates the needs of minorities and vulnerable populations. Invest in the development of sustainable human resource capacity, through multisectoral and inter-professional competency-based education and training to promote evidence-based approaches to spine care, and to build an appropriate healthcare working environment that optimizes the delivery of safe health services. Develop policies using the best available evidence to properly manage spine disorders and to prolong functional healthy life expectancy in the era of an aging population. Create a competent workforce and improve the healthcare infrastructure/facilities including equipment to provide evidence-based inter-professional rehabilitation services to patients with spinal cord injury throughout their continuum of care. Build collaborative and innovative translational research capacity within national, regional, and global healthcare systems for state-of-the-art and cost-effective spine care across the healthcare continuum ensuring equality, diversity, and inclusion of all stakeholders. Develop international consensus statements on patient outcomes and how they can be used to define and develop pathways for value-based care. Recognize that intervening on determinants of health including physical activity, nutrition, physical and psychosocial workplace environment, and smoking-free lifestyle can reduce the burden of spine disabilities and improve the health status and wellness of the population. At the third SPINE20 summit 2022 which took place in Bali, Indonesia, in August 2022, 17 associations endorsed its recommendations. CONCLUSION: SPINE20 advocacy efforts focus on developing public policy recommendations to improve the health, welfare, and wellness of all who suffer from spinal pain and disability. We propose that focusing on facilitating access to systems that prioritize value-based care delivered by a competent healthcare workforce will reduce disability and improve the productivity of the G20 nations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0300.002

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 head0.168
GPT teacher head0.444
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2022
Admission routes1
Has abstractyes

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