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Record W4400673100 · doi:10.1016/s2665-9913(24)00151-6

Assessing the impact of health-care access on the severity of low back pain by country: a case study within the GBD framework

2024· article· en· W4400673100 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Rheumatology · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of British Columbia
FundersQueensland HealthBill and Melinda Gates Foundation
KeywordsHealth careLow back painMedicineBusinessGerontologyPhysical therapyAlternative medicineEconomic growthEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is key for policy making. Low back pain is the leading cause of disability in terms of years lived with disability (YLDs). Due to sparse data, a current limitation of GDB is that a uniform severity distribution is presumed based on 12-Item Short Form Health Survey scores derived from US Medical Expenditure Panel Surveys (MEPS). We present a novel approach to estimate the effect of exposure to health interventions on the severity of low back pain by country and over time. METHODS: We extracted treatment effects for ten low back pain interventions from the Cochrane Database, combining these with coverage data from the MEPS to estimate the hypothetical severity in the absence of treatment in the USA. Severity across countries was then graded using the Health Access and Quality Index, allowing estimates of averted and avoidable burden under various treatment scenarios. FINDINGS: We included 210 trials from 36 Cochrane systematic reviews in the network analysis. The pooled effect sizes (measured as a standardised mean difference) for the most effective intervention classes were -0·460 (95% uncertainty interval -0·606 to -0·309) for a combination of psychological and physical interventions and -0·366 (-0·525 to -0·207) for surgery. Globally, access to treatment averted an estimated 17·6% (14·8 to 23·8) of the low back pain burden in 2020. If all countries had provided access to treatment at a level estimated for Iceland with the highest Health Access and Quality Index score, an extra 9·1% (6·4 to 11·2) of the burden of low back pain could be avoided. Even with full coverage of optimal treatment, a large proportion (65·9% [56·9 to 70·4]) of the low back pain burden is unavoidable. INTERPRETATION: This methodology fills an important shortcoming in the GBD by accounting for low back pain severity variations over time and between countries. Assumptions of unequal treatment access increased YLD estimates in resource-poor settings, with a modest decrease in countries with higher Health Access and Quality Index scores. Nonetheless, the large proportion of unavoidable burden indicates poor intervention efficacy. This method, applicable to other GBD conditions, provides policy makers with insights into health gains from improved treatment and underscores the importance of investing in research for new interventions. FUNDING: Bill and Melinda Gates Foundation and Queensland Health.

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.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.412
Teacher spread0.376 · 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