Global, regional, and national burden of spinal cord injury, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Bibliographic record
Abstract
BACKGROUND: Spinal cord injury (SCI) is a major cause of health loss due to premature mortality and long-term disability. We aimed to report on the global, regional, and national incidence, prevalence, and years of life lived with disability (YLDs) for SCI from 1990 to 2019, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. METHODS: Using GBD 2019 data pooled in DisMod-MR 2.1, a Bayesian meta-regression tool, we systematically derived numbers and age-standardised rate changes with 95% uncertainty intervals (95% UIs) for the incidence, prevalence, and YLDs for SCI from 1990 to 2019 for the whole world, 21 GBD regions, and 204 countries and territories. We report trends based on age, sex, year, cause of injury, and level of injury. FINDINGS: Globally, 20·6 million (95% UI 18·9 to 23·6) individuals were living with SCI in 2019. The incidence of SCI was 0·9 million (0·7 to 1·2) cases with an estimated 6·2 million (4·5 to 8·2) YLDs. SCI rates increased substantially from 1990 to 2019 for global prevalence (81·5%, 74·2 to 87·1), incidence (52·7%, 30·3 to 69·8), and YLDs (65·4%, 56·3 to 76·0). However, global age-standardised rates per 100 000 population showed small changes in prevalence (5·8%, 2·6 to 9·5), incidence (-6·1%, -17·2 to 1·5), and YLDs (-1·5%, -5·5 to 3·2). Data for 2019 shows that the incidence of SCI increases sharply until age 15-19 years, where it remains reasonably constant until 85 years of age and older. By contrast, prevalence and YLDs showed similar patterns to each other, with one peak at around age 45-54 years. The incidence, prevalence, and YLDs of SCI have consistently been higher in men than in women globally, with a slight and steady increase for both men and women from 1990 to 2019. Between 1990 and 2019, SCI at neck level was more common than SCI below neck level in terms of incidence (492 thousand [354 to 675] vs 417 thousand [290 to 585]), prevalence (10·8 million [9·5 to 13·9] vs 9·7 million [9·2 to 10·4]), and YLDs (4·2 million [3·0 to 5·8] vs 1·9 million [1·3 to 2·5]). Falls (477 thousand [327 to 683] cases) and road injuries (230 thousand [122 to 389] cases) were the two leading causes of SCI globally in 2019. INTERPRETATION: Although age-standardised rates of incidence, prevalence, and YLDs for SCI changed only slightly, absolute counts increased substantially from 1990 to 2019. Geographical heterogeneity in demographic, spatial, and temporal patterns of SCI, at both the national and regional levels, should be considered by policy makers aiming to reduce the burden of SCI. FUNDING: Bill & Melinda Gates Foundation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.023 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".