Joinpoint Regression Analysis of Trends in Multiple Sclerosis Incidence in Kuwait: 1980–2019
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system with unknown precise etiology. Temporally, a tendency for increasing MS incidence has been recorded worldwide. This cross-sectional cohort study sought to quantify trends in the age-standardized incidence rates (ASIRs) (per million person-years) of MS in Kuwait from 1980 to 2019, overall and by subcohorts defined by age at MS onset, sex, and nationality. METHODS: MS incidence data from 1980 to 2019 were obtained from the Kuwait National MS Registry (KNMSR). Using midyear relevant Kuwait population as denominator and the World Standard Population as a reference, MS ASIRs overall and by subcohorts defined by age at onset (0-19, 20-39, and 40+ years), sex (male and female), and nationality (Kuwaiti and non-Kuwaiti) were computed. Joinpoint regression analysis was conducted to estimate average annual percent change (AAPC) and its 95% confidence interval (CI) overall and by subcohorts. RESULTS: During 1980-2019, a total of 1,764 MS incident cases of 95.6 million person-years at-risk were diagnosed and registered in KNMSR. The overall MS ASIR (per million person-years) during the study period was 34.1 (95% CI: 16.1, 52.1). Between 1980 and 2010, in the total cohort, ASIRs of MS significantly increased by 13% (AAPC = 13.0; 95% CI: 10.8, 15.3; p < 0.001), followed by statistically nonsignificant declining trend during the ensuing period (AAPC = -3.8; 95% CI: -14.8, 8.8; p = 0.522). Joinpoint regression analysis revealed that 2 subcohorts of Kuwaiti females each with one joinpoint had significant increasing trends in MS ASIRs (0- to 19-year-old Kuwaiti females, AAPC: 1980-2009, 81.0; 95% CI: 58.2, 107.0; p = 0.001; 20- to 39-year-old Kuwaiti females, AAPC: 1980-1999, 131.7; 95% CI: 26.9, 322.8; p = 0.021). Additionally, of remaining 10, 6 subcohorts had significantly (p < 0.05) increasing trends in MS ASIRs from 1980 to 2019. CONCLUSIONS: From 1980 to 2010, Kuwait has an overall significantly increasing trend in MS ASIRs followed by a nonsignificant declining drift in the ensuing period. The increasing trend in MS risk appeared to be driven by increased risk among Kuwaiti females younger than 40 years. The underlying factors modulating MS risk in Kuwait need further studies.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".