Impact of relative deprivation and ethnicity on the incidence rate of amyotrophic lateral sclerosis
Bibliographic record
Abstract
Objective: This study assessed a sizable cohort of patients with amyotrophic lateral sclerosis (ALS) in a relatively deprived and ethnically diverse area in the northwest of England. We aimed to evaluate the interaction of relative deprivation and ethnicity with the incidence of ALS. Methods: Six hundred and ninety-three adults from Greater Manchester who were diagnosed with ALS between 1 January 2011 and 31 December 2021 were included in this study. Data were collected from electronic patient records. Relative deprivation was estimated using the Index of Multiple Deprivation 2019 and patients were divided into quartiles of deprivation in England. Ethnicity was sub-grouped into White, Southeast Asian, Black, and Other. Poisson’s regression analysis was used to calculate the incidence rate and its interactions with deprivation and ethnicity. Results: 55.4% of patients were male, 95.4% were White, 57.4% were in the two most deprived quartiles, and 87.2% had died by the end of the observation period. The crude incidence rate was 2.21 cases per 100,000 (95% CI 2.00–2.40) per year. There was no difference in the adjusted incidence rates among the quartiles of deprivation, even when considering ethnicity as a confounding variable. The risk of ALS in the White population was 2.08 (95% CI 1.47–3.04) times greater than that in the non-White population. Conclusion: In our cohort, relative deprivation was not an independent risk factor for ALS. A stronger association between White ethnicity and ALS was noted. The reason for this association remains unclear, highlighting the need for more research in this field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".