The need for FASTER CARE in the diagnosis of illness in people with intellectual disabilities
Bibliographic record
Abstract
The Confidential Inquiry into premature deaths of people with learning disabilities reported the median age at death for the 247 people with intellectual disabilities (ID) in the study to be on average 16 years sooner than in the general population of England and Wales. Almost one-quarter (22%) were under the age of 50 years when they died, compared with just 9% in the general population. A comparator group of people without ID, who died at a similar age and from similar causes, experienced significantly fewer problems in all aspects of care provision, coordination, and documentation. One of the contributory factors highlighted in the report was the delay in the care pathways of people with ID who had died, in particular delayed diagnosis. Of the 171 people with ID who had been identified as being unwell, by themselves or their carers, and who had responded promptly in reporting this to a doctor, almost one-quarter (23%) had one or more problems with their illness being diagnosed. This article describes what positive practice would look like in diagnosing illness in people with ID and how can we overcome some of the problems of diagnosing illness in people with ID.
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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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
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".