Characteristics and Incidence of Traumatic Brain Injury in Older Adults Using Home Care in Ontario from 2003–2013
Bibliographic record
Abstract
ObjectivesDescribe the characteristics and determine the annual cumulative incidence of traumatic brain injury (TBI) in older adults receiving home care in Ontario from 2003 to 2013.MethodsA retrospective cohort study of longitudinal data from the Ontario Association of Community Care Access Centers (N = 554,313). TBI, demographic variables, depression, neurological conditions, and recent falls were measured from the Resident Assessment Instrument–Home Care. Comparisons were made between service users with and without TBI using odds ratios. Standardized incidence rates were calculated and the 10-year trend of annual cumulative incidence rates was examined.ResultsCharacteristics associated with TBI: male sex (OR: 1.54), aboriginal origin (OR: 1.98), increasing age (low of OR: 1.22, in 70–74 years; high of OR: 2.31, in 90 years and older; comparison 65–69 years), being widowed (OR: 1.59), having one or more falls (OR: 2.31), the use of antidepressants (OR: 1.49) and the presence of depression (OR: 1.57), dementia (OR: 1.65), hemiplegia (OR: 4.34), multiple sclerosis (OR: 3.19) or parkinsonism (OR: 1.22). TBI incidence was significantly higher than rates previously reported in the literature. There was no change in the overall annual cumulative incidence over the 10-year period (p = .13).ConclusionsCertain demographic characteristics, neurological diseases, antidepressant use, and a recent fall are associated with TBI. Incidence of TBI is higher than previous estimates and the overall incidence is not changing over time. These results can be used to improve care of the elderly and to generate hypotheses for future research regarding TBI in the home care setting.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".