Characteristics of Centenarians in the Irish Hip Fracture Database.
Bibliographic record
Abstract
Aim Hip fractures are common amongst older people and result in significant morbidity and mortality. The Irish Hip Fracture Database (IHFD) collects data, from the 16 trauma orthopaedic units in Ireland, on patients aged 60 years and older who sustain hip fractures. This study aims to describe the characteristics of those patients aged 100 years and older in this database. Methods A retrospective analysis of the IHFD from 2012 to 2017. Characteristics of those patients aged 100 years and over were collected and analysed. Results 57 patients were identified for inclusion, 52 (91%) of which were women. Mean age was 101, while mean length of stay was 22.6 days. 51 (89%) fractures were due to low velocity trauma, consistent with likely high rates of osteoporosis in this group. The great majority underwent operative intervention. 50 (88%) were discharged alive. Fracture type varied widely. Only 24 (42%) patients were documented to have been seen by a geriatrician during admission. There were low reported rates of co-morbid medical conditions, likely due to lack of recorded data, rather than true low rates of co-morbidities in this group. Discussion This study provides insight into this distinct group of people, with important implications for future healthcare planning and budgeting.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".