The Burden of Hospitalized Hip Fractures: Patterns of Admissions in a Level I Trauma Center Over 20 Years
Bibliographic record
Abstract
BACKGROUND: To describe trends over 20 years in (1) number of admissions for hip fracture, (2) patients' demographics, type of fractures sustained by the patients, and their health status at admission, (3) surgical delays, and (4) acute care outcomes. METHODS: This trend was a study conducted in a Level I trauma center in Quebec, Canada. All patients (n = 3174) aged 65 and older, admitted with a hip fracture between 1985 and 2005 were included. Outcome measures were: number of admissions, age, gender, comorbidities at admission, surgical delays, postsurgical complications, inpatient mortality, discharge destinations. RESULTS: From 1985 to 2005, the number of admissions increased from 56 to 271, age at admission has increased by 2 years both in men and women (p < 0.01), women/men proportion has remained stable (3.2) over time. The adjusted proportions of minor and severe comorbidities at admission increased by 13% and 5% yearly (p < 0.01). Surgical delays decreased from 4.7 days +/- 16.5 days to 0.9 days +/- 1.9 days (p < 0.01). Acute care length of stay has drastically decreased from 37.0 days +/- 70.9 days to 16.7 days +/- 14.2 days (p < 0.01). Although severe postsurgical complications did not increase over time, the proportion of patients suffering from minor postsurgical complications increased by 22%. Inpatient death has decreased by 4% each year. CONCLUSION: The tremendous increase in the volume of older and sicker patients admitted for hip fracture has put an enormous demand on our Level I trauma center. The changes in clinical management implemented to face this challenge have helped improve acute care outcomes.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".