Haemophilia and ageing
Bibliographic record
Abstract
Men with haemophilia have not only the challenges of living with HIV and/or HCV infection and premature arthritis as complications of their disorder, but they also confront the other ails of ageing. These include genitourinary problems such as prostatic hypertrophy, prostatic cancer and renal stone disease, and arterial disease for which haemophilia is not protective. Progressive arthritis and declining fitness may lead to loss of independence which causes great concern. Associated with the physical aspects of ageing, many patients also suffer from psychological symptoms which may be precipitated by changes in work such as early retirement and altered family dynamics. Many older men with haemophilia may never have consulted primary care physicians because of the rarity and complexity of their disorder. Haemophilia centre staff often assume responsibility for the identification and management of all health problems of their patients. Even when other clinicians are involved, patients require their centre's involvement in the investigation and support of many procedures such as coronary artery surgery and urological surgery. This paper addresses falls in the older man with haemophilia, their causes and consequences and cardiovascular problems in particular. Very little literature has been published about these common problems. We need to be aware of the ageing issues in haemophilia and develop 'wellness' programs which are directed to the early identification of disease as well as preventative strategies to reduce the physical and psychological impacts of ageing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".