CHRONIC DISEASE AND TERMINAL DECLINE IN VERY OLD MEN: THE MANITOBA FOLLOW-UP STUDY
Bibliographic record
Abstract
Abstract The Manitoba Follow-up Study is in its 71st year of continuous operation. Since 1948, 3,983 aircrew recruits to the Royal Canadian Air Force during the Second World War have submitted routine medical examinations and completed questionnaires. On May 1, 2006, 1001 of these men (25%) were alive mean age of 86 years. The effects of 7 chronic diseases (CDs) diagnosed before 2006 were modeled with multinomial logistic regression to predict the pattern of decline of living and dying through an 11 year window to 2017. By 2017, 11% were still alive, 10% died very early in the window, 44% experienced a slow decline of a least three years to death, 17% experienced a step decline to death, and 18% experienced a terminal drop, death within six months of decline in functioning. Only 30% were free of CD in 2006; 36% had 1 CD, and 34% had more than 1 CD. As the number of CDs increased, the probability of remaining alive by 2017 decreased: 18% alive if no CD, 10% if 1 CD, 8% if 2 CDs, and 3% of >2 CDs. The chance of death with a terminal drop decreased: 22% if no CD, 20% if 1 CD, 14% if 2 CD, 11% if >2 CD. Conversely, the percent with a gradual decline to death increased with more CDs. Among old men are already in their 80s, a key determinant of the trajectory to end of life is the number of CDs.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".