Projected incidence of mechanical ventilation in Ontario to 2026: Preparing for the aging baby boomers*
Bibliographic record
Abstract
OBJECTIVE: The aging baby boomers are expected to have a significant impact on the healthcare system. Mechanical ventilation is an age-dependent, costly, and relatively nondiscretionary medical service that may be particularly affected by the aging population. We forecast the future incidence of mechanical ventilation to the year 2026 to understand the impact of aging baby boomers on critical care resources. DESIGN: Population-based, sex-specific, and age-specific mechanical ventilation incidences for adults for the year 2000 were directly standardized to population projections to estimate the incidence of mechanical ventilation, in 5-yr intervals, from 2006 to 2026. Sensitivity analyses were performed by varying population projections and mechanical ventilation incidence for the elderly. SETTING: Province of Ontario, Canada. PATIENTS: Noncardiac surgery, mechanically ventilated adults. INTERVENTIONS: None. MAIN RESULTS: The projected number of ventilated patients in 2026 was 34,478, representing an 80% increase from 2000. The crude incidence increased 31%, from 222 to 291 per 100,000 adults. The annually compounded projected growth rate during this 26-yr period was 2.3%, similar to the actual growth rate experienced in the 1990s. The projected incidence was relatively insensitive to changes in assumptions, with estimates for 2026 ranging from 31,473 to 36,313 ventilated adults. CONCLUSIONS: The incidence of mechanical ventilation projected to the year 2026 will steadily increase and outpace population growth as occurred in the 1990s. In the current environment in which intensive care unit resources are limited and ventilated patients already use a significant proportion of acute care resources, planning for this continued growth is necessary. Existing evidence-based strategies that improve both the efficiency and efficacy of critical care services should be carefully evaluated for widespread implementation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".