Building a home ventilation programme: population, equipment, delivery and cost
Bibliographic record
Abstract
Home mechanical ventilation (HMV) improves quality of life and survival in patients with neuromuscular disorders (NMD). Developing countries may benefit from published evidence regarding the prevalence, cost of equipment, technical issues and organisation of HMV in NMD, facilitating the development of local turn-key HMV programmes. Unfortunately, such evidence is scattered in the existing literature. We searched Medline for publications in English and French from 2005 to 2020. This narrative review analyses 24 international programmes of HMV. The estimated prevalence (min-max) of HMV is ±7.3/100 000 population (1.2-47), all disorders combined. The prevalence of HMV is associated with the gross domestic product per capita in these 24 countries. The prevalence of NMD is about 30/100 000 population, of which ±10% would use HMV. Nocturnal (8/24 hour), discontinuous (8-16/24 hours) and continuous (>16/24 hours) ventilation is likely to concern about 60%, 20% and 20% of NMD patients using HMV. A minimal budget of about 168€/patient/year (504€/100 000 population), including the cost of equipment solely, should address the cost of HMV equipment in low-income countries. When services and maintenance are included, the budget can drastically increase up to between 3232 and 5760€/patient/year. Emerging programmes of HMV in developing countries reveal the positive impact of international cooperation. Today, at least 12 new middle, and low-income countries are developing HMV programmes. This review with updated data on prevalence, technical issues, cost of equipment and services for HMV should trigger objective dialogues between the stakeholders (patient associations, healthcare professionals and politicians); potentially leading to the production of workable strategies for the development of HMV in patients with NMD living in developing countries.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".