The prevalence of chronic respiratory failure treated with home mechanical ventilation in Helsinki, Finland
Bibliographic record
Abstract
Objectives: Home mechanical ventilation (HMV) is a well-established treatment for chronic respiratory failure (CRF). In the Eurovent study (2001-2002) the estimated prevalence of European patients with CRF treated with HMV was 6.6/100 and 8.7/100 000 in Finland. In Canada (2012-2013) the prevalence was 12.9/100 000. The current prevalence is largely unknown. The aim of this study was to study the prevalence of CRF treated with HMV in Helsinki, Finland. Methods: We studied all HMV-patients’ medical files and collected information of the diagnosis behind CRF, how the diagnosis was made, treatment modality, co-morbidities, one-year mortality, smoking habits and information from the last follow-up visit. Results: On January 1st 2018 206 patients were treated with non-invasive ventilation (NIV)(N=202, 98%) or home mechanical invasive ventilation (HIMV) (N=4, 2%) in Helsinki University Hospital, Finland. The prevalence of HMV was 35.0/100 000. All the HIMV patients had a neuromuscular disease and the most common diagnosis in the NIV-group was obesity hypoventilation syndrome (OHS) (51%, N=102). The average age was 63 years in the NIV-group and 40 years in the HIMV-group. About half of the patients were ex-smokers (54%, N=106) and male (57%, N=117). One-year mortality was 13% (N=26), none of the HIMV patients died. Conclusions: Prevalence was higher in our study compared to older studies. There are many potential explanations for the growing prevalence, for instance a larger spectrum of diseases are now treated with HMV and also the prevalence of CRF is rising, largely due to OHS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".