Epidemiological trends of mechanically ventilated acute respiratory distress syndrome in the twenty-first century: a nationwide, population-based retrospective study
Bibliographic record
Abstract
PURPOSE: Acute respiratory distress syndrome (ARDS) is a prevalent respiratory condition associated with significant mortality. Current literature on ARDS epidemiology reports a wide range of incidence (7.2-78.9/100,000 population/year), hospital mortality (32-51%), and associated costs ($8476-$547,974). We have analyzed epidemiological trends of mechanically ventilated ARDS (MV-ARDS) in Spain from 2000 to 2022 using the Minimum Basic Data Set (MBDS), focusing on MV-ARDS incidence, associated mortality, and economic impact. METHODS: We conducted a nationwide, population-based retrospective study of all hospitalizations for MV-ARDS in Spanish hospitals-from January 1, 2000 to December 31, 2022-using MBDS records, with an estimated coverage of 99.5%. The study reports MV-ARDS incidence per 100,000 population/year, hospital mortality rate, and mean cost per patient. We also considered the effect of COVID-19 on MV-ARDS epidemiology. RESULTS: We analyzed 93,192 records of patients with a new diagnosis of MV-ARDS during the study period. MV-ARDS incidence ranged from 2.96 to 20.14/100,000 population-years, peaking in 2021. Mortality ranged between 38.0 and 55.0%, showing a declining trend, while the cost per patient increased, stabilizing ~€30,000-€40,000 after reaching a peak of €42,812 in 2011. During the COVID-19 pandemic, hospital stay lengthened (p < 0.001), while hospital mortality decreased (p < 0.001). There was an increased proportion of patients with obesity and diabetes mellitus, with fungal or viral etiologies. CONCLUSION: This is the largest epidemiological study on ARDS in Europe. MV-ARDS incidence has stabilized in recent years, with mortality showing a declining trend. ARDS-related costs have increased nearly fourfold. MBDS data could enhance ARDS understanding and guide future studies.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".