Additional file 1 of Rapidly improving ARDS differs clinically and biologically from persistent ARDS
Bibliographic record
Abstract
Additional file 1. Figure E1. Study Design. All patients were enrolled in the Early Assessment of Renal and Lung Injury (EARLI) cohort from November 2008 to May 2018. We analyzed data from 215 patients who met Berlin criteria for ARDS on day 1 or 2 of the study, were endotracheally intubated at the time of meeting Berlin criteria, and had plasma biomarker measurements available. Patients met criteria for rapidly improving ARDS if any of the following criteria were met: (i) Pao2:Fio2 > 300 or (ii) Spo2:Fio2 > 315 on the day following diagnosis of ARDS (day 2) or (iii) unassisted breathing by day 2 and for the next 48 hours (defined as absence of endotracheal intubate on day 2 through day 4). Table E1. Comorbidities were compared in patients with RIARDS versus persistent ARDS. Cirrhosis was more commonly identified in persistent ARDS. Other comorbidities were not significantly different between each group. Table E2. Concomitant medical conditions were compared in patients with RIARDS versus persistent ARDS. Hypertensive crisis at time of enrollment was more common in patients with RIARDS compared to those with persistent ARDS. Table E3. Type of steroids administered over the first 48 hours of ARDS diagnosis in patients with RIARDS compared to those with persistent ARDS. Table E4. Sensitivity analysis focused on patients with severe ARDS (defined by a PaO2:FiO2 equal to or less than 100 at time of enrollment). Vasopressor-dependent shock was more commonly seen in patients with severe persistent ARDS compared to severe RIARDS. Hospital mortality was significantly higher while ICU-free days was lower in those with severe persistent ARDS compared to severe RIARDS. Table E5. Sensitivity analysis focused on patients with severe ARDS. Patient comorbidities did not differ significantly between RIARDS and persistent disease among those with severe ARDS. Table E6. Sensitivity analysis focused on patients with severe ARDS. Concomitant medical conditions did not differ significantly between RIARDS and persistent disease among those with severe ARDS. Table E7. Sensitivity analysis focused on patients with severe ARDS. Ventilatory parameters did not differ significantly between RIARDS and persistent disease among those with severe ARDS. Table E8. Sensitivity analysis focused on patients with severe ARDS (defined by a PaO2:FiO2 equal to or less than 100 at time of enrollment). Plasma inflammatory biomarkers were significantly higher in those with severe persistent ARDS compared to severe RIARDS. Table E9. Sensitivity analysis comparing RIARDS and persistent disease among cases allocated to the hyperinflammatory phenotype. Similar to the results seen in the overall cohort, compared to patients with hyperinflammatory persistent ARDS, patients with hyperinflammatory RIARDS had significantly lower in-hospital mortality at 28 days and higher ICU-free days. However, contrary to results seen in the overall cohort, vasopressor-dependent shock on day 1 was equally prevalent. Severe hypoxemia was more commonly seen in persistent ARDS and not appreciated in RIARDS. Table E10. Sensitivity analysis comparing RIARDS and persistent disease among cases allocated to the hyperinflammatory phenotype. Microbiology and medications received did not differ between each group. Table E11. Sensitivity analysis comparing RIARDS and persistent disease among cases allocated to the hyperinflammatory phenotype. No significant differences were found in plasma inflammatory biomarker concentration between patients with RIARDS and persistent ARDS. Table E12. Total counts of missing values. Ventilatory parameters stratified by persistent ARDS versus RIARDS. Table E13. Total counts of missing values. Biomarkers stratified by persistent ARDS versus RIARDS. Table E14. Total counts of missing values. Comorbidities and concomitant medical conditions stratified by persistent ARDS versus RIARDS.
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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 | 0.002 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.707 | 0.044 |
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".