Re-analysis of ventilator-free days (VFD) in acute respiratory distress syndrome (ARDS) studies
Bibliographic record
Abstract
BACKGROUND: Over recent decades, improvements in healthcare have reduced mortality and morbidity rates in many conditions. This has resulted, in part, from the identification of effective interventions in randomised trials, and in conducting such trials, a composite outcome measure (COM) with multiple components will increase event rates, which allows study completion with a smaller sample size. In critical care research, the COM "ventilator-free days" (VFD) combines mortality and duration of mechanical ventilation (MV) into a single continuous measure, which can be analysed in a variety of ways. This study investigates the usefulness of Poisson and two-part Poisson models compared to t-distribution for the analysis of VFD. METHODS: Data from four studies (ALbuterol for the Treatment of ALI (ALTA), Early vs. Delayed Enteral Nutrition (EDEN), Hydroxymethylglutaryl-CoA reductase inhibition with simvastatin in Acute Lung Injury (ALI) to reduce pulmonary dysfunction (HARP-2), Statins for Acutely Injured Lungs from Sepsis (SAILS)) were used for analysis, with the VFD results summarised using mean, standard deviation (SD), median, interquartile range (25th and 75th percentiles) and minimum and maximum values. The statistical analyses that are compared used the t-test, Poisson, zero-inflated Poisson (ZIP) and two-part Logit-Poisson hurdle models. The analyses were exploratory in nature, and the significance level for differences in the estimates was set to 0.05. RESULTS: In HARP-2, which compared simvastatin and placebo, the mean (SD) VFD for all patients was 12.0 (10.2), but this mean value did not represent the data distribution as it falls in a zone between two peaks, with the lowest frequency of occurrence. The mean (SD) VFD after excluding patients who died before day 28 and patients who did not achieve unassisted breathing were 15.9 (8.7) and 18.2 (6.6), respectively. The mean difference (95% CI) between the two groups was 1.1 (95% CI: 0.7 to 2.8; p = 0.20) based on an independent t-test. However, when the two-part hurdle model was used, the simvastatin arm had a significantly higher number of non-zero values compared to the placebo group, which indicated that more patients were alive and free of mechanical ventilation in the simvastatin group. Similarly, in ALTA, this model found that significantly more patients were alive and free of MV in the control group. In EDEN and SAILS, there was no significant difference between the control and intervention groups. CONCLUSION: Our analyses show that the t-test and Poisson model are not appropriate for bi-modal data (such as VFD) where there is a large number of zero events. The two-part hurdle model was the most promising approach. There is a need for future research to investigate other analysis techniques, such as two-part quantile regression and to determine the impact on sample size requirements for comparative effectiveness trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".