Study protocol: The Improving Care of Acute Lung Injury Patients (ICAP) study
Bibliographic record
Abstract
INTRODUCTION: The short-term mortality benefit of lower tidal volume ventilation (LTVV) for patients with acute lung injury/acute respiratory distress syndrome (ALI/ARDS) has been demonstrated in a large, multi-center randomized trial. However, the impact of LTVV and other critical care therapies on the longer-term outcomes of ALI/ARDS survivors remains uncertain. The Improving Care of ALI Patients (ICAP) study is a multi-site, prospective cohort study that aims to evaluate the longer-term outcomes of ALI/ARDS survivors with a particular focus on the effect of LTVV and other critical care therapies. METHODS: Consecutive mechanically ventilated ALI/ARDS patients from 11 intensive care units (ICUs) at four hospitals in the city of Baltimore, MD, USA, will be enrolled in a prospective cohort study. Exposures (patient-based, clinical management, and ICU organizational) will be comprehensively collected both at baseline and throughout patients' ICU stay. Outcomes, including mortality, organ impairment, functional status, and quality of life, will be assessed with the use of standardized surveys and testing at 3, 6, 12, and 24 months after ALI/ARDS diagnosis. A multi-faceted retention strategy will be used to minimize participant loss to follow-up. RESULTS: On the basis of the historical incidence of ALI/ARDS at the study sites, we expect to enroll 520 patients over two years. This projected sample size is more than double that of any published study of long-term outcomes in ALI/ARDS survivors, providing 86% power to detect a relative mortality hazard of 0.70 in patients receiving higher versus lower exposure to LTVV. The projected sample size also provides sufficient power to evaluate the association between a variety of other exposure and outcome variables, including quality of life. CONCLUSION: The ICAP study is a novel, prospective cohort study that will build on previous critical care research to improve our understanding of the longer-term impact of ALI/ARDS, LTVV and other aspects of critical care management. Given the paucity of information about the impact of interventions on long-term outcomes for survivors of critical illness, this study can provide important information to inform clinical practice.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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".