Bibliographic record
Abstract
Pivotal sepsis clinical trials and preclinical research in 2012 are reviewed. For interventions ranging from synthetic complex starch solutions to recombinant human activated protein C, large multicenter randomized controlled trials generally failed to show benefit and some even demonstrated harm in the intervention group. In smaller innovative clinical trials simple interventions such as external cooling to control fever and biomarker-guided weaning from mechanical ventilation found potential benefit. Biomarkers for sepsis, including multimarker panels, are increasingly showing promise for clinical application. Breakthroughs in basic research in sepsis continue to highlight the complexity of the systemic inflammatory response and its consequences. A series of publications in AJRCCM follow the septic inflammatory response starting from intracellular structures and organelles to mitochondria and the cytoskeleton. Additional publications explore the key leukocyte subsets acting in sepsis, highlighting the underappreciated role of helper T-cell type 2-related pathways. Cellular remnants in the form of microparticles contribute to coagulopathy and further organ dysfunction. As a consequence, we suggest that sepsis may be the paradigm disease or condition requiring personalized care first to discover and validate new therapies and second to increase survival.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".