Monocytic HLA-DR expression and clinical outcomes in adult ICU patients with sepsis – a systematic review and meta-analysis
Bibliographic record
Abstract
Review question / Objective: The scope of this review was defined using PICOTS framework where 1) population: adult critically ill patients with sepsis or septic shock; 2) index prognostic factor: cell surface protein expression of mHLA-DR in blood; 3) comparative factor: none; 4) outcomes to be predicted: mortality, secondary infections, length of stay, and organ dysfunction score (sequential organ failure assessment [SOFA], multiple organ dysfunction score [MODS], logistic organ dysfunction score [LODS]), composite outcomes where component endpoints consist of at least one of the outcomes stated above (e.g., “adverse outcome” defined as death or secondary infection), 5) timing (of the prediction horizon and the moment of prognosis): any; and 6) setting: ICU. Condition being studied: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to severe infections. It can further progress to septic shock, which includes hemodynamic failure and increased mortality rates. A recent worldwide epidemiological study estimated 48.9 million sepsis cases and 11 million of sepsis-related deaths (~20% of global deaths in 2017). Although its management has advanced considerably, sepsis remains deadly and challenging to treat. The 28/30-day mortality averages around 25% for sepsis and 38% for septic shock in high-income countries. Current models describe the underlying pathophysiologic mechanisms of sepsis as an interplay between concurrent dysfunctional pro- and anti-inflammatory immune response.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".