The prognostic value of serum procalcitonin measurements in critically injured patients: a systematic review
Bibliographic record
Abstract
BACKGROUND: Major trauma is associated with high incidence of septic complications and multiple organ dysfunction (MOD), which markedly influence the outcome of injured patients. Early identification of patients at risk of developing posttraumatic complications is crucial to provide early treatment and improve outcomes. We sought to evaluate the prognostic value of serum procalcitonin (PCT) levels after trauma as related to severity of injury, sepsis, organ dysfunction, and mortality. METHODS: We searched PubMed, MEDLINE, EMBASE, the Cochrane Database, and references of included articles. Two investigators independently identified eligible studies and extracted data. We included original studies that assessed the prognostic value of serum PCT levels in predicting severity of injury, sepsis, organ dysfunction, and mortality among critically injured adult patients. RESULTS: Among 2015 citations, 19 studies (17 prospective; 2 retrospective) met inclusion criteria. Methodological quality of included studies was moderate. All studies showed a strong correlation between initial PCT levels and Injury Severity Score (ISS). Twelve out of 16 studies demonstrated significant elevation of initial PCT levels in patients who later developed sepsis after trauma. PCT level appeared a strong predictor of MOD in seven out of nine studies. While two studies did not show association between PCT levels and mortality, four studies demonstrated significant elevation of PCT levels in non-survivors versus survivors. One study reported that the PCT level of ≥ 5 ng/mL was associated with significantly increased mortality (OR 3.65; 95% CI 1.03-12.9; p = 0.04). CONCLUSION: PCT appears promising as a surrogate biomarker for trauma. Initial peak PCT level may be used as an early predictor of sepsis, MOD, and mortality in trauma population.
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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 | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".