Multinational, observational study of procalcitonin in ICU patients with presumed or confirmed pneumonia and requiring mechanical ventilation
Bibliographic record
Abstract
Respiratory tract infections requiring mechanical ventilation account for more than 50% of all infections treated in the ICU and prolonged hospital stay and high ICU mortality [ 1 – 3 ]. Procalcitonin (PCT) may help to identify patients at increased risk of worsening organ dysfunction associated with severe sepsis. The goal of this study was to assess whether maximum PCT concentrations are associated with deterioration of organ function. PCT-7 is a multicenter, multinational, observational study of the association of PCT levels with acute organ dysfunction and 28-day outcome in ICU patients with presumed or confirmed pneumonia and requiring mechanical ventilation. Procalcitonin was determined daily by LUMItest (BRAHMS AG, Germany) One hundred and ninety-seven patients (62.4% males) were enrolled from January 2003 to November 2004 in eight centers in Europe, the USA, and Canada. The mean age was 61.4 years (range 19–99); the mean APACHE II score was 23.7. Patients with high PCT levels had higher mortality rates (PCT cutoff: 2 ng/ml: odds ratio: 3.0 [95% CI: 1.4–6.4], P = 0.006; PCT cutoff: 4 ng/ml: odds ratio: 3.7 [95% CI: 1.8–7.8], P < 0.001). There was a significant correlation between the maximum SOFA score and the maximum PCT during the ICU stay ( r = 0.57; 95% CI: [0.45–0.66]; P < 0.001; n = 175). Both SOFA score and PCT elevations at any day had an area under the curve >0.7 in the receiver operator characteristic curve. In this first multicenter study on patients with pneumonia, high levels of PCT identify patients with organ dysfunction and a high risk of death.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".