A Molecular Biomarker to Diagnose Community-acquired Pneumonia on Intensive Care Unit Admission
Bibliographic record
Abstract
RATIONALE: Community-acquired pneumonia (CAP) accounts for a major proportion of intensive care unit (ICU) admissions for respiratory failure and sepsis. Diagnostic uncertainty complicates case management, which may delay appropriate cause-specific treatment. OBJECTIVES: To characterize the blood genomic response in patients with suspected CAP and identify a candidate biomarker for the rapid diagnosis of CAP on ICU admission. METHODS: The study comprised two cohorts of consecutively enrolled patients treated for suspected CAP on ICU admission. Patients were designated CAP (cases) and no-CAP patients (control subjects) by post hoc assessment. The first (discovery) cohort (101 CAP and 33 no-CAP patients) was enrolled between January 2011 and July 2012; the second (validation) cohort (70 CAP and 30 no-CAP patients) between July 2012 and June 2013. Blood was collected within 24 hours of ICU admission. MEASUREMENTS AND MAIN RESULTS: Blood microarray analysis of CAP and no-CAP patients revealed shared and distinct gene expression patterns. A 78-gene signature was defined for CAP, from which a FAIM3:PLAC8 gene expression ratio was derived with area under curve of 0.845 (95% confidence interval, 0.764-0.917) and positive and negative predictive values of 83% and 81%, respectively. Robustness of the FAIM3:PLAC8 ratio was ascertained by quantitative polymerase chain reaction in the validation cohort. The FAIM3:PLAC8 ratio outperformed plasma procalcitonin and IL-8 and IL-6 in discriminating between CAP and no-CAP patients. CONCLUSIONS: CAP and no-CAP patients presented shared and distinct blood genomic responses. We propose the FAIM3:PLAC8 ratio as a candidate biomarker to assist in the rapid diagnosis of CAP on ICU admission. Clinical trial registered with www.clinicaltrials.gov (NCT 01905033).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".