ArticleCritical care explorations2022
Club Cell Secretory Protein-Derived Acute Respiratory Distress Syndrome Phenotypes Predict 90-Day Mortality: A Reanalysis of the Fluids and Catheter Treatment Trial.
Article in Critical care explorations, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- Predicting mortality with machine learning & biomarkers: A cohort analysis from aerosolized β₂-agonist for treatment of acute lung injury (ALTA) trial.Physiological reports · 2026Trial
- Plasma matrix metalloproteinase-3 predicts mortality in acute respiratory distress syndrome: a biomarker analysis of a randomized controlled trial.Respiratory research · 2023Trial
- Current Clinical Perspectives of Biomarkers in Respiratory Diseases: A Narrative Review.Journal of clinical medicine · 2026Review
- The molecular ICU: a primer on omics, informatics and the future of precision critical care.Critical care (London, England) · 2026Review
- Current Insights into Clinical, Molecular, and Therapeutic Approaches to Acute Respiratory Distress Syndrome.Medical sciences (Basel, Switzerland) · 2026Review
- Clinical Phenotyping in Acute Respiratory Distress Syndrome: Steps Towards Personalized Medicine.Journal of clinical medicine · 2025Article
- Host Response Protein Biomarkers Indicative of Persistent Acute Kidney Injury in Critically Ill COVID-19 Patients.Critical care explorations · 2025Article
- Berberine protects against lung injury induced by liver transplantation through upregulating PPARγ and suppressing NF-κB-mediated pyroptosis pathway.Acta cirurgica brasileira · 2025Article
- Club Cell Secretory Protein-16 (CC16) as a Prognostic Biomarker for COVID-19 and H1N1 Viral Infections.Diagnostics (Basel, Switzerland) · 2024Article
- Validation of Prognostic Club Cell Secretory Protein (CC16) Cut-point in an Independent ALTA Cohort.Biomarker insights · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Club cell secretory protein (CC16) is a protein with potential utility as a lung-specific biomarker for acute respiratory distress syndrome. The purpose of this study was to characterize CC16 in plasma from patients enrolled in the Fluid and Catheter Treatment Trial (FACTT) to determine the prognostic value for patient outcomes in our subgroup of FACTT patients.
designA secondary biomarker analysis of a prospective randomized-controlled trial. The primary outcome was area under the receiver operating characteristic (AUROC) of CC16 for prediction of 90-day mortality. Secondary outcomes included differences in mortality, length of stay, and ventilator-free days (VFDs) between patients with high and low CC16. Statistical analyses were performed with IBM SPSS Statistics.
settingSingle-center laboratory analysis. SUBJECTS: Plasma samples from 68 FACTT subjects and 20 healthy controls.
interventionsCC16 was measured in patient plasma samples by enzyme-linked immunosorbent assay. MEASUREMENTS AND MAIN
resultsSubjects were an average of 48 years old (sd, 16.7 yr old) and 51.5% male. AUROC analysis of CC16 on day 1 showed an area under the ROC curve of 0.78 for prediction of mortality (odds ratio, 1.011; 95% CI, 1.003-1.021) with an optimal cutoff value of 45 ng/mL. Patients in the low CC16 group (<45 ng/mL) had lower mortality (7.5 vs 50.0%;
conclusionsCC16 demonstrated an acceptable AUROC for prediction of patient mortality with a cut point of 45 ng/mL. Patients with high CC16 on day 1 had worse outcomes compared with those with low CC16, suggesting a prognostic role for this lung-specific biomarker.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.