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Record W4416246694 · doi:10.1186/s12931-025-03406-3

The role of eCyPA as an inflammatory biomarker for predicting 28-day mortality in ARDS patients

2025· article· en· W4416246694 on OpenAlexaff
Juan Chen, Xue Dai, Jing Lv, Meijun Liu, Ewan C. Goligher, Wang Deng

Bibliographic record

VenueRespiratory Research · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsToronto General HospitalUniversity Health Network
FundersCentre Scientifique et Technique du BâtimentNatural Science Foundation of ChongqingChongqing Medical University
KeywordsARDSBiomarkerAcute respiratory distressSeverity of illnessInflammationPredictive value of testsRespiratory diseaseInflammatory response

Abstract

fetched live from OpenAlex

BACKGROUND: Acute respiratory distress syndrome (ARDS) is the primary manifestation of systemic inflammatory response syndrome in the lungs. Extracellular cyclophilin A (eCyPA) as a novel inflammatory marker, this study aims to investigate the expression of eCyPA in ARDS and its relationship with patient prognosis. METHODS: This retrospective study collected serum samples from adult patients diagnosed with acute respiratory distress syndrome (ARDS) upon their admission to ICU. Additionally, venous blood and bronchoalveolar lavage fluid were obtained from a lipopolysaccharide (LPS)-induced ARDS mouse model. The expression levels of extracellular cyclophilin A in serum and bronchoalveolar lavage fluid were quantified using enzyme-linked immunosorbent assay (ELISA). The data collection period extended from December 2021 to December 2023. Binary logistic regression analysis, ROC curve, Kaplan-Meier survival analysis were employed to evaluate the correlation with 28-day all-cause mortality in ARDS patients. An incremental prognostic value analysis was conducted to further investigate the enhancement in predictive value when combined with clinically significant indicators (platelet count and oxygenation index). Additionally, we assessed the dynamic trends of eCyPA and cytokines in serum and bronchoalveolar lavage fluid at 0, 1, 3, and 7 days in LPS-induced ARDS mouse models. RESULTS: A total of 50 patients were enrolled. The serum eCyPA expression level was significantly higher among non-survivors compared to survivors (7.2 ng/ml, interquartile range, IQR, 5.9-8.2 vs. 10.1 ng/ml, IQR 7.5-10.6; p = 0.002), and this finding remained consistent across various subgroups. eCyPA is an effective predictor of 28-day mortality in ARDS patients (AUC = 0.754). When combined with platelet count and oxygenation index, the prognostic value assessment improved the AUC to 0.887 (P < 0.001). In ARDS mice, eCyPA increased continuously over 7 days in serum and bronchoalveolar lavage fluid, the trend is similar to inflammatory cytokines in ARDS mice. CONCLUSIONS: The findings suggest that eCyPA may serve as a potential biomarker for predicting 28-day mortality in patients with acute respiratory distress syndrome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.078
GPT teacher head0.425
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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