Key result
Combined thrombosis biomarkers sTM, t-PAI·C, TAT, and PIC identify severe pneumonia with ~0.87 AUC.
Why the study?
Pneumonia is a major health problem and leading cause of mortality worldwide, prompting investigation of new automated plasma thrombosis biomarkers for diagnosis and prognosis in severe pneumonia.
Do thrombosis biomarkers (TAT, PIC, sTM, t-PAI·C) improve the early diagnosis and prognostic assessment of severe pneumonia?
Observational (n=438)
No
Do thrombosis biomarkers (TAT, PIC, sTM, t-PAI·C) improve the early diagnosis and prognostic assessment of severe pneumonia?
Effect estimate: AUC 0.868 (95% CI 0.837, 0.899)
p-value: p=<0.001
Thrombosis biomarkers including sTM, t-PAI·C, TAT, and PIC demonstrate utility in diagnosing severe pneumonia and predicting in-hospital mortality.
Thrombosis biomarkers may aid severe pneumonia triage; hypothesis-generating pending prospective outcome trials.
Background Pneumonia is a major health problem and the most important causes of mortality in all age groups worldwide. We investigated new automation technology to detect plasma biomarkers, including thrombinantithrombin complex (TAT), α2-plasmininhibitor-plasmin complex (PIC), soluble thrombomodulin (sTM), and tissue plasminogen activator-inhibitor complex (t-PAI·C), and evaluated their diagnostic performance and prognostic value for severe pneumonia patients. Methods We collected 414 patients date with pneumonia. sTM, t-PAI·C, TAT, PIC were measured by qualitative chemiluminescence immunoassay performed on HISCL analyzers. Other laboratory tests were evaluated on the day of non-severe pneumonia and severe pneumonia diagnosis. Results There were significant differences in sTM, t-PAI·C, TAT, PIC ( p < 0.0001), WBC ( p = 0.023), PCT ( p = 0.007) and IL-6 ( p = 0.002) between the severe pneumonia and non-severe pneumonia groups, Logistic regression analysis showed that sTM ( p = 0.001), t-PAI·C ( p = 0.001), TAT ( p = 0.022), PIC ( p = 0.000) and APTT ( p = 0.013) were independent risk factors for severe pneumonia. Logistic regression analysis showed that t-PAI·C ( p = 0.006) was an independent risk factor for hospital mortality in severe pneumonia. The AUC of sTM combined with t-PAI·C, TAT and PIC on diagnosis of patients with severe pneumonia was 0.868 (95% CI: 0.837, 0.899). Kaplan-Meier survival analysis with a log-rank test showed the in-hospital death rate of severe pneumonia was higher in the high TAT (≥ 5.58ng/mL) level than in group with low TAT (< 5.58ng/mL) level (log rank < 0.029). The same trend with high t-PAI·C was also found in severe pneumonia patients (log rank < 0.021). Conclusions The thrombosis markers are helpful for the diagnosis and prognostic assessment of severe pneumonia.
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Fan et al. (2026) conducted an observational in Severe pneumonia (n=438). Thrombosis biomarkers (sTM, TAT, PIC, t-PAI·C) vs. Non-severe pneumonia and healthy controls was evaluated on Diagnosis of severe pneumonia (AUC 0.868, 95% CI 0.837, 0.899, p=<0.001). The combination of thrombosis biomarkers sTM, t-PAI·C, TAT, and PIC demonstrated high diagnostic accuracy for severe pneumonia with an AUC of 0.868.
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