Evidence map›Paper›PMID 40406481›Full record

ArticleFrontiers in pharmacology2025

Prophylactic anticoagulant therapy is associated with improved survival in ICU patients with non-COVID-19 pneumonia: a retrospective cohort study.

Haiming Hu, Yixing Zhu, Ruikang Hu, Lijuan Zhao, Xiangwen Zeng, Xue Wu, Rui Qiu, Yihao Nie, Lokesh Sharma, De Chang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Haiming Hu *Department of Pulmonary and Critical Care Medicine at The Seventh Medical Center, College of Pulmonary and Critical Care Medicine of The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.
Yixing Zhu *Department of Pulmonary and Critical Care Medicine at The Seventh Medical Center, College of Pulmonary and Critical Care Medicine of The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.
Ruikang Hu *Graduate School of Chinese PLA General Hospital, Beijing, China.
Lijuan ZhaoGraduate School of Chinese PLA General Hospital, Beijing, China.
Xiangwen ZengGraduate School of Chinese PLA General Hospital, Beijing, China.
Xue WuDepartment of Pulmonary and Critical Care Medicine at The Seventh Medical Center, College of Pulmonary and Critical Care Medicine of The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.
Rui QiuDepartment of Pulmonary and Critical Care Medicine at The Seventh Medical Center, College of Pulmonary and Critical Care Medicine of The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.
Yihao NieSanquan College, Xinxiang Medical College, Xinxiang, Henan, China.
Lokesh SharmaDivision of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
De ChangDepartment of Pulmonary and Critical Care Medicine at The Seventh Medical Center, College of Pulmonary and Critical Care Medicine of The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.

Funding

UC San Diego RAPID Faculty Development Program in Infectious DiseasesR25AI147376 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ADRIANA H TREMOULET, Joann Trejo · 2020 to 2026
$2.5M
NIAID NIH HHS R25 AI147376
6 · The paper itself

Abstract

Background: Coagulation disorders are common complications in patients with pulmonary infections. Studies have suggested beneficial effects of anticoagulant therapies in patients with COVID-19. However, the usefulness of prophylactic anticoagulant therapies in patients with non-COVID-19 pulmonary infections is still a matter of debate. This study aimed to assessed the impact of prophylactic anticoagulant therapy in ICU patients with non-COVID-19 pneumonia. Methods: Patients were identified from the Medical Information Mart for Intensive Care-IV database. Propensity score matching (PSM) was utilized to minimize differences. Kaplan-Meier survival analysis was performed to assess mortality. Univariate and multivariate Cox regression models were used to identify prognostic factors for short-term mortality (7-day). The E-value was calculated to unmeasured confounding. To further explore the optimal anticoagulant administration, subgroup analyses were performed. We also explored the optimal administration strategies including the timing and duration of anticoagulant therapy. Results: A total of 1,000 ICU patients were included, with 500 receiving prophylactic anticoagulation therapy and 500 not. Both 7-day mortality (7.6% vs. 19.6%; p < 0.001) and 30-day mortality (19.6% vs. 31.2%; p < 0.001) in the anticoagulant group were lower than non-users. Kaplan-Meier survival analysis also showed a significantly lower prevalence of short-term mortality in patients who used anticoagulants. Both univariate (HR, 0.36; 95% CI, 0.25-0.53; p < 0.001) and multivariate (HR, 0.30; 95% CI, 0.21-0.44; p < 0.001) Cox regression analyses consistently demonstrated a significant reduction in short-term mortality associated with anticoagulation therapy. Subgroup analysis revealed that anticoagulant therapy was associated with reduced short-term mortality across most subgroups. Further analysis showed that late (≥6 h) and non-short-term (≥7 days) anticoagulation therapy were more effective. Conclusion: Our results support the potential value of prophylactic anticoagulation therapy as a strategy to improve survival in ICU patients with non-COVID-19 pneumonia.

Indexed as

ICUMIMIC databasemortalitynon-COVID-19 pneumoniaprophylactic anticoagulant therapy

Identifiers

PMID40406481
PMCPMC12095157

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.