ArticleClinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Exploring Risk Factors for Lower Extremity Deep Vein Thrombosis Patients with Co-existing Pulmonary Embolism Based on Multiple Logistic Regression Model.
Article in Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Systemic immune inflammation index guides machine learning for rapid TTP diagnosis: a retrospective cohort study.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Valuable data on deep vein thrombosis (DVT) patients with coexisting pulmonary embolism (PE) is scarce. This study aimed to identify risk factors associated with these patients and develop logistic regression models to select high-risk DVT patients with coexisting PE. We retrospectively collected data on 150 DVT patients between July 15, 2022, and June 15, 2023, dividing them into groups based on the presence of coexisting PE. Univariate and multivariate logistic regression analyses were performed to identify significant risk factors and construct predictive models. Discrimination and calibration statistics evaluated the validation and accuracy of the developed models. Of the 130 patients analyzed, 40 (30.77%) had coexisting PE. Univariate analysis revealed four significant predictors of DVT patients with coexisting PE: sex (OR 3.83, 95% CI: [1.76; 8.59],
Indexed as
Identifiers
What OpenQuestion holds
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.