What question did this study set out to answer?

To develop a predictive model for identifying asymptomatic pulmonary embolism (PE) in patients with deep vein thrombosis (DVT).

July 27, 2026Clinical and Applied Thrombosis/HemostasisOpen Access

Diagnostic Management of Asymptomatic Pulmonary Embolism: A Predictive Model Integrating Inflammatory Markers and Clinical Characteristics in Patients With Deep Vein Thrombosis

Q: What is the clinical evidence from this study?

Study design: Observational. Population: Lower extremity deep vein thrombosis (DVT) (n=401). Intervention: Clinical and inflammatory risk factors (hypertension, NLR, smoking duration, right DVT, leg swelling/pain). Primary outcome: Asymptomatic pulmonary embolism (AUC 0.874).

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Key result

Clinical predictive model identifies asymptomatic PE in hospitalized DVT patients with an AUC of ~0.87.

AUC 0.874
n=401

Why the study?

Routine CTPA screening for asymptomatic PE in patients with lower extremity DVT faces resource and contrast-agent limitations, requiring optimized diagnostic strategies to identify high-risk patients needing CTPA.

Does a predictive model integrating clinical characteristics and inflammatory markers accurately identify asymptomatic pulmonary embolism in hospitalized patients with deep vein thrombosis?

Population

401 patients admitted with lower extremity DVT without acute PE symptoms

Comparison

Asymptomatic PE (n=198) vs isolated DVT (n=203)

Design

Retrospective study

Authors

XMXiaomin MuJining Medical University QAQi AnJining First People's Hospital GWGuibin WanAffiliated Hospital of Jining Medical University

Discussion

Member takes

Overview

May aid risk stratification for asymptomatic PE in DVT; leaves open clinical adoption pending prospective validation.

Key Points

To develop a predictive model for identifying asymptomatic pulmonary embolism (PE) in patients with deep vein thrombosis (DVT).
Retrospective analysis of 401 patients admitted with lower extremity DVT from Jan 2022 to Apr 2024.
Binary logistic regression identified predictors of asymptomatic PE among included patients.
Participants classified into asymptomatic PE (n=198) and isolated DVT (n=203) groups after exclusions.
Hypertension, neutrophil-to-lymphocyte ratio (NLR), smoking duration, right distal DVT, right proximal DVT, and lower extremity swelling and pain were independent risk factors for asymptomatic PE (ORs ranging from 1.103 to 7.176).
The predictive model achieved an area under the curve (AUC) of 0.874, with a sensitivity of 73.74% and specificity of 82.27%.
Further external validation is needed to apply findings to broader DVT populations.

Study Design

Type

Observational (n=401)

Structured PICO

Does a predictive model integrating clinical characteristics and inflammatory markers accurately identify asymptomatic pulmonary embolism in hospitalized patients with deep vein thrombosis?

Population

401 hospitalized patients with lower extremity DVT, excluding those with acute PE symptoms or recent anticoagulation, evaluated for asymptomatic PE.

Exposure

Predictive model integrating hypertension, neutrophil-to-lymphocyte ratio (NLR), smoking duration, right distal DVT, right proximal DVT, and lower extremity swelling and pain

Outcome

Presence of asymptomatic pulmonary embolism detected by computed tomography pulmonary angiography (CTPA)

Main Result

Effect estimate: AUC 0.874

A predictive model using routine clinical factors and the neutrophil-to-lymphocyte ratio can accurately identify hospitalized DVT patients at high risk for asymptomatic PE, potentially optimizing the use of CTPA screening.

Limitations

Findings cannot be directly generalized to all DVT outpatients
Further external verification required to extend applicability to broader DVT cohorts
requires further external verification to extend applicability to broader DVT cohorts

Cite This Study

Mu et al. (2026) conducted an observational in Lower extremity deep vein thrombosis (DVT) (n=401). Clinical and inflammatory risk factors (hypertension, NLR, smoking duration, right DVT, leg swelling/pain) was evaluated on Asymptomatic pulmonary embolism (AUC 0.874). A predictive model integrating hypertension, NLR, smoking duration, right DVT, and leg swelling/pain identified asymptomatic PE in hospitalized DVT patients with an AUC of 0.874.

synapsesocial.com/papers/6a6794fcbb2605d1235fba20 https://doi.org/10.1177/10760296261472604

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July 27, 2026Clinical and Applied Thrombosis/HemostasisOpen Access

Diagnostic Management of Asymptomatic Pulmonary Embolism: A Predictive Model Integrating Inflammatory Markers and Clinical Characteristics in Patients With Deep Vein Thrombosis

View Full Paper

Ask AI

Bookmark

Key result

Clinical predictive model identifies asymptomatic PE in hospitalized DVT patients with an AUC of ~0.87.

AUC 0.874
n=401

Why the study?

Does a predictive model integrating clinical characteristics and inflammatory markers accurately identify asymptomatic pulmonary embolism in hospitalized patients with deep vein thrombosis?

Population

401 patients admitted with lower extremity DVT without acute PE symptoms

Comparison

Asymptomatic PE (n=198) vs isolated DVT (n=203)

Design

Retrospective study

Authors

XMXiaomin MuJining Medical University QAQi AnJining First People's Hospital GWGuibin WanAffiliated Hospital of Jining Medical University

Discussion

Member takes

Overview

May aid risk stratification for asymptomatic PE in DVT; leaves open clinical adoption pending prospective validation.

Key Points

To develop a predictive model for identifying asymptomatic pulmonary embolism (PE) in patients with deep vein thrombosis (DVT).
Retrospective analysis of 401 patients admitted with lower extremity DVT from Jan 2022 to Apr 2024.
Binary logistic regression identified predictors of asymptomatic PE among included patients.
Participants classified into asymptomatic PE (n=198) and isolated DVT (n=203) groups after exclusions.
Hypertension, neutrophil-to-lymphocyte ratio (NLR), smoking duration, right distal DVT, right proximal DVT, and lower extremity swelling and pain were independent risk factors for asymptomatic PE (ORs ranging from 1.103 to 7.176).
The predictive model achieved an area under the curve (AUC) of 0.874, with a sensitivity of 73.74% and specificity of 82.27%.
Further external validation is needed to apply findings to broader DVT populations.

Study Design

Type

Observational (n=401)

Structured PICO

Does a predictive model integrating clinical characteristics and inflammatory markers accurately identify asymptomatic pulmonary embolism in hospitalized patients with deep vein thrombosis?

Population

401 hospitalized patients with lower extremity DVT, excluding those with acute PE symptoms or recent anticoagulation, evaluated for asymptomatic PE.

Exposure

Predictive model integrating hypertension, neutrophil-to-lymphocyte ratio (NLR), smoking duration, right distal DVT, right proximal DVT, and lower extremity swelling and pain

Outcome

Presence of asymptomatic pulmonary embolism detected by computed tomography pulmonary angiography (CTPA)

Main Result

Effect estimate: AUC 0.874

Limitations

Findings cannot be directly generalized to all DVT outpatients
Further external verification required to extend applicability to broader DVT cohorts
requires further external verification to extend applicability to broader DVT cohorts

Cite This Study

synapsesocial.com/papers/6a6794fcbb2605d1235fba20 https://doi.org/10.1177/10760296261472604

Also Consider

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