Stratification of venous thromboembolism risk in stroke patients by Caprini score

Zhu, Xiaoping; Zhang, Tingting; Zhou, Luting; Yin, Xiaobing; Dong, Qiong

doi:10.21037/apm.2020.04.20

Cited by 7 publications

(3 citation statements)

References 16 publications

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“…A positive correlation between CRS and the risk of VTE in acutely ill medical patients was observed in 3 trials that enrolled 6268 participants (Table S5, Supplemental Digital Content 1, http://links.lww.com/SLA/E469). [18][19][20] The only retrospective study on patients with stroke who received mechanical and chemical prophylaxis reported the incidence of symptomatic VTE of 0.55%, which increased up to 2.17% in those with a Caprini score of ≥ 9. 20 Authors of another casecontrol trial concluded that VTE risk is elevated by 4 times in patients with ≥ 5 scores.…”

Section: Medical Patientsmentioning

confidence: 99%

“…[18][19][20] The only retrospective study on patients with stroke who received mechanical and chemical prophylaxis reported the incidence of symptomatic VTE of 0.55%, which increased up to 2.17% in those with a Caprini score of ≥ 9. 20 Authors of another casecontrol trial concluded that VTE risk is elevated by 4 times in patients with ≥ 5 scores. 19…”

Section: Medical Patientsmentioning

confidence: 99%

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The Thresholds of Caprini Score Associated With Increased Risk of Venous Thromboembolism Across Different Specialties

et al. 2023

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Objective: Estimation of the specific thresholds of the Caprini risk score (CRS) that are associated with the increased incidence of venous thromboembolism (VTE) across different specialties, including identifying the highest level of risk. Background: Accurate risk assessment remains an important but often challenging aspect of VTE prophylaxis. One well-established risk assessment model is CRS, which has been validated in thousands of patients from many different medical and surgical specialties. Methods: A search of MEDLINE and the Cochrane Library was performed in March 2022. Manuscripts that reported on (1) patients admitted to medical or surgical departments and (2) had their VTE risk assessed by CRS and (3) reported on the correlation between the score and VTE incidence, were included in the analysis. Results: A total of 4562 references were identified, and the full text of 202 papers was assessed for eligibility. The correlation between CRS and VTE incidence was reported in 68 studies that enrolled 4,207,895 patients. In all specialties, a significant increase in VTE incidence was observed in patients with a CRS of ≥ 5. In most specialties thresholds of ≥ 7, ≥ 9, and ≥ 11 to 12 were associated with dramatically increased incidences of VTE. In cancer, trauma, vascular, general, head and neck, and thoracic surgery patients with ≥ 9 and ≥ 11 to 12 scores the VTE incidence was extremely high (ranging from 13% to 47%). Conclusion:The Caprini score is being used increasingly to predict VTE in many medical and surgical specialties. In most cases, the VTE risk for individual patients increases dramatically at a threshold CRS of 7 to 11.

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Section: Medical Patientsmentioning

confidence: 99%

Section: Medical Patientsmentioning

confidence: 99%

The Thresholds of Caprini Score Associated With Increased Risk of Venous Thromboembolism Across Different Specialties

et al. 2023

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“…Zhu et al suggested using the Caprini score to assess risk of secondary VTE in stroke patients. 11 Nonetheless, the Caprini score is based on static assessment and cannot dynamically reflect changes in patient condition. 12 …”

Section: Introductionmentioning

confidence: 99%

Nomogram for Risk of Secondary Venous Thromboembolism in Stroke Patients: A Study Based on the MIMIC-IV Database

Lan,

Liu,

Guan

et al. 2024

Clin Appl Thromb Hemost

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This study aims to identify risk factors for secondary venous thromboembolism (VTE) in stroke patients and establish a nomogram, an accurate predictor of probability of VTE occurrence during hospitalization in stroke patients. Medical Information Mart for Intensive Care IV (MIMIC-IV) database of critical care medicine was utilized to retrieve information of stroke patients admitted to the hospital between 2008 and 2019. Patients were randomly allocated into train set and test set at 7:3. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for secondary VTE in stroke patients. A predictive nomogram model was constructed, and the predictive ability of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). This study included 266 stroke patients, with 26 patients suffering secondary VTE after stroke. A nomogram for predicting risk of secondary VTE in stroke patients was built according to pulmonary infection, partial thromboplastin time (PTT), log-formed D-dimer, and mean corpuscular hemoglobin (MCH). Area under the curve (AUC) of the predictive model nomogram was 0.880 and 0.878 in the train and test sets, respectively. The calibration curve was near the diagonal, and DCA curve presented positive net benefit. This indicates the model's good predictive performance and clinical utility. The nomogram effectively predicts the risk probability of secondary VTE in stroke patients, aiding clinicians in early identification and personalized treatment of stroke patients at risk of developing secondary VTE.

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Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke

Liu,

Li,

Zhou

et al. 2024

J Thromb Thrombolysis

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Stratification of venous thromboembolism risk in stroke patients by Caprini score

Cited by 7 publications

References 16 publications

The Thresholds of Caprini Score Associated With Increased Risk of Venous Thromboembolism Across Different Specialties

The Thresholds of Caprini Score Associated With Increased Risk of Venous Thromboembolism Across Different Specialties

Nomogram for Risk of Secondary Venous Thromboembolism in Stroke Patients: A Study Based on the MIMIC-IV Database

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke

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