Search
"The results provide evidence for the practitioner's early use of the Caprini to assess the thrombotic risk in patients with PICCs" Feng et al (2021).

Abstract:

Purpose: There was no optimal risk assessment tool to stratify the risk of peripherally inserted central catheter-related venous thromboembolism (PICC-RVT) in cancer patients. We currently use the Caprini risk assessment model for thrombotic risk assessment, but no evidence exists on the effectiveness of Caprini in such patients. This study was to assess the validity of the Caprini in Chinese cancer patients with PICCs.

Methods: We conducted a prospective study of 468 participants. Following calculating the Caprini score, color Doppler ultrasonography was performed every 7 days for 3 weeks to confirm PICC-RVT.

Results: There was a correlation between PICC-RVT and the Caprini score. Compared with scores of 5, the risk was 2.089-fold greater (95% CI 1.165-3.743, P = 0.012) in patients with a score of 6 and 7, and 7.156-fold greater (95% CI 3.157-16.217, P < 0.001) in patients with scores ≥8. The area under the receiver-operating characteristic curve was 0.636 (95% CI 0.590-0.680; P < 0.001). 6 was the best cutoff point for Caprini, with a sensitivity of 0.76 and a specificity of 0.44.

Conclusions: The Caprini can be used for high-risk screening of the PICC-RVT in cancer patients, and classification of the highest risk level using a score of 6 can be more clinically significant compared to 5 as recommended. The results provide evidence for the practitioner’s early use of the Caprini to assess the thrombotic risk in patients with PICCs and take timely prevention measures. But pharmacological prevention should be considered seriously for its low specificity.

Reference:

Feng Y, Zheng R, Fu Y, Xiang Q, Yue Z, Li J, Yu C, Jiang Y. Assessing the thrombosis risk of peripherally inserted central catheters in cancer patients using Caprini risk assessment model: a prospective cohort study. Support Care Cancer. 2021 Feb 16. doi: 10.1007/s00520-021-06073-4. Epub ahead of print. PMID: 33594508.