Implementation of Tunneled Peripherally Inserted Central Catheters Placement in Cancer Patients: A Randomized Multicenter Study

This study sought to evaluate the impact of the subcutaneous tunneling technique on peripherally inserted central catheter (PICC) placement. We randomized 694 patients who needed PICC placement to either the tunneled PICCs (experimental group) or the non-tunneled PICCs (control group) from August to December 2021. The cumulative frequency of complications was assessed as the primary outcome. Secondary outcomes comprised of the amount of bleeding, catheter insertion time, self-reported pain score, and one-puncture success rate. After 6 months of follow-up, the tunneled PICCs group showed a significant decrease in the frequency of total complications, especially in infection (3.0% vs. 7.1%, p = .021) and catheter-related thrombosis (3.3% vs. 8.3%, p = .008), although approximately 0.5 ml bleeding and 3.5 min time were increased. This randomized multicenter study supports the efficacy of subcutaneous tunneling technology in reducing PICC-related complications, enhancing patient comfort, and encouraging using subcutaneous tunneling technology for PICC placement.

Different diagnostic strategies using D-dimer for peripherally inserted central catheter-related upper extremity deep vein thrombosis

OBJECTIVE

Deep vein thrombosis (DVT) in the upper extremities caused by a peripherally inserted central venous catheter (PICC) is distinct from the typical DVT. This specific type of mural thrombus might have an effect on the D-dimer levels. In the present study, we aimed to ascertain whether the D-dimer level might be considered an independent diagnostic marker to rule out upper extremity DVT caused by PICCs.

METHODS

We performed a retrospective case-cohort study of 205 patients who had undergone D-dimer measurement and color Doppler ultrasound within 14 days after placement of a PICC to December 31, 2020, from January 1, 2018. The participants were followed up for 3 months to evaluate for upper extremity DVT. In addition, different D-dimer diagnostic strategies were analyzed.

RESULTS

Of the 205 included patients, 53 (25.9%) had had a negative D-dimer level. Of the 53 patients, 10 had had upper extremity DVT attributable to a PICC using color Doppler ultrasound. Of these 10 patients, 3 had developed upper extremity DVT during the 3-month follow-up. Using the various D-dimer diagnostic techniques, the negative predictive value for the D-dimer levels was 81.1%.

CONCLUSIONS

The present study has shown that the different D-dimer diagnostic strategies are not effective for safely excluding the diagnosis of suspected PICC-related upper extremity DVT. Adding PICC placement as a special factor in the modified Wells score, in addition to the D-dimer level, could securely rule out PICC-related upper extremity DVT; however, the diagnostic efficacy was low.

D-dimer level for ruling out peripherally inserted central catheter-associated upper extremity deep vein thrombosis and superficial vein thrombosis

AIMS

To examine the effectiveness of D-dimer values to be used as an independent diagnostic marker for excluding peripherally inserted central catheter-associated upper extremity deep vein thrombosis and superficial vein thrombosis.

DESIGN

This was a retrospective case-cohort study.

METHODS

Records were reviewed for 281 patients who underwent peripherally inserted central catheter insertion between 1 October 2017 and 1 October 2019. According to the modified Wells score after peripherally inserted central catheter insertion, the patients who had low vein thrombosis risk underwent a D-dimer test and colour Doppler ultrasound.

RESULTS

Among 281 patients, 180 patients (64%, 95% CI: 58.2%-69.4%) had negative D-dimer results and 39 of 180 patients had vein thrombosis despite having a negative D-dimer result, resulting in a failure rate of 21.7% (95% CI: 16.3%-28.3%). The negative predictive value of peripherally inserted central catheter-associated vein thrombosis in the cancer group (80.0%, 95% CI: 73.2%-85.4%) was higher than that of the non-cancer group (60.0%, 95% CI: 35.7%-80.2%). The negative predictive value of peripherally inserted central catheter-associated deep venous thrombosis (84.9%, 95% CI: 78.7%-89.6%) was lower than that of the PICC-associated superficial venous thrombosis (91.0%, 95% CI: 85.4%-94.6%).

CONCLUSION

The D-dimer levels maybe should not be used as a diagnostic index to rule out peripherally inserted central catheter-associated upper extremity vein thrombosis.

Development and Validation of a New Clinical Prediction Model of Catheter-Related Thrombosis Based on Vascular Ultrasound Diagnosis in Cancer Patients

Background: Central venous catheters are convenient for drug delivery and improved comfort for cancer patients, but they also cause serious complications. The most common complication is catheter-related thrombosis (CRT). Objectives: This study aimed to evaluate the incidence and risk factors for CRT in cancer patients and develop an effective prediction model for CRT in cancer patients. Methods: The development of our prediction model was based on a retrospective cohort (n = 3,131) from the National Cancer Center. Our prediction model was confirmed in a prospective cohort from the National Cancer Center (n = 685) and a retrospective cohort from the Hunan Cancer Hospital (n = 61). The predictive accuracy and discriminative ability were determined by receiver operating characteristic (ROC) curves and calibration plots. Results: Multivariate analysis demonstrated that sex, cancer type, catheter type, position of the catheter tip, chemotherapy status, and antiplatelet/anticoagulation status at baseline were independent risk factors for CRT. The area under the ROC curve of our prediction model was 0.741 (CI: 0.715-0.766) in the primary cohort and 0.754 (CI: 0.704-0.803) and 0.658 (CI: 0.470-0.845) in validation cohorts 1 and 2, respectively. The model also showed good calibration and clinical impact in the primary and validation cohorts. Conclusions: Our model is a novel prediction tool for CRT risk that accurately assigns cancer patients into high- and low-risk groups. Our model will be valuable for clinicians when making decisions regarding thromboprophylaxis.