Abstract
To analyze the incidence of PICC associated venous thrombosis. To predict the risk factors of thrombosis. To validate the best predictive model in predicting PICC associated thrombosis. Consecutive oncology cases in 341 who initially naive intended to be inserted central catheter for chemotherapy, were recruited to our dedicated intravenous lab. All patients used the same gauge catheter, Primary endpoint was thrombosis formation, the secondary endpoint was infusion termination without thrombosis. Two patients were excluded. 339 patients were divided into thrombosis group in 59 (17.4%) and non-thrombosis Group in 280 (82.6%), retrospectively. Tumor, Sex, Age, Weight, Height, BMI, BSA, PS, WBC, BPC, PT, D-dimer, APTT, FIB, Smoking history, Location, Catheter length, Ratio and Number as independent variables were analyzed by Fisher’s scoring, then Logistic risk regression, ROC analysis and nomogram was introduced. Total incidence was 17.4%. Venous mural thrombosis in 2 (3.4%), “fibrin sleeves” in 55 (93.2%), mixed thrombus in 2 (3.4%), symptomatic thrombosis in 2 (3.4%), asymptomatic thrombosis in 57 (96.6%), respectively. Height (χ² = 4.48, P = 0.03), D-dimer (χ² = 37.81, P < 0.001), Location (χ² = 7.56, P = 0.006), Number (χ² = 43.64, P < 0.001), Ratio (χ² = 4.38, P = 0.04), and PS (χ² = 58.78, P < 0.001), were statistical differences between the two groups analyzed by Fisher’s scoring. Logistic risk regression revealed that Height (β = −0.05, HR = 0.95, 95%CI: 0.911–0.997, P = 0.038), PS (β = 1.07, HR = 2.91, 95%CI: 1.98–4.27, P < 0.001), D-dimer (β0.11, HR = 1.12, 95%CI: 1.045–1.200, P < 0.001), Number (β = 0.87, HR = 2.38, 95% CI: 1.619–3.512, P < 0.001) was independently associated with PICC associated thrombosis. The best prediction model, D-dimer + Number as a novel co-variable was validated in diagnosing PICC associated thrombosis before PICC. Our research revealed that variables PS, Number, D-dimer and Height were risk factors for PICC associated thrombosis, which were slightly associated with PICC related thrombosis, in which, PS was the relatively strongest independent risk factor of PICC related thrombosis.
Highlights
Due to the toxicity of chemotherapy to the vascular wall, it is essential to establish a reliable, relatively long-term central venous access for cancer patients who required intravenous chemotherapy
Our research revealed that variables PS, Number, D-dimer and Height were risk factors for Peripherally Inserted Central Catheter (PICC) associated thrombosis, which were slightly associated with PICC related thrombosis, in which, PS was the relatively strongest independent risk factor of PICC related thrombosis
Among all the included cancer patients, 59 patients (17.4%) who developed PICC associated thrombosis during the PICC line placement were assigned into thrombosis group, while the remaining 280 patients (82.6%) were assigned to the non-thrombosis group, respectively
Summary
Due to the toxicity of chemotherapy to the vascular wall, it is essential to establish a reliable, relatively long-term central venous access for cancer patients who required intravenous chemotherapy. Inserted Central Catheter (PICC) was widely used in clinical scenarios because of its being performed, safety, long indwelling time, easy care and maintenance, less discomfort and low risk of infection. PICC, as an effective alternative to central venous catheter (CVC) could effectively avoid CVC related critical iatrogenic pneumothorax and gas embolism complications[1–4]. Multiple studies have confirmed high overall incidence (up to 30–40%) of PICC catheter related complications, including deep vein thrombosis (DVT), infection, fibrin sheath, superficial phlebitis, catheter prolapse, catheter displacement and blockage[5,6], among which, indwelling catheter vein and/or fibrin-sheath-shape catheter thrombosis prevails[7,8]. This paper summarized the incidence and analyzed the risk factors for PICC associated thrombosis in 339 cancer patients who received PICC placement, retrospectively. Based on the risk factors, a model was built and validated to predict the risk for PICC associated thrombosis
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