Objective:To explore the incidence and risk factors of peripherally inserted central catheter (PICC) related upper extremity venous thrombosis (UEVT) in patients with head and neck neoplasm so as to provide a basis for preventing thrombosis.Methods:This study used the design of prospective cohort study. From January 2016 to March 2018, UEVT follow-up examination by B ultrasound was carried out for 1 137 head and neck neoplasm patients with PICC selected by convenience sampling. Single factor and multivariate Cox regression were used to determine the risk factors of PICC related UEVT.Results:There were 3.6% (41/1 137) of patients with PICC related UEVT. Multivariate Cox regression showed that the independent risk factors of PICC related UEVT included the older patients ( RR=1.04, 95% CI: 1.01-1.07, P=0.013) , being with a history of PICC catheterization ( RR=3.22, 95% CI: 1.53-6.77, P=0.002) and high frequency of catheter delivery ( RR=1.98, 95% CI: 1.30-3.00, P=0.001) . Conclusions:Patients with head and neck neoplasm have the low incidence of PICC related UEVT. The independent risk factors of PICC related UEVT in patients with head and neck neoplasm include the older ages, history of PICC catheterization and high frequency of catheter delivery. Positive intervention should be carried out for those patients which may reduce the incidence of PICC related thrombosis.

Objective:To construct a risk assessment scale for flap necrosis after flap transplantation in patients with head and neck tumors, so as to provide an effective reference for clinical implementation of flap necrosis risk screening.Methods:The overall study period was from December 2020 to June 2021. Based on evidence, the item pool of the risk assessment scale for flap necrosis after flap transplantation in patients with head and neck tumors was preliminarily established. Using the Delphi method, 16 experts engaged in flap transplantation were selected for three rounds of consultation, and the risk assessment scale for flap necrosis after flap transplantation in patients with head and neck tumors was initially established. The weights were given to all indicators through the paired comparison.Results:In the first round, 16 questionnaires were distributed, and 15 valid questionnaires were recovered. In the second and third rounds, 15 questionnaires were distributed, and 15 valid questionnaires were recovered. Expert authority coefficients of the three rounds of expert consultation were 0.851, 0.853 and 0.853, respectively. The Kendall coordination coefficients of the three rounds of expert consultation were 0.377, 0.302 and 0.302 ( P<0.05) . The final constructed risk assessment scale for flap necrosis after flap transplantation in patients with head and neck tumors included 3 first-level indicators, 8 second-level indicators, and 32 third-level indicators. The weights were assigned to each indicator by paired comparison, and the weights of the first-level indicator patient factor, treatment factor, and nursing factor were 0.36, 0.38, and 0.26, respectively. Conclusions:The risk assessment scale for flap necrosis after flap transplantation in patients with head and neck tumors constructed by combining evidence-based and Delphi method is highly scientific and reliable. Its clinical applicability and effectiveness can be further verified in the future clinical flap evaluation process.

Objective:To investigate the value of nomogram predictive model established by the risk factors of upper extremity venous thrombosis risk associated with peripherally venous inserted central catheter (PICC) in cancer patients.Methods:A total of 1 032 patients who underwent PICC insertion between January 2016 and March 2017 in Zhejiang Cancer Hospital were selected by using prospective cohort study and convenience sampling. Risk factors of upper extremity venous thrombosis risk associated with PICC in cancer patients were evaluated by using Cox regression model. The nomogram predictive model of upper extremity venous thrombosis risk associated with PICC insertion was constructed. Bootstrap method was used to complete the inside check, and figure calibration was used to verify the nomogram.Results:A multivariate Cox regression analysis showed that trombosis history ( HR = 27.82, 95% CI 8.17-94.88, P < 0.01) and hyperlipidemia ( HR = 3.01, 95% CI 1.31-6.93, P = 0.009) were independent risk factors for upper extremity venous thrombosis associated with PICC. The nomogram model C-index was 0.71 (95% CI 0.63-0.80) based on the above risk factors, which indicated that the nomogram had a good differentiation. The calibration curve for predicting the probability of upper extremity venous thrombosis risk associated with PICC within one week, two weeks and one month deviated slightly from the standard curve, suggesting that the model might overestimate the risk of upper extremity venous thrombosis associated with PICC in cancer patients. Conclusions:The nomogram model has a good predictive value and strong operability, which can be used to predict the probability of upper extremity venous thrombosis associated with PICC in cancer patients after PICC insertion. It can provide a reference for identifying the high-risk cancer patients and formulating proper therapeutic strategies.

Objective::To establish the HPLC fingerprint of carbonized ginger and to determine the contents of zingerone, 6-gingerol, 6-shogaol, 10-gingerol, 8-shogaol and 10-shogaol with quantitative analysis of multi-components by single marker (QAMS). Method::The fingerprint of carbonized ginger was established by HPLC. All samples were analyzed by Waters SymmetryShield™ RP18 column (4.6 mm×250 mm, 5 μm) with gradient elution by acetonitrile(A)-water(B) (0-30 min, 25%-70%A; 30-50 min, 70%-90%A; 50-60 min, 90%A), the flow rate was 1.0 mL·min^-1, the detection wavelength was set at 240 nm and the column temperature was 30 ℃. Zingerone, 6-gingerol, 8-gingerol, 6-shogaol, 10-gingerol, 8-shogaol and 10-shogaol was chosen as marker ingredients to establish HPLC fingerprint of carbonized ginger decoction pieces. Taking 6-gingerol as internal reference standard, the contents of zingerone, 6-shogaol, 10-gingerol, 8-shogaol and 10-shogaol were determined at the detection wavelength of 220 nm and 280 nm according to the relative correction factor. Result::The HPLC fingerprint of carbonized ginger was obtained and 10 common peaks were designated, and 7 of them were identified as zingerone, 6-gingerol, 8-gingerol, 6-shogaol, 10-gingerol, 8-shogaol and 10-shogaol, respectively. And there were no significant differences between the quantitative results of external standard method and QAMS. It is suggested that the content limits of carbonized ginger should be not less than 0.020%of zingerone (C₁₁H₁₄O₃), 0.050%of 6-gingerol (C₁₇H₂₆O₄), 0.120%of 6-shogaol (C₁₇H₂₄O₃), 0.080%of 10-gingerol (C₂₁H₃₄O₄), 0.030%of 8-shogaol (C₁₉H₂₈O₃) and 0.050%of 10-shogaol (C₂₁H₃₂O₃) calculated with reference to the dried products, respectively. Conclusion::The developed method is accurate and feasible, which can provide a simple and effective method for the quality control of carbonized ginger.