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find Author "ZONG Zhen" 2 results
  • Application study of autologous platelet-rich plasma gel combined with vacuum sealing drainage in treatment of infectious wounds

    ObjectiveTo investigate the effect of vacuum sealing drainage (VSD) combined with autologous platelet-rich plasma gel (PRP) on postoperative wound infection and chronic poor wound healing, so as to provide more economical and safe treatment in clinic.MethodsThe patients with postoperative wound infection and chronic poor wound healing in the Second Affiliated Hospital of Nanchang University and Sixth Affiliated Hospital of Sun Yat-sen University from September 2018 to July 2019 were collected, then were divide into PRP+VSD group and VSD group according to treatment methods. The patients in the PRP+VSD group were filled with PRP and activator calcium thrombin following debridement, then covered with silver ion dressing and continuous VSD; in the VSD group were directly covered with silver ion dressing and then continuous VSD. The general situations of patients in the two groups during the process of replacing the VSD and the wound condition during dressing replacing were observed.ResultsThere were 100 patients in this study, 50 in the PRP+VSD group and 50 in the VSD group. There were no significant differences in the age, gender, body mass index, wound area before treatment, and wound infection type between the two groups (P>0.05). Compared with the VSD group, the PRP+VSD group had higher score of fresh granulation tissue coverage area (P<0.05), shorter wound closure time (P<0.05), shorter wound healing time (P<0.05), lower pain score (P<0.05), and less hospitalization expenses (P<0.05), lower rates of second debridement (P<0.05) and recurrent infection (P<0.05).ConclusionAutologous PRP combined with VSD in treatment of postoperative wound infection and chronic poor wound healing could shorten growth time of wound granulation tissue, promote rapid wound healing, reduce cost, and provide an economic, safe, and effective treatment method for clinical practice.

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  • A predictive model for the risk of lymph node metastasis in colorectal cancer

    ObjectiveTo explore the risk factors of lymph node metastasis in patients with colorectal cancer, and construct a risk prediction model to provide reference for clinical diagnosis and treatment.MethodsThe clinicopathological data of 416 patients with colorectal cancer who underwent radical resection of colorectal cancer in the Department of Gastrointestinal Surgery of the Second Affiliated Hospital of Nanchang University from May 2018 to December 2019 were retrospectively analyzed. The correlation between lymph node metastasis and preoperative inflammatory markers, clinicopathological factors and tumor markers were analyzed. Logistic regression was used to analyze the risk factors of lymph node metastasis, and R language was used to construct nomogram model for evaluating the risk of colorectal cancer lymph node metastasis before surgery, and drew a calibration curve and compared with actual observations. The Bootstrap method was used for internal verification, and the consistency index (C-index) was calculated to evaluate the accuracy of the model.ResultsThe results of univariate analysis showed that factors such as sex, age, tumor location, smoking history, hypertension and diabetes history were not significantly related to lymph node metastasis (all P>0.05). The factors related to lymph node metastasis were tumor size, T staging, tumor differentiation level, fibrinogen, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), fibrinogen/albumin ratio (FAR), fibrinogen/prealbumin ratio (FpAR), CEA, and CA199 (all P<0.05). The results of logistic regression analysis showed the FpAR [OR=3.630, 95%CI (2.208, 5.968), P<0.001], CA199 [OR=2.058, 95%CI (1.221, 3.470), P=0.007], CEA [OR=2.335, 95%CI (1.372, 3.975), P=0.002], NLR [OR=2.532, 95%CI (1.491, 4.301), P=0.001], and T staging were independent risk factors for lymph node metastasis. The above independent risk factors were enrolled to construct regression equation and nomogram model, the area under the ROC curve of this equation was 0.803, and the sensitivity and specificity were 75.2% and 73.5%, respectively. The consistency index (C-index) of the nomogram prediction model in this study was 0.803, and the calibration curve showed that the result of predicting lymph node metastasis was highly consistent with actual observations.ConclusionsFpAR>0.018, NLR>3.631, CEA>4.620 U/mL, CA199>21.720 U/mL and T staging are independent risk factors for lymph node metastasis. The nomogram can accurately predict the risk of lymph node metastasis in patients with colorectal cancer before surgery, and provide certain assistance in the formulation of clinical diagnosis and treatment plans.

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