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find Author "HU Lei" 2 results
  • Construction and validation of a prognostic nomogram model for gastric cancer liver metastasis

    Objective To establish a prediction model for the 1-, 3-, and 5-year survival rates in patients with gastric cancer liver metastases (GCLM) by analyzing prognostic factors based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods Clinical and pathological data from 591 patients diagnosed with GCLM between 2010 and 2015 were obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort at a 7 to 3 ratio. Independent predictors of GCLM were analyzed using univariate and multifactorial Cox regression. Consequently, nomograms were constructed. The model's accuracy was verified by calibration curve, ROC curve, and the C-index, and the clinical utility of the model was analyzed through decision curve analysis. Results Tumor differentiation grade, surgical status, and chemotherapy were significantly associated with the prognosis of GCLM patients, and these three factors were included in constructing the prognostic model and plotting the nomogram. The C-index was 0.706 (95%CI 0.677 to 0.735) and 0.749 (95%CI 0.710 to 0.788) for the training set and the internal validation cohort, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) was over 0.7 at 1, 3, and 5 years for both the training and validation cohorts. Conclusion The prediction model of the GCLM is developed based on the 3 factors, i.e., tumor differentiation grade, surgery, and chemotherapy, and shows good prediction accuracy and thus may promote clinical decision making and individualized treatment of GCLM patients.

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  • Clinical application of computer-assisted cannulated screw internal fixation system based on error correction method for femoral neck fractures

    Objective To investigate the clinical efficacy of computer-assisted cannulated screw internal fixation system based on error correction method for femoral neck fractures. Methods A retrospective analysis was made on the clinical data of 20 femoral neck fracture patients treated by computer-assisted cannulated screw internal fixation system based on error correction method between January 2014 and October 2015 (trial group), and 36 femoral neck fracture patients undergoing traditional manual surgery with closed reduction by cannulated screw fixation in the same period (the control group). There was no significant difference in gender, age, injury cause, side of fracture, types of fracture, and time from injury to operation between 2 groups (P>0.05). The operation time, intraoperative blood loss, intraoperative frequency of fluoroscopy and guide pin insertion, fracture healing time, fracture healing rate, and Harris hip score were compared between 2 groups. Results All incisions healed by first intention after operation, and no complication of blood vessel and nerve injury occurred. The operation time of trial group was significantly longer than that of control group (t=2.290,P=0.026), however, the intraoperative blood loss, intraoperative frequency of fluoroscopy and guide pin insertion of trial group were significantly less than those of control group (t=–10.650,P=0.000;t=18.320,P=0.000;t=–16.625,P=0.000). All patients were followed up 12-18 months (mean, 14.7 months). X-ray films showed that fracture healing was obtained in 2 groups, showing no significant difference in fracture healing time between 2 groups (t=0.208,P=0.836). No complication of ischemic necrosis of femoral head occurred during follow-up period. At last follow-up, the Harris hip score was 87.05±3.12 in trial group and was 86.78±2.83 in control group, showing no significant difference (t=0.333,P=0.741). Conclusion Computer-assisted cannulated screw internal fixation surgery based on error correction method for femoral neck fractures is better than traditional manual surgery in decreasing intraoperative radiation and surgical trauma during operation.

    Release date:2017-04-01 08:56 Export PDF Favorites Scan
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