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  1. Siegmund, Britta ; Rubio, Carlos A. ; et al.
    2021
    Online unknown
  2. A K, Shaytan ; R V, Novikov ; et al.
    In: Frontiers in Molecular Biosciences, Jg. 9 (2022-12-14)
    Online unknown
  3. Niu, Yi-Shuai
    2022
    Online unknown
  4. Wu, Tiantian ; Cao, Yuanwei ; et al.
    In: Journal of the American Chemical Society, Jg. 144 (2022-03-31), S. 6575-6582
    Online unknown
  5. Hoai An Le Thi ; Tao Pham Dinh
    In: Journal of Global Optimization, 2023-02-15
    Online unknown
  6. Sapozhnikov, Daniel M. ; Szyf, Moshe
    In: Scientific Reports, Jg. 13 (2023-02-09)
    Online unknown
    Siehe Detailanzeige für Volltext
  7. Lee, Jeongho ; Song, Yongju ; et al.
    In: 2023 IEEE International Conference on Big Data and Smart Computing (BigComp), 2023-02-01
    Online unknown
  8. Hoai An Le Thi ; Tao Pham Dinh ; et al.
    2023
    Online unknown
  9. Rasmussen, Claus
    2023
    Online unknown
  10. Wang, Xiaofang ; Fang, Dengjie ; et al.
    2023
    Online unknown
  11. Sutandyo Dwija Laksmana ; Husni Wahyu Wijaya ; et al.
    In: THE 4TH INTERNATIONAL CONFERENCE ON LIFE SCIENCE AND TECHNOLOGY (ICoLiST), 2023
    Online unknown
  12. Hoang Phuc Hau Luu ; Hoai Minh Le ; et al.
    2023
    Online unknown
  13. Alenzi, Adel F. ; Alkhaldi, Khaled ; et al.
    2023
    Online unknown
  14. Sarkar, Swarup ; Roy, Rupsa
    2023
    Online unknown
  15. Kabanda, Mwadham M. ; Bahadur, Indra
    In: Journal of Molecular Liquids, Jg. 381 (2023-07-01), S. 121804-121804
    Online unknown
  16. Liu, Qian ; Ding, Feng ; et al.
    In: Biomedical Signal Processing and Control, Jg. 84 (2023-07-01), S. 104856-104856
    Online unknown
  17. Stępień, Zbigniew ; Urzędowska, Wiesŀawa
    In: International Journal of Automotive Technology, Jg. 22 (2021-11-15), S. 1609-1618
    Online unknown
  18. ObjectiveTo establish a nomogram for predicting the risk of post-hepatectomy complications (PHC) in hepatic echinococcosis by analyzing the risk factors for PHC in two types of hepatic echinococcosis, and to investigate its value in clinical practice. MethodsA retrospective analysis was performed for the clinical data of 263 patients with two types of hepatic echinococcosis who underwent hepatectomy in Qinghai University Affiliated Hospital from January 2015 to August 2020, and among these patients, 93 were enrolled as PHC group and 170 were enrolled as control group. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups, and the independent samples t-test was used for comparison of normally distributed continuous data between two groups; the chi-square test and the Fisher’s exact test were used for comparison of categorical data between two groups. Univariate and multivariate logistic regression analyses were used to screen out independent risk factors for PHC, and a nomogram risk prediction model was established based on the weight of each independent risk factor. The Bootstrap resampling method was used for internal verification of the model; the receiver operating characteristic (ROC) curve was plotted to evaluate the discriminatory ability of the model; calibration curve and the Hosmer-Lemeshow test were used to evaluate the consistency of the model; decision curve analysis (DCA) was performed to verify the clinical effectiveness of the model. ResultsAlbumin-bilirubin (ALBI) score (odds ratio [OR]=3.694, 95% confidence interval [CI]: 1.860-7336, P<0.05), time of operation (OR=2.848, 95%CI: 1.384-5.859, P<0.05), intraoperative blood loss (OR=4.832, 95%CI: 2.384-9.793, P<0.05), and hydatid diameter (OR=3.073, 95%CI: 1.528-6.177, P<0.05) were independent risk factors for PHC in two types of hepatic echinococcosis. A nomogram risk prediction model was established based on the weight of the above four independent risk factors, and the model had an area under the ROC curve of 0.877 (95%CI: 0.831-0.923). The model had a consistency index of 0.871 after internal verification using the Bootstrap resampling method, suggesting that the model had good discriminatory ability. The fitting of the observed value and the actual value of the calibration curve and the Hosmer-Lemeshow test (P=0.905) showed that the predicted value of the nomogram risk prediction model had good consistency with the actual observed value. When the threshold probability was 35.6%, DCA showed a net clinical benefit of 22%, and the model had good clinical applicability within the threshold probability ranging from 8% to 89%. ConclusionALBI score, time of operation, intraoperative blood loss, and hydatid diameter are independent risk factors for PHC in patients with two types of hepatic echinococcosis, and the nomogram risk prediction model established based on these factors has good accuracy, consistency, and clinical practicability
    Hongye, LI
    In: Linchuang Gandanbing Zazhi, Jg. 37 (2021-11-01), Heft 11, S. 2632-2635
    Online unknown
  19. Hoai An Le Thi ; Tao Pham Dinh ; et al.
    In: Journal of Global Optimization, Jg. 73 (2018-08-21), S. 279-310
    Online unknown
  20. Sample, Kevin L. ; Hulland, John ; et al.
    In: Journal of Marketing Research, 2023-05-25, S. 002224372311663
    Online unknown
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