Postoperative drug-resistant bacteria infection in patients with acute Stanford type A aortic dissection under two-fluid numerical simulation model

Zang, Sheng
Zhang, Yu
Xu, Jiarui
Du, Yaming
Issa, Sahar
Al Dulaimi, Saeed Hameed Kurdi
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Elsevier B.V.
Objective: This study was to investigate the characteristics and related factors of postoperative drug-resistant bacteria infection (DRBI) in patients with acute Stanford A aortic dissection (AD) (AAAD) based on a two-fluid numerical simulation model (TFNS model). Methods: 50 patients with AAAD admitted to our hospital from July 2018 to October 2020 were selected as the research objects. The patients were rolled into an infection group and a non-infection group according to whether DRBI occurred after surgery. There were 21 patients in the infected group and 29 patients in the non-infected group. The clinical data of the patients were collected, including preoperative, intraoperative, and postoperative conditions. A TFNS model was constructed. The construction of vascular physical model could be completed by the construction of fluid area and solid area. The blood flows through the fluid area and the blood vessel wall was located in the solid area. The model was adopted to study the characteristics of DRBI. The data of the patients were analyzed to explore the relationship of the multi-DRBI to intraoperative blood loss, postoperative complications, intensive care unit (ICU) stay time, invasive procedures, and use of antibiotics. In addition, the multi-factor postoperative multi-DRBI was performed with the regression analysis. Results: There was no significant difference between the infected group and the non-infected group in antibiotics used such as cephalosporin, penicillin, glycopeptide, and quinolones (P > 0.05). The time spent on antibiotics was greatly lower in the infected group than in the non-infected group (P < 0.05). The ICU stay time in the infected group was 17.78 ± 11.55, and that in the non-infected group was 6.67 ± 4.36, without notable difference between the two groups (P < 0.05). In addition, there was no significant difference between the two groups in the time to transfer to the ICU, while there was one case infected with Staphylococcus aureus, Pseudomonas aeruginosa, and Enterobacter cloacae. The excessive plasma loss (odds ratio (OR) = 3.823, 95% confidential interval (CI) = 1.643–8.897), renal insufficiency (OR = 1.855, 95% CI = 1.076–3.199), ICU stay time (OR = 5.089, 95% CI = 1.507–17.187), indwelling time of nasal feeding tube (NFT) (OR = 3.225, 95% CI = 1.332–7.807), assisted ventilation (OR = 3.077, 95% CI = 1.640–5.773), tracheal intubation (OR = 5.078, 95% CI = 1.415–18.227), tracheotomy (OR = 0.073, 95% CI = 0.013–0.382), continuous renal replacement (CRR) therapy (OR = 0.111, 95% CI = 0.023–0.476), use time of antibiotics (OR = 1.089, 95% CI = 1.038–1.143) were independent risk factors for postoperative multi-DRBI. Conclusion: postoperative multi-DRBI was characterized by Acinetobacter baumannii infection with the largest proportion, followed by Klebsiella pneumoniae; excessive plasma loss, renal insufficiency, ICU stay time, indwelling time of NFT, assisted ventilation, tracheal intubation, tracheotomy, CRR therapy, and use time of antibiotics were all independent risk factors of postoperative multi-DRBI. In the postoperative care of AAAD patients, the inducing factors had to be informed to the patient, and relative measures should be taken to prevention and treatment, which was conductive to reducing the incidence of infection and promote the recovery of AAAD. © 2021 The Author(s)
This article is not available at CUD collection. The version of scholarly record of this article is published in Results in Physics (2021), available online at:
Drug-resistance bacteria, Infection, Stanford A, Two-fluid numerical simulation model, Type A aortic dissection
Zang, S., Zhang, Y., Xu, J., Du, Y., Issa, S., & Al Dulaimi, S. H. K. (2021). Postoperative drug-resistant bacteria infection in patients with acute stanford type A aortic dissection under two-fluid numerical simulation model. Results in Physics, 26.