Objective To explore the effect of standardized use of antibiotics on clinical indicators after thoracic surgery, such as pulmonary infection rate, incision infection rate, average length of hospital stay and total hospitalization cost. Methods We selected 468 patients (an observation group) who were hospitalized and received thoracic surgery from August to October 2011, 3 months after the implementation of the preventive antibiotics use protocol for thoracic surgery in West China Hospital, Sichuan University, and selected 343 patients (a control group) in the same period of the previous year (from August to October 2010). There were 326 males and 142 females with a mean age of 52.0±15.5 years in the observation group, and 251 males and 92 females with a mean age of 51.4±15.9 years in the control group. The level of antibiotic use, medication time, antibiotics cost, postoperative incision infection, incidence of pulmonary infection, postoperative hospital stay and total hospitalization cost were compared between the two groups. Results Compared with the control group, the time for preventive use of antibiotics was significantly shorter in the observation group (3.6±2.4 d vs. 6.1±3.1 d, P=0.020) and the total cost of antibiotic use significantly reduced (1 230.0±2 151.0 yuan vs.2 252.0±1 764.0 yuan, P<0.001). There was no significant difference between the two groups in hospitalization cost(36 345.0±13 320.0 yuanvs. 35 821.0±11 991.0 yuan, P=0.566), postoperative hospital stay (10.6±8.4 d vs. 10.7±5.3 d, P=0.390), the incidence of postoperative wound infection or postoperative pulmonary infection (1.5% vs. 2.3%, P=0.430; 19.2% vs. 22.2%, P=0.330). Conclusion The standardized use of antibiotics in thoracic surgery does not cause postoperative pulmonary infection and incision infection, and has no negative impact on clinical indicators. Significantly reducing the level of antibiotics use may have a positive effect on reducing medication time, in-hospital infection and the incidence of drug-resistant strains.
How to improve the performance of circulating tumor DNA (ctDNA) signal acquisition and the accuracy to authenticate ultra low-frequency mutation are major challenges of minimal residual disease (MRD) detection in solid tumors. In this study, we developed a new MRD bioinformatics algorithm, namely multi-variant joint confidence analysis (MinerVa), and tested this algorithm both in contrived ctDNA standards and plasma DNA samples of patients with early non-small cell lung cancer (NSCLC). Our results showed that the specificity of multi-variant tracking of MinerVa algorithm ranged from 99.62% to 99.70%, and when tracking 30 variants, variant signals could be detected as low as 6.3 × 10−5 variant abundance. Furthermore, in a cohort of 27 NSCLC patients, the specificity of ctDNA-MRD for recurrence monitoring was 100%, and the sensitivity was 78.6%. These findings indicate that the MinerVa algorithm can efficiently capture ctDNA signals in blood samples and exhibit high accuracy in MRD detection.