Objective:To construct and validate a predictive model for postoperative pulmonary complications (PPCs) in patients undergoing robot-assisted laparoscopic urological surgery.Methods:This retrospective study included the medical records of 932 patients who underwent robot-assisted laparoscopic urological surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to February 2022. The patients were divided into a training group ( n=559) and a validation group ( n=373) at a 6∶4 ratio. Logistic regression analysis was used to determine the independent risk factors for PPCs, and a nomogram prediction model was constructed based on these factors. The performance of the model was evaluated using the receiver operating characteristic curve and calibration curve, and the clinical benefit was assessed using the clinical decision curve analysis. Results:The independent risk factors for PPCs included advanced age (>60 yr), smoking history, respiratory tract infection within 1 month, preoperative low SpO 2 (<96%), and prolonged length of postoperative hospital stay ( P<0.05), and the body mass index (18.5-<28.0 kg/m 2) was a protective factor. The nomogram prediction model developed based on the aforementioned 6 influencing factors had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.76-0.86) in training group and 0.80 (95% confidence interval 0.75-0.86) in validation group. The calibration curve indicated a good consistency between the predicted and actual occurrence curves, and the clinical decision curve analysis showed good accuracy and net benefit of the prediction model. Conclusions:The predictive model for PPCs is successfully constructed based on age, low body mass index, smoking history, history of respiratory tract infection within 1 month, preoperative low SpO 2 and prolonged length of postoperative hospital stay and has good predictive performance in patients undergoing robot-assisted laparoscopic urological surgery.

Objective:To construct and validate a predictive model for postoperative pulmonary complications (PPCs) in patients undergoing robot-assisted laparoscopic urological surgery.Methods:This retrospective study included the medical records of 932 patients who underwent robot-assisted laparoscopic urological surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to February 2022. The patients were divided into a training group ( n=559) and a validation group ( n=373) at a 6∶4 ratio. Logistic regression analysis was used to determine the independent risk factors for PPCs, and a nomogram prediction model was constructed based on these factors. The performance of the model was evaluated using the receiver operating characteristic curve and calibration curve, and the clinical benefit was assessed using the clinical decision curve analysis. Results:The independent risk factors for PPCs included advanced age (>60 yr), smoking history, respiratory tract infection within 1 month, preoperative low SpO 2 (<96%), and prolonged length of postoperative hospital stay ( P<0.05), and the body mass index (18.5-<28.0 kg/m 2) was a protective factor. The nomogram prediction model developed based on the aforementioned 6 influencing factors had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.76-0.86) in training group and 0.80 (95% confidence interval 0.75-0.86) in validation group. The calibration curve indicated a good consistency between the predicted and actual occurrence curves, and the clinical decision curve analysis showed good accuracy and net benefit of the prediction model. Conclusions:The predictive model for PPCs is successfully constructed based on age, low body mass index, smoking history, history of respiratory tract infection within 1 month, preoperative low SpO 2 and prolonged length of postoperative hospital stay and has good predictive performance in patients undergoing robot-assisted laparoscopic urological surgery.

Objective:To observe the dynamic changes of serum RANTES during the treatment with nucleos(t)ide analogues combined with pegylated interferon alpha (peginterferon-α), and further analyze the predictive effect of RANTES on HBsAg clearance in patients with chronic hepatitis B.Methods:98 cases of chronic hepatitis B with quantitative HBsAg < 3 000 IU/ml and HBV DNA < 20 IU/ml after≥1 year NAs treatment were enrolled. Among them, 26 cases continued to receive NAs monotherapy, 72 cases received NAs combined with pegylated interferon alpha therapy. The changes in RANTES during treatment were observed. The receiver operating characteristic curve was used to analyze the early changes of RANTES to predict the HBsAg clearance during 48 weeks.Results:During 48 weeks, 15 cases (20.83%) had achieved HBsAg clearance in combination group, while no patient had achieved HBsAg clearance in NAs group. The overall serum RANTES level had decreased from baseline in NAs and combination group. At week 48, in the combination group, the serum RANTES level was decreased more significantly in patients with HBsAg clearance than patients without. Further analysis showed that, in combination group, HBsAg clearance rate of patients with serum RANTES decreased at week 12 and 24 was higher than patients with elevated (29.17% vs. 4.17%, P = 0.014; 28.00% vs. 4.55%, P = 0.052), and quantitative HBsAg reduction was larger significantly [(1.49 ± 1.26) log 10IU/ml vs. (0.73 ± 0.81) log 10IU/ml, P = 0.017; (1.54 ± 1.27) log 10IU/ml vs. (0.57 ± 0.56) log 10IU/ml, P = 0.004]. Receiver operating characteristic curve analysis showed that the baseline quantitative HBsAg and the reduction in quantitative HBsAg and serum RANTES during the early period were predictors of HBsAg clearance after 48-week combination therapy. Furthermore, the combination of baseline quantitative HBsAg and 12 - or 24-week reduction of serum RANTES were better predictors of HBsAg clearance than that of baseline quantitative HBsAg combined with HBsAg decrease at week 12 or 24. The area under the receiver operating characteristic curve of the former was 0.925 and 0.939, while that of the latter was 0.909 and 0.929, respectively. Conclusion:Early reduction of serum RANTES at week 12 and 24 can predict HBsAg loss in CHB patients receiving addition of peginterferon-α to ongoing NAs Therapy, so serum RANTES could be one of the key immunological markers for predicting HBsAg clearance.

Objective To estimate the effect of daily diurnal temperature range (DTR) on mortality in different areas in China.Methods A time series study using the data collected from 66 areas in China was conducted,and Meta-analysis was used to analyze the estimates of associations between DTR and daily mortality.Modifying effects of extremely low and high DTR-mortality relationship by season and socioeconomic status (SES) were also evaluated respectively.Cumulative excess risk (CER) was used as an index to evaluate the effects.Results The information about 1 260 913 registered deaths were collected between 1 January 2006 and 31 December 2011,we found the relationship between extreme DTR and mortality was non-linear in all regions and the exposure-response curve was J-shaped.In central and south areas of China,the result indicated the obvious acute effect of extremely high DTR,and the mortality effect in central area (CER=5.1％,95％CI:2.4％-7.9％) was significant higher than that in south area (CER=4.5％,95％CI:1.7％-7.3％).Regarding to the modification of seasons,the cumulative mortality effect of DTR in cold season (CER=5.8％,95％CI:2.5％-9.2％) was higher than that in hot season (CER=3.1％,95％CI:1.1％-5.1％).Generally,deaths among the elderly (≥75 years) were associated more strongly with extremely high DTR.Conclusions The mortality effects of extremely DTR in different areas and seasons showed different characteristics,that in central area and in cold season it was significantly stronger.After modified by season and SES,DTRs were the greatest threat to vulnerable population,especially to the elderly (≥75 years).Therefore,more attention should be paid to vulnerable groups and protection measures should be taken according to the local and seasonal conditions.