Objective::This study investigates the efficacy of analyzing fetal heart rate (FHR) signals based on Artificial Intelligence to obtain a baseline calculation and identify accelerations/decelerations in the FHR through electronic fetal monitoring during labor.Methods::A total of 43,888 cardiotocograph(CTG) records of female patients in labor from January 2012 to December 2020 were collected from the NanFang Hospital of Southern Medical University. After filtering the data, 2341 FHR records were used for the study. The ObVue fetal monitoring system, manufactured by Lian-Med Technology Co. Ltd., was used to monitor the FHR signals for these pregnant women from the beginning of the first stage of labor to the end of delivery. Two obstetric experts together annotated the FHR signals in the system to determine the baseline as well as accelerations/decelerations of the FHR. Our cardiotocograph network (CTGNet) as well as traditional methods were then used to automatically analyze the baseline and acceleration/deceleration of the FHR signals. The results of calculations were compared with the annotations provided by the obstetric experts, and ten-fold cross-validation was applied to evaluate them. The root-mean-square difference (RMSD) between the baselines, acceleration F-measure (Acc.F-measure), deceleration F-measure (Dec.F-measure), coefficient of synthetic inconsistency (SI) and the morphological analysis discordance index (MADI) were used as evaluation metrics. The data were analyzed by using a paired t-test. Results::The proposed CTGNet was superior to the best traditional method, proposed by Mantel, in terms of the RMSD.BL (1.7935 ± 0.8099 vs. 2.0293 ± 0.9267, t=-3.55 , P=0.004), Acc.F-measure (86.8562 ± 10.9422 vs. 72.2367 ± 14.2096, t= 12.43, P <0.001), Dec.F-measure (72.1038 ± 33.2592 vs. 58.5040 ± 38.0276, t= 4.10, P <0.001), SI (34.8277±20.9595 vs. 54.8049 ± 25.0265, t=-9.39, P <0.001), and MADI (3.1741 ± 1.9901 vs. 3.7289 ± 2.7253, t= -2.74, P= 0.012). The proposed CTGNet thus had significant advantages over the best traditional method on all evaluation metrics. Conclusion::The proposed Artificial Intelligence-based method CTGNet delivers good performance in terms of the automatic analysis of FHR based on cardiotocograph data. It promises to be a key component of smart obstetrics systems of the future.

Objective::This study investigates the efficacy of analyzing fetal heart rate (FHR) signals based on Artificial Intelligence to obtain a baseline calculation and identify accelerations/decelerations in the FHR through electronic fetal monitoring during labor.Methods::A total of 43,888 cardiotocograph(CTG) records of female patients in labor from January 2012 to December 2020 were collected from the NanFang Hospital of Southern Medical University. After filtering the data, 2341 FHR records were used for the study. The ObVue fetal monitoring system, manufactured by Lian-Med Technology Co. Ltd., was used to monitor the FHR signals for these pregnant women from the beginning of the first stage of labor to the end of delivery. Two obstetric experts together annotated the FHR signals in the system to determine the baseline as well as accelerations/decelerations of the FHR. Our cardiotocograph network (CTGNet) as well as traditional methods were then used to automatically analyze the baseline and acceleration/deceleration of the FHR signals. The results of calculations were compared with the annotations provided by the obstetric experts, and ten-fold cross-validation was applied to evaluate them. The root-mean-square difference (RMSD) between the baselines, acceleration F-measure (Acc.F-measure), deceleration F-measure (Dec.F-measure), coefficient of synthetic inconsistency (SI) and the morphological analysis discordance index (MADI) were used as evaluation metrics. The data were analyzed by using a paired t-test. Results::The proposed CTGNet was superior to the best traditional method, proposed by Mantel, in terms of the RMSD.BL (1.7935 ± 0.8099 vs. 2.0293 ± 0.9267, t=-3.55 , P=0.004), Acc.F-measure (86.8562 ± 10.9422 vs. 72.2367 ± 14.2096, t= 12.43, P <0.001), Dec.F-measure (72.1038 ± 33.2592 vs. 58.5040 ± 38.0276, t= 4.10, P <0.001), SI (34.8277±20.9595 vs. 54.8049 ± 25.0265, t=-9.39, P <0.001), and MADI (3.1741 ± 1.9901 vs. 3.7289 ± 2.7253, t= -2.74, P= 0.012). The proposed CTGNet thus had significant advantages over the best traditional method on all evaluation metrics. Conclusion::The proposed Artificial Intelligence-based method CTGNet delivers good performance in terms of the automatic analysis of FHR based on cardiotocograph data. It promises to be a key component of smart obstetrics systems of the future.

Objective To compare the efficacy and safety of 2 mg/d and 4 mg/d of terazosin in the treatment of benign prostatic hyperplasia (BPH) with lower urinary tract symptoms (LUTS).Methods A total of 120 BPH patients were randomly divided into 2 groups receiving 2 mg or 4 mg terazosin per day for 2 months. Arterial blood pressure, International Prostatic Symptom Score (IPSS) and peak flow rate (Qmax) before and after treatment were compared while side effects were estimated. Results Forty-six patients receiving 2 mg and 54 patients receiving 4 mg terazosin completed this study. Patients' age and pre-treatment blood pressure, IPSS and Qmax had no difference between the 2 groups. The improvement of IPSS (including obstructive score, irritating score and total IPSS) and Qmax was significantly better in 4 mg group. The percentage of patients experiencing greater than 30% improvement in Qmax in the 4 mg treatment groups was significantly higher than that of the 2 mg group (46.3% vs 23.9%, P=0.02). Side effects were rare and mild in both groups.Conclusion The improvements of IPSS and Qmax are significantly greater in 4 mg treatment of terazosin than that of 2 mg with no obvious increase of side effects.

In recent years,using stem cells to repair the bladder defect is a hot issue on the studies of bladder tissue engineering.They are ideal seed cells for bladder regeneration of tissue engineering depending on their self-renewal and multi-differentiation potential.In this paper,we give a review on the use of embryonic stem cells and adult stem cells as seed cells to repair the bladder defect by tissue engineering approach.

Objective To study the the causes, management and preventive measures for complications of holmium laser ureterolithotripsy. Methods Three hundred and seven cases of uteteral calculi from Jan. 2006 to Jan. 2010 were reported (203 men and 104 women, age ranged from 18-83 years,mean age 51.6 years). One hundred thirty-three patients had calculi in the lower ureter,94 in the middle part and 80in the upper ureter. Results The overall comminution rate was 89.9% (276/307 cases). sixteen cases (5.2%) were followed by ESWL due to the shift of the stones to the renal pelvis. The operation failed in 9 cases(2.9%), 3 cases(1%) had perforation,and recoveried after open operation. Deep infection was found in 3(1%)cases,which recoveried after anti-infective therapy. Conclusions Holmium laser ureterolithotripsy is an effective method for treating ureteral calculi, with advantage of high efficiacy,safety and minimal invasion. To master the operating induction, to raise operating technique and to take correct measure could reduce complications effectually.