Study on the construction of nomogram prediction model for prognostic assessment of heart failure patients based on serological markers and echocardiography

OBJECTIVE

We aimed to construct a nomogram prediction model for prognostic assessment of patients with heart failure (HF) based on serological markers and echocardiography.

PATIENTS AND METHODS

A total of 200 HF patients admitted to the Second Affiliated Hospital of Nanchang University from January 2018 to January 2020 were selected as the research objects. According to the New York Heart Association (NYHA) cardiac function classification, they were divided into 3 groups, including 65 cases of grade II, 97 cases of grade III, and 38 cases of grade IV. Three groups of echocardiographic parameters were compared [including left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), left ventricular end-systolic volume (LVESV)], differences in serum markers brain natriuretic peptide (BNP), soluble growth-stimulating expression gene 2 (sST2) and the Modified Early Warning Score (MEWS). The patients were divided into two groups according to their clinical outcomes during the follow-up period, including 52 cases in the death group and 148 cases in the survival group. The clinical data of the two groups were compared, and multi-factor logistic regression analysis was performed to screen out the independent risk factors affecting the patient's death. A nomogram model of the patient's mortality risk was constructed based on the independent risk factors. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the discrimination and accuracy of the nomogram model.

RESULTS

As the cardiac function class of elderly chronic heart failure (CHF) patients increases, LVEDD, LVESD, sST2, and MEWS increase and LVEF decreases (p<0.05). Multifactor analysis results showed that LVEF, LVEDD, sST2, and MEWS were independent factors affecting the clinical outcome of patients. The AUCs predicted using LVEF, LVEDD, sST2, and MEWS alone were 0.738, 0.775, 0.717, 0.831, and 0.768, respectively. There is a certain degree of discrimination, and the model has extremely high accuracy.

CONCLUSIONS

MEWS, LVEDD, and sST2 increase as the NYHA cardiac function grade of HF patients increases and LVEF decreases, which can reflect the severity of the disease to a certain extent. Additionally, the nomogram model established based on this has a high predictive value for the long-term prognosis of patients and can formulate effective intervention measures for quantitative values.

[Visualization analysis of research hotspots in pathogenesis of diabetic nephropathy in China]

The aim of this study is to analyze the research hotspots and development trends in the field of pathogenesis of diabetic nephropathy in China from 2013 to 2022. Based on China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Science and Technology Journal Database, China Biology Medicine disc, Web of Science core collection and PubMed database, the related literatures in the field of pathogenesis of diabetic nephropathy in China from 2013 to 2022, were retrieved to establish the database, and the VOSviewer software was used for bibliometric analysis. A total of 1 664 Chinese and 2 149 English literatures are included in this study. The scientific research results from 2013 to 2022 have shown an overall increasing trend. The research hotspots in the field of pathogenesis of diabetic nephropathy in China are mainly concentrated in Podocytes, Oxidative stress, Inflammation, Renal fibrosis, Urine protein, etc. The frontier hotspots in this field include Biomarkers, Nrf2, Gut microbiota, NLRP3 inflammasome, Apoptosis, MicroRNA, etc. Through visual analysis, the research hotspots and frontier trends of the pathogenesis of diabetic nephropathy in China can be visually presented, and then provide new ideas and directions for the further in-depth research on the pathogenesis of diabetic nephropathy.

Multiclass CBCT Image Segmentation for Orthodontics with Deep Learning

Accurate segmentation of the jaw (i.e., mandible and maxilla) and the teeth in cone beam computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment planning. Although various (semi)automated methods have been proposed to segment the jaw or the teeth, there is still a lack of fully automated segmentation methods that can simultaneously segment both anatomic structures in CBCT scans (i.e., multiclass segmentation). In this study, we aimed to train and validate a mixed-scale dense (MS-D) convolutional neural network for multiclass segmentation of the jaw, the teeth, and the background in CBCT scans. Thirty CBCT scans were obtained from patients who had undergone orthodontic treatment. Gold standard segmentation labels were manually created by 4 dentists. As a benchmark, we also evaluated MS-D networks that segmented the jaw or the teeth (i.e., binary segmentation). All segmented CBCT scans were converted to virtual 3-dimensional (3D) models. The segmentation performance of all trained MS-D networks was assessed by the Dice similarity coefficient and surface deviation. The CBCT scans segmented by the MS-D network demonstrated a large overlap with the gold standard segmentations (Dice similarity coefficient: 0.934 ± 0.019, jaw; 0.945 ± 0.021, teeth). The MS-D network–based 3D models of the jaw and the teeth showed minor surface deviations when compared with the corresponding gold standard 3D models (0.390 ± 0.093 mm, jaw; 0.204 ± 0.061 mm, teeth). The MS-D network took approximately 25 s to segment 1 CBCT scan, whereas manual segmentation took about 5 h. This study showed that multiclass segmentation of jaw and teeth was accurate and its performance was comparable to binary segmentation. The MS-D network trained for multiclass segmentation would therefore make patient-specific orthodontic treatment more feasible by strongly reducing the time required to segment multiple anatomic structures in CBCT scans.

Pathologic characteristics and prognosis of a rare advanced cervical cancer treated with radical surgery and radiotherapy

OBJECTIVE

To assess the prognosis of rare advanced.cervical carcinoma with post-radical-radiation surgery and to compare the clinic value between further surgery treatment group and non-surgery group after radical radiation therapy.

MATERIALS AND METHODS

From January 2002 to July 2010 there were 68 patients with advanced stage cervical carcinoma retrospectively analysed in Maternal and Child Health Hospital of Jiangxi Province. All patients were confirmed by histopathology before treatment, and clinical staging was based on updated 2009 FIGO staging. All patients were Stage Ib2 (local advanced) and more severe. There were 36 patients (29 adenocarcinoma (AC), six adenosquamous carcinoma (ASC), and one undifferentiated carcinoma) classified into observation group that was treated with radical radiation therapy + surgery (total hysterectomy + bilateral salpingo-oophorectomy); other 32 patients (26 AC, five ASC, and one undifferentiated carcinoma) classified into control group that was treated with radical radiation therapy with no further surgery. The radical radiation therapy included external-beam radiation and intracavitary therapy, standard point A dose added up to 85 Gy (these doses are recommended for most patients based on summation of conventional external-beam fractionation and low-dose rate 40-70 cGy/h brachytherapy equivalents), and 45-55 Gy was given to point B. All of the patients were followed up. The average follow-up time was 65.6 months and the survival rate between two groups were compared and analyzed whether there was residual lesion, metastasis, lymph vascular space invasion (LVSI) in the observation group.

RESULTS

In observation group there were 15 patients found positive. The positive rate was 41.7% (15/36), in which there nine cases with LVSI and residual foci, four cases with uterus invasion, and one case with only residual foci. Both of the two groups were followed up and the average follow-up time was 65.6 months (range 36-136). In observation group there were 25 cases that have survived until now and the average survival time was 66.6 months (range 36-136). Eleven patients died with an average survival time of 10.4 months (range 2-37). In control group there are 22 cases that survived until now (July 2013); the average survival time was 64.4 months (range 36-136). Ten patients died with an average survival time of 10.3 months (range 3-28). Three cases experienced serious complication in observation group and two cases in control group. There was no significant difference in survival time between the two groups.

CONCLUSION

Due to low efficacy results, post-radical-radiation surgery is not a feasible treatment regimen for rare advanced cervical carcinoma.

Angiotensin-converting enzyme polymorphisms and risk of spontaneous deep intracranial hemorrhage in Taiwan

BACKGROUND AND PURPOSE

This study examines whether angiotensin-converting enzyme (ACE) gene polymorphisms are associated with the risk of spontaneous deep intracerebral hemorrhage (SDICH) in Taiwan using a case-control study.

METHODS

Totally, 217 SDICH patients and 283 controls were recruited. Associations of ACE A-240T and ACE I/D polymorphisms with SDICH were examined under the additive model and adjusted for gender, age, body mass index, total cholesterol level, smoking history, alcohol use, hypertension, and use of ACE inhibitors.

RESULTS

Hypertension, diabetes mellitus, family history of spontaneous intracerebral hemorrhage (SICH), and low cholesterol level increase risk of female SDICH, whereas hypertension, alcohol use, smoking history, family history of SICH, and low cholesterol level are an important risk factor for male SDICH. After adjusting for covariates, only haplotype ACE T-D (OR = 2.7, 95% CI, 1.1-6.5, P = 0.02) was associated with female SDICH.

CONCLUSIONS

This study demonstrates that environmental risk factors play a major role and ACE polymorphisms play a minor role in contributing risk of SDICH in Taiwan.