Objective:To explore the clinical application value of sentinel lymph node biopsy (SLNB) in patients with early breast cancer after local excision surgery.Methods:A total of 93 breast cancer patients with clinical stage T is/T 1-2N 0M 0 who underwent SLNB and were confirmed by using tumor mass excision biopsy from March 2012 to November 2018 in Shanxi Bethune Hospital were retrospectively analyzed. According to the postoperative paraffin pathology, the patients who were successfully detected sentinel lymph node (SLN) were divided into SLN-positive group with metastasis or SLN-negative group without metastasis. The clinicopathological data were used to analyze influencing factors of SLN metastasis and SLN detection number after excision biopsy of breast masses in the two groups. Results:A total of 87 out of 93 patients were successfully detected SLN and the detection rate was 93.5% (87/93). A total of 255 SLN were detected, and the average number was 2.93 in per patient. All were subjected to rapid intraoperative freezing pathological, and 11 cases with positive SLN were detected. There were 17 patients who underwent axillary lymph node dissection (ALND), including 11 cases with positive SLN and 6 cases with SLN undetected. The paraffin pathology showed that 14 patients were confirmed as positive SLN, including 13 macrometastasis and 1 micrometastasis. The SLN false negative rate was 2.1% (3/14) of intraoperative frozen diagnosis. Univariate analysis showed that histological grade and intravascular thrombus of carcinoma were associated with SLN metastasis after breast cancer local excision; the number of SLN detection was effected by body mass index and staining method; the methylene staining method combined with radionuclide method could improve the detection rate of SLN (all P < 0.05). Multivariate analysis showed that the SLN non-detection of obesity patients was 2.651 times as much as that of normal patients (95% CI 1.592-8.194, P=0.010). Conclusion:The SLNB and appropriate tracer method will have a high SLN detection rate and better clinical application value for early breast cancer patients after breast mass resection.

Objective:To investigate the correlation between mental health and symptom distress in breast cancer patients.Methods:The clinical data of 110 female breast cancer patients at Shanxi Bethune Hospital from June 2017 to March 2018 were collected. The patients were assessed for symptomatic distress with depression self-rating scale (SDS). Functional assessment of cancer therapy-breast (FACT-B) and the functional assessment of chronic illness therapy-spiritual well-being (FACIT-SP) were used to make the mental assessment. Multiple linear regression analysis was used to analyze the effect of symptom distress on the mental health of the patients.Results:The scores of symptom distress, mental health, FACT-B and FACIT-SP were (19.94±5.78), (50.68±10.64), (16.85±4.75), (33.83±8.33), respectively. Multivariate analysis showed that mental health score of the patients with symptom distress > 18 scores was reduced by 5.15 points ( P=0.01) compared with the patients with symptom distress≤18 scores. Compared with the patients with annual household income < 50 000 yuan, the mental health score of patients with annual household income of 50 000-79 000 yuan was increased by 9.46 points ( P < 0.01), and the mental health score of patients with annual family income ≥ 80 000 yuan was increased by 5.92 points ( P < 0.01); compared with the patients in phase I, the mental health score of the patients in phaseⅡwas decreased by 2.62 points ( P=0.02), and the mental health score of the patients in phase Ⅲ was decreased by 4.98 points ( P < 0.01). Conclusions:Symptom distress is an independent risk factor for affecting mental health of breast cancer patients. Solving symptom distress of patients can improve mental health status of the patients.

By collecting and analyzing the explanation/conception, acupoint name, acupoint location, indications, acupuncture and moxibustion techniques and contraindications of
Acupuncture ; Acupuncture Points ; Acupuncture Therapy ; Humans ; Meridians ; Moxibustion

Objective:To explore the changes in acoustic features of 9-10-year-old primary school students with depressive symptoms, and based on these features and the random forest (RF) algorithm, construct a model for identifying depressive symptoms in primary school students, so as to provide an intelligent psychological health screening tool for schools and education departments.Methods:This was a case-control study.A total of 1 186 primary school students aged 9-10 from three primary schools in three regions of Jiangsu Province were selected as research subjects for psychological health screening from October 26, 2022 to February 13, 2023.Their demographic data, Depression-Anxiety-Stress Scale (DASS-21) scores, Insomnia Severity Index scores, and voice recordings were collected.Based on the DASS-21 scores, the participants were divided into a control group ( n=1 086) and a depression group ( n=100).Voice recordings were made using the neutral text " The North Wind and the Sun". openSMILE was used to extract 523 acoustic features from the pre-processed voice recordings.Group differences were assessed using independent-samples t-tests or chi-square tests.Pearson correlation analysis was conducted to examine the relationship between acoustic features and depression scores.Depressive symptoms were set as the dependent variable, and the correlated acoustic features were set as the independent variable to construct a classification model using the RF algorithm.The model performance was assessed using the receiver operating characteristic (ROC) curve, the area under the curve (AUC), precision, accuracy, recall, and F1 score. Results:Compared with the control group, the depression group showed significant differences in 105 acoustic features (44 spectral features, 49 source features, and 12 prosodic features) (all P<0.05).Correlation analysis showed that 12 acoustic features (7 spectral features, 4 source features, and 1 prosodic feature) were significantly correlated with the depression score (all P<0.05).Among the RF algorithm-based classification models, the spectral features demonstrated superior performance compared to source features and prosodic features (AUC=0.793), and the performance of the model based on the combination of these features was the best (AUC=0.818). Conclusions:Acoustic features may be an objective indicator to identify the depression of 9-10-year-old primary school students, and the classification model established based on acoustic features can identify the depressed primary school students.

Objective To compare the value of central venous pressure (CVP) measured by peripherally inserted central catheters (PICC) and centrally inserted central catheters (CICC) in elderly patients with severe diseases.Methods Paired design and self-controlled was applied in the research. CVP was measured by 2 different measurement approaches in patients with PICC and CICC simultaneously. The sample size was calculated by the enumeration method through the accuracy estimation of consistency evaluation of quantitative measurement, and the required number was 70.Results Among the 70 collected samples, the mean values of the measured CVP by PICC and CICC were (7.995±3.435) cmH2O and (7.743±3.277) cmH2O; no statistically significant difference was observed (t=1.622,P=0.109). The pearson's linear correlation coefficient of the CVP measured by 2 different measurement approaches was 0.926 (P<0.0001). A linear regression model through the origin of the CVP measured by 2 different measurement approaches was fitted with the linear regression equation of CVPPICC=1.023 CVPCICC (R2=0.978); and the 95%CI of the prediction line contained the reference line. The Bland-Altman plot showed that 64 samples fell within limits of agreement (LoA), LoA was -2.300-2.804, with a consistent rate of 91.43%. All the plots out of the LoA did not exceeded the 95%CI.Conclusions The CVP measured by CICC and PICC exhibit high consistency. Therefore, PICC can be used to replace the CICC in the CVP monitoring.