Objective To longitudinally investigate the characteristics of postoperative weight changes in patients with esophageal cancer and analyze its influencing factors, which can provide certain guidance for nutritional intervention in patients with esophageal cancer. Methods Patients with esophageal cancer who underwent surgical treatment at the Sichuan Cancer Hospital from December 2020 to February 2022 were prospectively included. The general information questionnaire and body composition analyzer were used to longitudinally investigate the patients’ weight and body composition before surgery (T0), 1 month after surgery (T1), 3 months after surgery (T2) and 6 months after surgery (T3), and the change characteristics were analyzed. The generalized estimating equation was used to analyze the influencing factors for postoperative weight changes in patients with esophageal cancer. Results A total of 130 patients were enrolled, including 110 males and 20 females, aged 42-79 (63.33±8.16) years. The weight and body composition of patients with esophageal cancer showed a continuous slow downward trend within 6 months after surgery. The weight loss rate of patients at 1, 3, and 6 months after surgery was 5.10%, 7.76%, and 9.86%, respectively. The analysis results of the influencing factors for postoperative weight showed that patients with the following characteristics had more weight loss: female (β=−7.703, P=0.001), ≥60 years (β=−3.657, P=0.010), smoking (β=4.622, P=0.010), low tumor differentiation degree (β=4.314, P=0.039), and high frequency of eating (β=−3.400, P=0.008). Conclusion Weight loss is an important health problem for patients with esophageal cancer after surgery, and patients have a continuous downward trend in weight within 6 months after surgery. Medical staff should pay special attention to the patients who are female, ≥60 years, having smoking history and low tumor differentiation degree.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion. METHODS: The proposed model consists of the Input, Backbone Network and Classification Head modules. The Input module carries out data augmentation to improve the sample quality and generalization ability of the model. The Backbone Network was responsible for feature extraction based on Yolov8 combined with CBAM, ECA, PSA attention mechanism and AIFI feature interaction module. The Classification Head consists of a convolutional layer and a softmax function to output the final probability value of each class. The images of the key structures (the eyes, face, head, thalamus, and spine) were annotated with frames by physicians for model training to improve the classification accuracy of the anterior occipital, posterior occipital, and transverse occipital orientations. RESULTS: The experimental results showed that the proposed model had excellent performance in the tire orientation classification task with the classification accuracy reaching 0.984, an area under the PR curve (average accuracy) of 0.993, and area under the ROC curve of 0.984, and a kappa consistency test score of 0.974. The prediction results by the deep learning model were highly consistent with the actual classification results. CONCLUSIONS The multi-feature fusion model proposed in this study can efficiently and accurately classify fetal orientation in intrapartum ultrasound videos.
Humans ; Female ; Ultrasonography, Prenatal/methods* ; Pregnancy ; Fetus/diagnostic imaging* ; Neural Networks, Computer ; Video Recording

Objective:To explore the clinical effect of endoscopic radical thyroidectomy via three-port gasless intermuscular approach.Methods:This is a retrospective cohort study. The data of 148 patients who underwent radical thyroidectomy at the Fourth General Surgery Department of the Second Affiliated Hospital of Harbin Medical University from January to June 2024 were retrospectively analyzed. There were 31 males and 117 females,aging (43.5±9.6) years (range: 21 to 64 years). The surgical method was selected according to the needs and wishes of patients. Among them, 77 cases underwent endoscopic radical thyroidectomy via unilateral three-port gasless intermuscular approach (three-port gasless group),and 71 cases underwent unilateral conventional open radical thyroidectomy(open group). The surgical technique exploration curve of the three-port gasless group was drawn based on the operation time and the number of lymph node dissections,and the technical exploration period and the technical maturity period were divided. The clinical data of the cases in the three-port gasless group and the open group were compared during the technical maturity period. The independent sample t test was used to compare the quantitative data between the two groups, and the χ2 test or Fisher exact probability method was used to compare the categorical data, respectively. Results:According to the technical exploration curve,there were 11 cases in the technical exploration period of the three-port gasless group,and 66 cases in the technical maturity period. In the technical mature period,the injury rate of temporary recurrent laryngeal nerve in the three-port gasless group was 1.5% (1/65),and the number of lymph node dissections was 5.9±3.5(range:0 to 14),which was not statistically significant compared with 4.4% (3/68) and 5.8±3.7(range:0 to 16) in the open group (all P>0.05). In the technical mature period,the operation time of the three-port gasless group was (39.2±6.2)minutes(range:30 to 55 minutes) and the postoperative drainage volume was (57.6±11.8) ml(range:30 to 90 ml),which were lower than those of the open group((67.8±13.9) minutes (range: 30 to 105 minutes) and (82.9±22.4)ml(range:50 to 175 ml)),and the differences were statistically significant ( t=15.303, 8.177, both P>0.05). During the technical maturity period,the postoperative hospital stay in the three-port gasless group was (3.2±0.4)days(range:3 to 4 days), which was not statistically different from that of the open group((3.2±0.4)days(range:3 to 5 days))( P>0.05). The incision satisfaction of patients in the three-port gasless group one month after the operation was higher than that of the control group (100% vs. 62.0%) ( P<0.01). Conclusion:Compared with open surgery,endoscopic radical thyroidectomy via three-port gasless intermuscular approach has certain advantages in terms of operation time, postoperative drainage volume and patient cosmetic satisfaction.

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

Objective:To evaluate the diagnostic performance of the 0-2 h high-sensitivity cardiac troponin T (hs-cTnT) cutoff recommended by the guidelines for the rule-out and rule-in diagnosis of suspected non-ST-segment elevation myocardial infarction (NSTEMI) patients of different age groups.Methods:This is a retrospective cohort study. Clinical data of 4 050 suspected NSTEMI patients who visited the Chest Pain Center of Zhongshan Hospital affiliated with Fudan University from January 2020 to December 2021 were retrospectively analyzed. Patients who visited from January 2020 to April 2021 (2 650 patients) were included as derivation cohort, and those who visited from May to December 2021 (1 400 patients) were included as validation cohort. The diagnostic performance of the guideline-recommended hs-cTnT 0-2 h cutoff for the rule-out and rule-in of NSTEMI diagnosis was compared among subgroups of patients aged ≤60, >60-70, and >70 years in the derivation group. Rule-out sensitivity, negative predictive value, and rule-out proportion, rule-in specificity, positive predictive value, and rule-in proportion were assessed. Cutoffs were established for subgroups with relatively lower diagnostic performance and validated in the validation group. Major adverse cardiovascular events (MACE) within 30 days after patient visit were used as the outcome, and survival curves were plotted using Kaplan-Meier curves, log-rank tests were used to analyze the incidence of MACE.Results:The sensitivity for ruled-out NSTEMI using the guideline-recommended 0-2 h cutoff in the subgroups of patients aged ≤60, >60-70, and >70 years in the derivation group was 100%; the negative predictive value was 100%; the ruled-out rates were 47.6% (331/696), 45.9% (491/1 070), and 28.5% (252/884), respectively. The specificity for ruled-in NSTEMI was 88.3%, 90.9%, and 86.4%, respectively; the positive predictive values were 55.3%, 59.3%, and 58.2%, respectively; the ruled-in rates were 22.6% (157/696), 19.5% (209/1 070), and 27.0% (239/884), respectively. With a requirement of sensitivity and negative predictive value >99%, the ruled-out cutoff for the subgroup of patients aged >70 years in the derivation group was established as 0 h hs-cTnT <6 ng/L or 0 h hs-cTnT<22 ng/L and 0-2 h Δhs-cTnT <5 ng/L, which increased the ruled-out rate of the subgroup aged >70 years to 45.6% (403/884). In the validation group, 42.2% (196/465) patients could be ruled-out. The incidence of MACE within 30 days for ruled-out patients aged >70 years using the established cutoff was 0.Conclusion:The diagnostic performance for the ruled-out and ruled-in diagnosis using the guideline-recommended 0-2 h hs-cTnT cutoff are relatively consistent across different age groups, but the ruled-out rate for patients aged >70 years is lower than for those aged ≤60 and >60-70 years. The ruled-out cutoff established in this study can be used to improve diagnostic performance of thus indicator on suspected NSTEMI patients.

Objective:To systematically evaluate predictive models for stress urinary incontinence (SUI) in pregnant and postpartum women, providing a reference for model development, application, and promotion.Methods:A comprehensive literature search was conducted in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, and China Biology Medicine disc for studies on SUI predictive models in pregnant and postpartum women. The search period was from database inception to September 30, 2024. Two researchers independently screened the literature and extracted data according to inclusion and exclusion criteria. The risk of bias in the predictive models was assessed using the prediction model risk of bias assessment tool.Results:A total of 23 studies were included, covering 31 predictive models for SUI, with a combined sample size of 14 473 women. Among them, six models focused on predicting SUI in pregnant women, while 25 models were developed for postpartum SUI. The predictive factors identified in these models were categorized into nine groups, including: general information for pregnant and postpartum women, delivery data, neonatal data, past history, abortion history, lifestyle data, pelvic floor muscle screening results, 2D and 3D ultrasound data, and serological indicators. Among these, age, mode of delivery, parity, body mass index, history of SUI, and neonatal weight were widely recognized as key predictive factors. External validation was performed in five studies. Five studies showed good applicability and low bias risk, except for one study that had limitations in both bias risk and applicability, and the remaining studies exhibited a high risk of bias but demonstrated good applicability.Conclusions:The methodological quality of SUI predictive models for pregnant and postpartum women needs further improvement. External validation remains insufficient. Future model development should be based on large-sample, prospective studies, incorporating appropriate predictive factors and stratifying SUI risk in different populations to enhance clinical applicability.

Objective:To search, evaluate, and summarize evidence regarding strategies to promote pelvic floor muscle contraction (PFMC) function in postpartum women, providing a basis for clinical practice.Methods:A comprehensive search was conducted in computer decision support systems, guideline websites, relevant professional association websites, and English and Chinese databases for evidence related to strategies to promote PFMC function in postpartum women. The sources included guidelines, expert consensus, evidence summaries, systematic reviews, and original studies, with the search period from June 2014 to January 2025. Two researchers independently assessed the quality of the included articles and extracted data for the evidence summary.Results:A total of 24 articles were included: nine guidelines, five expert consensus, three evidence summaries, two systematic reviews, and five original studies. The evidence was summarized across four domains: screening and assessment, team building, intervention strategies, and outcome evaluation, resulting in 25 key pieces of evidence.Conclusions:This study summarizes the best evidence for strategies to promote PFMC function in postpartum women, providing scientific and rigorous evidence for clinical practice. It supports the development of effective training programs to enhance postpartum women's quality of life.

Objective:To systematically evaluate predictive models for stress urinary incontinence (SUI) in pregnant and postpartum women, providing a reference for model development, application, and promotion.Methods:A comprehensive literature search was conducted in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, and China Biology Medicine disc for studies on SUI predictive models in pregnant and postpartum women. The search period was from database inception to September 30, 2024. Two researchers independently screened the literature and extracted data according to inclusion and exclusion criteria. The risk of bias in the predictive models was assessed using the prediction model risk of bias assessment tool.Results:A total of 23 studies were included, covering 31 predictive models for SUI, with a combined sample size of 14 473 women. Among them, six models focused on predicting SUI in pregnant women, while 25 models were developed for postpartum SUI. The predictive factors identified in these models were categorized into nine groups, including: general information for pregnant and postpartum women, delivery data, neonatal data, past history, abortion history, lifestyle data, pelvic floor muscle screening results, 2D and 3D ultrasound data, and serological indicators. Among these, age, mode of delivery, parity, body mass index, history of SUI, and neonatal weight were widely recognized as key predictive factors. External validation was performed in five studies. Five studies showed good applicability and low bias risk, except for one study that had limitations in both bias risk and applicability, and the remaining studies exhibited a high risk of bias but demonstrated good applicability.Conclusions:The methodological quality of SUI predictive models for pregnant and postpartum women needs further improvement. External validation remains insufficient. Future model development should be based on large-sample, prospective studies, incorporating appropriate predictive factors and stratifying SUI risk in different populations to enhance clinical applicability.