BACKGROUND: Previous evidence showed that ambient air pollution and cardiovascular mortality are related. However, there is a lack of evidence towards the modification effect of long-term lifestyle on the association between short-term ambient air pollution and death from cardiovascular events. METHOD: A total of 14,609 death from major adverse cardiovascular events (MACE) were identified among the China Kadoorie Biobank participants from 2013 to 2018. Ambient air pollution exposure including particulate matter 2.5 (PM_2.5), SO₂, NO₂, CO, and O₃ from the same period were obtained from space-time model reconstructions based on remote sensing data. Case-crossover design and conditional logistic regression was applied to estimate the effect of short-term exposure to air pollutants on MACE mortality. RESULTS: We found MACE mortality was significantly associated with PM_2.5 (relative percent increase 2.91% per 10 µg/m³ increase, 95% CI 1.32-4.53), NO₂ (5.37% per 10 µg/m³ increase, 95% CI 1.56-9.33), SO₂ (6.82% per 10 µg/m³ increase, 95% CI 2.99-10.80), and CO (2.24% per 0.1 mg/m³ increase, 95% CI 1.02-3.48). Stratified analyses indicated that drinking was associated with elevated risk of MACE mortality with NO₂ and SO₂ exposure; physical inactivity was associated with higher risk of death from MACE when exposed to PM_2.5; and people who had balanced diet had lower risk of MACE mortality when exposed to CO and NO₂. CONCLUSIONS The study results showed that short-term exposure to ambient PM_2.5, NO₂, SO₂, and CO would aggravate the risk of cardiovascular mortality, yet healthy lifestyle conduct might mitigate such negative impact to some extent.
Humans ; Cardiovascular Diseases/epidemiology* ; China/epidemiology* ; Male ; Female ; Air Pollution/adverse effects* ; Middle Aged ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; Environmental Exposure/adverse effects* ; Life Style ; Aged ; Adult ; Risk Factors ; Cross-Over Studies ; East Asian People

Objective:To investigate the clinical characteristics and offer diagnostic and therapeutic approaches for adult-onset idiopathic hypogonadotropic hypogonadism(AIHH).Methods:Clinical, laboratory, and imaging data, as well as follow-up information, of three male patients diagnosed with AIHH at the Department of Endocrinology and Metabolism of Nanfang Hospital, Southern Medical University, were systematically reviewed and analyzed.Results:All three patients were male, with a median age of 39 years(range, 22 to 40). Two patients reported symptoms of enlarged breasts and reduced sexual function, while one case solely reported a decline in sexual function. Physical examination showed that the median length of the penis was 6 cm(range, 5 to 6 cm), and the bilateral testicular volume was 7.96 mL(4.70-8.82 mL). Basal hormone levels at the time of initial visit to our hospital as follows: the median testosterone level was 0.32 ng/mL(0.24-2.96 ng/mL), median follicle stimulating hormone(FSH) level was 0.56 mIU/mL(0.1-0.75 mIU/mL), and the median luteinizing hormone(LH) level was 0.69 mIU/mL(0.1-1.03 mIU/mL). The levels of other hormones secreted by the anterior pituitary gland were normal. Hypothalamic-pituitary magnetic resonance imaging(MRI) showed that 1 patient had a pituitary microadenoma. Three patients were treated with pulsatile GnRH or gonadotropins, one of which had hypothalamic-pituitary-gonadal(HPG) axis function reversal after GnRH pulse pump therapy and lasted for 1 year, but then still had irreversible reduction.Conclusion:AIHH is marked by adult-onset disease and idiopathic hypogonadism. Enhancing fertility remains a critical requirement for these patients. Pulsatile GnRH treatment or gonadotropin therapy, as viable treatments, exhibit therapeutic effects, albeit with occasional fluctuations. Therefore, the emphasis lies in the timely consideration of fertility preservation.

Objectives:To analyze the safety of coronary artery stent rotational atherectomy due to stent underexpansion,in-stent restenosis,stent deformation,stent damage,and guide wire entrapment. Methods:A total of 19 patients with coronary artery disease who underwent coronary artery stent rotational atherectomy for the above reasons in 7 large heart centers in China from 2016 to 2022 were collected.Their baseline data,procedure process data,procedural complications,the occurrence of procedure-related adverse events(type 4a myocardial infarction,emergency coronary artery bypass grafting,and all-cause death)during hospitalization and major adverse cardiovascular events(MACE,including target vessel revascularization,stroke,all-cause death,and recurrent myocardial infarction)during post-discharge follow-up were retrospectively collected. Results:The mean age of the 19 patients was 70(64,73)years,and 13 patients were males.The mean left ventricular ejection fraction was(56.89±8.76)%.Radial artery approach was used in 13 patients,11 patients used 1 burr during the intervention period,6 patients used 2 burrs,and 2 patients used 3 burrs.The average times of burr passing through the lesion was(7.00±4.23)times.The surgical success rate was 100%,and the immediate lumen acquired area was(1.23±0.78)mm2.Drug-eluting stents were successfully implanted in all patients after spinning.Coronary slow blood flow occurred in 1 case after rotational grinding,which was improved after drug treatment.The burr was entrapmented in 3 cases and successfully pulled out after operation.No coronary artery perforation,coronary artery dissection,coronary artery spasm,emergency thoracotomy,or death occurred during the operation,and no procedure-related adverse events occurred during hospitalization.During 3 to 24 months of follow-up,1 patient underwent target vessel revascularization,and there were no MACE in other patients. Conclusions:Coronary artery stent rotational atherectomy in patients with stent underexpansion,in-stent restenosis,stent deformation,stent damage,and guide wire entrapment,is a feasible option,with a high surgical success rate and satisfactory safety.None of the patients experienced MACE during long-term follow-up.

Complete androgen insensitivity syndrome(CAIS) is characterized by lack of androgen response in target organs due to androgen receptor dysfunction, resulting in feminized external genitalia. Individuals with CAIS are typically advised to live as females. This article reports a patient diagnosed with CAIS and gender dysphoria in adulthood. Following the removal of a left pelvic mass, pathology indicated cryptorchidism with a concurrent Leydig cell tumor. Genetic testing revealed a deletion mutation in exon 3 of androgen receptor gene. During follow-up, the patient underwent gender reassignment, transitioning socially from female to male. This case provides new insights into gender allocation for CAIS patients.

Objective:To evaluate the role of histogram analysis based on amide proton transfer weighted (APTw) and apparent diffusion coefficient (ADC) imaging in predicting alpha-thalassemia/mental retardation syndrome X-linked ( ATRX) mutation in isocitrate dehydrogenase ( IDH)-mutant WHO grading 2/3 gliomas. Methods:Seventy-eight patients with IDH-mutant WHO grading 2/3 gliomas, admitted to and confirmed by surgical pathology in Department of Functional Neurosurgery, Neurosurgery Center, Zhujiang Hospital, Southern Medical University from June 2017 to October 2023, including 52 with ATRX wild and 26 with ATRX mutant-type, were selected. Preoperative 3D-APTw and ADC imaging data were collected; after post-processing, the lesions were segmented using lesion outlining method based on inclusion of peri-tumor edema and lesion outlining method based on tumor entity, respectively; after that, the histogram features (the 10 th percentile, 90 th percentile, maximum, mean, median, minimum, skewness, kurtosis, entropy, range, uniformity, and variance) were extracted from 3D-APTw and ADC imaging, respectively. Univariate Logistic regression was used to compare the differences in histogram features between patients in the ATRX mutant group and ATRX wild-type group, and multivariate Logistic regression was used to screen the independent predictors for ATRX mutation (a Logistic regression prediction model was constructed). Predictive values of independent predictors and Logistic regression prediction models in ATRX mutation were evaluated by receiver operating characteristic (ROC) curve. Results:(1) With lesion outlining method based on inclusion of peri-tumor edema, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw minimum, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity, and ADC entropy ( P<0.05). With lesion outlining method based on tumor entity, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw 90 th percentile, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity and ADC entropy ( P<0.05). (2) With lesion outlining method based on inclusion of peri-tumor edema, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were the independent predictor for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.168, 95% CI: 0.034-0.800, P=0.025; OR=0.508, 95% CI: 0.319-0.807, P=0.004). The constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.827-1.785×3D-APTw skewness-0.678×ADC kurtosis). With lesion outlining method based on tumor entity, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were independent predictors for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.164, 95% CI: 0.034-0.791, P=0.024; OR=0.496, 95% CI: 0.312-0.788, P=0.003); the constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.585-1.810×3D-APTw skewness-0.702×ADC kurtosis). (3) ROC curve analysis showed that, with lesion outlining method based on inclusion of peri-tumor edema, area under ROC curve (AUC) of 3D-APTw skewness and ADC kurtosis was 0.725 (95% CI: 0.608-0.842, P=0.001) and 0.794 (95% CI: 0.685-0.904), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.836 (95% CI: 0.729-0.942, P<0.001), and its sensitivity and specificity were 73.10% and 90.40% when the best threshold was 0.505. ROC curve showed that, with lesion outlining method based on tumor entity, AUC of 3D-APTw skewness and ADC kurtosis was 0.705 (95% CI: 0.587-0.823, P=0.003) and 0.808 (95% CI: 0.704-0.913), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.844 (95% CI: 0.739-0.949, P<0.001), and its sensitivity and specificity were 84.60% and 80.80% when the best threshold was 0.399. Conclusion:Histogram analysis based on 3D-APTw and ADC imaging can predict ATRX mutation in IDH mutant WHO grading 2/3 gliomas to a certain extent.

Objective:To improve work efficiency and reduce errors through intelligent pre-analytical process reengineering.Methods:Tumor and infection marker test samples from outpatients at Peking University Shenzhen Hospital from December 2021 to February 2023 were collected. The process was integrated with sample transportation, sample sorting and secondary transfer, and laboratory automation systems, while achieving full-process information monitoring. The number of manual intervention nodes, the turnaround time (TAT) from sample collection to testing and from collection to reporting, the proportion of intelligent pre-dilution, and the number of pre-analytical errors automatically identified were compared before and after the intelligent pre-analytical process reengineering to evaluate the effect of the reengineering. Chi-square test, Fisher′s exact probability method, and Mann-Whitney U test were used for statistical analysis.Results:After implementing the intelligent process reengineering, the number of manual intervention nodes has been reduced from 13 to 2. For outpatient tumor marker samples, after the first stage of reengineering, the median TAT from collection to reporting decreased from 185 (141, 242) min to 137 (102, 183) min ( Z=-54.932, P<0.001). After the second stage of reengineering, the median TAT from collection to reporting further decreased from 137 (102, 183) min to 100 (64, 150) min ( Z=-61.346, P<0.001). For infection marker samples, after the first stage of reengineering, the median TAT from collection to reporting decreased from 392 (282, 1386) min to 229 (176, 323) min ( Z=-68.636, P<0.001). After the second stage of reengineering, the median TAT from collection to reporting further decreased from 229 (176, 323) min to 160 (110, 236) min ( Z=-62.15, P<0.001). Conclusion:Intelligent pre-analytical process reengineering can optimize workflows, improve efficiency, and reduce errors.

We report a case of functional parathyroid cyst treated by ultrasound-guided anhydrous ethanol sclerotherapy and microwave ablation. The 63-year-old female patient was diagnosed to have functional parathyroid cyst with hypercalcemia, high PTH and cystic space-occupying lesions in the neck by ultrasound, radionuclide scanning and PTH measurement of the cystic fluid. The patient refused to receive cyst resection, and anhydrous ethanol sclerotherapy with microwave ablation was performed under ultrasound guidance. The procedure was completed smoothly without any complications either during or after the operation. Follow-up examination of the patient at 18 months after the operation showed a significant reduction of the mass and normal blood calcium and iPTH levels, demonstrating a clinical cure of the patient. Ablative treatment of functional parathyroid cyst has not been documented so far. This approach provides a minimally invasive treatment modality for such cases where surgical resection is not an option, but its efficacy and safety need to be evaluated in more cases with longer follow-up time.
Female ; Humans ; Middle Aged ; Microwaves/therapeutic use* ; Plastic Surgery Procedures ; Cysts ; Ethanol/therapeutic use* ; Ultrasonography, Interventional

OBJECTIVE: To develop a noninvasive method for prediction of 1p/19q codeletion in diffuse lower-grade glioma (DLGG) based on multimodal magnetic resonance imaging (MRI) radiomics. METHODS: We collected MRI data from 104 patients with pathologically confirmed DLGG between October, 2015 and September, 2022. A total of 535 radiomics features were extracted from T₂WI, T₁WI, FLAIR, CE-T₁WI and DWI, including 70 morphological features, 90 first order features, and 375 texture features. We constructed logistic regression (LR), logistic regression least absolute shrinkage and selection operator (LRlasso), support vector machine (SVM) and Linear Discriminant Analysis (LDA) radiomics models and compared their predictive performance after 10-fold cross validation. The MRI images were reviewed by two radiologists independently for predicting the 1p/19q status. Receiver operating characteristic curves were used to evaluate classification performance of the radiomics models and the radiologists. RESULTS: The 4 radiomics models (LR, LRlasso, SVM and LDA) achieved similar area under the curve (AUC) in the validation dataset (0.833, 0.819, 0.824 and 0.819, respectively; P>0.1), and their predictive performance was all superior to that of resident physicians of radiology (AUC=0.645, P=0.011, 0.022, 0.016, 0.030, respectively) and similar to that of attending physicians of radiology (AUC=0.838, P>0.05). CONCLUSION Multiparametric MRI radiomics models show good performance for noninvasive prediction of 1p/19q codeletion status in patients with in diffuse lower-grade glioma.
Humans ; Magnetic Resonance Imaging ; Chromosome Aberrations ; Area Under Curve ; Glioma/genetics* ; ROC Curve

Objective:To construct a diabetic foot classification prediction model based on radiomics features of fundus photographs.Methods:A total of 2 035 fundus photographs of patients with type 2 diabetes diagnosed at Nanfang Hospital between December 2011 and December 2018 were retrospectively collected [282 photographs from patients with diabetic foot(DF), and 1 753 from patients with diabetes mellitus(DM)]. All fundus photographs were randomly divided into a training set(1 424 photos) and a test set(611 photos) using a computer generated random number at 7∶3. After pre-processing the fundus photographs, a total of 4 128 texture features based on the gray matrix were extracted by the Radiomic toolkit, and 11 339 other features were extracted using the ToolboxDESC toolkit. The LASSO algorithm was used to select the 30 features most relevant to DF, and then the Bootstrap + 0.632 self-sampling method was used to further select the 7 best combinations. Logistic regression analysis was used to obtain the regression coefficients and establish the final diabetic foot classification prediction model. ROC curve was drawn, and AUC, sensitivity, specificity, and accuracy of the training and test sets were calculated to verify its prediction performance. Results:We screened 7 fundus radiomics markers for diabetic foot patients, and based on this established a DF/DM classification prediction model. The AUC, sensitivity, specificity, and accuracy of the model were 0.958 6, 0.984 0, 0.920 0, and 0.928 0 in the training set, and 0.927 1, 0.988 9, 0.881 0, and 0.896 9 in the test set, respectively.Conclusion:In this study, seven DF fundus markers were screened using radiomics technology. Based on this, a highly accurate and easy-to-use DF/DM classification model was constructed. This technology has the potential to increase the efficiency of DF screening programs.