OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

Objective To analyze the disease burden of early-onset colorectal cancer (EOCRC) at the global, regional, and national levels from 1990 to 2021, and to predict the disease burden trend from 2022 to 2026. Methods Based on the Global Burden of Disease (GBD) database, the incidence, mortality, and disability-adjusted life year (DALY) rate of EOCRC across 204 countries and regions from 1990 to 2021 were obtained. The time trends of these indicators were assessed by calculating the estimated annual percentage change (EAPC), and the contributions of ten risk factors to the EOCRC burden were analyzed. The autoregressive integrated moving average (ARIMA) model was used to predict the disease burden from 2022 to 2026. Results From 1990 to 2021, the number of new global EOCRC cases increased from 107 310 to 211 890, with the incidence rising from 3.96 to 5.37 per 100 000 people. In 2021, global EOCRC incidence, mortality, and DALY rate increased with age; males had higher rates than females in terms of incidence, mortality, and DALY rate in all age groups. In 2021, East Asia had the highest number of new cases, deaths, and DALY. From 1990 to 2021, the global EAPC for incidence rate was 0.96%, and death rate was –0.38%. ARIMA model indicated that from 2022 to 2026, the global incidence of EOCRC would continue to rise, while mortality and DALY rate would be expected to decline. Conclusions The disease burden of EOCRC has significantly increased globally from 1990 to 2021, with notable regional, age, and sex differences. By 2026, the mortality and DALY rate of EOCRC will decline, while the incidence is expected to further increase, highlighting the urgency of taking active measures to address the growing trend of EOCRC.

OBJECTIVE: To explore the clinical and genetic characteristics of two children diagnosed with two rare genetic diseases simultaneously. METHODS: Two children with comorbidity of two genetic diseases due to dual genetic mutations diagnosed at the Third Affiliated Hospital of Zhengzhou University respectively in May 2022 and March 2023 were selected as the study subjects. Clinical and genetic data of the two children were retrospectively analyzed. This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethic No. 2021-062-01). RESULTS: Child 1 was a 2-year-and-4-month-old boy whose clinical manifestations included facial dysmorphism, developmental delay, short stature, microcephaly, cleft palate, cryptorchidism, hypospadias, recurrent infections and immunological abnormalities. Whole exome sequencing revealed that he had harbored a heterozygous c.6595delT (p.Y2199Ifs*65) variant of the KMT2D gene and a heterozygous c.1892G>A (p.R631Q) variant of the PIK3R1 gene. This has led to a dual genetic diagnosis of Kabuki syndrome and PI3Kδ-related immunodeficiency type 36. Child 2 was a 15-year-old girl whose clinical manifestations included epilepsy, Albright's hereditary osteodystrophy, long body trunk, short limbs, hypocalcemia, hyperphosphatemia and hyperparathyroidism. The child also had a family history of short stature. Whole exome sequencing revealed that she had harbored a heterozygous c.2T>C (p.Met1?) variant of the GNAS gene and deletion of exons 2 to 6 of the SHOX gene. The two variants have led to dual diagnose of pseudohypoparathyroidism and X-linked idiopathic short stature. CONCLUSION When the clinical phenotype of a genetic disease is complex and cannot be fully explained with a single genetic variant, multiple pathogenic variants should be considered, and this may lead to the diagnosis of co-morbid genetic diseases. To adopt or supplement corresponding genetic testing in time and re-analyze the genetic data may facilitate accurate diagnosis of co-morbid genetic diseases.
Child, Preschool ; Female ; Humans ; Male ; Class Ia Phosphatidylinositol 3-Kinase/genetics* ; Comorbidity ; Exome Sequencing ; Mutation ; Rare Diseases/genetics* ; Retrospective Studies ; Adolescent

The advantages of few-shot learning in arrhythmia detection were introduced.The research progress of few-shot learning strategies,including metric learning,transfer learning and data augmentation,was reviewed when applied to arrhythmia detection.The limitations of few-shot learning in arrhythmia detection were analyzed.It was pointed out that the graph neural network and new incremental learning techniques would be involved in the future development of few-shot learning in arrhythmia detection.[Chinese Medical Equipment Journal,2025,46(8):104-112]

Objective:To explore the short-term clinical effects of deep cervical lymph node-venous anastomosis in the treatment of Alzheimer’s disease (AD).Methods:A prospective exploratory study was conducted on the treatment of AD patients using the cervical deep lymph node-venous anastomosis technique in Scar and Wound Treatment Department, Plastic Surgery Hospital, Chinese Academy of Medical Sciences, from September to October 2024. The patients underwent high-frequency ultrasound to locate deep cervical lymph nodes and the external jugular vein. Under general anesthesia, bilateral deep cervical lymph node-venous anastomoses were performed. Indocyanine green (ICG) lymphography was conducted via subcutaneous injection behind the ear to visualize lymph nodes in levels Ⅱ and Ⅲ. After making a skin incision along the posterior margin of the sternocleidomastoid muscle, the external jugular vein, internal jugular veins, and associated lymph nodes were exposed. Adjacent veins were selected for anastomosis of lymph node. Using microsurgical techniques, end-to-side or end-to-end anastomosis was completed for lymph nodes in levels Ⅱ and Ⅲ. Preoperative assessments included the mini-mental state examination (MMSE, a higher score indicates better cognitive function), Alzheimer’s disease assessment scale-cognitive subscale (ADAS-Cog, a higher score indicates greater impairment of cognitive function), Alzheimer’s disease cooperative study scale for activities of daily living (ADCS-ADL, a higher score indicates better ability to perform daily activity), and neuropsychiatric inventory (NPI, a higher score indicates more severe behavioral and emotional symptom). Postoperative follow-up included the same scales to observe changes in cognitive function, activities of daily living, and emotional communication.Results:Four patients (1 male, 3 females, aged 58-79 years) with AD were included. All were diagnosed based on cerebrospinal fluid biomarkers. All patients successfully underwent bilateral deep cervical lymph node-venous anastomoses. On average, 4.3 (2-7 per person) anastomoses were performed per patient. Surgical procedures lasted an average of 6.5 h (5.5-8.5 h) with minimal blood loss (less than 50 ml). Patients resumed normal activity within 6 hours postoperatively and were discharged after an average of 4.1 d (3.5-5.0 d). Postoperative complications included one case each of aspiration pneumonia, lower limb venous thrombosis, and transient delirium, all of whom resolved without long-term effects. Clinical symptoms, including memory decline, mood swings, and anxiety, showed varying degrees of improvement. Patients reported enhanced quality of life, emotional stability, and social engagement, confirming the procedure’s safety and potential cognitive benefits. At one month postoperatively, the MMSE scores of the four patients increased by an average of 0.8 points compared to preoperative levels. Additionally, the two patients who completed the ADAS-Cog assessments showed a decrease in their scores (reduced by 1.0 points and 11.3 points, respectively, compared to preoperative scores), indicating a certain degree of improvement in cognitive function during this period. The ADCS-ADL and NPI scores of four patients varied significantly, without showing any clear pattern.Conclusion:Lymphovenous anastomosis of the deep cervical lymph node-venous anastomosis may provide a new surgical intervention approach for AD, but further large-scale studies and long-term follow-up are needed to validate its safety and effectiveness.

Objective:To explore the clinical and genetic characteristics of two children diagnosed with two rare genetic diseases simultaneously.Methods:Two children with comorbidity of two genetic diseases due to dual genetic mutations diagnosed at the Third Affiliated Hospital of Zhengzhou University respectively in May 2022 and March 2023 were selected as the study subjects. Clinical and genetic data of the two children were retrospectively analyzed. This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethic No. 2021-062-01).Results:Child 1 was a 2-year-and-4-month-old boy whose clinical manifestations included facial dysmorphism, developmental delay, short stature, microcephaly, cleft palate, cryptorchidism, hypospadias, recurrent infections and immunological abnormalities. Whole exome sequencing revealed that he had harbored a heterozygous c.6595delT (p.Y2199Ifs*65) variant of the KMT2D gene and a heterozygous c. 1892G>A (p.R631Q) variant of the PIK3R1 gene. This has led to a dual genetic diagnosis of Kabuki syndrome and PI3Kδ-related immunodeficiency type 36. Child 2 was a 15-year-old girl whose clinical manifestations included epilepsy, Albright′s hereditary osteodystrophy, long body trunk, short limbs, hypocalcemia, hyperphosphatemia and hyperparathyroidism. The child also had a family history of short stature. Whole exome sequencing revealed that she had harbored a heterozygous c. 2T>C (p.Met1? ) variant of the GNAS gene and deletion of exons 2 to 6 of the SHOX gene. The two variants have led to dual diagnose of pseudohypoparathyroidism and X-linked idiopathic short stature. Conclusion:When the clinical phenotype of a genetic disease is complex and cannot be fully explained with a single genetic variant, multiple pathogenic variants should be considered, and this may lead to the diagnosis of co-morbid genetic diseases. To adopt or supplement corresponding genetic testing in time and re-analyze the genetic data may facilitate accurate diagnosis of comorbid genetic diseases.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Objective:To investigate the clinical effect of indocyanine green angiography (ICGA)-assisted design and harvest of expanded flaps for scar reconstruction.Methods:This study was a retrospective observational study. From April 2019 to August 2023, 19 patients with scars (8 males, 11 females; aged 3-38 years) treated at the Plastic Surgery Hospital of Peking Union Medical College and Chinese Academy of Medical Sciences met the inclusion criteria. The scars were distributed on the head, face, trunk, and extremities. In stage Ⅰ surgery, skin soft tissue expanders were implanted in suitable areas around the scars for skin soft tissue expansion. In stage Ⅱ surgery, the scar tissue was excised, resulting in wound areas ranging from 100 to 210 cm 2, and expanded flaps were designed. ICGA was used to identify target perforators and their accompanying veins, and the flap design was adjusted to ensure the inclusion of complete arterial and venous axes. The expanded flap with an area of 120 to 240 cm2 was harvested using unilateral back-cut technique and transferred to the recipient site, and the donor site wound was sutured directly. The durations of the arterial and venous phases of ICGA during flap design were recorded. The length-to-width ratios of the back-cut flaps were calculated for different regions. After stage Ⅱ surgery, the blood perfusion and survival of the flap, the wound healing at the donor site, and the occurrence of complications were observed. During follow-up, the appearance, color, and texture of the patient's flap were observed. Results:The arterial phase of ICGA lasted 10-27 (18±5) s, and the venous phase lasted 78-116 (100±10) s. The length-to-width ratios of the back-cut flaps were 1.22±0.32, 1.63±0.12, and 1.15±0.21 for the head and neck, trunk, and limb regions, respectively. After stage Ⅱ surgery, one patient had a large area of insufficient blood perfusion in the flap. By comparing ICGA images before and after flap transfer, the sutures at the oral commissure were loosened, the blood flow of the flap was restored. The blood perfusion of the flaps in other patients was good. All flaps survived completely, with well-healed donor site wounds and no complications. During 0.5-14.0 months of follow-up, all flaps of patients demonstrated excellent appearance, with color and texture matching the surrounding skin.Conclusions:As a means of superficial blood flow visualization, ICGA can not only clearly show the microvascular distribution of the expanded flap before operation, assist in optimizing the design of the flap, but also evaluate the blood perfusion of the flap after operation, reduce the occurrence of complications, and provide a full-process navigation for the harvesting of expanded flaps, thereby improving the safety of flap transfer for scar reconstruction.

The advantages of few-shot learning in arrhythmia detection were introduced.The research progress of few-shot learning strategies,including metric learning,transfer learning and data augmentation,was reviewed when applied to arrhythmia detection.The limitations of few-shot learning in arrhythmia detection were analyzed.It was pointed out that the graph neural network and new incremental learning techniques would be involved in the future development of few-shot learning in arrhythmia detection.[Chinese Medical Equipment Journal,2025,46(8):104-112]

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.