Objective To investigate the clinical value of modified BI?RADS classification by using the coronal plane of automatic breast volume scaner. Methods The total of 201 BI?RADS 3~5 classification of breast masses were retrospectively analyzed. All masses underwent conventional ultrasound and ABVS examination. Using BI? RADS classification standard terms to describe various information of breast masses, and record the coronal image of the masses on the complete interface echo, convergence sign, angle, burr, which classified BI?RADS ultimately. Results The coronal plane of convergence sign, complete interface echo, angulation and burr were significantly different between benign and malignant tumors (P<0.0001). The sensitivity of ABVS convergent sign in diagnosing breast malignant tumors was 68.2%, specificity was 93.4% and accuracy was 82%. The conventional ultrasound combined with the coronal feature of ABVS modified by BI?RADS classification showed that 3 kinds of malignant rate reduced from 8.5%to 3.2%. The rate of malignant 4a decreased from 25.2%to 12.1%and the rate of malignant 5 increased from 94.2% to 98%. Conclusion The convergence sign of ABVS can be used as a significant independent predictor of breast malignant tumors;ultrasound combined with ABVS is helpful to improve the accuracy of ultrasound BI?RADS classification.

Objective:To study the risk factors of intra-abdominal infection after hepatectomy in patients with primary liver neoplasms.Methods:The clinical data of patients with primary liver neoplasms who underwent hepatectomy at the Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2019 to December 2021 were retrospectively analyzed. Of 1 229 patients who were enrolled, 48 patients developed postoperative abdominal infection. There were 45 males and 3 females, with age of 58.0 (45.0, 66.0) years old in the infected group. Forth-eight patients without postoperative abdominal infection were selected based on the random number formula to be allocated to the uninfected group to include 44 males and 4 females with age of 58.5 (48.5, 64.8) years old. The general data, preoperative and postoperative laboratory test results, types of liver neoplasms and hepatectomy, pathogenic infective microorganisms and their drug sensitivity tests were collected. Univariate analysis was used to analyze the related factors of intra-abdominal infection after hepatectomy, and significant factors were included in logistic multivariate regression analysis.Results:Of 24 pathogenic strains which were detected in the 143 samples of abdominal infection, the positive rate of culture was 16.78%(24/143). Multivariate logistic regression analysis showed that prealbumin <180 mg/L ( OR=3.757, 95% CI: 1.117-12.634), intraoperative blood transfusion ( OR=6.363, 95% CI: 1.301-31.113) and the time of drainage tube placement ≥7 d ( OR=31.098, 95% CI: 6.906~140.029) were independent risk factors of intra-abdominal infection after hepatectomy. Conclusion:Prealbumin <180 mg/L, intraoperative blood transfusion and the time of drainage tube placement ≥7 d were independent risk factors of intra-abdominal infection after hepatectomy for primary liver neoplasms.

OBJECTIVEProviding evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) via analyzing the outbreak detection performance of Moving Percentile Method (MPM) by optimizing thresholds in different provinces.

METHODSWe collected the amount of MPM signals, response results of signals in CIDARS, cases data in nationwide Notifiable Infectious Diseases Reporting Information System, and outbreaks data in Public Health Emergency Reporting System of 16 infectious diseases in 31 provinces in Chinese mainland from January 2011 to October 2013. The threshold with the optimal sensitivity, the shortest time to detect outbreak and the least number of signals was considered as the best threshold of each disease in Chinese mainland and in each province.

RESULTSAmong all the 16 diseases, the optimal thresholds of 10 diseases, including dysentery, dengue, hepatitis A, typhoid and paratyphoid, meningococcal meningitis, Japanese encephalitis, scarlet fever, leptospirosis, hepatitis, typhus in country level were the 90(th) percentile (P90), which was the same as provincial level for those diseases.For the other 6 diseases, including other infectious diarrhea, influenza, acute hemorrhagic conjunctivitis, mumps, rubella and epidemic hemorrhagic fever, the nationwide optimal thresholds were the 80th percentile (P80), which was different from that by provinces for each disease. For these 6 diseases, the number of signals generated by MPM with the optimal threshold for each province was decreased by 23.71% (45 557), 15.59% (6 124), 14.07% (1 870), 9.44% (13 881), 8.65% (1 294) and 6.03% (313) respectively, comparing to the national optimal threshold, while the sensitivity and time to detection of CIDARS were still the same.

CONCLUSIONOptimizing the threshold by different diseases and provinces for MPM in CIDARS could reduce the number of signals while maintaining the same sensitivity and time to detection.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Population Surveillance ; methods

OBJECTIVEFor providing evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) by comparing the early-warning performance of the temporal model and temporal-spatial model in CIDARS.

METHODSThe application performance for outbreak detection of temporal model and temporal-spatial model simultaneously running among 208 pilot counties in 20 provinces from 2011 to 2013 was compared; the 16 infectious diseases were divided into two classes according to the disease incidence level; cases data in nationwide Notifiable Infectious Diseases Reporting Information System was combined with outbreaks reported to Public Health Emergency Reporting System, by adopting the index of the number of signals, sensitivity, false alarm rate and time for detection.

RESULTSThe overall sensitivity of temporal model and temporal-spatial model for 16 diseases was 96.23% (153/159) and 90.57% (144/159) respectively, without significant difference (Z = -1.604, P = 0.109), and the false alarm rate of temporal model (1.57%, 57 068/3 643 279) was significantly higher than that of temporal-spatial model (0.64%, 23 341/3 643 279) (Z = -3.408, P = 0.001), while the median time for detection of these two models was not significantly different, which was 3.0 days and 1.0 day respectively (Z = -1.334, P = 0.182).For 6 diseases of type I which represent the lower incidence, including epidemic hemorrhagic fever,Japanese encephalitis, dengue, meningococcal meningitis, typhus, leptospirosis, the sensitivity was 100% for both models (8/8, 8/8), and the false alarm rate of both temporal model and temporal-spatial model was 0.07% (954/1 367 437, 900/1 367 437), with the median time for detection being 2.5 days and 3.0 days respectively. The number of signals generated by temporal-spatial model was reduced by 2.29% compared with that of temporal model.For 10 diseases of type II which represent the higher incidence, including mumps, dysentery, scarlet fever, influenza, rubella, hepatitis E, acute hemorrhagic conjunctivitis, hepatitis A, typhoid and paratyphoid, and other infectious diarrhea, the sensitivity of temporal model was 96.03% (145/151), and the sensitivity of temporal-spatial model was 90.07% (136/151), the number of signals generated by temporal-spatial model was reduced by 59.36% compared with that of temporal model. Compared to temporal model, temporal-spatial model reduced both the number of signals and the false alarm rate of all the type II diseases;and the median of outbreak detection time of temporal model and temporal-spatial model was 3.0 days and 1.0 day, respectively.

CONCLUSIONOverall, the temporal-spatial model had better outbreak detection performance, but the performance of two different models varies for infectious diseases with different incidence levels, and the adjustment and optimization of the temporal model and temporal-spatial model should be conducted according to specific infectious disease in CIDARS.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Models, Theoretical ; Population Surveillance ; methods ; Spatio-Temporal Analysis

OBJECTIVETo analyze the implement performance of China Infectious Diseases Automated-alert and Response System (CIDARS) of 31 provinces in mainland China, and to provide the evidences for further promoting the application and improvement of this system.

METHODSThe amount of signals, response situation and verification outcome of signals related to 32 infectious diseases of 31 provinces in mainland China in CIDARS were investigated from 2011 to 2013, the changes by year on the proportion of responded signals and timeliness of signal response were descriptively analyzed.

RESULTSA total of 960 831 signals were generated nationwide on 32 kinds of infectious diseases in the system, with 98.87% signals (949 936) being responded, and the median (the 25(th) percentile to the 75(th) percentile (P25-P75) ) of time to response was 1.0 (0.4-3.3) h. Among all the signals, 242 355 signals were generated by the fixed-value detection method, the proportion of responded signals was 96.37% (62 349/64 703), 98.75% (68 413/69 282) and 99.37% (107 690/108 370), respectively, and the median (P25-P75) of time to response was 1.3 (0.3-9.7), 0.8(0.2-4.9) and 0.7 (0.2-4.2) h, respectively. After the preliminary data verification, field investigation and laboratory test by local public health staffs, 100 232 cases (41.36%) were finally confirmed.In addition, 718 476 signals were generated by the temporal aberration detection methods, and the average amount of signal per county per week throughout the country were 1.53, and 8 155 signals (1.14%) were verified as suspected outbreaks. During these 3 years, the proportion of signal response was 98.89% (231 149/233 746), 98.90% (254 182/257 015) and 99.31% (226 153/227 715), respectively, and the median (P25-P75) of time to response was 1.1 (0.5-3.3), 1.0 (0.5-2.9) and 1.0 (0.5-2.6) h, respectively.

CONCLUSIONFrom 2011 to 2013, the proportion of responded signals and response timeliness of CIDARS maintained a rather high level, and further presented an increasing trend year by year. But the proportion of signals related to suspected outbreaks should be improved.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Population Surveillance ; methods

Chest tightness variant asthma(CTVA)is an atypical form of asthma with chest tightness as the sole or predominant symptom.The underlying receptors for chest tightness are bronchial C-fibers or rapidly adapting receptors.The nerve impulses are transmitted via the vagus nerve and processed in different regions of the cerebral cortex.Chest tightness is associated with sensory perception,and CTVA patients may have heightened ability to detect subtle changes in lung function,but such sensory perception is unrelated to respiratory muscle activity,lung hyperinflation,or mechanical loading of the respiratory system.Airway inflammation,pulmonary ventilation dysfunction(especially involving small airways),and airway hyperresponsiveness may underlie the sensation of chest tightness.CTVA patients are prone to comorbid anxiety and depression,which share similar central nervous system processing pathways with dyspnea,suggesting a possible neurological basis for the development of CTVA.This article examines the recognition and mechanisms of chest tightness,and explores the pathogenesis of CTVA,focusing on its association with airway inflammation,ventilation dysfunction,airway hyperresponsiveness,and psychosocial factors.