Acupuncture and moxibustion in treatment of chronic obstructive pulmonary disease at stable stage: a network Meta-analysis / 中国针灸

The efficacy on chronic obstructive pulmonary disease (COPD) at stable stage treated with different methods of acupuncture and moxibustion was evaluated using network Meta-analysis method. The articles of the randomized controlled trial (RCT) on stable COPD treated with acupuncture and moxibustion were searched electronically in CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Web of Science and Cochrane library. The search was conducted from the inception of the databases to March 20th, 2022. Data analysis was performed using R4.1.1, Stata16.0 and RevMan5.3 softwares. A total of 48 RCTs were included, involving 15 kinds of acupuncture and moxibustion interventions and a sample size of 3 900 cases. The results of network Meta-analysis showed that: ① For the forced expiratory volume in one second predicted (FEV1%), both the governor vessel moxibustion combined with conventional treatment (G+C therapy) and the yang-supplementing moxibustion combined with conventional treatment (Y+C therapy) obtained the better effect than that of the conventional treatment (P<0.05), and the G+C therapy was more effective compared with the thread-embedding therapy combined with conventional treatment (E+C therapy) and warm needling (P<0.05). ② Concerning to COPD assessment test (CAT) score, the results indicated that the Y+C therapy, and the mild moxibustion combined with conventional treatment (M+C therapy) were more effective when compared with the conventional treatment (P<0.05), and the effect of the Y+C therapy was better than that of the E+C therapy (P<0.05). ③ Regarding six-minute walking distance (6MWD), the effect of acupuncture combined with conventional treatment (A+C therapy) was better than that of either the E+C therapy or the conventional treatment (P<0.05). The effect of the G+C therapy was optimal for improving FEV1%, the Y+C therapy obtained the best effect for improving CAT score, and A+C therapy was the most effective for improving 6MWD. Due to the limitation of the quality and quantity of included studies, this conclusion needs to be further verified through high-quality RCT.

An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit / 南方医科大学学报

OBJECTIVE@#To construct an inherent interpretability machine learning model as an explainable boosting machine model (EBM) for predicting one-year risk of death in patients with severe ischemic stroke.@*METHODS@#We randomly divided the data of 2369 eligible patients with severe ischemic stroke in the MIMIC-Ⅳ(2.0) database, who were admitted in ICU in 2008 to 2019, into a training dataset (80%) and a test dataset (20%), and assessed the prognosis of the patients using the EBM model. The prediction performance of the model was evaluated by calculating the area under the receiver operating characteristic (AUC) curve. The calibration curve and Brier score were used to evaluate the degree of calibration of the model, and a decision curve was generated to assess the net clinical benefit.@*RESULTS@#The EBM model constructed in this study had good discrimination power, calibration and net benefit, with an AUC of 0.857 (95% CI: 0.831-0.887) for predicting prognosis of severe ischemic stroke. Calibration curve analysis showed that the standard curve of the EBM model was the closest to the ideal curve. Decision curve analysis showed that the model had the greatest net benefit rate at the prediction probability threshold of 0.10 to 0.80. The top 5 independent predictive variables based on the EBM model were age, SOFA score, mean heart rate, mechanical ventilation, and mean respiratory rate, whose significance scores ranged from 0.179 to 0.370.@*CONCLUSION@#This EBM model has a good performance for predicting the risk of death within one year in patients with severe ischemic stroke and allows clinicians to better understand the contributing factors of the patients' outcomes through the model interpretability.

UhpTE350Q mutation along with the presence of fosA6/5 genes in the genome probably contributes to inherent fosfomycin resistance of Klebsiella pneumoniae / 南方医科大学学报

OBJECTIVE@#To investigate the molecular mechanism underlying inherent fosfomycin resistance of Klebsiella pneumoniae (K. pneumoniae).@*METHODS@#The draft genomic sequences of 14 clinical hypervirulent/hypermucoviscous K. pneumoniae (HvKP/ HmKP) isolates were obtained using the next-generation sequencing technology. The genomic sequences were analyzed using the Resistance Gene Identifier (RGI) software for predicting the resistome based on homology and SNP models in the Comprehensive Antibiotic Resistance Database (CARD) and for identification of the presence of phosphomycin resistancerelated genes uhpt and fosA and their mutations in the bacterial genomes. The results were verified by analyzing a total of 521 full-length genomic sequences of K. pneumonia strains obtained from GenBank.@*RESULTS@#All the 14 clinical isolates of HvKP/ HmKP carried hexose phosphate transporter (UhpT) gene mutation, in which the glutamic acid was mutated to glutamine at 350aa (UhpTE350Q mutation); the presence of fosA6 gene was detected in 12 (85.71%) of the isolates and fosA5 gene was detected in the other 2 (14.29%) isolates. Analysis of the genomic sequences of 521 K. pneumonia strains from GenBank showed that 508 (97.50%) strains carried UhpTE350Q mutation, 439 (84.26%) strains harbored fosA6, and 80 (15.36%) strains harbored fosA5; 507 (97.31%) strains were found to have both UhpTE350Q mutation and fosA6/5 genes in the genome. Only 12 (2.30%) strains carried fosA6/5 genes without UhpTE350Q mutation; 1 (0.19%) strain had only UhpTE350Q mutation without fosA6/5 genes, and another strain contained neither UhpTE350Q mutation nor fosA6/5 genes.@*CONCLUSION@#UhpTE350Q mutation with the presence of fosA6/5 genes are ubiquitous in K. pneumonia genomes, indicating a possible intrinsic mechanism of fosfomycin resistance in the bacterium to limit the use of fosfomycin against infections caused by K. pneumoniae, especially the multi-resistant HvKP/HmKP strains.

High expression of death-associated protein 5 promotes glucose metabolism in gastric cancer cells and correlates with poor survival outcomes / 南方医科大学学报

OBJECTIVE@#To investigate the prognostic value of death-associated protein 5 (DAP5) in gastric cancer (GC) and its regulatory effect on aerobic glycolysis in GC cells.@*METHODS@#We analyzed DAP5 expression levels in GC and adjacent tissues and its association with survival outcomes of GC patients using public databases. We collected paired samples of GC and adjacent tissues from 102 patients undergoing radical resection of GC in our hospital from June, 2012 to July, 2017, and analyzed the correlation of DAP5 expression level detected immunohistochemically with the clinicopathological parameters of the patients. Cox regression analysis, Kaplan-Meier analysis, and ROC curves were used to explore the independent risk factors and the predictive value of DAP5 expression for 5-year survival of the patients. In the cell experiments, we observed the changes in aerobic glycolysis in MGC-803 cells following lentivirus-mediated DAP5 knockdown or overexpression by measuring glucose uptake and cellular lactate level and using qRT-PCR and Western blotting.@*RESULTS@#Analysis using the public databases showed that DAP5 was highly expressed in GC and correlated with tumor progression and poor survival outcomes of the patients (P < 0.05). In the clinical samples, DAP5 expression was significantly higher in GC than in the adjacent tissues (3.19±0.60 vs 1.00±0.12; t=36.863, P < 0.01), and a high expression of DAP5 was associated with a reduced 5-year survival rate of the patients (17.6% vs 72.5%; χ2=29.921, P < 0.05). A high DAP5 expression, T3-4, N2-3, and CEA≥5 ng/mL were identified as independent risk factors affecting 5-year survival outcomes of GC (P < 0.05), for which DAP5 expression showed a prediction sensitivity, specificity and accuracy of 73.2%, 80.4% and 79.0%, respectively. In MGC-803 cells, DAP5 knockdown significantly reduced glucose uptake, lactate level and the expressions of GLUT1, HK2 and LDHA, and DAP5 overexpression produced the opposite effects (P < 0.05).@*CONCLUSION@#A high expression of DAP5 in GC, which enhances cellular aerobic glycolysis to promote cancer progression, is correlated with a poor survival outcome and may serve as a biomarker for evaluating long-term prognosis of GC patients.

Brief analysis of research and application status of artificial intelligence and related advanced technology in oral medicine / 中华口腔医学杂志

Artificial intelligence revealed its application prospects that could bring change in oral medicine. Artificial intelligence related papers in oral medicine field increased year by year since the 1990s. In order to provide reference for further research, the literature on artificial intelligence studies and its application in oral medicine were retrieved from multiple databases and summarized. The evolution of hot spots on artificial intelligence and related state of the art technology in oral medicine were analyzed.

Scoping review of progress in cohort studies of autism spectrum disorder / 中华流行病学杂志

Objective: To understand the status of autism spectrum disorder (ASD) cohort studies and explore the feasibility of constructing ASD disease-specific cohorts based on real-world data (RWD). Methods: ASD cohort studies published by December 2022 were collected by literature retrieval from major Chinese and English databases. And the characteristics of the cohort were summarized. Results: A total of 1 702 ASD cohort studies were included, and only 60 (3.53%) were from China. A total of 163 ASD-related cohorts were screened, of which 55.83% were birth cohorts, 28.22% were ASD-specific cohorts, and 4.91% were ASD high-risk cohorts. Most cohorts used RWD such as hospital registries or conducted community-based field surveys to obtain participant information and identified patients with ASD by scales or clinical diagnoses. The contents of the studies included ASD incidence and prognostic risk factors, ASD comorbidity patterns and the impact of ASD on self-health and their offspring's health. Conclusions: ASD cohort studies in developed countries have been in the advanced stage, while the Chinese studies are still in their infancy. RWD provides the data basis for ASD-specific cohort construction and offers new opportunities for research, but work such as case validation is still needed to ensure the scientific nature of cohort construction.

Global incidence and mortality of renal cell carcinoma in 2020 / 中华流行病学杂志

Objective: To analyze the global epidemiology of renal cell carcinoma (RCC) in 2020. Methods: The incidence and mortality data of RCC in the cooperative database GLOBOCAN 2020 of International Agency for Research on Cancer of WHO and the human development index (HDI) published by the United Nations Development Programme in 2020 were collated. The crude incidence rate (CIR), age-standardized incidence rate (ASIR), crude mortality rate (CMR), age-standardized mortality rate (ASMR) and mortality/incidence ratio (M/I) of RCC were calculated. Kruskale-Wallis test was used to analyze the differences in ASIR or ASMR among HDI countries. Results: In 2020, the global ASIR of RCC was 4.6/100 000, of which 6.1/100 000 for males and 3.2/100 000 for females and ASIR was higher in very high and high HDI countries than that in medium and low HDI countries. With the rapid increase of age after the age of 20, the growth rate of ASIR in males was faster than that in females, and slowed down at the age of 70 to 75. The truncation incidence rate of 35-64 years old was 7.5/100 000 and the cumulative incidence risk of 0-74 years old was 0.52%. The global ASMR of RCC was 1.8/100 000, 2.5/100 000 for males and 1.2/100 000 for females. The ASMR of males in very high and high HDI countries (2.4/100 000-3.7/100 000) was about twice that of males (1.1/100 000-1.4/100 000) in medium and low HDI countries, while the ASMR of female (0.6/100 000-1.5/100 000) did not show significant difference. ASMR continued to increase rapidly with age after the age of 40, and the growth rate of males was faster than that of females. The truncation mortality rate of 35-64 years old was 2.1/100 000, and the cumulative mortality risk of 0-74 years old was 0.20%. M/I decreases with the increase of HDI, with M/I as 0.58 in China, which was higher than the global average of 0.39 and the United States' 0.17. Conclusion: The ASIR and ASMR of RCC presented significant regional and gender disparities globally, and the heaviest burden was in very high HDI countries.

Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network / 生物医学工程学杂志

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.

Exploration and practice on construction of Tibetan medicine prescription information database and knowledge discovery / 中国中药杂志

This study aimed to explore the underlying framework and data characteristics of Tibetan prescription information. The information on Tibetan medicine prescriptions was collected based on 11 Tibetan medicine classics, such as Four Medical Canons(Si Bu Yi Dian). The optimal classification method was used to summarize the information structure of Tibetan medicine prescriptions and sort out the key problems and solutions in data collection, standardization, translation, and analysis. A total of 11 316 prescriptions were collected, involving 139 011 entries and 63 567 pieces of efficacy information of drugs in prescriptions. The information on Tibe-tan medicine prescriptions could be summarized into a "seven-in-one" framework of "serial number-source-name-composition-efficacy-appendix-remarks" and 18 expansion layers, which contained all information related to the inheritance, processing, origin, dosage, semantics, etc. of prescriptions. Based on the framework, this study proposed a "historical timeline" method for mining the origin of prescription inheritance, a "one body and five layers" method for formulating prescription drug specifications, a "link-split-link" method for constructing efficacy information, and an advanced algorithm suitable for the research of Tibetan prescription knowledge discovery. Tibetan medicine prescriptions have obvious characteristics and advantages under the guidance of the theories of "three factors", "five sources", and "Ro-nus-zhu-rjes" of Tibetan medicine. Based on the characteristics of Tibetan medicine prescriptions, this study proposed a multi-level and multi-attribute underlying data architecture, providing new methods and models for the construction of Tibetan medicine prescription information database and knowledge discovery and improving the consistency and interoperability of Tibetan medicine prescription information with standards at all levels, which is expected to realize the "ancient and modern connection-cleaning up the source-data sharing", so as to promote the informatization and modernization research path of Tibetan medicine prescriptions.

Exploration and example interpretation of real-world herbal prescription classification based on similarity matching algorithm / 中国中药杂志

In observational studies, herbal prescriptions are usually studied in the form of "similar prescriptions". At present, the classification of prescriptions is mainly based on clinical experience judgment, but there are some problems in manual judgment, such as lack of unified criteria, labor consumption, and difficulty in verification. In the construction of a database of integrated traditional Chinese and western medicine for the treatment of coronavirus disease 2019(COVID-19), our research group tried to classify real-world herbal prescriptions using a similarity matching algorithm. The main steps include 78 target prescriptions are determined in advance; four levels of importance labeling shall be carried out for the drugs of each target prescription; the combination, format conversion, and standardization of drug names of the prescriptions to be identified in the herbal medicine database; calculate the similarity between the prescriptions to be identified and each target prescription one by one; prescription discrimination is performed based on the preset criteria; remove the name of the prescriptions with "large prescriptions cover the small". Through the similarity matching algorithm, 87.49% of the real prescriptions in the herbal medicine database of this study can be identified, which preliminarily proves that this method can complete the classification of herbal prescriptions. However, this method does not consider the influence of herbal dosage on the results, and there is no recognized standard for the weight of drug importance and criteria, so there are some limitations, which need to be further explored and improved in future research.

Meta-analysis of Simotang Oral Liquid in treatment of functional dyspepsia in adults / 中国中药杂志

This study was conducted to evaluate the efficacy and safety of Simotang Oral Liquid in the treatment of functional dyspepsia in adults. "Simotang Oral Liquid" "Simotang" "Si Mo Tang" "Si Mo Tang Oral Liquid" were used for retrieval of the relevant papers from CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, Springer Link, and Web of Science from database inception to June 2021. Randomized controlled trial(RCT) of Simotang Oral Liquid in the treatment of functional dyspepsia in adults was screened out for Meta-analysis which was conducted in RevMan 5.3. A total of 16 RCTs were included. Meta-analysis showed that compared with the control group, Simotang Oral Liquid increased the total response rate and lowered the traditional Chinese medicine syndrome scores, serum cholecystokinin(CCK), serum nitric oxide(NO), and incidence of adverse reactions. However, the serum substance P(SP) had no statistical difference between the two groups. Simotang Oral Liquid is effective and safe in the treatment of functional dyspepsia in adults. However, this study has evidence and limitations, so the conclusions need to be further verified by large sample and multicenter clinical studies.

Factors associated with deep infiltrating endometriosis, adenomyosis and ovarian endometrioma

INTRODUCTION@#To compare epidemiological features and clinical presentations of deep infiltrating endometriosis with endometrioma and adenomyosis, as well as to identify risk factors for the respective histologically confirmed conditions.@*METHOD@#Patients undergoing index surgery at the National University Hospital, Singapore for endometriosis or adenomyosis over a 7-year period-from 2015 to 2021-were identified from hospital databases using the Table of Surgical Procedures coding. Social and epidemiological features of cases with histologically confirmed diagnoses of endometrioma only, adenomyosis only, and deep infiltrating endometriosis were compared. Significant variables from univariate analysis were entered into 3 binary multivariate logistic regression models to obtain independent risk factors for: deep infiltrating endometriosis versus endometrioma only, deep infiltrating endometriosis versus adenomyosis only, and adenomyosis only versus endometrioma only.@*RESULTS@#A total of 258 patients were included with 59 ovarian endometrioma only, 47 adenomyosis only, and 152 deep infiltrating endometrioses. Compared to endometrioma only, deep infiltrating endometriosis was associated with higher rates of severe dysmenorrhoea (odds ratio [OR] 2.80, 95% confidence interval [CI] 1.02-7.70) and out-of-pocket private surgical care (OR 4.72, 95% CI 1.85-12.04). Compared to adenomyosis only, deep infiltrating endometriosis was associated with a higher fertility desire (OR 13.47, 95% CI 1.01-180.59) and a lower body mass index (OR 0.89, 95% CI 0.79-0.99). In contrast, heavy menstrual bleeding was the hallmark of adenomyosis, being less common in patients with endometriosis.@*CONCLUSION@#Deep infiltrating endometriosis is associated with severe dysmenorrhoea, pain related to urinary and gastrointestinal tracts, higher fertility desire and infertility rate. Patients with pain symptomatology and subfertility should be referred early to a tertiary centre with the capability to diagnose and manage deep infiltrating endometriosis.

Current situation of acupuncture and moxibustion patents in China and abroad / 中国针灸

The patents of acupuncture and moxibustion in China and abroad was analyzed, aiming to provide support for the innovative development of acupuncture industry. With the China Think Tank of Patent of Traditional Chinese Medicine and the PatSnap database as data sources, based on the mathematical statistics method, the application trend, legal status, patent types, transformation and distribution of major technical fields of acupuncture patents in China and abroad were analyzed. As a result, a total of 53,422 acupuncture patents were screened, involving 49 countries and 4 organizations. The patent types were mainly utility model patents. Although the application number of acupuncture patent had increased rapidly, the average patent conversion rate was generally low, approximately 4%. In the context of global economic integration, the acupuncture industry is developing at a high speed. It is suggested to take advantage of the "Belt and Road Initiative" to improve the international acceptance of acupuncture and moxibustion, adhere to the principle of attaching equal importance to the number and quality of patents, promote the in-depth cooperation of industry-university-research, and promote high-quality development of acupuncture and moxibustion.

Weight bias and stigma in healthcare professionals: a narrative review with a Singapore lens

Addressing weight stigma is essential to obesity management as it causes inequalities in healthcare and impacts the outcomes of health. This narrative review summarises systematic review findings about the presence of weight bias in healthcare professionals, and interventions to reduce weight bias or stigma in these professionals. Two databases (PubMed and Cumulative Index to Nursing and Allied Health Literature [CINAHL]) were searched. Seven eligible reviews were identified from 872 search results. Four reviews identified the presence of weight bias, and three investigated trials to reduce weight bias or stigma in healthcare professionals. The findings may help further research and the treatment, health and well-being of individuals with overweight or obesity in Singapore. Weight bias was prevalent among qualified and student healthcare professionals globally, and there is a lack of clear guidance for effective interventions to reduce it, particularly in Asia. Future research is essential to identify the issues and inform initiatives to reduce weight bias and stigma among healthcare professionals in Singapore.

Electrocardiogram signal classification based on fusion method of residual network and self-attention mechanism / 生物医学工程学杂志

In the diagnosis of cardiovascular diseases, the analysis of electrocardiogram (ECG) signals has always played a crucial role. At present, how to effectively identify abnormal heart beats by algorithms is still a difficult task in the field of ECG signal analysis. Based on this, a classification model that automatically identifies abnormal heartbeats based on deep residual network (ResNet) and self-attention mechanism was proposed. Firstly, this paper designed an 18-layer convolutional neural network (CNN) based on the residual structure, which helped model fully extract the local features. Then, the bi-directional gated recurrent unit (BiGRU) was used to explore the temporal correlation for further obtaining the temporal features. Finally, the self-attention mechanism was built to weight important information and enhance model's ability to extract important features, which helped model achieve higher classification accuracy. In addition, in order to mitigate the interference on classification performance due to data imbalance, the study utilized multiple approaches for data augmentation. The experimental data in this study came from the arrhythmia database constructed by MIT and Beth Israel Hospital (MIT-BIH), and the final results showed that the proposed model achieved an overall accuracy of 98.33% on the original dataset and 99.12% on the optimized dataset, which demonstrated that the proposed model can achieve good performance in ECG signal classification, and possessed potential value for application to portable ECG detection devices.

An image classification method for arrhythmias based on Gramian angular summation field and improved Inception-ResNet-v2 / 生物医学工程学杂志

Arrhythmia is a significant cardiovascular disease that poses a threat to human health, and its primary diagnosis relies on electrocardiogram (ECG). Implementing computer technology to achieve automatic classification of arrhythmia can effectively avoid human error, improve diagnostic efficiency, and reduce costs. However, most automatic arrhythmia classification algorithms focus on one-dimensional temporal signals, which lack robustness. Therefore, this study proposed an arrhythmia image classification method based on Gramian angular summation field (GASF) and an improved Inception-ResNet-v2 network. Firstly, the data was preprocessed using variational mode decomposition, and data augmentation was performed using a deep convolutional generative adversarial network. Then, GASF was used to transform one-dimensional ECG signals into two-dimensional images, and an improved Inception-ResNet-v2 network was utilized to implement the five arrhythmia classifications recommended by the AAMI (N, V, S, F, and Q). The experimental results on the MIT-BIH Arrhythmia Database showed that the proposed method achieved an overall classification accuracy of 99.52% and 95.48% under the intra-patient and inter-patient paradigms, respectively. The arrhythmia classification performance of the improved Inception-ResNet-v2 network in this study outperforms other methods, providing a new approach for deep learning-based automatic arrhythmia classification.

Automatic sleep staging model based on single channel electroencephalogram signal / 生物医学工程学杂志

Sleep staging is the basis for solving sleep problems. There's an upper limit for the classification accuracy of sleep staging models based on single-channel electroencephalogram (EEG) data and features. To address this problem, this paper proposed an automatic sleep staging model that mixes deep convolutional neural network (DCNN) and bi-directional long short-term memory network (BiLSTM). The model used DCNN to automatically learn the time-frequency domain features of EEG signals, and used BiLSTM to extract the temporal features between the data, fully exploiting the feature information contained in the data to improve the accuracy of automatic sleep staging. At the same time, noise reduction techniques and adaptive synthetic sampling were used to reduce the impact of signal noise and unbalanced data sets on model performance. In this paper, experiments were conducted using the Sleep-European Data Format Database Expanded and the Shanghai Mental Health Center Sleep Database, and achieved an overall accuracy rate of 86.9% and 88.9% respectively. When compared with the basic network model, all the experimental results outperformed the basic network, further demonstrating the validity of this paper's model, which can provide a reference for the construction of a home sleep monitoring system based on single-channel EEG signals.

A 25 años de la implementación del identificador de objeto digital / Twenty-five years after the implementation of the Digital Object Identifier

RESUMEN El identificador de objeto digital, conocido en inglés como digital object identifier y abreviado DOI, surgido en 1997, es una cadena alfanumérica única que identifica un contenido electrónico y proporciona un enlace permanente a su ubicación en internet. A 25 años de la implementación de esta herramienta, todavía quedan muchas revistas con un impacto considerable que no cuentan con DOI. Cuba no lo tiene porque le es negado por las grandes agencias registradoras. Fue objetivo de los autores de esta comunicación destacar la importancia del DOI como herramienta básica para el control de la documentación digital. Se concluyó que su principal aporte es asegurar la identificación persistente y unívoca de un documento, a través de un registro sistemático central de sus metadatos. Se recomienda que siempre que esté disponible el DOI en línea, se utilice en la cita bibliográfica, para mejorar la visibilidad de las revistas y los propios investigadores.

ABSTRACT The Digital Object Identifier, abbreviated as DOI and emerged in 1997, is a unique alphanumeric string that identifies electronic content and provides a permanent link to its location on the Internet. Twenty-five years after the implementation of this tool, there are still many journals with a considerable impact which do not have DOIs. Cuba does not have it because it is denied by the big registration agencies. The objective of this article was to highlight the importance of the DOI as a basic tool for the control of digital documentation. We concluded that its main contribution is to ensure the persistent and unique identification of a document, through a central systematic record of its metadata. It is recommended that whenever the DOI is available online, it is used in the bibliographic citation, to improve the visibility of the journals and the researchers themselves.

Hospitalizations and adverse drug events in the Brazilian unified health system: a ten-year retrospective analysis of routine data

ABSTRACT OBJECTIVE To describe the frequency and characteristics of hospitalizations for/with adverse drug events in the Brazilian unified health system routine data. METHODS Nationwide retrospective study using data obtained from a period of ten years from the Brazil Hospital Information System (SIH-SUS), an administrative database that registers hospitalizations in the unified health system. We selected hospitalizations with primary and/or secondary diagnosis related to adverse drug events according to a list of validated International Classification Disease 10th edition (ICD-10) codes. These events were described according to year, age group, sex, length of hospital stay, mortality, hospital costs, Brazilian geographical region, and category of ICD-10 codes. Crude hospitalization rates of adverse drug events per 100,000 inhabitants were obtained and Joinpoint Regression was used to analyze temporal changes in these rates along the years. The most frequent ICD-10 codes were also identified. RESULTS Over ten years, 603,663 hospitalizations in Brazil were found in the database, out of which 2.5% of the patients died. Though 2009 had the highest prevalence of hospitalization per 100,000 inhabitants (32.57), no significant annual change in rates was found for the entire period. All age groups and sexes presented a jointpoint in temporal series; however, only women had a significative increase trend. The most frequent codes were from the chapter of mental and behavioral disorders (F19.2, F19.0, and F19.5 codes). CONCLUSIONS The database methodology can be useful to estimate frequencies of adverse drug events and perform characterization nationwide and to help monitor morbidity along the years.

Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network / 生物医学工程学杂志

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk classification of sudden cardiac death and the screening of family genetic diseases. This research proposed a HCM automatic detection method based on convolution neural network (CNN) model, using single-lead electrocardiogram (ECG) signal as the research object. Firstly, the R-wave peak locations of single-lead ECG signal were determined, followed by the ECG signal segmentation and resample in units of heart beats, then a CNN model was built to automatically extract the deep features in the ECG signal and perform automatic classification and HCM detection. The experimental data is derived from 108 ECG records extracted from three public databases provided by PhysioNet, the database established in this research consists of 14,459 heartbeats, and each heartbeat contains 128 sampling points. The results revealed that the optimized CNN model could effectively detect HCM, the accuracy, sensitivity and specificity were 95.98%, 98.03% and 95.79% respectively. In this research, the deep learning method was introduced for the analysis of single-lead ECG of HCM patients, which could not only overcome the technical limitations of conventional detection methods based on multi-lead ECG, but also has important application value for assisting doctor in fast and convenient large-scale HCM preliminary screening.