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Objective The study aimed to elucidate the evolution of the syndromes in Traditional Chinese Medicine ( TCM ) and TCM syndrome elements in different chronic stages of psoriasis vulgaris. Methods A database was constructed using electronic medical records collected from July 2019 to March 2024 from 1, 049 patients with psoriasis vulgaris. The study used Sankey diagrams and network association graphs to analyze the evolution of TCM syndromes and their elements in patients at the different stages: initial diagnosis, progressive stage (Week 2-3), progressive stage (Week 4-5), skin lesion improvement stage ( Week 6 - 7 ), and remission stage. The syndrome elements network was constructed using community detection algorithms, and the association rules between local skin lesion syndrome difierentiation and overall syndrome difierentiation were displayed using heatmaps. Results ( i) Initial diagnosis. In the syndrome differentiation of local skin lesions, blood heat syndrome was the most common (79.79%); among the disease location of TCM syndrome elements (called " disease location, , ）, liver was the most prevalent ( 35.62%); and among the pathological factors of TCM syndrome elements ( called " pathological factors " ), fire (heat) was the most common (75. 48%). ( ii) Active stage (Week 2-3). In the syndrome differentiation of local skin lesions, blood heat syndrome remained the most prevalent (73. 13%) ； among the disease location, liver was still the most prevalent (31.71%); and among the pathological factors, fire ( heat) continued to be the most common (82. 11%), while dampness (22. 26%) and qi stagnation (8. 39%) began to increase. ( 111) Active stage ( Week 4-5). The syndrome differentiation of local skin lesions was dominated by blood heat syndrome (45. 91%) and blood dryness syndrome (37. 19%) ； among disease location, the interior was the most prevalent ( 15. 25%) ； and among the pathological factors, fire (heat) remained the most common ( 50. 66%), with an increase in yin deficiency ( 34. 26%). ( iv) Skin lesion improvement stage (Week 6 - 7 ). In the syndrome differentiation of local skin lesions, both blood dryness syndrome (49.44%) and blood stasis syndrome ( 33.33%) increased; among the disease location, meridians increased most significantly and became the most prevalent (13.44%); and among the pathological factors, blood stasis increased most significantly and became the most prevalent (28.20%). ( V ) Remission stage. In the syndrome difierentiation of local skin lesions, blood stasis syndrome became the primary (55.69%), while the percentage of blood dryness syndrome decreased ( 21. 16%) ； meridians (25.71%) and blood stasis ( 62. 34%) remained the most predominant syndrome elements related to disease location or pathological factors. Conclusion The overall pattern of TCM syndromes in psoriasis vulgaris evolved from excess to deficiency. From the initial diagnosis to the active phase (Week 2-3), heat syndrome dominated ； during the active phase ( Week 4-5), heat syndrome coexisted with damp syndrome or yin deficiency syndrome; changes in the syndrome element network were the most significant during the lesion improvement phase, with blood stasis gradually increasing and peaking during the remission phase. Blood stasis, dampness, and qi stagnation were pervasive throughout psoriasis vulgaris ； qi stagnation and blood stasis may be the main elements causing further deterioration and prolonged course of the disease during the active phase in patients. [ABSTRACT FROM AUTHOR]

Addressing the challenges of capturing the correlation between information extraction tasks and the contextual information in doctor-patient dialogues during electronic medical record construction, this paper proposed a Transformer-based collaborative information extraction method called CT-JIE(collaborative Transformer for joint information extraction). Firstly, this method utilized a sliding window combined with Bi-LSTM to acquire historical information from the dialogues and employed a label-aware module to capture task-related information in the dialogue context. Secondly, the global attention module enhanced the model s ability to perceive the context of symptom entities and their status. Finally, the interactive guidance module explicitly modeled the interaction among intent recognition, slot filling, and status recognition tasks to capture the complex contexts and relationships among multiple tasks. Experiments demonstrate that this method outperforms other baseline and ablation models on the IMCS21 and CMDD datasets, showing strong generalization ability and performance advantages in handling joint information extraction tasks. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To establish the closed-loop management mode of rational drug use in the hospital based on the level-six standard of electronic medical record system, so as to escort the rational drug use of outpatients and provide reference for the construction of intelligent pharmacy. METHODS: Artificial intelligence technology was used to manage all aspects of rational drug use in outpatient department, such as physician prescription, pharmacist review, drug dispensing and prescription review, the closed-loop system was established in line with the level-six standard of electronic medical record system. Meanwhile, the irrational rate of outpatient prescriptions before closed-loop management (from Mar. to May 2023) and after closed-loop management ( from Jun. to Aug. 2023) were analyzed retrospectively. RESULTS: After implementation of the closed-loop management mode of rational drug use in outpatient department, the irrational rate of outpatient prescriptions was 3. 56% (40 723 / 1 145 056), which was 1. 01% lower than 4. 57% (52 681 / 1 153 154) before management, the difference was statistically significant (P < 0. 01). The number of prescriptions for other types of inappropriate drugs except for the selection of unsuitable drugs decreased significantly. The average drug cost per outpatient visit was 146. 20 RMB, with a reduction of 7. 67% compared with before management cost of 158. 35 RMB, effectively improving the performance assessment indicators of public hospitals. CONCLUSIONS: The closed-loop management mode of rational drug use in outpatients established by the hospital meets the requirements of the level-six standard of electronic medical record system, which can standardize the work flow of medical personnel and reduce irrational drug use in outpatient department. [ABSTRACT FROM AUTHOR]

Background: Thirst is a common symptom among patients with endotracheal intubation in the intensive care unit (ICU), with an estimated prevalence of 88%. Purpose: This study was designed to compare the effectiveness of cold saline spray and cold water spray in alleviating thirst, and to explore the maintenance and sustained effects of both groups in relieving thirst among patients with endotracheal intubation in the ICU. Methods: Patients with indwelling tracheal tubes in the medical ICU were recruited from one medical center in northern Taiwan and randomly assigned to either the cold saline (n = 18) or cold water (n = 18) group. The cold saline group received three rounds of cold saline spray at a temperature of 2°C -- 8°C. Each round consisted of 10 sprays directed toward each of the four surfaces of the oral cavity followed by a 5-minute wait period. This process was repeated three times, with 30-minute intervals between interventions. The cold water group received the same intervention steps using a cold water spray at 2°C -- 8°C. Thirst intensity was measured using a numeric rating scale before and after each of the three interventions in both groups. Demographic and relevant physiological data were collected on the participants by reviewing their medical records. Results: Both of the interventions were found to effectively alleviate thirst intensity, with no significant difference between the two groups in terms of thirst intensity reduction after each intervention detected. Only the cold water spray had a maintenance effect, while the two groups had a continuous sustained effect in alleviating thirst intensity. Conclusion: Both of the interventions effectively alleviated thirst, and the cold water spray had both maintenance and sustained effects in alleviating thirst intensity. Based on the results, the cold water spray method may be considered as the priority treatment for thirst alleviation by healthcare providers in the clinical management of patients with tracheal intubation. [ABSTRACT FROM AUTHOR]

The Chinese clinical natural language is rich in a large amount of medical record information. Naming entity recognition for electronic medical records can help establish medical auxiliary diagnostic systems, which is of great significance for the development of the medical field. At the same time, it is conducive to downstream tasks such as relationship extraction and the implementation of knowledge graphs. However, Chinese electronic medical records have problems with difficulty in Chinese word segmentation, numerous medical terminology, and special expressions, which can easily lead to incorrect expression of text features. Therefore, this paper proposes a medical named entity recognition research model based on enhanced word information and graph attention, which improves the performance of the network model by enhancing local and global features. Due to the fact that embedding a single word vector for Chinese entity recognition can easily ignore word information and semantics in the text, this paper embeds a highly correlated word vector in the word vector, which not only enhances text representation but also avoids word segmentation errors. Additionally, a Med- Bert model for learning medical knowledge is embedded in the word embedding layer, which can dynamically generate feature vectors according to different contexts, helps solve the problem of polysemy and specialized vocabulary in electronic medical records. At the same time, adding a graph attention module in the coding layer enhances the network's ability to learn text context relationships and enhances the model's learning of medical special grammar. Finally, F1 values of 86.38% and 84.76% are obtained on the cEHRNER and cMedQANER datasets, respectively, showing better robustness compared to other models. [ABSTRACT FROM AUTHOR]

Blockchain technology has great potentiality in the secure sharing of electronic health records. However, current solutions face issues such as large storage space and low consensus efficiency. This paper proposed a novel scheme based on blockchain and friend and relative nodes. Firstly, this paper adopted a distributed file system to store users’ complete electronic health records on offline servers, and constructed a set of user’s friend and relative nodes. Each user’s data was stored redundantly by its friend and relative nodes, and only the block’s header information was stored on the chain, reducing storage space. Then, this paper designed a data access mechanism based on multi-signature technology, using Shamir secret sharing mechanism to distribute user’s private keys to their relatives and friends. More than half of the relatives and friends could use their own private keys to reconstruct users’ private keys, solving data access problems in emergency situations. Finally, this paper proposed a credit based Byzantine fault-tolerant consensus mechanism, which used the top 10% nodes with credit values as the leader node set and utilized a random algorithm to generate the master node in the leader node set. And it improved consensus security. The experimental results show that compared with existing methods, the proposed scheme reduces the on-chain storage space by 1/7, improves data access efficiency by 15 times, and has higher consensus security while ensuring good latency and throughput. The proposed scheme can achieve secure and efficient sharing of electronic health records, providing a case for the application of blockchain in the medical field. [ABSTRACT FROM AUTHOR]

Symptom inference is a critical component of the medical dialogue system for automatic diagnosis. With the improvement of online diagnosis in recent years, the number of doctor- patient dialogue texts has continued to increase. The initial research on symptom inference based on electronic health records has gradually shifted to doctor-patient dialogue texts. However, most existing studies ignore the special role and symptom entity structure prior knowledge in dialogue, which can help the model learn contextual associations better. Therefore, this paper proposes an improved selfattention network based on the prior knowledge of role and entity structure and combines it with a pre-trained language model. The proposed model integrates the prior knowledge of role and entity structure into the encoding stage of the text, and can more accurately infer the attributes of symptom entities. Experimental results on the CHIP-MDCFNPC dataset of the CBLUE2.0 show that the proposed model outperforms the baseline model, which verifies the effectiveness of prior knowledge and model structure. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of China Medical University is the property of Journal of China Medical University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background During the 13th Five-Year Plan in China, the rapid development of the informatization construction in the primary health of China has greatly promoted the improvement of the service level and quality of the primary health institutions, but there are still deficiencies in some aspects. Objective To investigate the status of informatization construction of primary health institutions in Jiangsu Province, in order to analyze the existing problems and provide corresponding countermeasures. Methods From July to October 2020, a stratified random sampling method was used to select 500 primary health institutions from 13 cities in Jiangsu Province to carry out a questionnaire survey. The contents of the questionnaire included the financial planning and fund sources for infomatization construction of the primary health institutions, status of information system construction of hospitals, the informatization of residents' health records, the deployment of informatization staffs, medical information sharing, status of telemedicine and satisfaction to the informationization of the primary health institutions. The vice president of business filled in the questionnaire according to the truth. Results A total of 416 valid questionnaires from the primary health institutions were obtained, accounting for 26.5% (416/1 567) of all the primary health institutions in the province. 80.0% (333/416) of the informatization construction of primary health institutions is planned by the county (city, district) government, and 67.3% (280/416) got fund from the government finance. 99.0% (412/416) of the primary health institutions constructed hospital information management system, 92.1% (383/416) constructed outpatient system, 81.7% (340/416) constructed electronic medical record system, 45.0% (187/416) constructed clinical information system, 98.3% (409/416) constructed information system of residents' health records. 31.3% (130/416) of the primary health institutions shared medical information to the patients, 83.9% (349/416) shared the medical information to the community health service station and the village clinics, 14.2% (59/416) shared the medical information to the superior hospitals, 29.1% (121/416) shared the medical information over the county, 4.3% (18/416) shared the medical information over the city. 38.2% (159/416) of the primary health institutions carried out such services as online appointment, ECG or CT diagnosis, and 15.6% (65/416) carried out real-time outpatient service. 81.3% (338/416) of the primary health institutions showed satisfaction to the informatization construction, and the institutions with different types or in different cities showed different satisfaction. Conclusion The overall informatization of primary health institutions in Jiangsu is is relatively good, but there are still phenomena such as unbalanced regional development, low level of cross-regional information sharing and lack of popularization of telemedicine, which needs to be further improved.

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problems of word segmentation errors, fuzzy word boundaries and low model calculation efficiency in the process of entity recognition task, a Chinese electronic medical record named entity recognition method that combines multiple features and IDCNN is proposed. This method first constructs a CNN-based character embedding algorithm to train the char vector, then splices it with the word vector and other additional features, then sends it to the iterative expanded convolutional neural network for feature learning, and finally decodes the optimal label sequence through CRF. Experimental results show that the F1 value of this method in the CCKS 2017 Chinese electronic medical record dataset reaches 91.36%, and the training efficiency is better than the existing model, which verifies the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Angle Health Law Review is the property of Angle Publishing Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, the development of deep learning-based multimodal learning is advancing rapidly, and is widely used in the field of artificial intelligence-generated content, such as image-text conversion and image-text generation. Electronic health records are digital information such as numbers, charts, and texts generated by medical staff using information systems in the process of medical activities. The multimodal fusion method of electronic health records based on deep learning can assist medical staff in the medical field to comprehensively analyze a large number of medical multimodal data generated in the process of diagnosis and treatment, thereby achieving accurate diagnosis and timely intervention for patients. In this article, we firstly introduce the methods and development trends of deep learning-based multimodal data fusion. Secondly, we summarize and compare the fusion of structured electronic medical records with other medical data such as images and texts, focusing on the clinical application types, sample sizes, and the fusion methods involved in the research. Through the analysis and summary of the literature, the deep learning methods for fusion of different medical modal data are as follows: first, selecting the appropriate pre-trained model according to the data modality for feature representation and post-fusion, and secondly, fusing based on the attention mechanism. Lastly, the difficulties encountered in multimodal medical data fusion and its developmental directions, including modeling methods, evaluation and application of models, are discussed. Through this review article, we expect to provide reference information for the establishment of models that can comprehensively utilize various modal medical data.

Objective To summarize the characteristics and changes of traumatic brain injury (TBI) in Tongzhou district of Beijing with the rapid development of social economy, in order to provide the theoretical basis for adjustment of the prevention and treatment strategies in high risk population. Methods The home pages of electronic health record (EHR) of patients with TBI from December 1, 2004 to October 22, 2018 were automatically extracted from the EHR of Beijing Luhe Hospital, Capital Medical University. The clinical characteristics were retrospectively analyzed, and the risk factors related to death at discharge were screened by univariate and multivariate forward Logistic regression analysis. Results A total of 4058 patients with TBI were screened out, of which 3683 cases (90.76%) survived and 375 cases (9.24%) died at discharge. The mortality at discharge was significantly different among different age (χ² = 51.526, P = 0.000), causes of injury (χ² = 82.349, P = 0.000), treatment modalities (χ² = 186.270, P = 0.000) and hospital length (χ² = 9.842, P = 0.000). The mortality of patients aged 45-64, 65-74 and ≥ 75 years was higher than that of patients aged 15-24 and 25-44 years (P < 0.01, for all), and the mortality of patients aged ≥ 75 years was higher than that of patients aged 45-64 years (P = 0.001). The mortality of patients with traffic accident injury was higher than that of fall injury (P = 0.000), and the mortality of patients with traffic accident injury, fall injury and other cases was higher than that of violent injury (P = 0.000, for all). The mortality of patients received neurosurgery and non-neurosurgery was higher than that of conservative treatment (P = 0.000, for all). The mortality of patients with hospital lengh of 1-14 d was higher than that of 15-30 d and > 30 d (P = 0.000, for all). Logistic regression analysis showed that 45-64 years old (OR = 2.285, 95%CI: 1.428-3.657; P = 0.001), 65-74 years old (OR = 4.025, 95%CI: 2.334-6.941; P = 0.000), ≥ 75 years old (OR = 5.757, 95%CI: 3.317-9.991; P = 0.000), hospital admission in year 2007-2010 (OR = 1.856, 95%CI: 1.376-2.504; P = 0.000), treatment with neurosurgery (OR = 6.465, 95%CI: 4.991-8.376; P = 0.000) and non-neurosurgical procedures (OR = 3.389, 95%CI: 1.828 to 6.283; P = 0.000), hospital length 1-14 d (OR = 6.023, 95%CI: 3.822-9.490; P = 0.000) were risk factors for death at discharge of TBI patients, and violent injury was a protective factor for death at discharge (OR = 0.245, 95%CI: 0.112-0.537; P = 0.000). Conclusions The mortality of TBI is still high, patients over 45 years, hospital admission in year 2007-2010, traffic accident injury, treatment with neurosurgery and non-neurosurgery, and hospital length of 1-14 d had a higher mortality at discharge. [ABSTRACT FROM AUTHOR]

Nervous system diseases are associated with complexity and diversity. As a result, the prognosis of patients deeply depends on physicians' clinical experience and their diagnosis and treatment level. With the exponential growth of medical big data and the development of statistical analysis tools, more researchers discover the pathogenesis of diseases and assist clinical process through the mining of big data, so as to improve the diagnosis, treatment, and prognosis of nervous system diseases. This paper elaborates the application of three kinds of medical big data in nervous system diseases, including structured data, radiomics, and bioinformatics. doi：10.3969/j.issn.1672⁃6731.2021.03.002

The data in electronic medical records are often missing, significantly affecting the analysis results. The ICU(intensive care unit)patients’ data in MIMIC database were analyzed for missing value interpolation, and the dataset consists of 23 groups of commonly used clinical physiological variables and 5260 samples without missing values. A K-nearest neighbor interpolation method was proposed based on deep embedded clustering. This method takes deep embedded clustering as the core, constructs the sample proximity matrix through multiple clustering, and then regards the average value of K-nearest neighbor of missing samples as the missing values. Compared with mean interpolation, median interpolation, a posteriori distribution estimation interpolation and conditional mean interpolation, the proposed method obtains higher similarity between the interpolated results and the original data, and better retains the differences between various samples. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND: The posterolateral column fracture on tibial plateau is the difficult point of traumatic orthopedics. The choice of operative approach is one of critical steps of treatment. However, nowadays there is not an acknowledged standard of choosing approach to be accepted by most scholars. OBJECTIVE: To investigate the characteristics and the incidence rate of posterolateral column fracture on tibial plateau, discuss the application prospect on adopting expanded lateral approach to treat the posterolateral column fracture. METHODS: The data of the patients with tibial plateau fractures were screened by International Classification of Disease Code from an electronic medical records database of the patients hospitalized in Mindong Hospital Affiliated to Fujian Medical University between July 2009 and March 2019. The Picture and Archiving Communication System was used to review the radiographic record on all patients’ tibial plateau fractures. Schatzker classification and three-column classification was respectively used to classify the fracture types. The posterior column was divided into posterolateral and posteromedial column. The “independent posterolateral column fracture” was defined as a fracture whose main fragment disconnected with lateral and posteromedial columns’ main body. The fracture characteristics of the posterolateral column were researched. The expanded lateral approach was adopted to treat 21 cases with displaced independent posterolateral column fractures. RESULTS AND CONCLUSION: (1) Totally 426 patients were enrolled, including 427 tibial plateau fractures. The posterolateral column fractures were involved in 267 cases and the “independent posterolateral column fractures” were involved in 126 cases. Totally 73 cases had lateral column fracture + displaced independent posterolateral column fracture within 4 cm under the articular surface on tibial plateau. (2) Twenty-one cases adopted expanded lateral approach obtained bony union. (3) It is concluded that expanded lateral approach suits lateral column + displaced independent posterolateral column fracture within 4 cm under the articular surface on tibial plateau. It will be singly adopted to treat Schatzker type II fracture or combined medial approach to treat Schatzker type V and VI fractures. The percentage of cases having the indication to adopt expanded lateral approach is about 17% in all tibial plateau fractures. The expanded lateral approach has a good application prospect. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To probe into the adverse drug reactions of drug-induced thrombocytopenia based on clinical data of patients with drug-induced thrombocytopenia in Jiangsu Shengze Hospital Affiliated to Nanjing Medical University( hereinafter referred to as "our hospital"), so as to improve the understanding of clinicians on drug-induced thrombocytopenia and reflect the value of pharmacists. METHODS: Through the LIS system of laboratory department of our hospital, the test data of all patients with platelet counts lower than normal values were collected from 2017 to 2020. Patients' gender, age, platelet count, clinical diagnosis and medication data were investigated through the HIS system and electronic medical records, the causes of the disease were investigated, adverse drug reactions were determined, and the drug types and mechanisms of thrombocytopenia were analyzed. RESULTS: Totally 44 581 cases of test data were collected and 2 024 patients with thrombocytopenia were extracted from LIS system, of which 280 patients ( 13. 83%) were drug-induced thrombocytopenia. Among 280 patients with drug-induced thrombocytopenia, 135 were males ( 48. 21 % ) and 145 were females ( 51. 79%), the majority were aged from 60 to 70 years. The drugs that induced thrombocytopenia were mainly antineoplastic drugs( 234 cases, 83. 57%), including 376 case-times of various types of antineoplastic drugs, and the top 3 drugs ranked by the number of case-times were platinum drugs(128 case-times, 34. 04%), antimetabolites(81 case-times, 21. 54% ) and anti-tumor botanical drugs (67 case-times, 17. 82%). CONCLUSIONS: There are many causes of thrombocytopenia, and according to the investigation, drug-induced thrombocytopenia accounts for the 3rd highest number of cases. A higher proportion of patients who develop drug-induced thrombocytopenia are the elderly > 60 years old receiving anti-tumor drugs. It is suggested that clinicians need to monitor the use of relevant drugs in high-risk groups and adjust the dose or change the drugs in time to reduce the occurrence of drug-induced thrombocytopenia. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To evaluate the potentially inappropriate medication ( PIM ) m elderly patients with multiple drug use based on two criteria in the geriatrics department of Zhongshan Hospital Affiliated to Xiamen University ( hereinafter referred to as "our hospital"), and to explore the influencing factors of PIM. METHODS: The electronic medical record system was used to retrospectively collect the relevant information of inpatients and outpatients in our hospital. Based on the Beers criteria (Version 2019) and the Chinese Catalogue of Potentially Inappropriate Medication for the Elderly( hereinafter referred to as the "Chinese PIM criteria"), the PIM types were evaluated, and the binary logistic regression method was used to analyze the influencing factors of PIM. RESULTS: A total of 140 elderly patients with multiple drugs ( 69 inpatients and 71 outpatients) were enrolled. Totally 41 patients ( 29. 29%) were detected with PIM by using the Beers criteria (Version 2019), and 88 patients ( 62. 86%) were detected with PIM by using the Chinese PIM criteria. Logistic regression analysis showed that among the influencing factors for PIM screened by the Beers criteria ( Version 2019), drug quantity and age-adjusted Charlson comorbidity index( aCCI) were the risk factors( OR> 1, P 1, P

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Supportive care is a primary method for treating dengue fever. Understanding the symptoms of dengue fever and its related nursing diagnosis is crucial for nurses as references for individual care. This research study was motivated by the few literature reviews available on this topic. Purpose: This study was developed to elucidate the symptoms experienced by hospitalized patients with dengue fever and to compare the consistency between symptoms and nursing diagnoses. Methods: A retrospective descriptive research method was employed. The data were collected from the electronic medical records of patients in the data pools of two regional hospitals in Kaohsiung City. A total of 105 patient records were acquired covering the period 2014-2016. IBM SPSS Statistics v22 was used to examine the descriptive statistics of patient attributes and symptoms of dengue fever using averages and percentages and the inferential statistics of symptoms, hospitalization days, and nursing diagnosis using the Chi-square test and Kappa consistency coefficient. Results: The average age of inpatients was 51.0 ± 27.3 years and the average length of hospital stays was 6.1 ± 3.6 days. The common symptoms were fever and headache. The consistency between nursing diagnosis and symptoms ranged up to 45.4%, including hyperthermia, acute pain, nausea, risk of ineffective gastrointestinal perfusion, and risk of bleeding. Inconsistency of nursing diagnosis was found to be 27.3%, including anxiety, deficient fluid volume, and risk of falls. The rate of undiagnosed symptoms was found to be 27.3%, including diarrhea, risk of infection, and impaired oral mucous membrane. Conclusions / Implications for Practice: The reasons for the inconsistency between symptoms and nursing diagnoses may relate to insufficient nursing knowledge of dengue fever and inadequate nursing diagnosis education resulting in insufficient clinical experience / poor judgment amongst nursing staff. The findings of this study suggest the need for continuity of education to make the use of a dengue-fever-symptom checklist more widespread in patient care. [ABSTRACT FROM AUTHOR]

This article describes the care experience of an elderly person who committed suicide by taking sleeping pills. The nursing duration lasted from 23 February to 27 February 2019. Information was collected by thorough observation, conversations, and reviews of medical records. Relevant information was collected using Gordon's 11 functional evaluation and comprehensive nursing assessments. Consequently, existing sexual impairment, personal coping with dysfunction, and stressful role of caregiver were the main health issues identified. Moreover, cross-team cooperation was used to proactively provide relevant information and available social resources to make an overall positive adaptation. It is recommended that the community can detect cases early and provide the best long-term care needs through professional assessment. Another long-term care agency should pay attention to the prevention of elderly depression and suicide. In addition, suicide will be prevented if good evaluation regarding the depression of the elderly is done. [ABSTRACT FROM AUTHOR]

Aiming at the problems of time series data extraction and medical concept expression difficulty in electronic medical record ( EMR) field, this paper proposed a time-controlled long-term and short-term memory neural network ( FT-LSTM) prediction model. The model efficiently captured multidimensional features, and further enabled accurate prediction of future clinical events. First, it used the FastText method to interpret vector representations of medical events, more effectively capture rich conceptual relationships in medical information. Then, it designed a time gate based on the original LSTM model to better capture the long-term and short-term information, model the event information to improve the prediction performance. The experimental results on the MIMIC-ill dataset show that, using the FT-LSTM model can predict event results with higher precision, which is of great significance. [ABSTRACT FROM AUTHOR]

The purpose of this study is to construct a risk management model of electronic records in accordance with archival appraisal elements and the theoretical framework of risk management. The Delphi method was taken to generalize the expert consensus of electronic record risks, which can provide the basis for archival agencies to self-check their risk factors. In addition, considering the feasibility of promoting into practical, this study implemented an empirical case study to recommend a risk classification structure. The complete mode of electronic records risk management, according on the base of case study, was including of risk identification, risk assessment and implement strategy were addressed. The result proposed 63 risk indicators for agencies to carry out electronic records risk assessment. The study applied the risk assessment checklist to conduct risk identification and assessment surveys of individual cases, most of which fell in low risk areas. According to the risk management theory, the risk management strategy of electronic records was proposed. For risk indicators with risk values between 3 and 4, it was recommended to adopt a prevention strategy, risk indicators with a risk value of 4 or higher, and adopted a prevention and mitigation strategy to deal with them. Finally, the risk management framework of electronic records was proposed. The contribution of this study was to accomplish a risk checklist and set up the practice assessment model for the archival agencies as a reference to put risk management into practice. [ABSTRACT FROM AUTHOR]

In line with information and communication technology (ICT) trends, nursing practice and its preparations are expected to change fundamentally over the coming decade. The Sustainable Development Goals (SDGs), issued by the United Nations, identify nurses as playing a significant role in achieving these goals and as using new technologies that will likely change how they deliver care to patients. Particularly for nursing care in developing countries, it is essential to emphasize the increased use and interoperability of electronic health records (EHR), mobile devices, big data analytics, and artificial intelligence. Four case studies, including the Malawi HIV system, community-based mobile APP in South Africa, the cloud base hospital information system (HIS) project in Marshall island, and smart hemodialysis in Vietnam, are examined in this article. In the near future, both information technology skills and interaction will have a significant impact on the nursing profession. [ABSTRACT FROM AUTHOR]

Aiming at the problems in the research methods of named entity recognition and entity relationship extraction in Chinese electronic medical records), this paper proposed an entity identification and entity relationship based on bidirectional long short-term memory and conditional random field (CRF). The method fir st used word embedding technology to convert text into numerical vector, as the input of neural network BiLSTM, combined with CRF chain structure for sequence labeling, output the maximum probability sequence, and mapping the recognition result knowledge graph by using the database tool Neo4j. Experiments show that the method can significantly improve the accuracy, recall rate and F value of entity identification and entity relationship extraction in Chinese electronic medical records. The experimental results meet the needs of clinical system applications, and have a guiding role in helping to study and construct clinical decision support systems and personalized medical recommendation services. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To analyze the effect of pleural adhesion on the thoracoscopic lobectomy in patients with non-small cell lung cancer, and explore the influencing factors of postoperative complications after thoracoscopic lobectomy. Methods:Patients with non-small cell lung cancer who underwent thoracoscopic lobectomy in our department from January 2014 to December 2017 were collected. The basic data of patients were collected by searching electronic medical records and telephone follow-up, including gender, age, BMI index, Percentage predicted forced expiratory volume in 1 s (FEV1%), American Society of Anesthesiologists (ASA), postoperative pathological findings, and preoperative complications. The patient's surgery-related conditions were collected, including pleural adhesion, operative time, intraoperative bleeding, intraoperative conversion, postoperative drainage, length of hospital stay, complications, and 30-day postoperative death. Patients were divided into two groups according to whether they had pleural adhesion or not. The basic information and postoperative conditions of the two groups were compared and analyzed. The effects of pleural adhesion on intraoperative and postoperative results were observed. In addition, the patients were divided into two groups according to whether they had postoperative complications or not. The indexes of two groups were comparatively analyzed. Logistic regression analysis was performed to investigate the risk factors for postoperative complications. Results: According to the inclusion and exclusion criteria, a total of 447 patients were included in the study and 142 patients had pleural adhesion. The operative time, intraoperative bleeding, conversion to thoracotomy, drainage at two days after surgery, drainage time, postoperative hospital stay, and postoperative complications of patients with pleural adhesion were higher than those of patients without pleural adhesion (P＜0.05). The age, female proportion, smoking number, preoperative respiratory complications, pleural adhesion, ASA score, and operation time of patients with postoperative complications were higher than those without postoperative complications (P<0.05). Pleural adhesion (OR=4.185, P=0.020), ASA scores (OR=1.143, P=0.001), smoking (OR=3.329, P=0.005), extended operative time (OR=1.623, P=0.038) and preoperative respiratory complications (OR=2.713, P=0.027) were independent risk factors for the postoperative complications. Conclusions: Pleural adhesion increases the difficulty of thoracoscopic lobectomy in patients with non-small cell lung cancer, intraoperative conversion, and risk of postoperative complications. [ABSTRACT FROM AUTHOR]

Background & Problems: Obtaining complete electronic dialysis nursing records, a tool that facilitates communication between medical teams, is critical in terms of maintaining the continuity of nursing procedures and nursing quality. An analysis of our unit indicated that nurses lacked sufficient familiarity with electronic dialysis nursing record systems. Moreover, they received insufficient training in operating these systems and lacked the guidelines necessary to maintain these records properly. Furthermore, these systems tend to be poorly designed, and an inspection system for dialysis nursing records is currently unavailable. These factors led to a rate of record completeness of only 58.2%. Purpose: To raise the rate of completeness for electronic nursing records to above 90%. Resolution: An intervention was conducted to accomplish seven tasks. These tasks included: modify the electronic dialysis nursing record system, input preset phrases in order to facilitate record compilation in the system, devise a manual to instruct staff on recordkeeping procedures, organize in-service training on system operations, conduct clinical scenario simulations for nurses to practice operating the system, recruit informatics nurses to teach other nurses about the operations, and implement an inspection system for these electronic records. Result: After implementing the intervention, the rate of completeness for electronic nursing records improved to 96% and the average time required for nurses to complete a nursing record decreased from 21 mins 35 s to 8 mins 15 s. Conclusion: The developed intervention significantly improved the completeness of electronic nursing records, reduced the time required for recordkeeping, and ensured adequate nursing quality for dialysis patients. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Using patient records and information systems not only improves collaboration among healthcare professionals but also enhances patient-care outcomes. Based on this, inter-professional collaboration has been increasingly applied in patient care in recent years. Purpose: To explore the acceptance of nurses of the inter-disciplinary care system, the patient-record completion rate, and the consultation response rate. Methods: A questionnaire was developed based on Davis Technology Acceptance Model and DeLone & McLean Information Systems Success Model that included the key elements of system success (system quality and information quality) and attitudes toward use (perceived usefulness and perceived ease of use). A patient record checklist and the number of consultation responses were collected as well. Results: This study collected 185 completed questionnaires and 817 copies of patient records as well as the associated consultation response rates. The results revealed that nurses held positive attitudes and that questionnaire variables were positively correlated. Additionally, perceived usefulness explained 60% of the variation in attitude toward use. In addition, the rate of completion for patient records in subcategories increased from 41% to 62%. Finally, while the overall team response rate of the social-worker and respiratory groups increased, that of the rehabilitation group decreased. Conclusions: Nurses accept the need to use inter-disciplinary care systems to enhance the completeness of patient records. However, the decreased consultation response rate may relate to the inability to update system functions. It is suggested that an auto-consultation response function be designed to provide reminders in order to improve the consultation response rate. [ABSTRACT FROM AUTHOR]

The best first-aid treatment for cardiac arrest patients is advanced cardiac life support (ACLS) in terms both of saving lives and of reducing the incidence of sequelae. The American Heart Association (AHA) published updated ACLS guidelines for care in 2015. These updated guidelines emphasized the importance of teamwork in resuscitation, noting that, in addition to standard procedures, team members should be familiar with their distinct roles and should cooperate together during emergent situations. Implementing ACLS is not easy due to stress and unfamiliarity with the process and thus often achieves less-than-optimal results in practice. However, ACLS is a standard approach that uses the same procedures to address different cardiac arrest situations. Therefore, we wanted to use an information system to assist the medical team to fully implement the ACLS process. The information system helps the medical team perform resuscitation actions more intensively and precisely while avoiding problems and mistakes due to forgetfulness / unfamiliarity, facilitating an optimal resuscitation effort. Concurrently, electronic medical and nursing records are completed automatically, avoiding the need for medical staff to compile these records afterwards. This information system helps save time and effort and improves precision. Furthermore, data analysis is more convenient, which facilitates the effective management and supervision of resuscitation quality. The information system performs timing, prompting, and guidance in accordance with the ACLS process and records the procedures that will used in emergency treatment (i.e., chest compression frequency, establishment of intravenous route, placement of endotracheal tubes, electric shock, drug type, dose) with a simple click of a mouse. Finally, the associated medical record is completed and logged as soon as the automatically generated file is uploaded. All hospital staffs may use this information system to assist in the implementation of advanced CPR. The system improves the quality of the first aid measures applied in life support, reduces the burden on clinics and medical staff, and streamlines the preparation and submission of medical records. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Lung Cancer is the property of Chinese Journal of Lung Cancer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: The aims of this study were to explore the factors that influenced hospital staff in protecting the privacy of the electronic medical record (EMR) and to conduct a multi-group analysis comparing perceptions about EMR privacy protection by physicians and other hospital staff. Methods: Based on the Theory of Planned Behavior, a cross-sectional survey was conducted to collect data from one military hospital in southern Taiwan. The study subjects were all hospital staff and were recruited via convenience sampling. Results: A total of 129 valid questionnaires was collected. Attitude (AT), subjective norm (SN), and perceived behavioral control (PBC) were positively related to hospital staffs' intention (I) to protect EMR privacy. Moreover, the relationships of AT→I, SN→I, and PBC→I varied significantly between physicians and other hospital staff. Physicians had stronger beliefs about the relationships between SN→I and PBC→I. Conclusions: This study suggested that the subject hospital should offer more training programs pertinent to the protection of EMR privacy. Physicians should also be reminded to engage in these training programs. The hospital could improve staff intention to protect EMR privacy through the influence of the director or their colleagues and also by providing sufficient software and hardware to protect EMR privacy. These measures could decrease patients' concerns about privacy of the EMR and be beneficial to the promotion of the EMR in the future. [ABSTRACT FROM AUTHOR]

Objective The purpose of this study was to analyze the relation of blood glucose variability and 28-day mortality in patients with different degree sepsis. Methods From September 1, 2010 to September 30, 2012, all adult patients diagnosed with sepsis and treated at least 3 days in Emergency ICU (EICU) of the first affiliated hospital of Kunming Medical University were enrolled in the study. Then the blood glucose levels and the other requisite clinical data were obtained from historical electronic medical records of patients excluding the patients reached exclusive criteria. The maximum and mean of blood glucose, and the glucose variability (the standard deviation,SD of blood glucose) in each patient were calculated. The patients were assigned according to severity of sepsis, then the relationship between SD of blood glucose and 28-day mortality was statistically assessed. Results There was an important correlation between SD of blood glucose and 28-day mortality (OR=4.237, =0.021) . The glucose variability increased with the serious of sepsis ( = 0.016) . Conclusion Glucose variability is an independent predictor of 28-day mortality in septic patients. In addition, the severity of sepsis has a positive correlation with blood glucose variability. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the recognition of acute respiratory infection (ARI) by a pretrained model based on electronic medical records (EMRs). Methods: 38 581 EMRs were obtained from Chongqing University Three Gorges Hospital in December 2021. Bidirectional encoder representation from transformers (BERT) pretrained model was used to identify ARI in EMRs. The results of medical professionals were considered as the gold standard to calculate the sensitivity, specificity, Kappa value, and area under the curve of the receiver operating characteristic (AUC). Results: There were 3 817 EMRs in the test set, with 1 200 ARIs. A total of 1 205 cases were determined as ARI by the model, with a sensitivity of 92.67% (1 112/1 200) and a specificity of 96.45% (2 524/2 617). The model identified ARI with similar accuracy in males and females (AUCs 0.95 and 0.94, respectively), and was more accurate in identifying ARI cases in those aged less than 18 than in adults 18-59 and adults 60 and older (AUCs 0.94, 0.89 and 0.94, respectively). The current model had a better identification of ARIs in outpatient patients than that in hospitalized patients, with AUCs of 0.74 and 0.95, respectively. Conclusion: The use of the BERT pretrained model based on EMRs has a good performance in the recognition of ARI cases, especially for the outpatients and juveniles. It shows a great potential to be applied to the monitoring of ARI cases in medical institutions.

PURPOSE: To design an excel form which can prompt dental implant patient appointment through color change, which can scientifically manage implant EMR library through appropriate interlinkage and number. METHODS: An excel form based on operating system Windows XP was designed and software 2003 Microsoft excel was used, which was configured to change color with the passage of time by the use of command "conditional format". RESULTS: An excel form was designed. The color turned to red automatically on the day the patient underwent implant surgery. It turned to yellow when the patient recalled 2 weeks after the first operation, to green when the patient underwent secondary operation. It was designed to be gray when all the procedures of implant restoration was finished. In addition, we could know patients' main implant situation through directly opening his EMR when clicking on his name or number. CONCLUSIONS: Dentists can remind the implant patient appointment schedule through color change of an excel form, and can consult the implant patient EMR directly through interlinkage or number. [ABSTRACT FROM AUTHOR]

Purpose: This study was performed to compare the costs of nursing interventions implemented for the obstetrical and gynecological patients using Korean Reimbursement System and ABC codes system developed in the US for costing out interventions performed by health care professional. Methods: First, the narrative data on nursing interventions were extracted from electronic medical record system of a tertiary university and mapped with Nursing Intervention Classification (NIC) by two researchers until 100% consent was reached. Narrative nursing interventions mapped with NIC were then remapped with ABC codes system using the electronic program developed in the research. The mapping data were analyzed with real numbers, frequency, percentage, mean, and standard deviation. Results: More nursing interventions were mapped with ABC codes than Korean reimbursement system. Total of 97 different types of narrative interventions could be mapped with NIC, 43 NIC interventions could be reimbursed by ABC code but only 16 NIC interventions were reimbursed by Korea Reimbursement System. Conclusion: Korean medical insurance fee system needs amendment to include more comprehensively interventions performed by nurses which are very important to patient outcomes. Further study is needed to develop strategies to costing out nursing interventions. [ABSTRACT FROM AUTHOR]

We analyzed the contents and structure of current electronics medical records, anti proposed a definition of Five-Tuples pattern and another more fine-grained definition of two-turples pattern and semantic classes. On this foundation, we proposed a series of algorithms including patterns generalization, patterns automatic extraction and medical information extraction. The experiments with 312 actual medical records show that the system performs well both in the precision and recall. And because of the functionality of self-learning, the system will be more outstanding with an increase in the training corpus. [ABSTRACT FROM AUTHOR]

The paper analyzes the specificity of term recognition in acupuncture clinical literature and compares the advantages and disadvantages of three named entity recognition (NER) methods adopted in the field of traditional Chinese medicine. It is believed that the bi-directional long short-term memory networks-conditional random fields (Bi LSTM-CRF) may communicate the context information and complete NER by using less feature rules. This model is suitable for term recognition in acupuncture clinical literature. Based on this model, it is proposed that the process of term recognition in acupuncture clinical literature should include 4 aspects, i.e. literature pretreatment, sequence labeling, model training and effect evaluation, which provides an approach to the terminological structurization in acupuncture clinical literature.

The medical literature contains a wealth of valuable medical knowledge. At present, the research on extraction of entity relationship in medical literature has made great progress, but with the exponential increase in the number of medical literature, the annotation of medical text has become a big problem. In order to solve the problem of manual annotation time such as consuming and heavy workload, a remote monitoring annotation method is proposed, but this method will introduce a lot of noise. In this paper, a novel neural network structure based on convolutional neural network is proposed, which can solve a large number of noise problems. The model can use the multi-window convolutional neural network to automatically extract sentence features. After the sentence vectors are obtained, the sentences that are effective to the real relationship are selected through the attention mechanism. In particular, an entity type (ET) embedding method is proposed for relationship classification by adding entity type characteristics. The attention mechanism at sentence level is proposed for relation extraction in allusion to the unavoidable labeling errors in training texts. We conducted an experiment using 968 medical references on diabetes, and the results showed that compared with the baseline model, the present model achieved good results in the medical literature, and F1-score reached 93.15%. Finally, the extracted 11 types of relationships were stored as triples, and these triples were used to create a medical map of complex relationships with 33 347 nodes and 43 686 relationship edges. Experimental results show that the algorithm used in this paper is superior to the optimal reference system for relationship extraction.

Objective: To explore the rule of point selection in treatment of cerebral palsy with acupuncture in preschool children., Methods: Based on the electronic medical records of Xi'an Encephalopathy Hospital of TCM, through structuring medical record text, acupuncture prescriptions were extracted. Using the data mining tools of the ancient and modern medical record cloud platform V2.2.3 and the clinical effective prescription and molecular mechanism analysis system of traditional Chinese medicine V2.0, the cluster analysis and complex network analysis were conducted on acupuncture prescriptions., Results: Of 1584 acupuncture prescriptions for cerebral palsy in children, there were 84 acupoints and stimulating areas of scalp acupuncture, of which, foot-motor-sensory area, balance area and Sanyinjiao (SP 6) were the top 3 acupoints with the highest use rate. With cluster analysis, 5 groups of common supplementary acupoints and stimulating areas were found, named, Weizhong (BL 40) and Waiguan (TE 5), Shousanli (LI 10), Xingjian (LR 2), Xuanzhong (GB 39) and Chengfu (BL 36), foot-motor-sensory area, balance area and Sanyinjiao (SP 6), Xuehai (SP 10) and Fenglong (ST 40), Pishu (BL 20), motor area and Yanglingquan (GB 34). With complex network analysis on core prescriptions, 13 core acupoints and stimulating areas of scalp acupuncture were obtained, including 3 core main points, i.e. Sanyinjiao (SP 6), balance area and foot-motor-sensory area and 10 sub-core points, i.e. Taichong (LR 3), motor area, Xuehai (SP 10), Ganshu (BL 18), Pishu (BL 20), Yanglingquan (GB 34), Sishencong (EX-HN 1), Baihui (GV 20), Fengchi (GB 20) and Shenshu (BL 23)., Conclusion: In treatment of acupuncture for cerebral palsy in preschool children, the core prescriptions reveal the simultaneous treatment of exterior and interior, the mutual regulation of yin and yang and the combination of acupoints with stimulating ares of scalp acupuncture for both encephalopathy and paralysis.