detect

检测
  • 文章类型: Journal Article
    背景:亚硫酸氢盐(HSO3-)用作漂白剂,抗氧化剂,抗菌,和生物系统中酶促反应的调节剂。然而,亚硫酸氢盐含量异常对健康有害。次氯酸(HOCl),作为生物活性小分子,对于维持生物体的正常生物学功能至关重要。其平衡的破坏可导致氧化应激和各种疾病。因此,监测HOCl和HSO3-在细胞和体内水平的波动对研究其生理和病理功能至关重要。
    结果:这项研究利用噻吩香豆素-茚二酮结构构建了一种新型的NIR双功能比色荧光探针,以鉴定次氯酸盐(ClO-)和亚硫酸氢盐(HSO3-)。通过使用CSO-IO识别HSO3-和HOCl,产生了两种不同的产品,显示绿色和蓝色荧光,分别。该性质有效地允许同时双功能检测HSO3-(LOD:113nM)和HOCl(LOD:43nM)。
    结论:在这项工作中,生物相容性分子CSO-IO已被有效设计用于检测活细胞和斑马鱼中的HOCl/HSO3-。因此,双功能荧光探针有可能作为分子工具在复杂的生物系统中同时检测HSO3-衍生化合物和HOCl。
    BACKGROUND: Bisulfite (HSO3-) serves as a bleaching agent, antioxidant, antimicrobial, and regulator of enzymatic reactions in biosystem. However, abnormal levels of bisulfite can be detrimental to health. Hypochlorous acid (HOCl), which acts as bioactive small molecules, is crucial for maintaining normal biological functions in living organisms. Disruption of its equilibrium can lead to oxidative stress and various diseases. Therefore, it\'s essential to monitor the fluctuations of HOCl and HSO3- at cellular and in vivo levels to study their physiological and pathological functions.
    RESULTS: This study constructed a novel NIR bifunctional colorimetric fluorescent probe using thienocoumarin-indanedione structures to identify hypochlorite (ClO-) and bisulfite (HSO3-). By using CSO-IO to recognize HSO3- and HOCl, two distinct products were generated, displaying green and blue fluorescence, respectively. This property effectively allows for the simultaneous dual-functional detection of HSO3- (LOD: 113 nM) and HOCl (LOD: 43 nM).
    CONCLUSIONS: In this work, the biocompatible molecule CSO-IO has been effectively designed to detect HOCl/HSO3- in living cells and zebrafish. As a result, the dual-functional fluorescent probe has the potential to be utilized as a molecular tool to detect HSO3- derived compounds and HOCl simultaneously within the complex biological system.
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  • 文章类型: Journal Article
    自2020年初SARS-CoV-2大流行爆发以来,次氯酸钠消毒剂的数量显着增加。次氯酸钠经历水解以产生用于病毒根除的次氯酸。这种基于氯的消毒剂由于其有效性而广泛用于公共消毒。虽然次氯酸钠消毒很方便,过度和不分青红皂白的使用会损害水环境,并对人类健康构成威胁。次氯酸,活性氧,在对流层中起着至关重要的作用,平流层化学,和氧化能力。此外,次氯酸作为生物系统中的活性氧是至关重要的,其不规则的新陈代谢和水平与几种疾病有关。因此,鉴定次氯酸对准确了解其环境和生物学功能至关重要。这里,我们构建了一种新的荧光探针,利用扭曲的分子内电荷转移机制快速准确地检测环境水和生物系统中的次氯酸。当暴露于次氯酸时,探针显示荧光显着增加,展示了其优异的选择性,快速响应时间(小于10秒),一个大的斯托克斯位移(~102纳米),和15.5nM的低检测限。
    Since the onset of the SARS-CoV-2 pandemic in early 2020, there has been a notable rise in sodium hypochlorite disinfectants. Sodium hypochlorite undergoes hydrolysis to generate hypochlorous acid for virus eradication. This chlorine-based disinfectant is widely utilized for public disinfection due to its effectiveness. Although sodium hypochlorite disinfection is convenient, its excessive and indiscriminate use can harm the water environment and pose a risk to human health. Hypochlorous acid, a reactive oxygen species, plays a crucial role in the troposphere, stratospheric chemistry, and oxidizing capacity. Additionally, hypochlorous acid is vital as a reactive oxygen species in biological systems, and its irregular metabolism and level is associated with several illnesses. Thus, it is crucial to identify hypochlorous acid to comprehend its environmental and biological functions precisely. Here, we constructed a new fluorescent probe, utilizing the twisted intramolecular charge transfer mechanism to quickly and accurately detect hypochlorous acid in environmental water and biosystems. The probe showed a notable increase in fluorescence when exposed to hypochlorous acid, demonstrating its excellent selectivity, fast response time (less than 10 seconds), a large Stokes shift (∼ 102 nm), and a low detection limit of 15.5 nM.
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  • 文章类型: Journal Article
    急性肾损伤(AKI)是临床恶化和肾毒性的标志。虽然有许多研究提供了早期检测AKI的预测模型,使用基于分布式研究网络(DRN)的时间序列数据预测AKI发生的研究很少见。
    在这项研究中,我们旨在通过将基于可解释长短期记忆(LSTM)的模型应用于使用DRN的肾毒性药物的患者的基于医院电子健康记录(EHR)的时间序列数据来检测AKI的早期发生.
    我们使用DRN对6家医院的数据进行了多机构回顾性队列研究。对于每个机构,使用5种用于AKI的药物构建了基于患者的数据集,并使用可解释的多变量LSTM(IMV-LSTM)模型进行训练。这项研究使用倾向评分匹配来减轻人口统计学和临床特征的差异。此外,证明了每个机构和药物的AKI预测模型贡献变量的时间注意力值,使用单向方差分析确认了病例和对照数据之间非常重要的特征分布差异。
    这项研究分析了8643例和31,012例有和没有AKI的患者,分别,6家医院在分析AKI发作的分布时,万古霉素显示起病较早(中位数12,IQR5-25天),与其他药物相比,阿昔洛韦最慢(中位数23,IQR10-41天)。我们用于AKI预测的时间深度学习模型对大多数药物表现良好。阿昔洛韦在每种药物的受试者工作特征曲线评分下的平均面积最高(0.94),其次是对乙酰氨基酚(0.93),万古霉素(0.92),萘普生(0.90),和塞来昔布(0.89)。根据AKI预测模型中变量的时间注意力值,已证实的淋巴细胞和钙万古霉素的关注度最高,而淋巴细胞,白蛋白,血红蛋白会随着时间的推移而减少,尿液pH值和凝血酶原时间有增加的趋势。
    可以通过基于EHR的DRN应用基于时间序列数据的IMV-LSTM来实现对AKI爆发的早期监测。这种方法可以帮助识别风险因素,并在AKI发生前开出引起肾毒性的药物时,早期发现药物不良反应。
    UNASSIGNED: Acute kidney injury (AKI) is a marker of clinical deterioration and renal toxicity. While there are many studies offering prediction models for the early detection of AKI, those predicting AKI occurrence using distributed research network (DRN)-based time series data are rare.
    UNASSIGNED: In this study, we aimed to detect the early occurrence of AKI by applying an interpretable long short-term memory (LSTM)-based model to hospital electronic health record (EHR)-based time series data in patients who took nephrotoxic drugs using a DRN.
    UNASSIGNED: We conducted a multi-institutional retrospective cohort study of data from 6 hospitals using a DRN. For each institution, a patient-based data set was constructed using 5 drugs for AKI, and an interpretable multivariable LSTM (IMV-LSTM) model was used for training. This study used propensity score matching to mitigate differences in demographics and clinical characteristics. Additionally, the temporal attention values of the AKI prediction model\'s contribution variables were demonstrated for each institution and drug, with differences in highly important feature distributions between the case and control data confirmed using 1-way ANOVA.
    UNASSIGNED: This study analyzed 8643 and 31,012 patients with and without AKI, respectively, across 6 hospitals. When analyzing the distribution of AKI onset, vancomycin showed an earlier onset (median 12, IQR 5-25 days), and acyclovir was the slowest compared to the other drugs (median 23, IQR 10-41 days). Our temporal deep learning model for AKI prediction performed well for most drugs. Acyclovir had the highest average area under the receiver operating characteristic curve score per drug (0.94), followed by acetaminophen (0.93), vancomycin (0.92), naproxen (0.90), and celecoxib (0.89). Based on the temporal attention values of the variables in the AKI prediction model, verified lymphocytes and calcvancomycin ium had the highest attention, whereas lymphocytes, albumin, and hemoglobin tended to decrease over time, and urine pH and prothrombin time tended to increase.
    UNASSIGNED: Early surveillance of AKI outbreaks can be achieved by applying an IMV-LSTM based on time series data through an EHR-based DRN. This approach can help identify risk factors and enable early detection of adverse drug reactions when prescribing drugs that cause renal toxicity before AKI occurs.
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  • 文章类型: Journal Article
    背景:声乐生物标志物,从声音特征的声学分析中得出,提供非侵入性的医疗筛查途径,诊断,和监测。先前的研究证明了通过智能手机记录语音的声学分析来预测2型糖尿病的可行性。在这项工作的基础上,这项研究探讨了音频数据压缩对声学声乐生物标志物开发的影响,这对于在医疗保健中更广泛的适用性至关重要。
    目的:本研究的目的是分析常见的音频压缩算法(MP3,M4A,和WMA)由3种不同的转换工具以2种比特率应用,影响对声音生物标志物检测至关重要的特征。
    方法:使用转换为MP3,M4A的未压缩语音样本,研究了音频数据压缩对声学声乐生物标志物开发的影响。和WMA格式在2比特率(320和128kbps)与MediaHuman(MH)音频转换器,WonderShare(WS)UniConverter,和快进运动图像专家组(FFmpeg)。数据集包括来自505名参与者的记录,总共17298个音频文件,使用智能手机收集。参与者每天记录一个固定的英语句子,最多6次,最长14天。特征提取,包括音高,抖动,强度,和梅尔频率倒谱系数(MFCC),是使用Python和Parselmouth进行的。使用Wilcoxon符号秩检验和Bonferroni校正进行多重比较用于统计分析。
    结果:在这项研究中,最初从505名参与者那里录制了36,970个音频文件,筛选后,有17298张录音符合固定的句子标准。音频转换软件之间的差异,MH,WS,和FFmpeg,值得注意的是,影响压缩结果,如恒定或可变比特率。分析包括不同的数据压缩格式和广泛的语音特征和MFCC。Wilcoxon符号秩检验得出P值,低于Bonferroni校正的显著性水平的那些表明由于压缩引起的显著改变。结果表明了跨格式和比特率的压缩的特定特征影响。与WS转换的文件相比,MH转换的文件表现出更大的弹性。比特率也影响了功能稳定性,38例唯一受单一比特率影响。值得注意的是,语音特征在各种转换方法中显示出比MFCC更高的稳定性。
    结论:发现压缩效果具有特定特征,MH和FFmpeg表现出更大的弹性。某些功能一直受到影响,强调理解特征弹性对诊断应用的重要性。考虑到声乐生物标志物在医疗保健中的实施,为数据存储或传输目的找到通过压缩保持一致的功能是很有价值的。专注于特定的功能和格式,未来的研究可以拓宽范围,包括不同的特征,实时压缩算法,和各种记录方法。这项研究增强了我们对音频压缩对语音特征和MFCC的影响的理解,为跨领域开发应用程序提供见解。该研究强调了特征稳定性在处理压缩音频数据中的重要性,为在不断发展的技术环境中使用明智的语音数据奠定基础。
    BACKGROUND: Vocal biomarkers, derived from acoustic analysis of vocal characteristics, offer noninvasive avenues for medical screening, diagnostics, and monitoring. Previous research demonstrated the feasibility of predicting type 2 diabetes mellitus through acoustic analysis of smartphone-recorded speech. Building upon this work, this study explores the impact of audio data compression on acoustic vocal biomarker development, which is critical for broader applicability in health care.
    OBJECTIVE: The objective of this research is to analyze how common audio compression algorithms (MP3, M4A, and WMA) applied by 3 different conversion tools at 2 bitrates affect features crucial for vocal biomarker detection.
    METHODS: The impact of audio data compression on acoustic vocal biomarker development was investigated using uncompressed voice samples converted into MP3, M4A, and WMA formats at 2 bitrates (320 and 128 kbps) with MediaHuman (MH) Audio Converter, WonderShare (WS) UniConverter, and Fast Forward Moving Picture Experts Group (FFmpeg). The data set comprised recordings from 505 participants, totaling 17,298 audio files, collected using a smartphone. Participants recorded a fixed English sentence up to 6 times daily for up to 14 days. Feature extraction, including pitch, jitter, intensity, and Mel-frequency cepstral coefficients (MFCCs), was conducted using Python and Parselmouth. The Wilcoxon signed rank test and the Bonferroni correction for multiple comparisons were used for statistical analysis.
    RESULTS: In this study, 36,970 audio files were initially recorded from 505 participants, with 17,298 recordings meeting the fixed sentence criteria after screening. Differences between the audio conversion software, MH, WS, and FFmpeg, were notable, impacting compression outcomes such as constant or variable bitrates. Analysis encompassed diverse data compression formats and a wide array of voice features and MFCCs. Wilcoxon signed rank tests yielded P values, with those below the Bonferroni-corrected significance level indicating significant alterations due to compression. The results indicated feature-specific impacts of compression across formats and bitrates. MH-converted files exhibited greater resilience compared to WS-converted files. Bitrate also influenced feature stability, with 38 cases affected uniquely by a single bitrate. Notably, voice features showed greater stability than MFCCs across conversion methods.
    CONCLUSIONS: Compression effects were found to be feature specific, with MH and FFmpeg showing greater resilience. Some features were consistently affected, emphasizing the importance of understanding feature resilience for diagnostic applications. Considering the implementation of vocal biomarkers in health care, finding features that remain consistent through compression for data storage or transmission purposes is valuable. Focused on specific features and formats, future research could broaden the scope to include diverse features, real-time compression algorithms, and various recording methods. This study enhances our understanding of audio compression\'s influence on voice features and MFCCs, providing insights for developing applications across fields. The research underscores the significance of feature stability in working with compressed audio data, laying a foundation for informed voice data use in evolving technological landscapes.
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  • 文章类型: Journal Article
    背景:人工智能(AI)的使用可以彻底改变医疗保健,但这引发了风险担忧。因此,了解临床医生如何信任和接受AI技术至关重要。胃肠病学,由于其性质是基于图像和干预重的专业,是人工智能辅助诊断和管理可以广泛应用的领域。
    目的:本研究旨在研究胃肠病学家或胃肠外科医生如何接受和信任AI在计算机辅助检测(CADe)中的使用,计算机辅助表征(CADx),和计算机辅助干预(CADi)在结肠镜检查中结直肠息肉。
    方法:我们于2022年11月至2023年1月进行了基于网络的问卷调查,涉及亚太地区的5个国家或地区。问卷包括用户背景和人口统计等变量;使用人工智能的意图,感知风险;接受;以及对人工智能辅助检测的信任,表征,和干预。我们为参与者提供了与结肠镜检查和结直肠息肉管理相关的3种AI方案。这些场景反映了结肠镜检查中现有的AI应用,即息肉的检测(CADe),息肉(CADx)的表征,和AI辅助息肉切除术(CADi)。
    结果:总计,165胃肠病学家和胃肠外科医师使用医学交流专家设计的结构化问卷对基于网络的调查做出了回应。参与者的平均年龄为44岁(SD9.65),大部分为男性(n=116,70.3%),大多在公立医院工作(n=110,66.67%)。参与者报告了相对较高的AI暴露,111人(67.27%)报告使用人工智能进行消化系统疾病的临床诊断或治疗。胃肠病学家对在诊断中使用AI非常感兴趣,但在风险预测和接受AI方面表现出不同程度的保留。大多数参与者(n=112,72.72%)也表示有兴趣在未来的实践中使用AI。CADe被83.03%(n=137)的受访者接受,CADx被78.79%(n=130)接受,CADi的接受率为72.12%(n=119)。85.45%(n=141)的受访者信任CADe和CADx,72.12%(n=119)的受访者信任CADi。在风险认知方面没有特定应用的差异,但更有经验的临床医生给出了较低的风险评级.
    结论:胃肠病学家报告了在大肠息肉治疗中使用AI辅助结肠镜检查的总体接受度和信任度较高。然而,此信任级别取决于应用场景。此外,风险感知之间的关系,接受,信任在胃肠病学实践中使用人工智能并不简单。
    BACKGROUND: The use of artificial intelligence (AI) can revolutionize health care, but this raises risk concerns. It is therefore crucial to understand how clinicians trust and accept AI technology. Gastroenterology, by its nature of being an image-based and intervention-heavy specialty, is an area where AI-assisted diagnosis and management can be applied extensively.
    OBJECTIVE: This study aimed to study how gastroenterologists or gastrointestinal surgeons accept and trust the use of AI in computer-aided detection (CADe), computer-aided characterization (CADx), and computer-aided intervention (CADi) of colorectal polyps in colonoscopy.
    METHODS: We conducted a web-based questionnaire from November 2022 to January 2023, involving 5 countries or areas in the Asia-Pacific region. The questionnaire included variables such as background and demography of users; intention to use AI, perceived risk; acceptance; and trust in AI-assisted detection, characterization, and intervention. We presented participants with 3 AI scenarios related to colonoscopy and the management of colorectal polyps. These scenarios reflect existing AI applications in colonoscopy, namely the detection of polyps (CADe), characterization of polyps (CADx), and AI-assisted polypectomy (CADi).
    RESULTS: In total, 165 gastroenterologists and gastrointestinal surgeons responded to a web-based survey using the structured questionnaire designed by experts in medical communications. Participants had a mean age of 44 (SD 9.65) years, were mostly male (n=116, 70.3%), and mostly worked in publicly funded hospitals (n=110, 66.67%). Participants reported relatively high exposure to AI, with 111 (67.27%) reporting having used AI for clinical diagnosis or treatment of digestive diseases. Gastroenterologists are highly interested to use AI in diagnosis but show different levels of reservations in risk prediction and acceptance of AI. Most participants (n=112, 72.72%) also expressed interest to use AI in their future practice. CADe was accepted by 83.03% (n=137) of respondents, CADx was accepted by 78.79% (n=130), and CADi was accepted by 72.12% (n=119). CADe and CADx were trusted by 85.45% (n=141) of respondents and CADi was trusted by 72.12% (n=119). There were no application-specific differences in risk perceptions, but more experienced clinicians gave lesser risk ratings.
    CONCLUSIONS: Gastroenterologists reported overall high acceptance and trust levels of using AI-assisted colonoscopy in the management of colorectal polyps. However, this level of trust depends on the application scenario. Moreover, the relationship among risk perception, acceptance, and trust in using AI in gastroenterology practice is not straightforward.
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  • 文章类型: Journal Article
    背景:在依靠行政卫生数据时,对医院获得性压力性伤害(HAPI)的监视通常是次优的,众所周知,国际疾病分类(ICD)代码具有很长的延迟,并且编码不足。我们在自由文本笔记上利用自然语言处理(NLP)应用程序,特别是住院护理笔记,来自电子病历(EMR),更准确、更及时地识别HAPI。
    目的:这项研究旨在表明,基于EMR的表型算法比单独的ICD-10-CA算法更适合检测HAPI,而临床日志使用护理笔记通过NLP以更高的准确性记录。
    方法:在2015年至2018年在卡尔加里进行的一项临床试验中,从当地三级急性护理医院的从头到脚皮肤评估中确定了患有HAPI的患者。艾伯塔省,加拿大。与出院摘要数据库链接后,从EMR数据库中提取试验期间记录的临床记录。在模型开发过程中,通过顺序正向选择处理了几种临床注释的不同组合。使用随机森林(RF)开发了用于HAPI检测的文本分类算法,极端梯度提升(XGBoost),和深度学习模型。调整分类阈值以使该模型能够实现与基于ICD的表型研究相似的特异性。评估了每个模型的性能,并在指标之间进行了比较,包括灵敏度,正预测值,负预测值,和F1得分。
    结果:本研究使用了来自280名符合条件的患者的数据,其中97例患者在试验期间出现HAPI.RF是最佳执行模型,灵敏度为0.464(95%CI0.365-0.563),特异性0.984(95%CI0.965-1.000),F1评分为0.612(95%CI为0.473-0.751)。与先前报道的基于ICD的算法的性能相比,机器学习(ML)模型在不牺牲太多特异性的情况下达到了更高的灵敏度。
    结论:基于EMR的NLP表型算法在HAPI病例检测中的性能优于单独的ICD-10-CA代码。EMR中每日生成的护理笔记是ML模型准确检测不良事件的宝贵数据资源。该研究有助于提高自动化医疗质量和安全监控。
    BACKGROUND: Surveillance of hospital-acquired pressure injuries (HAPI) is often suboptimal when relying on administrative health data, as International Classification of Diseases (ICD) codes are known to have long delays and are undercoded. We leveraged natural language processing (NLP) applications on free-text notes, particularly the inpatient nursing notes, from electronic medical records (EMRs), to more accurately and timely identify HAPIs.
    OBJECTIVE: This study aimed to show that EMR-based phenotyping algorithms are more fitted to detect HAPIs than ICD-10-CA algorithms alone, while the clinical logs are recorded with higher accuracy via NLP using nursing notes.
    METHODS: Patients with HAPIs were identified from head-to-toe skin assessments in a local tertiary acute care hospital during a clinical trial that took place from 2015 to 2018 in Calgary, Alberta, Canada. Clinical notes documented during the trial were extracted from the EMR database after the linkage with the discharge abstract database. Different combinations of several types of clinical notes were processed by sequential forward selection during the model development. Text classification algorithms for HAPI detection were developed using random forest (RF), extreme gradient boosting (XGBoost), and deep learning models. The classification threshold was tuned to enable the model to achieve similar specificity to an ICD-based phenotyping study. Each model\'s performance was assessed, and comparisons were made between the metrics, including sensitivity, positive predictive value, negative predictive value, and F1-score.
    RESULTS: Data from 280 eligible patients were used in this study, among whom 97 patients had HAPIs during the trial. RF was the optimal performing model with a sensitivity of 0.464 (95% CI 0.365-0.563), specificity of 0.984 (95% CI 0.965-1.000), and F1-score of 0.612 (95% CI of 0.473-0.751). The machine learning (ML) model reached higher sensitivity without sacrificing much specificity compared to the previously reported performance of ICD-based algorithms.
    CONCLUSIONS: The EMR-based NLP phenotyping algorithms demonstrated improved performance in HAPI case detection over ICD-10-CA codes alone. Daily generated nursing notes in EMRs are a valuable data resource for ML models to accurately detect adverse events. The study contributes to enhancing automated health care quality and safety surveillance.
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  • 文章类型: Journal Article
    肼(N2H4),一种重要的化工原料,改善人们的生活,促进人类进步。肼的使用或泄漏已造成环境污染,影响水,土壤,和生物。肼同时由于其致癌特性而对人类健康存在可能的风险。因此,肼的快速和精确检测在环境研究和生物环境中至关重要。我们制备了一种红色荧光开启探针(XT-HZ)来特异性检测肼。该探针对具有570nm的激发波长和625nm的发射波长的肼(63nM)具有低检测限。此外,探针XT-HZ具有优异的水溶性,高选择性,对肼的检测具有良好的灵敏度。最后,XT-HZ探针用于活细胞中N2H4的成像,斑马鱼和环境水样。
    Hydrazine (N2H4), a crucial chemical raw material, enhances people\'s lives and fosters human progress. Hydrazine usage or leakage has caused environmental contamination, affecting water, soil, and living beings. Hydrazine simultaneously presents a possible risk to human health due to its carcinogenic properties. Thus, quick and precise detection of hydrazine is crucial in environmental studies and biological contexts. We prepared a red-emitting fluorescence turn-on probe (XT-HZ) to detect hydrazine specifically. The probe has a low detecting limit for hydrazine (63 nM) with excitation wavelength at 570 nm and emission wavelength at 625 nm. Besides, the probe XT-HZ had excellent water solubility, high selectivity, and good sensitivity for detecting hydrazine. Finally, probe XT-HZ was applied in the imaging of N2H4 in living cells, zebrafish and environmental water samples.
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  • 文章类型: Journal Article
    这篇观点论文考虑了作者对智能手机潜在作用的看法,可穿戴设备,和其他癌症诊断技术。我们相信,这些技术可能是追求早期癌症诊断的有价值的补充,因为它们提供了及时检测信号或症状的解决方案,并监测行为的细微变化,否则可能会被遗漏。除了信号检测,技术可以帮助症状解释,指导和促进获得医疗保健。本文旨在概述为什么这些技术对早期癌症检测有价值的科学原理。以及概述研究和开发的下一步步骤,以推动调查智能手机和可穿戴设备在这方面的潜力,并优化实施。我们提请注意成功实施的潜在障碍,包括通过与目标群体的强大研究来开发具有足够实用性和准确性的信号和传感器的难度。存在监管挑战;创新加剧不平等的潜力;以及围绕可接受性的问题,摄取,以及预期目标群体和医疗保健从业人员的正确使用。最后,有可能对个人和医疗保健服务造成意想不到的后果,包括不必要的焦虑,增加症状负担,过度调查,以及医疗资源的不当使用。
    This viewpoint paper considers the authors\' perspectives on the potential role of smartphones, wearables, and other technologies in the diagnosis of cancer. We believe that these technologies could be valuable additions in the pursuit of early cancer diagnosis, as they offer solutions to the timely detection of signals or symptoms and monitoring of subtle changes in behavior that may otherwise be missed. In addition to signal detection, technologies could assist symptom interpretation and guide and facilitate access to health care. This paper aims to provide an overview of the scientific rationale as to why these technologies could be valuable for early cancer detection, as well as outline the next steps for research and development to drive investigation into the potential for smartphones and wearables in this context and optimize implementation. We draw attention to potential barriers to successful implementation, including the difficulty of the development of signals and sensors with sufficient utility and accuracy through robust research with the target group. There are regulatory challenges; the potential for innovations to exacerbate inequalities; and questions surrounding acceptability, uptake, and correct use by the intended target group and health care practitioners. Finally, there is potential for unintended consequences on individuals and health care services including unnecessary anxiety, increased symptom burden, overinvestigation, and inappropriate use of health care resources.
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  • 文章类型: Journal Article
    背景:研究表明,在儿童性虐待(CSA)的所有幸存者中,只有大约一半的人在儿童期和青春期发现了这种虐待。这令人担忧,因为CSA与以后生活中的大量痛苦有关。儿童和青少年精神病学(CAP)中暴露于CSA的儿童和青少年比例明显高于普通人群。医疗保健专业人士报告说,发现CSA是一项复杂而具有挑战性的任务。然而,我们对它们在发现CSA时是如何进行的知之甚少。因此,有必要更多地了解医疗保健人员的经验,以促进和增加CSA披露。该研究旨在探索挪威的CAP医疗保健专业人员在评估和检测CSA时如何进行,他们如何体验这项工作,以及阻碍或促进他们努力的因素。
    方法:本研究采用混合方法。数据是通过匿名在线调查收集的,生成定量和定性数据。样本由CAP的111名医疗保健专业人员组成,其中84%是女性,平均年龄40.7岁(范围24-72;sd=10.8)。CAP临床经验的平均年数为8.3年(范围0-41;sd=7.5)。定量数据采用描述性统计分析,相关性,和独立样本t检验,而定性数据是使用基于团队的定性内容分析进行分析的。
    结果:结果表明,CSA的检测被视为重要的,但是CAP中的复杂任务,现有程序被认为是不够的。当他们怀疑或检测到CSA时,治疗师大多对如何进行有信心,然而他们很少检测到CSA。在最初的评估中,他们采用了标准化的程序,但是如果他们对可能的CSA的怀疑持续存在,他们似乎更依赖临床判断。确定了CSA检测的具体挑战和促进者,在个人和组织中。
    结论:该研究强调了医疗专业人员和CAP系统在评估CSA时面临的挑战和复杂性,这可能是低检测率的原因。结果表明,医疗保健专业人员认为,临床自主性和针对性能力发展的空间可能会改善CSA检测。此外,研究结果表明,CAP需要定义机构内部和机构之间的角色和责任。
    BACKGROUND: Research shows that only around half of all survivors of child sexual abuse (CSA) disclose the abuse during childhood and adolescence. This is worrying, as CSA is related to substantial suffering later in life. The proportion of children and adolescents who have been exposed to CSA is significantly higher in Child and Adolescent Psychiatry (CAP) than in the general population. Healthcare professionals report that uncovering CSA is a complex and challenging task. However, we know little about how they proceed when uncovering CSA. More knowledge of healthcare personnel\'s experience is therefore necessary to facilitate and increase CSA disclosure. The study aims to explore how CAP healthcare professionals in Norway proceed when assessing and detecting CSA, how they experience this work, and what hinders or facilitates their efforts.
    METHODS: The study employed a mixed method approach. Data was collected through an anonymous online survey, generating both quantitative and qualitative data. The sample consisted of 111 healthcare professionals in CAP, of whom 84% were women, with a mean age of 40.7 years (range 24-72; sd = 10.8). Mean years of CAP clinical experience were 8.3 years (range 0-41; sd = 7.5). The quantitative data was analysed using descriptive statistics, correlations, and independent sample t-tests, while the qualitative data was analysed using a team-based qualitative content analysis.
    RESULTS: The results showed that detection of CSA was viewed as an important, but complex task in CAP, and the existing procedures were deemed to be insufficient. The therapists mostly felt confident about how to proceed when they suspected or detected CSA, yet they seldom detected CSA. In their initial assessment they applied standardised procedures, but if their suspicion of possible CSA persisted, they seemed to rely more on clinical judgement. Specific challenges and facilitators for CSA detection were identified, both in the individual and in the organisation.
    CONCLUSIONS: The study highlights the challenges and complexities healthcare professionals and the CAP system face when assessing CSA, which may account for the low detection rate. The results show that healthcare professionals believe room for clinical autonomy and targeted competence development may improve CSA detection. Additionally, the findings suggest a need for CAP to define roles and responsibilities within and between agencies.
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  • 文章类型: Journal Article
    注意力缺陷/多动障碍(ADHD)是最常见和可遗传的神经发育障碍之一,可能持续一生。先前编写了一份关于土耳其青年多动症诊断和管理的共识报告。然而,与会者和管理选择相当有限,过去十年的发展需要修订和更新共识。因此,本综述旨在总结Türkiye儿童和青少年精神科医生对儿童ADHD的性质和管理的共识。为了这些目标,多动症的病因,诊断和评估过程,流行病学,发展演讲,鉴别诊断和合并症,我们回顾了课程/结局和药理学以及非药理学管理方案,并提出了临床实践建议.由于ADHD是一种对功能有广泛影响的慢性疾病,经常伴有其他精神障碍,建议采用多维治疗方法.然而,因为这种疾病有神经生物学基础,药物治疗是治疗的主要手段。其他疗法可能包括心理社会疗法,行为疗法,以学校为基础的治疗方法,和家庭教育。本综述在国家和全球层面为多动症提供了建议。它包含有关ADHD的信息,这些信息将有助于并促进临床医生的决策过程。建议在临床实践中考虑该指南。
    Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common and heritable neurodevelopmental disorders which may last through the life-span. A consensus report on diagnosis and management of ADHD among Turkish youth was prepared previously. However, the participants as well as the management options were rather limited and developments in the past decade necessitated a revision and update of the consensus. Therefore, this review aims to summarize the consensus among Child and Adolescent Psychiatrists from Türkiye on the nature and management of pediatric ADHD. For those aims, the etiology of ADHD, diagnostic and evaluation process, epidemiology, developmental presentations, differential diagnoses and comorbidities, course/outcome and pharmacological as well as non-pharmacological management options were reviewed and suggestions for clinical practice are presented. Since ADHD is a chronic disorder with wide-ranging effects on functionality that is frequently accompanied by other mental disorders, a multidimensional therapeutic approach is recommended. However, since the disorder has neurobiological basis, pharmacotherapy represents the mainstay of treatment. Additional therapies may include psychosocial therapy, behavioral therapy, school-based therapeutic approaches, and family education. This review provides recommendations for ADHD at the national and global levels. It contains information about ADHD that will contribute to and facilitate clinicians\' decision-making processes. It is advisable to consider this guideline in clinical practice.
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