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Background The incidence of Non-alcoholic fatty liver disease (NAFLD) in China and USA is extremely high and rising. TikTok has become a popular channel for medical information dissemination and we aimed to evaluate the quality and reliability of NAFLD related videos on TikTok, in both its USA and Chinese versions. Methods We analyzed the top 100 NAFLD videos on both the USA version and Chinese version of TikTok, a total of 200 videos, from which keywords were extracted and scored using the Global Quality Scale (GQS), modified DISCERN (mDISCERN), and Medical Quality Video Evaluation Tool (MQ-VET). Exploring the relationship between video quality and audience related factors, as well as ranking, through Spearman correlation analysis. Results The mDISCERN scores of videos on the USA version of TikTok is higher than that on the Chinese version ( P  < 0.01), but there is no significant difference in the GQS and MQ-VET scores. The GQS, mDISCERN and MQ-VET scores of videos published by medical practitioners were significantly higher than those of non-medical practitioners ( P  < 0.001). However, there was no significant correlation between video quality and popularity indicators. Conclusion The quality of NAFLD related short videos on TikTok is acceptable, but the reliability is mediocre, and there is still room for improvement. The videos published by USA medical practitioners are more reliable than those of Chinese medical practitioners. The most concerned topic of both countries is diet. The TikTok recommendation algorithm may limit access to high-quality health videos, and further research on other platforms and languages is necessary.

High-precision extraction of mangrove areas is a crucial prerequisite for estimating mangrove area as well as for regional planning and ecological protection. However, mangroves typically grow in coastal and near-shore areas with complex water colors, where traditional mangrove extraction algorithms face challenges such as unclear region segmentation and insufficient accuracy. To address this issue, in this paper we propose a new algorithm for mangrove identification and extraction based on Orthogonal Matching Filter–Weighted Least Squares (OMF-WLS) target spectral information. This method first selects GF-6 remote sensing images with less cloud cover, then enhances mangrove feature information through preprocessing and band extension, combining whitened orthogonal subspace projection with the whitened matching filter algorithm. Notably, this paper innovatively introduces Weighted Least Squares (WLS) filtering technology. WLS filtering precisely processes high-frequency noise and edge details in images using an adaptive weighting matrix, significantly improving the edge clarity and overall quality of mangrove images. This innovative approach overcomes the bottleneck of traditional methods in effectively extracting edge information against complex water color backgrounds. Finally, Otsu’s method is used for adaptive threshold segmentation of GF-6 remote sensing images to achieve target extraction of mangrove areas. Our experimental results show that OMF-WLS improves extraction accuracy compared to traditional methods, with overall precision increasing from 0.95702 to 0.99366 and the Kappa coefficient rising from 0.88436 to 0.98233. In addition, our proposed method provides significant improvements in other metrics, demonstrating better overall performance. These findings can provide more reliable technical support for the monitoring and protection of mangrove resources.

Background Many studies suggest that patient satisfaction is significantly negatively correlated with the waiting time. A well-designed healthcare system should not keep patients waiting too long for an appointment and consultation. However, in China, patients spend notable time waiting, and the actual time spent on diagnosis and treatment in the consulting room is comparatively less. Methods We developed an artificial intelligence (AI)-assisted module and name it XIAO YI. It could help outpatients automatically order imaging examinations or laboratory tests based on their chief complaints. Thus, outpatients could get examined or tested before they went to see the doctor. People who saw the doctor in the traditional way were allocated to the conventional group, and those who used XIAO YI were assigned to the AI-assisted group. We conducted a retrospective cohort study from August 1, 2019 to January 31, 2020. Propensity score matching was used to balance the confounding factor between the two groups. And waiting time was defined as the time from registration to preparation for laboratory tests or imaging examinations. The total cost included the registration fee, test fee, examination fee, and drug fee. We used Wilcoxon rank-sum test to compare the differences in time and cost. The statistical significance level was set at 0.05 for two sides. Results Twelve thousand and three hundred forty-two visits were recruited, consisting of 6171 visits in the conventional group and 6171 visits in the AI-assisted group. The median waiting time was 0.38 (interquartile range: 0.20, 1.33) hours for the AI-assisted group compared with 1.97 (0.76, 3.48) hours for the conventional group ( p  < 0.05). The total cost was 335.97 (interquartile range: 244.80, 437.60) CNY (Chinese Yuan) for the AI-assisted group and 364.58 (249.70, 497.76) CNY for the conventional group ( p  < 0.05). Conclusions Using XIAO YI can significantly reduce the waiting time of patients, and thus, improve the outpatient service process of hospitals.

ObjectiveTo propose and test an innovative model by integrating the Unified Theory of Acceptance and Use of Technology and Knowledge-Attitude-Practice model to explain the mechanisms influencing the adoption of digital health technologies by elderly patients with chronic diseases from the perspective of both internal and external factors, promoting the acceptance and utilisation of digital health technologies among elderly chronically ill patients.Study designA face-to-face questionnaire survey was conducted from July to September 2023.Study settingThe study was conducted in 12 medical institutions in Shanghai, including 6 tertiary hospitals, 3 secondary hospitals and 3 community hospitals.Participants1222 participants aged 60 years or more, diagnosed with one or more of the following chronic diseases: essential hypertension, type 2 diabetes, coronary atherosclerotic heart disease, stroke and chronic obstructive pulmonary disease, were involved in the study using convenience sampling. Critically ill emergency patients and those who were involved in medical disputes were excluded.Outcome measureThe behavioural intention and usage behaviour of older patients with chronic diseases to use digital health technologies.ResultsThe explanatory power of the proposed model for behavioural intention was 72.9%. There is a significant negative association between technology anxiety and the intention to use digital health technologies among older patients with chronic diseases (β=−0.224, p<0.001); effort expectancy (β=0.530, p<0.001) and performance expectancy (β=0.193, p<0.001) were also significantly associated with intention to use digital health technologies. Men (β=−0.104, p=0.016), relatively younger (β=−0.061, p=0.005), with experience in using digital health technologies (β=−0.452, p<0.001) were more likely to translate behavioural intention into use behaviour.ConclusionsAcceptance of digital health technologies among older patients with chronic diseases was associated with a combination of internal and external factors, with the former playing a dominant role. These valuable findings provided insights and inspiration for improving digital health technologies acceptance and utilisation among older patients with chronic diseases.

BackgroundAsthma represents a significant global health challenge, exhibiting considerable variation in prevalence, incidence, mortality and disability-adjusted life years (DALYs) across regions and countries. This study evaluates global, regional and national trends in asthma burden from 1990 to 2021, analysing associations with temporal, geographical and demographical factors.MethodsUsing open data from the Global Burden of Disease (GBD) database (1990–2021), we analysed changes in asthma prevalence, incidence, mortality and DALYs by gender, age and Socio-Demographic Index (SDI) groups. Joinpoint regression analysis calculated the average annual percentage change (AAPC) and annual percentage change (APC).ResultsFrom 1990 to 2021, the age-standardised prevalence and incidence rates of asthma declined by 40.01% and 29.89%, respectively. While asthma deaths increased slightly, the age-standardised mortality rate (ASMR) declined by 46.01%. The highest prevalence was observed in South Asia, East Asia and high-income North America, while low-SDI regions exhibited elevated mortality and DALYs. The age and sex-specific patterns indicated a higher asthma burden among females. The results of the joinpoint analysis indicated a global age-standardised incidence rate increase between 2005 and 2010 for both males and females. The ASMR exhibited a statistically significant decline from 1990 to 2021.ConclusionsThe global age-standardised rate of asthma burden declined from 1990 to 2021. However, asthma remains a significant public health issue, particularly in regions with lower socioeconomic development. Understanding global and regional trends in asthma can inform future policies and interventions, aiming to promote more equitable prevention, diagnosis and treatment worldwide.

Study designA retrospective study of incomplete cervical spinal cord injury (SCI) treated with and without hyperbaric oxygen (HBO) therapy after operation.ObjectiveTo investigate the effects of hyperbaric oxygen therapy on patients’ postoperative recovery after incomplete cervical spinal cord injury.SettingShulan Hangzhou Hospital, Hangzhou, China.MethodsWe analyzed the clinical data of 78 patients admitted in the Orthopedic Department of our hospital from June 2014 to June 2016, due to trauma-induced incomplete cervical spinal cord injury. All study subjects underwent nerve decompression and internal fixation procedures within 2 weeks of injury. The patients were divided into hyperbaric oxygen therapy (HBO) group (n = 40) and non-hyperbaric oxygen therapy (NHBO) group (n = 38) according to the chosen treatment option. The NHBO group only receive the conventional treatment regimen while the HBO group received a combination of conventional treatment and hyperbaric oxygen therapy. The subsequent changes in spinal functions and activities of daily living (ADL) were assessed by The American Spinal Injury Association (ASIA) scale and the Barthel Index at different time points (pretreatment, 1 month and 3 months of treatment, as well as 6 months, 1 year, 2 years, and 3 years after the surgical procedure).ResultsThere were no significant differences in age, gender, injury site, and disease condition between patients (p > 0.05). The results showed a significant difference in treatment total effectiveness rate between the HBO and NHBO groups (p < 0.05) (90% and 78.9%, respectively). Analyses of the ASIA scores and Barthel indices between the two groups indicated significant differences at 1 month and 3 months treatment time points, as well as 6 months and 1 year after the initial operation (p < 0.05). It showed that subjects in the HBO group had a better recovery than their NHBO counterparts, with the 1-month treatment time point being the most significant. In addition, the results indicated significant improvements in Barthel Index scores as well as ASIA sensory and motor function scores in both groups after a 1-month treatment, with the HBO group faring significantly better than the NHBO group (p < 0.01).ConclusionsOur results not only showed that hyperbaric oxygen therapy is safe and effective for the treatment of incomplete cervical spinal cord injury but also indicated that the longer the treatment lasts (therapy initiation within 3 months after the surgical operation), the better the effects. In addition, a correct hyperbaric oxygen therapy leads to a peak in recovery within the first postoperative 3 months and can effectively promote spinal cord functions, reduce the disabilities, and improve patients’ quality of life.

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, and CT imaging plays a crucial role in its diagnosis and management. However, the clinical use of CT is limited by factors, such as suboptimal image quality, diagnostic complexity and the labour-intensive nature of parameter evaluation. Artificial intelligence (AI) is increasingly transforming many areas of medicine. Its integration into CAD CT imaging can enhance image postprocessing, streamline anatomical and functional analyses, support treatment planning and improve risk prediction. This review summarises recent advances in these AI applications, aiming to promote their practical adoption and further development.

Aims This study aimed to investigate the current state of nursing interns’ spiritual care competency (SCC) and its relationship with their spiritual health. Background Spiritual care is a vitally important component of holistic nursing. Understanding the spiritual care competency of nursing interns can help nursing managers and educators identify weaknesses in spiritual care practices, develop intervention measures to enhance SCC, and improve the quality of nursing services. However, the relationship between spiritual health and SCC among nursing interns remains unclear. Methods A total of 361 nursing interns were recruited from three general hospitals. An online questionnaire assessed nursing interns’ sociodemographic characteristics, spiritual care competency, and spiritual health. Statistical analyses included Pearson’s correlation analysis, T-test, analysis of variance (ANOVA), and multiple stepwise linear regression analysis. Results The average spiritual care competency score among nursing interns was 107.24 ± 21.67 out of a possible 135, indicating a medium-high level of competency. Spiritual care competency was positively correlated with spiritual health ( P  < 0.01). The multiple stepwise linear regression model ( n  = 361) had an explained variance ( R 2  = 0.300), showing that spiritual health and the manner of receiving spiritual training were the main factors influencing the interns’ spiritual care competency ( P  < 0.001). Conclusion The findings suggest that improving the spiritual health of nursing interns can enhance their spiritual care competency.

Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development. The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms. We conducted a nationwide, cross-sectional survey of NICU staff working in grade III level A hospitals in 27 Chinese provinces to investigate current clinical practices, perceptions, decision-making processes, and decision-support requirements for clinical ECG alarms. A comparative analysis was conducted on the results using the chi-square, Kruskal-Wallis, or Mann-Whitney U tests. In total, 1019 respondents participated in this study. NICU staff reported experiencing a significant number of nuisance alarms and negative perceptions as well as practices regarding ECG alarms. Compared to nurses, physicians had more negative perceptions. Individuals with higher education levels and job titles had more negative perceptions of alarm systems than those with lower education levels and job titles. The mean difficulty score for decision-making about ECG alarms was 2.96 (SD 0.27) of 5. A total of 62.32% (n=635) respondents reported difficulty in resetting or modifying alarm parameters. Intelligent module-assisted decision support systems were perceived as the most popular form of decision support. This study highlights the negative perceptions and strong decision-making requirements of NICU staff related to ECG alarm handling. Health care policy makers must draw attention to the decision-making requirements and provide adequate decision support in different forms.

Recent studies have suggested a relationship between gut microbiota and non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). However, the nature and direction of this potential causal relationship are still unclear. This study used two-sample Mendelian randomization (MR) to clarify the potential causal links. Summary-level Genome-Wide Association Studies (GWAS) statistical data for gut microbiota and NAFLD/NASH were obtained from MiBioGen and FinnGen respectively. The MR analyses were performed mainly using the inverse-variance weighted (IVW) method, with sensitivity analyses conducted to verify the robustness. Additionally, reverse MR analyses were performed to examine any potential reverse causal associations. Our analysis, primarily based on the IVW method, strongly supports the existence of causal relationships between four microbial taxa and NAFLD, and four taxa with NASH. Specifically, associations were observed between Enterobacteriales ( =0.04), ( =0.04), ( =0.02), and ( =0.04) and increased risk of NAFLD. ( =0.03) and ( =0.04) could increase the risks of NASH while ( =0.04) and ( =0.005) could decrease them. We also identified that NAFLD was found to potentially cause an increased abundance in ( =0.007) and ( =0.002). However, we found no evidence of reverse causation in the microbial taxa associations with NASH. This study identified several specific gut microbiota that are causally related to NAFLD and NASH. Observations herein may provide promising theoretical groundwork for potential prevention and treatment strategies for NAFLD and its progression to NASH in future.