Does air pollution fuel irrational behaviors in stock investments?

This paper investigates the influence of air pollution on irrational behaviors in stock trading through behavioral experiments in laboratory, simulating air pollution by burning straw and mosquito coils. The results of this study show that air pollution significantly improves disposition effect and repurchase effect in an asymmetric way, which are thought as irrational behaviors in stock investments, making subjects prefer selling winning stocks (part of disposition effect) and repurchasing stocks that have fallen in price since the sale (part of repurchase effect). Furthermore, regret, a negative emotion, is the psychological mechanism by which air pollution influences the irrational behaviors.

Genome assembly of autotetraploid Actinidia arguta highlights adaptive evolution and enables dissection of important economic traits.

Actinidia arguta, the most widely distributed Actinidia species and the second cultivated species in the genus, can be distinguished from the currently cultivated Actinidia chinensis on the basis of its small and smooth fruit, rapid softening, and excellent cold tolerance. Adaptive evolution of tetraploid Actinidia species and the genetic basis of their important agronomic traits are still unclear. Here, we generated a chromosome-scale genome assembly of an autotetraploid male A. arguta accession. The genome assembly was 2.77 Gb in length with a contig N50 of 9.97 Mb and was anchored onto 116 pseudo-chromosomes. Resequencing and clustering of 101 geographically representative accessions showed that they could be divided into two geographic groups, Southern and Northern, which first diverged 12.9 million years ago. A. arguta underwent two prominent expansions and one demographic bottleneck from the mid-Pleistocene climate transition to the late Pleistocene. Population genomics studies using paleoclimate data enabled us to discern the evolution of the species' adaptation to different historical environments. Three genes (AaCEL1, AaPME1, and AaDOF1) related to flesh softening were identified by multi-omics analysis, and their ability to accelerate flesh softening was verified through transient expression assays. A set of genes that characteristically regulate sexual dimorphism located on the sex chromosome (Chr3) or autosomal chromosomes showed biased expression during stamen or carpel development. This chromosome-level assembly of the autotetraploid A. arguta genome and the genes related to important agronomic traits will facilitate future functional genomics research and improvement of A. arguta.

Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model.

BACKGROUND: Stroke is a prevalent disease with a significant global impact. Effective assessment of stroke severity is vital for an accurate diagnosis, appropriate treatment, and optimal clinical outcomes. The National Institutes of Health Stroke Scale (NIHSS) is a widely used scale for quantitatively assessing stroke severity. However, the current manual scoring of NIHSS is labor-intensive, time-consuming, and sometimes unreliable. Applying artificial intelligence (AI) techniques to automate the quantitative assessment of stroke on vast amounts of electronic health records (EHRs) has attracted much interest. OBJECTIVE: This study aims to develop an automatic, quantitative stroke severity assessment framework through automating the entire NIHSS scoring process on Chinese clinical EHRs. METHODS: Our approach consists of two major parts: Chinese clinical named entity recognition (CNER) with a domain-adaptive pre-trained large language model (LLM) and automated NIHSS scoring. To build a high-performing CNER model, we first construct a stroke-specific, densely annotated dataset "Chinese Stroke Clinical Records" (CSCR) from EHRs provided by our partner hospital, based on a stroke ontology that defines semantically related entities for stroke assessment. We then pre-train a Chinese clinical LLM coined "CliRoberta" through domain-adaptive transfer learning and construct a deep learning-based CNER model that can accurately extract entities directly from Chinese EHRs. Finally, an automated, end-to-end NIHSS scoring pipeline is proposed by mapping the extracted entities to relevant NIHSS items and values, to quantitatively assess the stroke severity. RESULTS: Results obtained on a benchmark dataset CCKS2019 and our newly created CSCR dataset demonstrate the superior performance of our domain-adaptive pre-trained LLM and the CNER model, compared with the existing benchmark LLMs and CNER models. The high F1 score of 0.990 ensures the reliability of our model in accurately extracting the entities for the subsequent automatic NIHSS scoring. Subsequently, our automated, end-to-end NIHSS scoring approach achieved excellent inter-rater agreement (0.823) and intraclass consistency (0.986) with the ground truth and significantly reduced the processing time from minutes to a few seconds. CONCLUSION: Our proposed automatic and quantitative framework for assessing stroke severity demonstrates exceptional performance and reliability through directly scoring the NIHSS from diagnostic notes in Chinese clinical EHRs. Moreover, this study also contributes a new clinical dataset, a pre-trained clinical LLM, and an effective deep learning-based CNER model. The deployment of these advanced algorithms can improve the accuracy and efficiency of clinical assessment, and help improve the quality, affordability and productivity of healthcare services.

RAPID-ED: A predictive model for risk assessment of patient's early in-hospital deterioration from emergency department.

Introduction: The objective of this multi-center retrospective cohort study was to devise a predictive tool known as RAPID-ED. This model identifies non-traumatic adult patients at significant risk for cardiac arrest within 48 hours post-admission from the emergency department. Methods: Data from 224,413 patients admitted through the emergency department (2016-2020) was analyzed, incorporating vital signs, lab tests, and administered therapies. A multivariable regression model was devised to anticipate early cardiac arrest. The efficacy of the RAPID-ED model was evaluated against traditional scoring systems like National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) and its predictive ability was gauged via the area under the receiver operating characteristic curve (AUC) in both hold-out validation set and external validation set. Results: RAPID-ED outperformed traditional models in predicting cardiac arrest with an AUC of 0.819 in the hold-out validation set and 0.807 in the external validation set. In this critical care update, RAPID-ED offers an innovative approach to assessing patient risk, aiding emergency physicians in post-discharge care decisions from the emergency department. High-risk score patients (≥13) may benefit from early ICU admission for intensive monitoring. Conclusion: As we progress with advancements in critical care, tools like RAPID-ED will prove instrumental in refining care strategies for critically ill patients, fostering an improved prognosis and potentially mitigating mortality rates.

Development of a composite healthy ageing score: evidence from middle-to-older aged Australians.

We developed and validated a composite healthy ageing score (HAS) to address the absence of a definitive composite score comprising multiple health domains that measure healthy ageing in epidemiology. The HAS is developed from 13 health domains reported to influence healthy ageing. Data to measure these domains was extracted from the 45 and Up Study baseline. We applied best practices for scale validation and development. Physical functioning, cognitive function, mental health, sleep, quality of life, balance, social connections and overall health were retained. Functional capacity and resilience were uncovered as underlying latent structures. The HAS ranges from 0 to 16 with higher scores indicating a better health profile. This research contributes a comprehensive measuring tool, HAS, It enables examination and comparison of individual or collective health profiles and the investigation of the factors that influence their chances of living healthy for longer.

The proportion of the population living longer is increasing, but longevity does not necessarily imply ageing well. Advancements in medicine have made it possible for people to live longer even while managing multiple ailments. The determinants of how well one age result from a complex interaction of various factors. This paper examined thirteen factors that can influence healthy ageing to construct a healthy ageing score comprising the crucial health domains relevant to ageing well. We found that 8 of the 13 health domains, namely: physical functioning, cognitive function, balance and falls, overall health, mental health, quality of life, sleep and social connections were crucial to ageing well. Individuals were scored a 2, a 1 or 0 based on whether they met recommended levels for each domain item and aggregated as the healthy ageing score. The score ranges from 0 to 16, with higher scores indicating a healthier ageing profile.

Treatment outcomes of radium-223 in patients with metastatic castration-resistant prostate cancer: An experience before National Health Insurance reimbursement in Taiwan.

BACKGROUND: Radium-223 (Ra-223), an α-particle-emitting isotope, inhibits bony metastases and prevents patients from skeletal-related events in metastatic castration-resistant prostate cancer (mCRPC). We retrospectively reviewed the treatment response, predictive factors, and adverse events (AEs) of Ra-223 before the National Health Insurance reimbursement in a Taiwanese tertiary institute. METHODS: Patients treated with Ra-223 before January 2019 were enrolled and categorized into progressive disease (PD) and clinical benefits (CB) groups. Laboratory data before and after the treatment were collected, and spider plots concerning percentage changes of alkaline phosphatase (ALP), lactate dehydrogenase (LDH), and prostate-specific antigen (PSA) were prepared and calculated statistically. CB/PD, baseline ALP, LDH, and PSA levels were also adopted as stratification factors for overall survival (OS). RESULTS: Among 19 patients included, 5 (26.3%) and 14 (73.4%) belonged to the PD and CB groups, respectively, with no significant difference observed in the baseline laboratory data. The percentage changes in ALP, LDH, and PSA levels after Ra-223 treatment were statistically significant among the two groups (ALP: CB 54.3 ± 21.4% vs PD 77.6 ± 11.8%, p = 0.044; LDH: CB 88.2 ± 22.8% vs PD 138.3 ± 49.0%, p = 0.046; PSA: CB 97.8 ± 61.7% vs PD 277.0 ± 101.1%, p = 0.002). The trends of LDH between the two groups in spider plot were separated significantly. There were no differences in the AEs between the two groups. CB had a longer median OS than the PD group (20.50 months vs 9.43 months, p = 0.009). Patients with LDH <250 U/L at baseline tended to have longer OS but without significance. CONCLUSION: The CB rate of Ra-223 was 73.7%. No predictive factor for treatment response was obtained from pretreatment data. The mean percentage changes in ALP, LDH, and PSA levels compared with baseline significantly differed between the CB and PD groups, especially the LDH levels. The CB and PD groups showed different OS, with LDH levels exhibiting the potential to predict OS.

[Electroencephalogram Features of Anti-N-Methyl-D-Aspartate Receptor Encephalitis and Their Value for Clinical Assessment].

Objective: To analyze the electroencephalogram (EEG) features of anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) and to study the clinical assessment value of the degree of EEG background slowing and the presence of δ brush. Methods: We enrolled 52 patients with anti-NMDARE and collected their clinical data, including age, sex, form of disease onset, status of tumor comorbidity, auxiliary examination findings (cerebrospinal fluid [CSF] anti-methyl-D-aspartate receptor antibody titers, magnetic resonance imaging [MRI] reports, and EEG results), treatment status, and follow-up after discharge. The degree of EEG background abnormality and the presence of δ brush in the EEG of patients with different clinical features were analyzed. Results: Among the 52 patients, 7 (14%) had normal EEG, and 45 (87%), abnormal EEG, including 25 (48%) with mild abnormalities, 11 (21%) with moderate abnormalities, and 9 (17%) with severe abnormalities. δ brush was seen in 6 (12%) patients. At the time of EEG, 32 (62%) patients were in the mild condition group and 20 (38%) patients were in the severe condition group. After 1 year of follow-up, there were 45 (86%) patients in the good prognosis group and 7 (14%) patients in the poor prognosis group. The exacerbation of EEG background abnormalities and the presence of δ brush were indications for an increase in the proportion of patients who were in severe condition, who needed ICU admission, and who had poor prognosis ( P<0.01). The worse the EEG background abnormalities, the higher the proportion of CSF antibody titers>1∶10 ( P=0.035), and the higher the proportion of patients initiating second-line immunotherapy ( P=0.008). The δ brush was seen a higher proportion in patients with comorbid tumors ( P=0.012). The probability of δ brush presence was higher in the first-time diagnosis cases than that in recurrent cases ( P=0.023). Conclusions: The degree of EEG slowing and the presence of δ brush have shown consistent performance in assessing patients' condition and predicting prognosis. The slower the EEG, the more severe the disease, and the worse the prognosis. The presence of δ brush indicates severe disease and poor prognosis. EEG slowing is correlated with the immune status of patients with anti-NMDARE. The slower the EEG, the more severe the immune abnormalities. In clinical practice, patient EEG should be under dynamic monitoring in order to evaluate the effect of immunotherapy. If EEG slowing is not improved, enhanced immunotherapy should be considered as early as possible. The δ brush is seen at a higher proportion in patients with comorbid tumors. Therefore, active efforts should be made to screen for tumors when δ brush is present.

The influence of subjective socioeconomic status on executive functions in middle-aged and older adults.

Subjective socioeconomic status (SES) has been shown to influence both psychological and biological outcomes. However, less is known about whether its influence extends to cognitive outcomes. We examined the relation between subjective SES and executive functions (EF)-a set of cognitive control processes-and its underlying mechanisms. By analyzing a nationally representative cohort of middle-aged and older adults (age 40-80) from the MIDUS 2 National Survey and Cognitive Project, we tested a serial mediation model with sense of control and health as sequential mediators. Using structural equation modeling, we found that subjective SES is indirectly related to EF via sense of control and health, above and beyond objective SES and other key covariates. Our study highlights one of the possible biopsychosocial mechanisms that underlies the relation between status-related subjective perceptions of inequalities and executive functioning skills in middle and late adulthood.

Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China.

Flooding is a serious challenge that increasingly affects residents as well as policymakers. Many studies have noted that decreasing the urban flood vulnerability (UFV) is an indispensable strategy for reducing flood risks; however, some studies have several pertinent assessment limitations. The objective of this study is to assess the UFV of the Xuanwu-Qinhuai-Jianye-Gulou-Yuhua (XQJGY) region from 2012 to 2018 by integrating various indicators into a composite index. This study uses the environment for visualizing images (ENVI) and the geographic information system (GIS) to extract indicators that have geographic attributes for the assessment of UFV and the process analysis method is then used to explore the relationship between these indicators. The results indicated that: (1) The UFV of Xuanwu, Qinhuai, and Gulou decreased from 2012 to 2018 and the UFV of Jianye and Gulou increased from 2012 to 2015 and decreased from 2015 to 2018. (2) The vegetation coverage, precipitation during the flood season, population density, and highway density significantly contributed to the UFV. (3) There also exist transformation pathways between the indicators that led to vulnerability in five districts. This study provides a theoretical basis for the government to manage floods.

Predicting Hospice Transitions in Dementia Caregiving Dyads: An Exploratory Machine Learning Approach.

Background and Objectives: Hospice programs assist people with serious illness and their caregivers with aging in place, avoiding unnecessary hospitalizations, and remaining at home through the end-of-life. While evidence is emerging of the myriad of factors influencing end-of-life care transitions among persons living with dementia, current research is primarily cross- sectional and does not account for the effect that changes over time have on hospice care uptake, access, and equity within dyads. Research Design and Methods: Secondary data analysis linking the National Health and Aging Trends Study to the National Study of Caregiving investigating important social determinants of health and quality-of-life factors of persons living with dementia and their primary caregivers (n = 117) on hospice utilization over 3 years (2015-2018). We employ cutting-edge machine learning approaches (correlation matrix analysis, principal component analysis, random forest [RF], and information gain ratio [IGR]). Results: IGR indicators of hospice use include persons living with dementia having diabetes, a regular physician, a good memory rating, not relying on food stamps, not having chewing or swallowing problems, and whether health prevents them from enjoying life (accuracy = 0.685; sensitivity = 0.824; specificity = 0.537; area under the curve (AUC) = 0.743). RF indicates primary caregivers' age, and the person living with dementia's income, census division, number of days help provided by caregiver per month, and whether health prevents them from enjoying life predicts hospice use (accuracy = 0.624; sensitivity = 0.713; specificity = 0.557; AUC = 0.703). Discussion and Implications: Our exploratory models create a starting point for the future development of precision health approaches that may be integrated into learning health systems that prompt providers with actionable information about who may benefit from discussions around serious illness goals-for-care. Future work is necessary to investigate those not considered in this study-that is, persons living with dementia who do not use hospice care so additional insights can be gathered around barriers to care.

An integrated technical, economic, and environmental framework for evaluating the rooftop photovoltaic potential of old residential buildings.

Energy-saving reconstruction of old residential buildings is a vital way to achieve sustainable development, but the potential of rooftop photovoltaic (PV) energy-saving in old residential buildings has not been studied. This study established a basic framework for the estimation of rooftop PV technical, economic and environmental potential in the old residential buildings of Nanjing City, and provide the prediction results for the development of rooftop PV development plan in Nanjing. We estimated the available area, maximum electricity generation, environmental and economic benefits of rooftop PV in five districts of Nanjing by using building roof profile data, calculation method of maximum solar radiation at optimal tilt angle and GIS method. We find that the electricity generation potential of installing rooftop PV in the old residential buildings in the study area would meet about 17.7-20% of the residential electricity demand under three scenarios of the PV performance ratios (PR). Additionally, the carbon reduction potential of the life cycle rooftop PV reaches 13912874.12t (PR = 0.85), 13094469.76t (PR = 0.8), and 12276065.4t (PR = 0.75), respectively; and the result of economic potential shows that the life cycle of rooftop PV cannot generate economic benefits with an NPV value less than 0. The feasibility analysis framework provided in this paper can be applied to the assessment of rooftop PV potential in other cities in China, and provide valuable advice for the rational planning of rooftop PV.

Automated assessment of infant motor development to predict infant age: The determination of objective metrics of spontaneous kicking.

Though early intervention can improve outcomes for children with motor disabilities, delays in diagnosis can impact the success of intervention programs. Prior work indicates that spontaneous kicking patterns can be used to model typical infant motor development to assist in the early detection of motor delays. However, abnormalities in spontaneous movements are not well defined or readily observable through traditional functional assessments. In this research, a method is introduced for the early detection of delays through the assessment of spontaneous kicking data gathered using a wearable sensing suit. We present formulations of kinematic features identified in the clinical space, identify which features are significant predictors of infant age, and establish normative values. Finally, we offer an analysis of preterm (PT) infant data compared to normative values derived from term infants. Term and PT infants ranging in age from 1 to 10 months were studied. We found that frequency, duration, acceleration, inter-joint coordination, and maximum joint excursion metrics had a significant correlation with age. From these features, models of typical kicking development were created using data from term, typically developing infants. When compared to normative trends, PT infants display differing developmental trends.

Gender-specific and age-specific associations of the homoeostasis model assessment for IR (HOMA-IR) with albuminuria and renal function impairment: a retrospective cross-sectional study in Southeast China.

OBJECTIVES: The study aimed to investigate the association of insulin resistance (IR), which was estimated by the homoeostasis model assessment for IR (HOMA-IR), with albuminuria and renal function impairment in a general Chinese population. DESIGN: A retrospective cross-sectional study. SETTING AND PARTICIPANTS: A total of 13 742 adults (age: ≥18 years) who underwent a health check-up at a hospital in Southeast China during 2013-2014 were enrolled. 216 subjects were excluded due to lack of enough fasting time, be pregnant, have chronic diseases influencing metabolic functions or have glomerulonephritis, renal cancer, kidney transplant. Eventually, 7552 men and 5974 women were included for the present analysis. PRIMARY OUTCOME MEASURES: The association of HOMA-IR with albuminuria and renal function impairment were analysed. The HOMA-IR cut-off value for detecting albuminuria and renal function impairment were determined. RESULTS: An increase in the HOMA-IR quartile was significantly associated with the prevalence of albuminuria and renal function impairment in all men and women aged >45 years. The multivariable logistic regression analyses revealed a significant association of the HOMA-IR with albuminuria and renal function impairment in subjects aged >45 years of the fourth quartiles compared with those of the first quartile after adjusting for potential confounders (albuminuria: men OR, 2.39; 95% CI 1.51 to 3.79, p<0.001; women OR, 2.40; 95% CI 1.44 to 4.01; p=0.001; renal function impairment: men OR, 2.30; 95% CI 1.50 to 3.51; p<0.001; women OR, 2.20; 95% CI 1.35 to 3.58; p=0.002). The optimal cut-off value of HOMA-IR for detecting albuminuria and renal function impairment was 2.69 in men aged ≤45 years, 1.60 in men aged >45 years and 1.86 in women aged >45 years. CONCLUSIONS: Our study revealed that HOMA-IR was significantly associated with albuminuria and renal function impairment in individuals aged >45 years.

The cost-saving effect of continuity of care (COC): an analysis of institutional COC on diabetic treatment costs using panel 2SLS regressions.

BACKGROUND: The high costs of chronic conditions call for new treatment approaches that reduce costs while ensuring desirable health outcomes. There has been a growing transformation of care delivery models from conventional referral systems to integrated care models. This study seeks to evaluate the cost-saving impact of integrated care delivery model under pay-for-performance (P4P) scheme with continuity of care at institution level (ICOC). METHODS: We analyzed the Taiwan National Health Insurance claim data of 21,725 diabetic patients who visited clinics and/or hospitals at least four times a year for 8 years. Using average local provider P4P participation rate (for each accreditation level) as an instrumental variable in two-stage least squares (2SLS) regressions, we have estimated consistent estimates of the ICOC elasticities for all-cause inpatient and outpatient costs. RESULTS: Our results show that ICOC significantly reduced inpatient costs but increased outpatient costs with the elasticity for treatment costs of -11.6 and 1.03, respectively. The decrease in inpatient costs offset the increase in outpatient costs and the resulting total cost saving showed significant association with ICOC. The saving effect of ICOC is especially robust among patients who used clinics as their principal source of care. CONCLUSIONS: Institutional continuity of care has a substantial impact on the treatment costs of diabetes patients. In the context where inpatient care costs are significantly higher than that of the outpatient care, ICOC would lead to a meaningful cost-saving effect. For new diabetes patients, care by clinics demonstrated the strongest saving effect.

Assessment of the effect of ethanol extracts from Cinnamomum camphora seed kernel on intestinal inflammation using simulated gastrointestinal digestion and a Caco-2/RAW264.7 co-culture system.

Cinnamomum camphora seeds have multiple bioactivities. There were few studies on the effect of C. camphora seeds on intestinal inflammation in vitro and in vivo. The study aimed to investigate the effects of ethanol extracts from C. camphora seed kernel on intestinal inflammation using simulated gastrointestinal digestion and a Caco-2/RAW264.7 co-culture system. Results showed that the digested ethanol extracts (dEE) were rich in polyphenols, and a total of 17 compounds were tentatively identified using UPLC-LTQ-Orbitrap-MS/MS. dEE increased cell viability, while decreasing the production of reactive oxygen species, and the secretion and gene expression of inflammatory markers (NO, PGE2, TNF-α, IL-1ß and IL-6). dEE also down-regulated NF-κB/MAPK pathway activities by suppressing the phosphorylation of relevant signaling molecules (p65, IκBα, ERK and p38), as well as the expression of TLR4 receptor protein. Furthermore, dEE may improve intestinal barrier function by increasing the TEER value, and the expression of tight junction proteins (ZO-1, claudin-1 and occludin). The results suggest the ethanol extracts from C. camphora seed kernel may have strong anti-inflammatory activities, and a potential application in the prevention or treatment of intestinal inflammation and enhancement of intestinal barrier function in organisms.

Application of a 72 h National Early Warning Score and Incorporation with Sequential Organ Failure Assessment for Predicting Sepsis Outcomes and Risk Stratification in an Intensive Care Unit: A Derivation and Validation Cohort Study.

We investigated the best timing for using the National Early Warning Score 2 (NEWS2) for predicting sepsis outcomes and whether combining the NEWS2 and the Sequential Organ Failure Assessment (SOFA) was applicable for mortality risk stratification in intensive care unit (ICU) patients with severe sepsis. All adult patients who met the Third International Consensus Definitions for Sepsis and Septic Shock criteria between August 2013 and January 2017 with complete clinical parameters and laboratory data were enrolled as a derivation cohort. The primary outcomes were the 7-, 14-, 21-, and 28-day mortalities. Furthermore, another group of patients under the same setting between January 2020 and March 2020 were also enrolled as a validation cohort. In the derivation cohort, we included 699 consecutive adult patients. The 72 h NEWS2 had good discrimination for predicting 7-, 14-, 21-, and 28-day mortalities (AUC: 0.780, 0.724, 0.700, and 0.667, respectively) and was not inferior to the SOFA (AUC: 0.740, 0.680, 0.684, and 0.677, respectively). With the new combined NESO tool, the hazard ratio was 1.854 (1.203-2.950) for the intermediate-risk group and 6.810 (3.927-11.811) for the high-risk group relative to the low-risk group. This finding was confirmed in the validation cohort using a separated survival curve for 28-day mortality. The 72 h NEWS2 alone was non-inferior to the admission SOFA or day 3 SOFA for predicting sepsis outcomes. The NESO tool was found to be useful for 7-, 14-, 21-, and 28-day mortality risk stratification in patients with severe sepsis.

Measuring Success of Patients' Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation.

BACKGROUND: Mobile health services are gradually being introduced to support patients' self-management of chronic conditions. The success of these services is contingent upon patients' continuous use of them. OBJECTIVE: This study aims to develop a model to measure the success of patients' continuous use of mobile health services for the self-management of chronic conditions. METHODS: The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. RESULTS: The model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients' intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (ß=.195, P=.03), perceived usefulness (ß=.307, P=.004), and user satisfaction (ß=.254, P=.04) with the mobile health service. Information quality (ß=.235, P=.005), system quality (ß=.192, P=.02), and service quality (ß=.494, P<.001) had a significantly positive influence on perceived usefulness but not on user satisfaction. Perceived usefulness had a significantly positive influence on user satisfaction (ß=.664, P<.001). In a result opposite to the original hypothesis, perceived health status did not negatively influence patients' intention to continue using the mobile health service but showed a significantly positive correlation. CONCLUSIONS: This study developed a theoretical model to predict and explain patients' continuous use of mobile health services for self-management of chronic conditions and empirically tested the model. Perceived usefulness, user satisfaction, and health status contributed to patients' intention to make continuous use of mobile health services for self-managing their chronic conditions.

Automated Annotation of Epileptiform Burden and Its Association with Outcomes.

OBJECTIVE: This study was undertaken to determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients. METHODS: A single center retrospective analysis was made of 1,967 neurologic, medical, and surgical patients who underwent >16 hours of continuous electroencephalography (EEG) between 2011 and 2017. We developed an artificial intelligence algorithm to annotate 11.02 terabytes of EEG and quantify epileptiform activity burden within 72 hours of recording. We evaluated burden (1) in the first 24 hours of recording, (2) in the 12-hours epoch with highest burden (peak burden), and (3) cumulatively through the first 72 hours of monitoring. Machine learning was applied to estimate the effect of epileptiform burden on outcome. Outcome measure was discharge modified Rankin Scale, dichotomized as good (0-4) versus poor (5-6). RESULTS: Peak epileptiform burden was independently associated with poor outcomes (p < 0.0001). Other independent associations included age, Acute Physiology and Chronic Health Evaluation II score, seizure on presentation, and diagnosis of hypoxic-ischemic encephalopathy. Model calibration error was calculated across 3 strata based on the time interval between last EEG measurement (up to 72 hours of monitoring) and discharge: (1) <5 days between last measurement and discharge, 0.0941 (95% confidence interval [CI] = 0.0706-0.1191); 5 to 10 days between last measurement and discharge, 0.0946 (95% CI = 0.0631-0.1290); >10 days between last measurement and discharge, 0.0998 (95% CI = 0.0698-0.1335). After adjusting for covariates, increase in peak epileptiform activity burden from 0 to 100% increased the probability of poor outcome by 35%. INTERPRETATION: Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes. ANN NEUROL 2021;90:300-311.

A Comprehensive 6A Framework for Improving Patient Self-Management of Hypertension Using mHealth Services: Qualitative Thematic Analysis.

BACKGROUND: Hypertension affects over 15% of the world's population and is a significant global public health and socioeconomic challenge. Mobile health (mHealth) services have been increasingly introduced to support hypertensive patients to improve their self-management behaviors, such as adherence to pharmacotherapy and lifestyle modifications. OBJECTIVE: This study aims to explore patients' perceptions of mHealth services and the mechanisms by which the services support them to self-manage their hypertension. METHODS: A semistructured, in-depth interview study was conducted with 22 outpatients of the General Hospital of Ningxia Medical University from March to May 2019. In 2015, the hospital introduced an mHealth service to support community-dwelling outpatients with self-management of hypertension. Content analysis was conducted by following a grounded theory approach for inductive thematic extraction. Constant comparison and categorization classified the first-level codes with similar meanings into higher-level themes. RESULTS: The patient-perceived mechanisms by which the mHealth service supported their self-management of hypertension were summarized as 6A: access, assessment, assistance, awareness, ability, and activation. With the portability of mobile phones and digitization of information, the mHealth service provided outpatients with easy access to assess their vital signs and self-management behaviors. The assessment results gave the patients real-time awareness of their health conditions and self-management performance, which activated their self-management behaviors. The mHealth service also gave outpatients access to assistance, which included health education and self-management reminders. Both types of assistance could also be activated by abnormal assessment results, that is, uncontrolled or deteriorating blood pressure values, discomfort symptoms, or not using the service for a long period. With its scalable use to handle any possible information and services, the mHealth service provided outpatients with educational materials to learn at their own pace. This led to an improvement in self-management awareness and ability, again activating their self-management behaviors. The patients would like to see further improvements in the service to provide more useful, personalized information and reliable services. CONCLUSIONS: The mHealth service extended the traditional hypertension care model beyond the hospital and clinician's office. It provided outpatients with easy access to otherwise inaccessible hypertension management services. This led to process improvement for outpatients to access health assessment and health care assistance and improved their awareness and self-management ability, which activated their hypertension self-management behaviors. Future studies can apply the 6A framework to guide the design, implementation, and evaluation of mHealth services for outpatients to self-manage chronic conditions.

[Interpretation of the international expert recommendations of clinical features to prompt referral for diagnostic assessment of cerebral palsy].

Under the guidance and support of national policies in recent years, the community medical system has been developed rapidly, among which primary child healthcare is carried out routinely in community hospitals, greatly alleviating the pressure of specialized pediatric hospitals and departments of pediatrics in secondary and tertiary general hospitals. However, due to the lack of professional training for primary child healthcare personnel in community medical institutions, early symptoms of children with cerebral palsy cannot be identified and so children with cerebral palsy are often unable to receive early diagnosis and intervention, which may affect their prognosis. An article about international expert consensus and recommendations on early identification and referral of cerebral palsy in community medical institutions was published in Development Medicine and Child Neurology in 2020. It proposed six clinical features that should prompt referral and two warning signs that warrant enhanced monitoring, as well as five recommendations for referral to medical experts and other healthcare professionals for the diagnosis of cerebral palsy. The recommendations may help primary child healthcare personnel in community medical institutions to early identify the children at high risk of cerebral palsy, thus reducing the delay of referral and intervention. This article gives an interpretation of the recommendations based on the actual situation in China, in order to improve the ability of primary child healthcare personnel in community medical institutions to early identify high-risk signals of cerebral palsy and conduct reasonable referral. This will help to achieve the early identification, early diagnosis, and early intervention to improve the prognosis of children with cerebral palsy.