With online health information becoming increasingly popular among patients, concerns have been raised about the impact of patients' Internet health information-seeking behavior on their relationship ...with physicians. Therefore, it is pertinent to understand the influence of online health information on the patient-physician relationship.
Our objective was to systematically review existing research on patients' Internet health information seeking and its influence on the patient-physician relationship.
We systematically searched PubMed and key medical informatics, information systems, and communication science journals covering the period of 2000 to 2015. Empirical articles that were in English were included. We analyzed the content covering themes in 2 broad categories: factors affecting patients' discussion of online findings during consultations and implications for the patient-physician relationship.
We identified 18 articles that met the inclusion criteria and the quality requirement for the review. The articles revealed barriers, facilitators, and demographic factors that influence patients' disclosure of online health information during consultations and the different mechanisms patients use to reveal these findings. Our review also showed the mechanisms in which online information could influence patients' relationship with their physicians.
Results of this review contribute to the understanding of the patient-physician relationship of Internet-informed patients. Our main findings show that Internet health information seeking can improve the patient-physician relationship depending on whether the patient discusses the information with the physician and on their prior relationship. As patients have better access to health information through the Internet and expect to be more engaged in health decision making, traditional models of the patient-provider relationship and communication strategies must be revisited to adapt to this changing demographic.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background
This study evaluated the safety, effectiveness, and feasibility of indocyanine green (ICG) tracing in guiding lymph-node (LN) dissection during laparoscopic D2 radical gastrectomy in ...patients with advanced gastric cancer (AGC) after neoadjuvant chemotherapy (NAC).
Method
We retrospectively analyzed data on 313 patients with clinical stage of cT1-4N0-3M0 who underwent laparoscopic radical gastrectomy after NAC between February 2010 and October 2020 from two hospitals in China. Grouped according to whether ICG was injected. For the ICG group (
n
= 102) and non-ICG group (
n
= 211), 1:1 propensity matching analysis was used.
Results
After matching, there was no significant difference in the general clinical pathological data between the two groups (ICG vs. non-ICG: 94 vs. 94). The average number of total LN dissections was significantly higher in the ICG group and lower LN non-compliance rate than in the non-ICG group. Subgroup analysis showed that among patients with LN and tumor did not shrink after NAC, the number of LN dissections was significantly more and LN non-compliance rate was lower in the ICG group than in the non-ICG group. Intraoperative blood loss was significantly lesser in the ICG group than in the non-ICG group, while the recovery and complications of the two groups were similar.
Conclusion
For patients with poor NAC outcomes, ICG tracing can increase the number of LN dissections during laparoscopic radical gastrectomy, reduce the rate of LN non-compliance, and reduce intraoperative bleeding. Patients with AGC should routinely undergo ICG-guided laparoscopic radical gastrectomy.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The aetiology of Alzheimer's disease (AD) is believed to involve environmental exposure and genetic susceptibility. The aim of our present systematic review and meta-analysis was to roundly evaluate ...the association between AD and its modifiable risk factors.
We systematically searched PubMed and the Cochrane Database of Systematic Reviews from inception to July 2014, and the references of retrieved relevant articles. We included prospective cohort studies and retrospective case-control studies.
16,906 articles were identified of which 323 with 93 factors met the inclusion criteria for meta-analysis. Among factors with relatively strong evidence (pooled population >5000) in our meta-analysis, we found grade I evidence for 4 medical exposures (oestrogen, statin, antihypertensive medications and non-steroidal anti-inflammatory drugs therapy) as well as 4 dietary exposures (folate, vitamin E/C and coffee) as protective factors of AD. We found grade I evidence showing that one biochemical exposure (hyperhomocysteine) and one psychological condition (depression) significantly increase risk of developing AD. We also found grade I evidence indicative of complex roles of pre-existing disease (frailty, carotid atherosclerosis, hypertension, low diastolic blood pressure, type 2 diabetes mellitus (Asian population) increasing risk whereas history of arthritis, heart disease, metabolic syndrome and cancer decreasing risk) and lifestyle (low education, high body mass index (BMI) in mid-life and low BMI increasing the risk whereas cognitive activity, current smoking (Western population), light-to-moderate drinking, stress, high BMI in late-life decreasing the risk) in influencing AD risk. We identified no evidence suggestive of significant association with occupational exposures.
Effective interventions in diet, medications, biochemical exposures, psychological condition, pre-existing disease and lifestyle may decrease new incidence of AD.
Epilepsy is seen historically as a disease of aberrant neuronal signaling manifesting as seizures. With the discovery of numerous auto‐antibodies and the subsequent growth in understanding of ...autoimmune encephalitis, there has been an increasing emphasis on the contribution of the innate and adaptive immune system to ictogenesis and epileptogenesis. Pathogenic antibodies, complement activation, CD8+ cytotoxic T cells, and microglial activation are seen, to various degrees, in different seizure‐associated neuroinflammatory and autoimmune conditions. These aberrant immune responses are thought to cause disruptions in neuronal signaling, generation of acute symptomatic seizures, and, in some cases, the development of long‐term autoimmune epilepsy. Although early treatment with immunomodulatory therapies improves outcomes in autoimmune encephalitides and autoimmune epilepsies, patient identification and treatment selection are not always clear‐cut. This review examines the role of the different components of the immune system in various forms of seizure disorders including autoimmune encephalitis, autoimmune epilepsy, Rasmussen encephalitis, febrile infection–related epilepsy syndrome (FIRES), and new‐onset refractory status epilepticus (NORSE). In particular, the pathophysiology and unique cytokine profiles seen in these disorders and their links with diagnosis, prognosis, and treatment decision‐making are discussed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract Background Neuropsychiatric symptoms (NPS) are being increasingly recognized as common serious problems in Alzheimer’s disease (AD). However, published data on the prevalence of NPS in ...persons with AD are conflicting. This meta-analysis aimed to estimate the prevalence of NPS in persons with AD. Methods Studies published from 1964 to September 30, 2014, were identified from PubMed and Embase database, reference lists and conference abstracts. We calculated prevalence rates and conducted meta-regression analysis with random-effects model, according to study characteristics, population demographics or condition information. Results We identified 48 eligible articles, which provided data for 12 NPS reported in Neuropsychiatric Inventory (NPI). The most frequent NPS was apathy, with an overall prevalence of 49% (95% CI 41–57%), followed by depression, aggression, anxiety and sleep disorder, the pooled prevalence estimates of which were 42% (95% CI 37–46%), 40% (95% CI 33–46%), 39% (95% CI 32–46%) and 39% (95% CI 30–47%), respectively. The less prevalent NPS were irritability (36%, 31–41%), appetite disorder (34%, 27–41%), aberrant motor behavior (32%, 25–38%), delusion (31%, 27–35%), disinhibition (17%, 12–21%) and hallucination (16%, 13–18%). Least common was euphoria, with an overall prevalence of 7% (95% CI 5–9%). Limitations Several aspects, such as the quality of included studies were not always optimal and there was significant heterogeneity of prevalence estimate across studies. Conclusions NPS were observed to be highly prevalent in AD patients. Disease duration, age, education level, population origin and the severity of cognitive impairment had influence on the prevalence of some NPS.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Alzheimer's disease (AD), the most important progressive neurodegenerative disorder, is characterized by cognitive and behavioral disabilities. Nowadays, tau, as a microtubuleassociated protein and a ...principle neuropathological hallmark of AD, provides us a neoteric perspective to explore further aetiopathogenesis and therapeutic strategy. The hyperphosphorylation and abnormal aggregation of tau, combined with its decreased clearance, form neurofibrillary tangles (NFTs) and exert neurotoxicity in AD.
Recent investigations aim to prevent the deposition of NFT and accelerate the clearance of NFT. Intriguingly, immunization strategies targeting tau effectively ameliorates the tau-associated pathology in AD. In addition, modified therapies targeting tau should be regarded as a potential way to treat AD. These progresses open new avenues for AD.
Here, we review the recent literature of potential mechanisms of the tau in AD and discuss the modified therapeutic strategies for AD.
We sought to identify the risk factors for predicting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD).
We searched 6 electronic databases for cohort studies published ...from January 1966 to March 2015. Eligible studies were required to be relevant to the subject and provide sufficient data for our needs.
60 cohort studies with 14,821 participants from 16 countries were included in the meta-analysis. The strongest positive associations between risk factors and the progression from MCI to AD were found for abnormal cerebrospinal fluid (CSF), phosphorylated τ (p-τ) (relative risk (RR)=2.43, 95% CI=1.70 to 3.48), abnormal CSF τ/Aβ1-42 (RR=3.77, 95% CI=2.34 to 6.09), hippocampal atrophy (RR=2.59, 95% CI=1.95 to 3.44), medial temporal lobe atrophy (RR=2.11, 95% CI=1.70 to 2.63) and entorhinal atrophy (RR=2.03, 95% CI=1.57 to 2.62). Further positive associations were found for the presence of apolipoprotein E (APOE)ε4ε4 and at least 1 APOEε4 allele, CSF total-τ (t-τ), white matter hyperintensity volume, depression, diabetes, hypertension, older age, female gender, lower mini-mental state examination (MMSE) score and higher AD assessment scale cognitive subscale (ADAS-cog) score. Negative associations were found for high body mass index (RR=0.85, 95% CI=0.76 to 0.96) and higher auditory verbal learning test delay score (RR=0.86, 95% CI=0.77 to 0.96).
Patients with MCI with APOEε4, abnormal CSF τ level, hippocampal and medial temporal lobe atrophy, entorhinal atrophy, depression, diabetes, hypertension, older age, female gender, lower MMSE score and higher ADAS-cog score, had a high risk for the progression to AD.
Software defect prediction, which predicts defective code regions, can help developers find bugs and prioritize their testing efforts. To build accurate prediction models, previous studies focus on ...manually designing features that encode the characteristics of programs and exploring different machine learning algorithms. Existing traditional features often fail to capture the semantic differences of programs, and such a capability is needed for building accurate prediction models. To bridge the gap between programs' semantics and defect prediction features, this paper proposes to leverage a powerful representation-learning algorithm, deep learning, to learn semantic representation of programs automatically from source code. Specifically, we leverage Deep Belief Network (DBN) to automatically learn semantic features from token vectors extracted from programs' Abstract Syntax Trees (ASTs). Our evaluation on ten open source projects shows that our automatically learned semantic features significantly improve both within-project defect prediction (WPDP) and cross-project defect prediction (CPDP) compared to traditional features. Our semantic features improve WPDP on average by 14.7% in precision, 11.5% in recall, and 14.2% in F1. For CPDP, our semantic features based approach outperforms the state-of-the-art technique TCA+ with traditional features by 8.9% in F1.
This paper describes the design and performance of a 6-kW, full-bridge, bidirectional isolated dc-dc converter using a 20-kHz transformer for a 53.2-V, 2-kWh lithium-ion (Li-ion) battery energy ...storage system. The dc voltage at the high-voltage side is controlled from 305 to 355 V, as the battery voltage at the low-voltage side (LVS) varies from 50 to 59 V. The maximal efficiency of the dc-dc converter is measured to be 96.0% during battery charging, and 96.9% during battery discharging. Moreover, this paper analyzes the effect of unavoidable dc-bias currents on the magnetic-flux saturation of the transformer. Finally, it provides the dc-dc converter loss breakdown with more focus on the LVS converter.
Biodiversity across multiple trophic levels is required to maintain multiple ecosystem functions. Yet it remains unclear how multitrophic diversity and species interactions regulate ecosystem ...multifunctionality. Here, combining data from 9 different trophic groups (including trees, shrubs, herbs, leaf mites, small mammals, bacteria, pathogenic fungi, saprophytic fungi, and symbiotic fungi) and 13 ecosystem functions related to supporting, provisioning, and regulating services, we used a multitrophic perspective to evaluate the effects of elevation, diversity, and network complexity on scale‐dependent subalpine forest multifunctionality. Our results demonstrated that elevation and soil pH significantly modified species composition and richness across multitrophic groups and influenced multiple functions simultaneously. We present evidence that species richness across multiple trophic groups had stronger effects on multifunctionality than species richness at any single trophic level. Moreover, biotic associations, indicating the complexity of trophic networks, were positively associated with multifunctionality. The relative effects of diversity on multifunctionality increased at the scale of the larger community compared to a scale accounting for neighboring interactions. Our results highlight the paramount importance of scale‐ and context‐dependent multitrophic diversity and interactions for a better understanding of mountain ecosystem multifunctionality in a changing world.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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