Search Results (12)

Background/Objectives: Contemporary heart failure (HF) guidelines recommend early initiation of four foundational drug classes in HFrEF. However, real-world prescription rates of guideline-directed medical therapy (GDMT) at discharge remain low, and comparative data in this setting is limited. We aimed to explore the association between GDMT intensity prescribed at or before hospital discharge and clinical outcomes. Methods: MEDLINE and EMBASE were searched through March 2026 (PROSPERO CRD420261352137). A frequentist random-effects network meta-analysis grouped regimens into four intensity nodes (single/none, double, triple, quadruple), with the primary analysis restricted to adjusted hazard ratios. The primary outcome was the composite of all-cause mortality (ACM) and HF hospitalization (HFH). Secondary outcomes were HFH alone, ACM, and cardiovascular mortality. Confidence was rated with CINeMA. Estimates are reported as associations, not treatment effects. Results: Twenty-seven studies (26 observational, 1 RCT; 73,174 patients) were included. Among SGLT2i-era cohorts, quadruple therapy was suboptimally prescribed (pooled 34%, range 11.6–55.2%). For the primary composite endpoint, more complete regimens were associated with progressively lower event rates versus single or no therapy (double: hazard ratio 0.76, 95% CI 0.68–0.84; triple: 0.72, 0.64–0.81; quadruple: 0.52, 0.36–0.75; τ² = 0). A consistent ordinal gradient was seen across outcomes, with quadruple therapy ranking first numerically for every outcome in which it was estimable. The direction and ordering were preserved in a sensitivity analysis additionally incorporating risk ratios, on stratification by follow-up duration, and in an alternative network anchored to incomplete therapy. Because most evidence was observational, the magnitude of these associations should not be interpreted as a causal treatment effect and likely reflects residual confounding and selection bias. Conclusions: Discharge GDMT remains an important opportunity to improve outcomes in patients with HF. Adequately powered randomized trials are required to establish the incremental benefit of this approach and to close the gap between evidence and practice. Full article

The rapid growth of video content development requires more effective compression solutions than traditional ones. Although neural video compression has demonstrated impressive advances, the current methods are having a hard time with how to effectively model long-range temporal dependencies and react to different content properties. We introduce STAC (Spatio-Temporal Adaptive Context), a transformer-based neural video compression scheme that does not have these limitations, and makes three original contributions. First, the Adaptive Context Selector (ACS) is the dynamic evaluation and selection of the most informative reference frames, based on learned relevance scoring, in place of the traditional use of predetermined adjacent frame sets. Second, Enhanced Sliding Window Attention (ESWA) is an effective computational model of spatio-temporal correlations by the integration of learnable local bias and temporal gating information into a computationally adjustable attention model. Third, a dual-path entropy model is an adaptively learned fusion gate that combines channel-wise autoregressive prediction with spatio-temporal prediction to produce better probability estimations for entropy coding. Trained on the Vimeo-90k dataset using a four-phase curriculum with the Adam optimiser over approximately 2.2 M total steps. We tested STAC using six benchmark videos, such as UVG, MCL-JCV, and HEVC Class B, C, D and E videos, at varying test settings. The experimental findings prove that STAC, on average, saves a BD-rate of 32.20% in the YUV colourspace with an intra-period of −1. The consistent improvement across both PSNR and MS-SSIM metrics confirms that STAC’s coding gains arise from genuinely improved probability modelling, rather than metric-specific optimisation. Evaluations were performed on six standard benchmarks (UVG, MCL-JCV, and HEVC Classes B, C, D, and E) under 24 experimental configurations (six datasets × 2, and colourspaces × 2 intra-period settings), with all methods tested under identical conditions using the same sequences, frames (96 per sequence), and VTM-17.0 anchor codec. STAC achieves 32.20% average BD-rate savings over VTM under YUV IP = −1, outperforming the prior state-of-the-art DCMVC by 2.70 percentage points. Under IP = 32, STAC achieves −27.01%, with only 5.19 pp degradation versus 6.42 pp for DCMVC. The results generalise to the RGB colourspace (−31.23%) and scale from 240p (−35.19%) to 4K (−36.35%). Full article

Population-adjusted indirect comparisons (PAICs), including Matching-Adjusted Indirect Comparison and Simulated Treatment Comparison, are increasingly used to inform health technology assessments. These methods offer a pragmatic approach to generating comparative evidence between treatments when head-to-head trial data are unavailable and standard indirect treatment comparison methods are unfeasible. In rare diseases, however, PAICs often face substantial methodological challenges arising from small sample sizes, limited covariate overlap, and the frequent use of unanchored comparisons that rely on unverifiable assumptions. These limitations can lead to unstable estimates, reduced precision, and bias that may undermine the reliability of findings. Methodological refinements—such as optimized weighting, Bayesian approaches, and doubly robust estimators—provide some improvements but do not resolve these fundamental issues. Current European Joint Clinical Assessment guidance recommends that anchored PAICs be applied with great caution, while unanchored PAICs are considered highly problematic, and other methods should be used instead. We argue that PAICs can play a supportive role within a multidimensional and deliberative HTA process, contributing to comparative assessment alongside other evidence sources when available data are limited. However, their results require careful interpretation and transparent communication of uncertainty. Future research should prioritize the further development of formal frameworks to quantify bias and systematically assess robustness, thereby preventing overstatement of the credibility of PAIC-derived evidence in rare disease contexts. Full article

Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) about the correctness of autonomy decisions, which is distorted by human anchoring and omission bias. Specifically, (i) anchoring bias (tendency to confirm prior opinion) causes the imperception of key information and miscomprehending correctness of autonomy decisions; (ii) omission bias (inaction tendency) causes the overestimation of predicted loss caused by takeover. This paper proposes a novel HAIP safety assessment method considering effects of the above biases. First, an SA-based takeover decision model (SAB-TDM) is proposed. In SAB-TDM, SA perception and comprehension affected by anchoring bias are quantified with the Adaptive Control of Thought-Rational (ACT-R) theory and Anchoring Adjustment Model (AAM); behavioral utility prediction affected by omission bias is quantified with Prospect Theory. Second, guided by SAB-TDM, a dynamic Bayesian network is used to assess HAIP safety. A case study on autonomous ship collision avoidance verifies effectiveness of the method. Results show that the above biases mutually contribute to seriously threaten HAIP safety. Full article

The aim of this study was to evaluate whether trading experience reduces exposure to heuristic-driven biases, namely availability bias, anchoring and adjustments bias, representativeness bias, and confirmation biases of individual investors operating in the Indian stock market, through the moderating role of the Big Five personality traits. To achieve these research objectives, primary data were collected through a structured questionnaire. The sample consisted of 408 individual investors trading on the Indian stock market, who were selected on a convenient basis. Confirmatory factor analysis and Cronbach’s alpha were used to measure the validity and reliability of the data. Further analysis was conducted using Pearson’s correlation and multiple regression. The results of this study prove that increased trading experience does not always reduce the susceptibility to heuristic biases. Increased trading experience reduces the susceptibility to availability, and anchoring and adjustment heuristics of individual investors operating on the Indian stock market. The present study has some relevant implications for investors, portfolio managers, financial advisors, and other interested persons in the stock market. Full article

This paper presents a novel method for the performance of an all-silicon accelerometer by adjusting the ratio of the Si-SiO₂ bonding area, and the Au-Si bonding area in the anchor zone, with the aim of eliminating stress in the anchor region. The study includes the development of an accelerometer model and simulation analysis which demonstrates the stress maps of the accelerometer under different anchor–area ratios, which have a strong impact on the performance of the accelerometer. In practical applications, the deformation of the comb structure fixed by the anchor zone is influenced by the stress in the anchor region, causing a distorted nonlinear response signal. The simulation results demonstrate that when the area ratio of the Si-SiO₂ anchor zone to the Au-Si anchor zone decreases to 0.5, the stress in the anchor zone decreases significantly. Experimental results reveal that the full-temperature stability of zero-bias is optimized from 133 μg to 46 μg when the anchor–zone ratio of the accelerometer decreases from 0.8 to 0.5. At the same time, the full-temperature stability of the scale factor is optimized from 87 ppm to 32 ppm. Furthermore, zero-bias full-temperature stability and scale factor full-temperature stability are improved by 34.6% and 36.8%, respectively. Full article

Objectives: Cognitive biases (CB), an important source of medical errors, have been investigated in many clinical specialties. They have never been demonstrated in the field of neurocognitive disorders and Alzheimer’s disease, where the diagnostic accuracy is complex, particularly regard- ing their differential diagnoses. This study aims to establish the presence of CB in this field, their frequency and to understand the context favouring their appearance, as well as to propose pro- tective strategies (i.e., “debiasing”). Method: 15 clinicians in memory consultation (neuropsychologists, doctors, nurses) took part in interviews in 2020, including a structured interview, a discussion based on a list of CBs referenced in medicine and a reflective writing exercise relating to an experience involving a bias in the diag- nosis of Alzheimer’s disease (AD). Among these biases where fixing on the patient’s initial pres- entation and not adjusting one’s diagnostic hypothesis despite the presence of new elements (“anchoring bias”), being influenced by the clinical context or the way in which the information is transmitted (“frame effect”), looking for clinical elements that validate the diagnostic hypothesis and not those that would redirect it (“confirmation bias”), looking for typical manifestations of a disease and missing atypical clinical pictures (“representativeness bias”) and being influenced by the patient’s psychiatric context (“psychosis error”). The frequency of CBs was analysed semi-quantitatively and then compared between professions and age groups. The narratives were analysed qualitatively to identify contextual factors and possible protective strategies. Results: The most frequently cited CBs in the interviews were confirmation bias (86.67%), repre- sentativeness bias (80%), psychosis error (60%), frame effect (46.67%) and anchoring bias (46.67%). Differences were noted between the subgroups. Neuropsychologists more often noted the multiple alternatives CB, while doctors more frequently mentioned the overconfidence and availability CB. Juniors frequently described multiple alternatives CB, psychosis error and confir- mation CB, while seniors more frequently noted confidence error and outcome bias. Participants mentioned patient, caregiver, diagnostic procedure and clinical picture elements to explain their biases. They cited several protective strategies including a systematic approach to diagnosis, regular monitoring of their progress, interdisciplinarity and frequent supervision. Conclusion: CBs are found in Memory Centres as everywhere else in medicine and are influenced by age and profession. Protective factors to prevent CBs can be integrated into the diagnostic and follow-up process. Full article

This cross-sectional study aimed to clarify how cognitive biases and situational factors related to diagnostic errors among physicians. A self-reflection questionnaire survey on physicians’ most memorable diagnostic error cases was conducted at seven conferences: one each in Okayama, Hiroshima, Matsue, Izumo City, and Osaka, and two in Tokyo. Among the 147 recruited participants, 130 completed and returned the questionnaires. We recruited primary care physicians working in various specialty areas and settings (e.g., clinics and hospitals). Results indicated that the emergency department was the most common setting (47.7%), and the highest frequency of errors occurred during night-time work. An average of 3.08 cognitive biases was attributed to each error. The participants reported anchoring bias (60.0%), premature closure (58.5%), availability bias (46.2%), and hassle bias (33.1%), with the first three being most frequent. Further, multivariate logistic regression analysis for cognitive bias showed that emergency room care can easily induce cognitive bias (adjusted odds ratio 3.96, 95% CI 1.16−13.6, p-value = 0.028). Although limited to a certain extent by its sample collection, due to the sensitive nature of information regarding physicians’ diagnostic errors, this study nonetheless shows correlations with environmental factors (emergency room care situations) that induce cognitive biases which, in turn, cause diagnostic errors. Full article

When making decisions under uncertainty, people in all walks of life, including highly trained medical professionals, tend to resort to using ‘mental shortcuts’, or heuristics. Anchoring-and-adjustment (AAA) is a well-known heuristic in which subjects reach a judgment by starting from an initial internal judgment (‘anchored position’) based on available external information (‘anchoring information’) and adjusting it until they are satisfied. We studied the effects of the AAA heuristic during diagnostic decision-making in mammography. We provided practicing radiologists (N = 27 across two studies) a random number that we told them was the estimate of a previous radiologist of the probability that a mammogram they were about to see was positive for breast cancer. We then showed them the actual mammogram. We found that the radiologists’ own estimates of cancer in the mammogram reflected the random information they were provided and ignored the actual evidence in the mammogram. However, when the heuristic information was not provided, the same radiologists detected breast cancer in the same set of mammograms highly accurately, indicating that the effect was solely attributable to the availability of heuristic information. Thus, the effects of the AAA heuristic can sometimes be so strong as to override the actual clinical evidence in diagnostic tasks. Full article

This study investigated biased prediction of cumulative precipitation, using a variety of patterns of histories of cumulative precipitation, to explore how such biased prediction could delay evacuation or evacuation orders. The irrationality in predicting the future of cumulative precipitation was examined to obtain insights into the causes of delayed evacuation or evacuation orders using a simulated prediction of future cumulative precipitation based on the cumulative precipitation history. Anchoring and adjustment, or availability bias stemming from asymmetry of information, was observed in the prediction of cumulative precipitation, and found to delay evacuation or evacuation orders. Full article

The role of primary tumor resection in patients with pancreatic neuroendocrine neoplasms (PanNENs) and unresectable distant metastases remains controversial. We aimed to evaluate the effect of palliative primary tumor resection (PPTR) on overall survival (OS) in this setting. We searched the MEDLINE, Embase, Cochrane Library, Web of Science and SCOPUS databases up to January 2020 and used the Newcastle–Ottawa scale (NOS) criteria to assess quality/risk of bias. A total of 5661 articles were screened. In 10 studies, 5551 unique patients with stage IV PanNEN and unresectable metastases were included. The five-year OS for PanNEN patients undergoing PPTR in stage IV was 56.6% vs. 23.9% in the non-surgically treated patients (random effects relative risk (RR): 1.70; 95% CI: 1.53–1.89). Adjusted analysis of pooled hazard ratios (HR) confirmed longer OS in PanNEN patients undergoing PPTR (random effects HR: 2.67; 95% CI: 2.24–3.18). Cumulative OS analysis confirmed an attenuated survival benefit over time. The complication rate of PPTR was as high as 27%. In conclusion, PPTR may exert a survival benefit in stage IV PanNEN. However, the included studies were subject to selection bias, and special consideration should be given to PPTR anchored to a multimodal treatment strategy. Further longitudinal studies are warranted, with long-term follow-up addressing the survival outcomes associated with surgery in stage IV disease. Full article

Research integrating cognitive abilities and personality has focused on the role of personality traits. We propose a theory on the role of intraindividual variability of personality states (hereafter state variability) on perspective taking, in particular, the ability to infer other peoples’ mental states. First, we review the relevant research on personality psychology and social cognition. Second, we propose two complementary routes by which state variability relates to anchoring and adjustment in perspective taking. The first route, termed ego-dispersion, suggests that an increased state variability decreases egocentric bias, which reduces anchoring. The second route, termed perspective-pooling, suggests that an increased state variability facilitates efficient adjustment. We also discuss how our theory can be investigated empirically. The theory is rooted in an ecological interpretation of personality and social cognition, and flags new ways for integrating these fields of research. Full article