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Aim: To identify and synthesise qualitative studies on barriers and facilitators perceived by dialysis patients in relation to self‐care and disease management. Design: Systematic review of qualitative studies. Data Sources: Qualitative study articles were extracted from PUBMED, MEDLINE, COCHRANE, WEB OF SCIENCE (WOS), CINAHL PsycINFO and EMBASE and electronic journals of the Spanish Society of Nephrology and Spanish Society of Nephrological Nursing until May 2022. Studies on barriers and/or facilitators affecting self‐care and disease management expressed by people undergoing haemodialysis or peritoneal dialysis were included. Review Methods: The SPICE (Setting, Perspective, Intervention, Comparison and Evaluation) strategy was used to develop issues and subissues through the thematic synthesis of the qualitative findings. GRADE‐CERQual was used to evaluate the articles. Results: From 172 articles, 15 qualitative articles about barriers and facilitators perceived by patients concerning self‐care and disease management were finally included. Identified eight facilitators and four barriers. Conclusion: Patients perceived a significant number of barriers and facilitators. It is possible to identify which aspects facilitate self‐management of their disease and to understand that the processes are individualised. This is why therapeutic strategies should be designed to foster the participation and empowerment of the person in the management of the disease. Implications for the profession and/or patient care: Identifying the barriers and facilitators concerning the management of chronic kidney disease furnishes us with knowledge for individualised clinical practice and improved care processes. Impact: This review is the first to synthesise barriers and facilitators in haemodialysis patients about the management of their disease and treatment. The results enable the proposal of improvements in the training of healthcare personnel, clinical practice guidelines and action protocols to improve the daily life and management of the disease by patients. No patient or public contribution due to this is a systematic review. [ABSTRACT FROM AUTHOR]

The ability of organophosphate pesticides to disturb immune function has been demonstrated by in vivo and in vitro studies, but evidence of such effects on humans remains scarce. To assess the association between organophosphate pesticides exposure and cytokine levels in Mexican flower workers, a cross-sectional study was carried out. A questionnaire was provided to 121 male flower workers, and urine and blood samples were collected. Using gas chromatography, urinary concentrations of dialkylphosphate metabolites were determined. The serum cytokine levels, IL-4, IL-5, IL-6, IL-8, and IL-10, were measured using multiplex analysis, and levels of INF-γ and TNF-α by ELISA. We found that a higher dialkylphosphate concentration decreased the pro-inflammatory cytokines INF-γ (β = -0.63; 95 % CI: -1.22, -0.05), TNF-α (β= -1.18; 95 % CI: -2.38, 0.02), and IL-6 (β= -0.59; 95 % CI: -1.29, 0.12), and increased IL-10 (β=0.56; 95 % CI: 0.02, 1.09), the main anti-inflammatory cytokine, suggesting an imbalance of the immune response in flower workers., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Artificial intelligence (AI) is often used to predict human behavior, thus potentially posing limitations to individuals' and collectives' freedom to act. AI's most controversial and contested applications range from targeted advertisements to crime prevention, including the suppression of civil disorder. Scholars and civil society watchdogs are discussing the oppressive dangers of AI being used by centralized institutions, like governments or private corporations. Some suggest that AI gives asymmetrical power to governments, compared to their citizens. On the other hand, civil protests often rely on distributed networks of activists without centralized leadership or planning. Civil protests create an adversarial tension between centralized and decentralized intelligence, opening the question of how distributed human networks can collectively adapt and outperform a hostile centralized AI trying to anticipate and control their activities. This paper leverages multi-agent reinforcement learning to simulate dynamics within a human-machine hybrid society. We ask how decentralized intelligent agents can collectively adapt when competing with a centralized predictive algorithm, wherein prediction involves suppressing coordination. In particular, we investigate an adversarial game between a collective of individual learners and a central predictive algorithm, each trained through deep Q-learning. We compare different predictive architectures and showcase conditions in which the adversarial nature of this dynamic pushes each intelligence to increase its behavioral complexity to outperform its counterpart. We further show that a shared predictive algorithm drives decentralized agents to align their behavior. This work sheds light on the totalitarian danger posed by AI and provides evidence that decentrally organized humans can overcome its risks by developing increasingly complex coordination strategies., (© 2023 The Authors. Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)

As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals., (© 2022. The Author(s).)

Background: Weaning from venoarterial extracorporeal membrane oxygenation (VA-ECMO) support fails in 30% to 70% of patients., Objective: To explore the utility of echocardiographic parameters in predicting successful disconnection from VA-ECMO., Methods: Patients receiving VA-ECMO in a referral hospital were included. The relationships between echocardiographic parameters during the weaning trial and weaning success (survival > 24 hours after VA-ECMO explant and no death from cardiogenic shock, heart failure, or cardiac arrest during the hospital stay) and survival were evaluated., Results: Of 85 patients included, 61% had successful weaning. Parameters significantly related to weaning success were higher left ventricular ejection fraction (LVEF; 40% in patients with weaning success vs 30% in patients with weaning failure, P = .01), left ventricular outflow tract velocity time integral (15 cm vs 11 cm, P = .01), aortic valve opening in every cycle (98% vs 91% of patients, P = .01), and normal qualitative right ventricular function (60% vs 42% of patients, P = .02). The LVEF remained as an independent predictor of weaning success (hazard ratio, 0.938; 95% CI, 0.888-0.991; P = .02). An LVEF >33.4% was the optimal cutoff value to discriminate patients with successful weaning (area under the curve, 0.808; sensitivity, 93%; specificity, 72%) and was related to higher survival at discharge (60% vs 20%, P < .001)., Conclusion: Among weaning trial echocardiographic parameters, LVEF was the only independent predictor of successful VA-ECMO weaning. An LVEF >33.4% was the optimal cutoff value to discriminate patients with successful weaning and was related to final survival., (©2022 American Association of Critical-Care Nurses.)

Influencing others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated it) is a problem that has attracted much research interest. Nevertheless, existing literature has ignored the possibility that the source might strategically modify the network structure (by rewiring links or introducing fake nodes) to escape detection. Here, without restricting our analysis to any particular diffusion scenario, we close this gap by evaluating two mechanisms that hide the source-one stemming from the source's actions, the other from the network structure itself. This reveals that sources can easily escape detection, and that removing links is far more effective than introducing fake nodes. Thus, efforts should focus on exposing concealed ties rather than planted entities; such exposure would drastically improve our chances of detecting the diffusion source., Competing Interests: Authors declare no competing interests., (© 2022 The Authors.)

Background: Age over 70 years seems to confer poor prognosis for patients under mechanical circulatory support (MCS). Advanced age is usually a relative contraindication. Our objective was to assess the impact of age on survival of patients with short-term MCS., Methods: Retrospective analysis of ≥70-year-old patients supported with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) or Impella CP® due to cardiogenic shock and other situations of hemodynamic instability in a referral hospital (elderly group), compared with younger patients (<70 years). We analyze factors associated with survival in elderly group., Results: Out of 164 short-term MCS implants from 2013 to October 2020, 45 (27.4%) correspond to ≥70-year-old patients (73.3% VA-ECMO; 26.7% Impella CP®), 80% as bridge to recovery and 15.6% for high-risk percutaneous coronary intervention (PCI). We found no significant differences in complications developed between both groups. Survivals at discharge (40% vs. 43.7%, p = 0.403) and at follow-up (median 13.6 [30] months) were similar in elderly and young patients (35.6% vs. 37.8%, log-rank p = 0.061). Predictive factors of mortality in elderly patients were peripheral artery disease (p = 0.037), higher lactate (p = 0.003) and creatinine (p = 0.035) at implant, longer cardiac arrest (p = 0.003), and worse post-implantation left ventricular ejection fraction (p = 0.003). Patients with indication of MCS for high-risk PCI had higher survival compared to other indications (p = 0.013)., Conclusion: Short-term MCS with VA-ECMO or Impella CP® in elderly patients may be a reasonable option in hemodynamic compromise situations as bridge to recovery or elective high-risk PCI, without a significant increase in complications or mortality. Age should not be an absolute contraindication, but careful selection of candidate patients is necessary., (© 2021 International Center for Artificial Organs and Transplantation and Wiley Periodicals LLC.)

Policymakers commonly employ non-pharmaceutical interventions to reduce the scale and severity of pandemics. Of non-pharmaceutical interventions, physical distancing policies-designed to reduce person-to-person pathogenic spread - have risen to recent prominence. In particular, stay-at-home policies of the sort widely implemented around the globe in response to the COVID-19 pandemic have proven to be markedly effective at slowing pandemic growth. However, such blunt policy instruments, while effective, produce numerous unintended consequences, including potentially dramatic reductions in economic productivity. In this study, we develop methods to investigate the potential to simultaneously contain pandemic spread while also minimizing economic disruptions. We do so by incorporating both occupational and contact network information contained within an urban environment, information that is commonly excluded from typical pandemic control policy design. The results of our methods suggest that large gains in both economic productivity and pandemic control might be had by the incorporation and consideration of simple-to-measure characteristics of the occupational contact network. We find evidence that more sophisticated, and more privacy invasive, measures of this network do not drastically increase performance., (© 2021. The Author(s).)