Multi-Timescale Perceptual History Resolves Visual Ambiguity

When visual input is inconclusive, does previous experience aid the visual system in attaining an accurate perceptual interpretation? Prolonged viewing of a visually ambiguous stimulus causes perception to alternate between conflicting interpretations. When viewed intermittently, however, ambiguous stimuli tend to evoke the same percept on many consecutive presentations. This perceptual stabilization has been suggested to reflect persistence of the most recent percept throughout the blank that separates two presentations. Here we show that the memory trace that causes stabilization reflects not just the latest percept, but perception during a much longer period. That is, the choice between competing percepts at stimulus reappearance is determined by an elaborate history of prior perception. Specifically, we demonstrate a seconds-long influence of the latest percept, as well as a more persistent influence based on the relative proportion of dominance during a preceding period of at least one minute. In case short-term perceptual history and long-term perceptual history are opposed (because perception has recently switched after prolonged stabilization), the long-term influence recovers after the effect of the latest percept has worn off, indicating independence between time scales. We accommodate these results by adding two positive adaptation terms, one with a short time constant and one with a long time constant, to a standard model of perceptual switching

Automatic term identification for bibliometric mapping

A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well

Як уникнути підйому рівня води?

East Africa’s Lake Victoria provides resources and services to millions of people on the lake’s shores and abroad. In particular, the lake’s fisheries are an important source of protein, employment, and international economic connections for the whole region. Nonetheless, stock dynamics are poorly understood and currently unpredictable. Furthermore, fishery dynamics are intricately connected to other supporting services of the lake as well as to lakeshore societies and economies. Much research has been carried out piecemeal on different aspects of Lake Victoria’s system; e.g., societies, biodiversity, fisheries, and eutrophication. However, to disentangle drivers and dynamics of change in this complex system, we need to put these pieces together and analyze the system as a whole. We did so by first building a qualitative model of the lake’s social-ecological system. We then investigated the model system through a qualitative loop analysis, and finally examined effects of changes on the system state and structure. The model and its contextual analysis allowed us to investigate system-wide chain reactions resulting from disturbances. Importantly, we built a tool that can be used to analyze the cascading effects of management options and establish the requirements for their success. We found that high connectedness of the system at the exploitation level, through fisheries having multiple target stocks, can increase the stocks’ vulnerability to exploitation but reduce society’s vulnerability to variability in individual stocks. We describe how there are multiple pathways to any change in the system, which makes it difficult to identify the root cause of changes but also broadens the management toolkit. Also, we illustrate how nutrient enrichment is not a self-regulating process, and that explicit management is necessary to halt or reverse eutrophication. This model is simple and usable to assess system-wide effects of management policies, and can serve as a paving stone for future quantitative analyses of system dynamics at local scales

Retreatment of hepatitis C non-responsive to Interferon. A placebo controlled randomized trial of Ribavirin monotherapy versus combination therapy with Ribavirin and Interferon in 121 patients in the Benelux [ISRCTN53821378]

BACKGROUND: Evidence based medicine depends on unbiased selection of completed randomized controlled trials. For completeness it is important to publish all trials. This report describes the first large randomised controlled trial where combination therapy was compared to placebo therapy and to ribavirin monotherapy, which has not been published untill now. METHODS: One hundred and twenty one patients with chronic hepatitis C and elevated transaminases who did not respond to previous treatment with standard interferon monotherapy, were included from 16 centers in Belgium, the Netherlands and Luxembourg between 1992 and 1996. Patient poor-response characteristics were: genotype 1 (69%), HCV RNA above 2 × 10(6 )copies/ml (55%) and cirrhosis (38%). Patients were randomized to 6 months combination therapy with interferon alpha-2b (3 MU tiw) and ribavirin (1000–1200 mg / day), 6 months ribavirin monotherapy (1000–1200 mg / day) or 6 months ribavirin placebo. The study was double blinded for the ribavirin / placebo component. One patient did not fit the entry criteria, and 3 did not start. All 117 patients who received at least one dose of treatment were included in the intention to treat analysis. RESULTS: At the end of treatment, HCV RNA was undetectable in 35% of patients on combination therapy and in none of the patients treated with ribavirin monotherapy or placebo. The sustained virological response rate at 6 months after therapy was 15% for patients treated with interferon and ribavirin. During the 6 months treatment period 13% of patients on interferon ribavirin combination therapy, 13% of patients on ribavirin monotherapy and 11% of patients on placebo withdrew due to side effects or noncompliance. At 24 weeks of treatment the mean Hb level was 85% of the baseline value, which means a mean decrease from 9.1 mmol/l to 7.8 mmol/l. The Hb levels at the end of treatment were not significantly different from patients treated with ribavirin monotherapy (p = 0.76). End of treatment WBC was significantly lower in patients treated with combination therapy, compared to ribavirin (p < 0.01) as well as for patients treated with ribavirin monotherapy compared to placebo (p < 0.01). DISCUSSION: This belated report on the only placebo controlled study of interferon ribavirin combination therapy in non responders to standard doses of interferon monotherapy documents the effectiveness, be it limited, of this approach as well as the dynamics of the effects on blood counts

Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study

Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p

Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study

Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p

Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study

Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p

Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study

Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p

Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study

Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p