36 research outputs found

    FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks

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    The US Food and Drug Administration is clearing an increasing number of artificial intelligence and machine learning (AI/ML)-based medical devices through the 510(k) pathway. This pathway allows clearance if the device is substantially equivalent to a former cleared device (ie, predicate). We analysed the predicate networks of cleared AI/ML-based medical devices (cleared between 2019 and 2021), their underlying tasks, and recalls. More than a third of cleared AI/ML-based medical devices originated from non-AI/ML-based medical devices in the first generation. Devices with the longest time since the last predicate device with an AI/ML component were haematology (2001), radiology (2001), and cardiovascular devices (2008). Especially for devices in radiology, the AI/ML tasks changed frequently along the device's predicate network, raising safety concerns. To date, only a few recalls might have affected the AI/ML components. To improve patient care, a stronger focus should be placed on the distinctive characteristics of AI/ML when defining substantial equivalence between a new AI/ML-based medical device and predicate devices

    Bacterial computing with engineered populations

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    We describe strategies for the construction of bacterial computing platforms by describing a number of results from the recently completed bacterial computing with engineered populations project. In general, the implementation of such systems requires a framework containing various components such as intracellular circuits, single cell input/output and cell–cell interfacing, as well as extensive analysis. In this overview paper, we describe our approach to each of these, and suggest possible areas for future research

    Reflection of neuroblastoma intratumor heterogeneity in the new OHC-NB1 disease model

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    Accurate modeling of intratumor heterogeneity presents a bottleneck against drug testing. Flexibility in a preclinical platform is also desirable to support assessment of different endpoints. We established the model system, OHC-NB1, from a bone marrow metastasis from a patient diagnosed with MYCN-amplified neuroblastoma and performed whole-exome sequencing on the source metastasis and the different models and passages during model development (monolayer cell line, 3D spheroid culture and subcutaneous xenograft tumors propagated in mice). OHC-NB1 harbors a MYCN amplification in double minutes, 1p deletion, 17q gain and diploid karyotype, which persisted in all models. A total of 80-540 single-nucleotide variants (SNVs) was detected in each sample, and comparisons between the source metastasis and models identified 34 of 80 somatic SNVs to be propagated in the models. Clonal reconstruction using the combined copy number and SNV data revealed marked clonal heterogeneity in the originating metastasis, with 4 clones being reflected in the model systems. The set of OHC-NB1 models represents 43% of somatic SNVs and 23% of the cellularity in the originating metastasis with varying clonal compositions, indicating that heterogeneity is partially preserved in our model system

    Temporal changes in the epidemiology, management, and outcome from acute respiratory distress syndrome in European intensive care units: a comparison of two large cohorts

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    Background: Mortality rates for patients with ARDS remain high. We assessed temporal changes in the epidemiology and management of ARDS patients requiring invasive mechanical ventilation in European ICUs. We also investigated the association between ventilatory settings and outcome in these patients. Methods: This was a post hoc analysis of two cohorts of adult ICU patients admitted between May 1–15, 2002 (SOAP study, n = 3147), and May 8–18, 2012 (ICON audit, n = 4601 admitted to ICUs in the same 24 countries as the SOAP study). ARDS was defined retrospectively using the Berlin definitions. Values of tidal volume, PEEP, plateau pressure, and FiO2 corresponding to the most abnormal value of arterial PO2 were recorded prospectively every 24 h. In both studies, patients were followed for outcome until death, hospital discharge or for 60 days. Results: The frequency of ARDS requiring mechanical ventilation during the ICU stay was similar in SOAP and ICON (327[10.4%] vs. 494[10.7%], p = 0.793). The diagnosis of ARDS was established at a median of 3 (IQ: 1–7) days after admission in SOAP and 2 (1–6) days in ICON. Within 24 h of diagnosis, ARDS was mild in 244 (29.7%), moderate in 388 (47.3%), and severe in 189 (23.0%) patients. In patients with ARDS, tidal volumes were lower in the later (ICON) than in the earlier (SOAP) cohort. Plateau and driving pressures were also lower in ICON than in SOAP. ICU (134[41.1%] vs 179[36.9%]) and hospital (151[46.2%] vs 212[44.4%]) mortality rates in patients with ARDS were similar in SOAP and ICON. High plateau pressure (> 29 cmH2O) and driving pressure (> 14 cmH2O) on the first day of mechanical ventilation but not tidal volume (> 8 ml/kg predicted body weight [PBW]) were independently associated with a higher risk of in-hospital death. Conclusion: The frequency of and outcome from ARDS remained relatively stable between 2002 and 2012. Plateau pressure > 29 cmH2O and driving pressure > 14 cmH2O on the first day of mechanical ventilation but not tidal volume > 8 ml/kg PBW were independently associated with a higher risk of death. These data highlight the continued burden of ARDS and provide hypothesis-generating data for the design of future studies

    The clinical relevance of oliguria in the critically ill patient : Analysis of a large observational database

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    Funding Information: Marc Leone reports receiving consulting fees from Amomed and Aguettant; lecture fees from MSD, Pfizer, Octapharma, 3 M, Aspen, Orion; travel support from LFB; and grant support from PHRC IR and his institution. JLV is the Editor-in-Chief of Critical Care. The other authors declare that they have no relevant financial interests. Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Urine output is widely used as one of the criteria for the diagnosis and staging of acute renal failure, but few studies have specifically assessed the role of oliguria as a marker of acute renal failure or outcomes in general intensive care unit (ICU) patients. Using a large multinational database, we therefore evaluated the occurrence of oliguria (defined as a urine output 16 years) patients in the ICON audit who had a urine output measurement on the day of admission were included. To investigate the association between oliguria and mortality, we used a multilevel analysis. Results: Of the 8292 patients included, 2050 (24.7%) were oliguric during the first 24 h of admission. Patients with oliguria on admission who had at least one additional 24-h urine output recorded during their ICU stay (n = 1349) were divided into three groups: transient - oliguria resolved within 48 h after the admission day (n = 390 [28.9%]), prolonged - oliguria resolved > 48 h after the admission day (n = 141 [10.5%]), and permanent - oliguria persisting for the whole ICU stay or again present at the end of the ICU stay (n = 818 [60.6%]). ICU and hospital mortality rates were higher in patients with oliguria than in those without, except for patients with transient oliguria who had significantly lower mortality rates than non-oliguric patients. In multilevel analysis, the need for RRT was associated with a significantly higher risk of death (OR = 1.51 [95% CI 1.19-1.91], p = 0.001), but the presence of oliguria on admission was not (OR = 1.14 [95% CI 0.97-1.34], p = 0.103). Conclusions: Oliguria is common in ICU patients and may have a relatively benign nature if only transient. The duration of oliguria and need for RRT are associated with worse outcome.publishersversionPeer reviewe

    Accounting for long-term directional trends on year-to-year synchrony in species fluctuations

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    What determines the stability of communities under environmental fluctuations remains one of the most debated questions in ecology. Scholars generally agree that the similarity in year-to-year fluctuations between species is an important determinant of this stability. Concordant fluctuations in species abundances through time (synchrony) decrease stability while discordance in fluctuations (anti-synchrony) should stabilize communities. Researchers have interpreted the community-wide degree of synchrony in temporal fluctuations as the outcome of different processes. However, existing synchrony measures depend not only on year-to-year species fluctuations, but also on long-term directional trends in species composition, for example due to land-use or climate change. The neglected effect of directional trends in species composition could cause an apparent increase in synchrony that is not due to year-to-year fluctuations, as species that simultaneously increase (or decrease) in abundance over time will appear correlated, even if they fluctuate discordantly from year to year. The opposite pattern is also conceivable, where different species show contrasting trends in their abundances, thus overestimating year-to-year anti-synchrony. Therefore, trends in species composition may limit our understanding of potential ecological mechanisms behind synchrony between species. We propose two easily implementable solutions, with corresponding R functions, for testing and accounting for the effect of trends in species composition on overall synchrony. The first approach is based on computing synchrony over the residuals of fitted species trends over time. The second approach, applicable to already existing indices, is based on three-terms local variance, i.e. computing variance over three-years-long, movable windows. We demonstrate these methods using simulations and data from real plant communities under long-term directional changes, discussing when one approach can be preferred. We show that accounting for long-term temporal trends is necessary and that separation of effect of trends and year-to-year fluctuation provides a better understanding of ecological mechanisms and their connections with ecological theory.This research was supported by the Czech Science Foundation (GAČR 16-15012S and GAČR 17-05506S
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