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BACKGROUND: Severe lung disease frequently presents with both refractory hypoxemia and right ventricular (RV) failure. OxyRVAD is an extra-corporeal membrane oxygenation (ECMO) configuration of RV bypass that also supplements gas exchange. This systematic review summarizes the available literature regarding the use of OxyRVAD in the setting of severe lung disease with associated RV failure. METHODS: PubMed, Embase, and Google Scholar were queried on September 27th, 2023, for articles describing the use of an OxyRVAD configuration. The main outcome of interest was survival to ICU discharge. Data on the duration of OxyRVAD support and device-related complications were also recorded. RESULTS: Of 475 identified articles, 33 were retained for analysis. Twenty-one articles were case reports and 12 were case series representing a total of 103 patients. No article provided a comparison group. Most patients (76.4%) were transitioned to OxyRVAD from another type of mechanical support. OxyRVAD was used as a bridge to transplant or curative surgery in 37.4% and as a bridge to recovery or decision in 62.6%. Thirty-one patients (30.1%) were managed with the dedicated single-access dual-lumen ProtekDuo cannula. Median time on OxyRVAD was twelve days (IQR 8-23) and survival to ICU discharge was 63.9%. Device-related complications were infrequently reported. CONCLUSION: OxyRVAD support is a promising alternative for RV support when gas exchange is compromised with good ICU survival in selected cases. Comparative analyses in patients with RV failure with and without severe lung disease are needed.
ABSTRACT
Background: Computational analysis of routine electroencephalogram (rEEG) could improve the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic performances of computed biomarkers for epilepsy in individuals undergoing rEEG. Methods: We searched MEDLINE, EMBASE, EBM reviews, IEEE Explore and the grey literature for studies published between January 1961 and December 2022. We included studies reporting a computational method to diagnose epilepsy based on rEEG without relying on the identification of interictal epileptiform discharges or seizures. Diagnosis of epilepsy as per a treating physician was the reference standard. We assessed the risk of bias using an adapted QUADAS-2 tool. Results: We screened 10 166 studies, and 37 were included. The sample size ranged from 8 to 192 (mean=54). The computed biomarkers were based on linear (43%), non-linear (27%), connectivity (38%), and convolutional neural networks (10%) models. The risk of bias was high or unclear in all studies, more commonly from spectrum effect and data leakage. Diagnostic accuracy ranged between 64% and 100%. We observed high methodological heterogeneity, preventing pooling of accuracy measures. Conclusion: The current literature provides insufficient evidence to reliably assess the diagnostic yield of computational analysis of rEEG. Significance: We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.
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BACKGROUND: Older adults are underrepresented in research. Heterogeneity of research processes in this population, specifically in long-term care (LTC) and geriatric acute care (GAC), is not well described and may impede the design, planning, and conduct of research. In this study, we identified, quantified, and mapped stakeholders, research stages, and transversal themes of research processes, to develop a mapping framework to improve research capacity by better characterizing this heterogeneity. METHODS: Multicomponent mixed methods study. An environmental scan was used to initiate a preliminary framework. We conducted a systematic literature search on processes, barriers, and methods for clinical research in GAC and LTC to extract and update stakeholders, research stages, and themes. Importance and interactions of elements were synthesized via heatmaps by number of articles, mentions, and content intersections. RESULTS: For our initial framework and environmental scan, we surveyed 24 stakeholders. Of 9277 records, 68 articles were included in our systematic review and allowed us to identify 12 stakeholders, 13 research stages, 17 transversal themes (either barriers, facilitators, general themes, or recommendations), and 1868 intersections. Differences in relative importance between LTC and GAC emerged for stakeholders (staff, managers vs. caregivers, ethics committees), and for research stages (funding, facility recruitment vs. ethics, individual recruitment). Crucial themes according to specific stakeholders were collaboration for the research team; communication, trust, and human resources for managers; heterogeneity for patients and residents. A heatmap framework synthesizing vital stakeholders and themes per research stage was generated. CONCLUSIONS: We identified and quantified the interactions between stakeholders, stages, and themes to characterize heterogeneity in LTC and GAC research. Our framework may serve as a blueprint to co-construct and improve each stage of the research process.
Subject(s)
Geriatrics , Long-Term Care , Aged , HumansABSTRACT
INTRODUCTION: The diagnosis of epilepsy frequently relies on the visual interpretation of the electroencephalogram (EEG) by a neurologist. The hallmark of epilepsy on EEG is the interictal epileptiform discharge (IED). This marker lacks sensitivity: it is only captured in a small percentage of 30 min routine EEGs in patients with epilepsy. In the past three decades, there has been growing interest in the use of computational methods to analyse the EEG without relying on the detection of IEDs, but none have made it to the clinical practice. We aim to review the diagnostic accuracy of quantitative methods applied to ambulatory EEG analysis to guide the diagnosis and management of epilepsy. METHODS AND ANALYSIS: The protocol complies with the recommendations for systematic reviews of diagnostic test accuracy by Cochrane. We will search MEDLINE, EMBASE, EBM reviews, IEEE Explore along with grey literature for articles, conference papers and conference abstracts published after 1961. We will include observational studies that present a computational method to analyse the EEG for the diagnosis of epilepsy in adults or children without relying on the identification of IEDs or seizures. The reference standard is the diagnosis of epilepsy by a physician. We will report the estimated pooled sensitivity and specificity, and receiver operating characteristic area under the curve (ROC AUC) for each marker. If possible, we will perform a meta-analysis of the sensitivity and specificity and ROC AUC for each individual marker. We will assess the risk of bias using an adapted QUADAS-2 tool. We will also describe the algorithms used for signal processing, feature extraction and predictive modelling, and comment on the reproducibility of the different studies. ETHICS AND DISSEMINATION: Ethical approval was not required. Findings will be disseminated through peer-reviewed publication and presented at conferences related to this field. PROSPERO REGISTRATION NUMBER: CRD42022292261.
