Background
During thyroid surgery, preservation of parathyroid gland (PG) feeding vessels is often impossible. The aim of the Fluogreen study was to determine the feasibility of using indocyanine ...green (ICG)-based intraoperative mapping angiograms of the PG (iMAP) to improve vascular preservation.
Study design
This prospective study enrolled all patients undergoing thyroid lobectomy or total thyroidectomy at the Hôpital Européen Marseille between September and December 2018. After exploring the thyroid lobe by autofluorescence to locate the PGs, ICG solution was injected intravenously to locate the PG feeding vessels and guide dissection. A second ICG injection was administered at the end of the lobectomy to assess perfusion of the PGs. The primary outcome was the quality of the angiogram, scaled as iMAP 0 (not informative), iMAP 1 (general vascular pattern visible but no clear vascular pedicle flowing into the PG), or iMAP 2 (clear vascular pedicle flowing into the PG). The secondary outcome was the PG perfusion score at the end of surgery, scaled from ICG 0 (no perfusion) to ICG 2 (intense uptake).
Results
A total of 47 adult patients were analyzed, including 34 total thyroidectomies and 13 lobectomies. ICG angiography assessed 76 PGs, which were scored as iMAP 2 in 24 cases (31.6%), iMAP 1 in 46 (60.5%) and iMAP 0 in six (7.9%). At the end of dissection, the ICG perfusion score was significantly better for the PGs with informative angiography (iMAP 1 or 2), than for the PGs with uninformative angiography (iMAP 0), or the PGs not evaluated by vascular angiography (
p
< 0.05).
Conclusion
iMAP is feasible and provides direct vascular information in one
-
third of the cases. Further improvements to this technology are necessary, and the influence of this technique on patient outcomes during thyroidectomy will need to be further evaluated.
Objective
Recent studies have highlighted that systemic lupus erythematosus (SLE) is characterized by different types of symptoms: type 1 symptoms related to inflammation and disease activity and ...type 2 symptoms such as fatigue, anxiety-depression, and pain. Our aim was to investigate the relation between type 1 and type 2 symptoms, and their impact on health-related quality of life (HRQoL) in SLE.
Methods
A literature review was conducted about disease activity/type1 and type 2 symptoms. Articles in English published after 2000 were located on Medline via Pubmed. The articles chosen evaluated at least one type 2 symptom or HRQoL using a validated scale in adult patients.
Results
Overall, 182 articles were analyzed and 115 were retained including 21 randomized, controlled trials and corresponding to 36 831 patients. We found that in SLE, inflammatory activity/type 1 symptoms were mostly uncorrelated with type 2 symptoms and/or HRQoL. Several studies even showing an inverse relationship. No or weak correlation was observed in 85, 3% (92, 6%), 76, 7% (74, 4%) and 37, 5% (73, 1%) of studies (patients) for fatigue, anxiety-depression, and pain, respectively. For HRQoL, no or weak correlation was observed in 77, 5% of studies (88% of patients).
Conclusion
Type 2 symptoms are poorly correlated with inflammatory activity/type 1 symptoms in SLE. Possible explanations and implications for clinical care and therapeutic evaluation are discussed.
Objective
Lupus is a chronic complex autoimmune disease. Non-adherence to treatment can affect patient outcomes. Considering patients’ preferences into medical decisions may increase acceptance to ...their medication. The PREFERLUP study used unsupervised clustering analysis to identify profiles of patients with similar treatment preferences in an online community of French lupus patients.
Methods
An online survey was conducted in adult lupus patients from the Carenity community between August 2018 and April 2019. Multiple Correspondence Analysis (MCA) was used with three unsupervised clustering methods (hierarchical, kmeans and partitioning around medoids). Several indicators (measure of connectivity, Dunn index and Silhouette width) were used to select the best clustering algorithm and choose the number of clusters.
Results
The 268 participants were mostly female (96%), with a mean age of 44.3 years 83% fulfilled the American College of Rheumatology (ACR) self-reported diagnostic criteria for systemic lupus erythematosus. Overall, the preferred route of administration was oral (62%) and the most important feature of an ideal drug was a low risk of side-effects (32%). Hierarchical clustering identified three clusters. Cluster 1 (59%) comprised patients with few comorbidities and a poor ability to identify oncoming flares; 84% of these patients desired oral treatments with limited side-effects. Cluster 2 (13%) comprised younger patients, who had already participated in a clinical trial, were willing to use implants and valued the compatibility of treatments with pregnancy. Cluster 3 (28%) comprised patients with a longer lupus duration, poorer control of the disease and more comorbidities; these patients mainly valued implants and injections and expected a reduction of corticosteroid intake.
Conclusions
Different profiles of lupus patients were identified according to their drug preferences. These clusters could help physicians tailor their therapeutic proposals to take into account individual patient preferences, which could have a positive impact on treatment acceptance and then adherence. The study highlights the value of data acquired directly from patient communities.
To evaluate the impact of local therapeutic recommendation updates made by the COVID multidisciplinary consultation meeting (RCP) at the Hôpital Européen Marseille (HEM) through the description of ...the drug prescriptions for COVID-19 during the first two waves of the epidemic.
This retrospective observational study analysed data from the hospital's pharmaceutical file. We included all patients hospitalized for COVID-19 between February 1, 2020 and January 21, 2021 and extracted specific anti-COVID-19 therapies (ST) from computerized patient record, as well as patients' demographic characteristics, comorbidities and outcome. The evolution of ST prescriptions during the study period was described and put into perspective with the updates of local recommendations made during the first (V1, from 2/24/2020 to 7/27/2020), and second (V2, from 7/28/2020 to 1/21/2021) epidemic waves.
A total of 607 COVID-19 hospitalized patients, 197 during V1 and 410 during V2. Their mean age was 65 years-old, and they presented frequent comorbidities. In total, 93% of hospitalized patients received ST: anticoagulants (90%), glucocorticoids (39%) mainly during V2 (49% vs 17%, P<0.001), and azithromycin (30%) mainly during V1 (71% vs 10%, P<0.001). Lopinavir/ritonavir and hydroxychloroquine were prescribed to 17 and 7 inpatients, respectively, and only during V1. Remdesivir was never administered. A total of 22 inpatients were enrolled into clinical trials.
The effective dissemination of evidence-based and concerted recommendations seems to have allowed an optimized management of COVID-19 drug therapies in the context of this emerging infection with rapidly evolving therapeutic questions.
Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for ...selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection.
In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene.
Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module.
Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.
As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the ...development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/ .
Objective
Life habits (LH) encompass an individual’s engagement in daily activities such as nutrition, fitness, personal care, communication, housing, and mobility, along with his/her social role ...(responsibility, interpersonal relationships, community life, education, employment, and recreation). This qualitative study explores the nature and context of LH restrictions in systemic lupus erythematosus (SLE) individuals across their SLE journey.
Methods
Narrative interviews were conducted with adult SLE patients. Interview transcripts were subjected to a thematic content analysis, using the Disability Creation Process model as a framework.
Results
Forty participants were interviewed. Three major themes were highlighted: (1) Temporality, capabilities, and environmental contexts: although all participants experienced LH restrictions at some point, the expression of these limitations depended on the individual’s and SLE disease characteristics as well as on temporal (time of life and lupus course) and environmental (material, social, and societal) contexts. (2) Identity issues, illness stigma, and (fear of) discriminations: LH were discussed through the lens of participants’ social roles and identities. While illness stigma can influence social relations, it is also expressed at a societal level. (3) Masking and minimizing strategies: due to illness stigma and fear of discrimination, participants developed strategies to manage their relationships, including masking and minimization. Their use was both advantageous and disadvantageous regarding LH.
Conclusions
For individuals with SLE, LH restrictions must be considered as an ongoing process that takes place within specific contexts. Our findings provide many opportunities for interventions that can benefit patients and their families, as well as healthcare providers.
An increasing number of studies have provided strong evidence that gut microbiota interact with the immune system and stimulate various mechanisms involved in the pathogenesis of auto-immune diseases ...such as Systemic Lupus Erythematosus (SLE). Indeed, gut microbiota could be a source of diagnostic and prognostic biomarkers but also hold the promise to discover novel therapeutic strategies. Thus far, specific SLE microbial signatures have not yet been clearly identified with alteration patterns that may vary between human and animal studies. In this study, a comparative analysis of a clinically well-characterized cohort of adult patients with SLE showed reduced biodiversity, a lower
Firmicutes/Bacteroidetes
(
F/B
) ratio, and six differentially abundant taxa compared with healthy controls. An unsupervised clustering of patients with SLE patients identified a subgroup of patients with a stronger alteration of their gut microbiota. Interestingly, this clustering was strongly correlated with the disease activity assessed with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score (
p = 0.03
, odd ratio = 15) and the identification of specific alterations involving the
F/B
ratio and some different taxa. Then, the gut microbiota of pristane-induced lupus and control mice were analyzed for comparison with our human data. Among the six differentially abundant taxa of the human disease signature, five were common with our murine model. Finally, an exhaustive cross-species comparison between our data and previous human and murine SLE studies revealed a core-set of gut microbiome species that might constitute biomarker panels relevant for future validation studies.
Aortitis is a classic manifestation of large vessel vasculitis. Antiphospholipid syndrome (APS), sometimes known as Hughes syndrome, is an acquired autoimmune disorder that manifests clinically as ...recurrent venous or arterial thrombosis. Patients with APS may also suffer from various underlying diseases, most frequently systemic lupus erythematosus (SLE). Catastrophic antiphospholipid syndrome (CAPS) is a rare but serious complication of APS characterized by failure of several organs due to diffuse microcirculatory thrombi. Its main manifestations involve the kidneys, lungs, heart and central nervous system, and require early diagnosis and rapid therapeutic management. While APS can affect virtually any blood vessel, aortitis is not a known symptom of APS. We report the case of a 36-year-old patient with APS and SLE who presented with CAPS during pregnancy, with no concomitant SLE flare. The first manifestation of CAPS was aortitis, preceding renal, cardiac and haematological manifestations. The outcome was favourable with combined treatment including corticosteroids, anticoagulants, plasma exchange and rituximab. We then carried out a literature search for papers describing the presence of aortitis in APS and/or SLE. In the cases of aortic involvement identified in the literature, including another case of CAPS, the occurrence of aortitis in SLE, often associated with the presence of antiphospholipid antibodies/APS, suggests that aortitis should be considered as an under-recognized manifestation and potential non-criterion feature of APS.
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