ABSTRACT
Routine clinical assays, such as conventional immunohistochemistry, often fail to resolve the regional heterogeneity of complex inflammatory skin conditions. We introduce MANTIS (Multiplex Annotated Tissue Imaging System), a flexible analytic pipeline compatible with routine practice, specifically designed for spatially resolved immune phenotyping of the skin in experimental or clinical samples. On the basis of phenotype attribution matrices coupled to α-shape algorithms, MANTIS projects a representative digital immune landscape while enabling automated detection of major inflammatory clusters and concomitant single-cell data quantification of biomarkers. We observed that severe pathological lesions from systemic lupus erythematosus, Kawasaki syndrome, or COVID-19-associated skin manifestations share common quantitative immune features while displaying a nonrandom distribution of cells with the formation of disease-specific dermal immune structures. Given its accuracy and flexibility, MANTIS is designed to solve the spatial organization of complex immune environments to better apprehend the pathophysiology of skin manifestations.
Subject(s)
COVID-19 , Lupus Erythematosus, Systemic , Humans , COVID-19/pathology , SkinABSTRACT
Two successive COVID-19 flares occurred in Switzerland in spring and autumn 2020. During these periods, therapeutic strategies have been constantly adapted based on emerging evidence. We aimed to describe these adaptations and evaluate their association with patient outcomes in a cohort of COVID-19 patients admitted to the hospital. Consecutive patients admitted to the Geneva Hospitals during two successive COVID-19 flares were included. Characteristics of patients admitted during these two periods were compared as well as therapeutic management including medications, respiratory support strategies and admission to the ICU and intermediate care unit (IMCU). A mutivariable model was computed to compare outcomes across the two successive waves adjusted for demographic characteristics, co-morbidities and severity at baseline. The main outcome was in-hospital mortality. Secondary outcomes included ICU admission, Intermediate care (IMCU) admission, and length of hospital stay. A total of 2'983 patients were included. Of these, 165 patients (16.3%, n = 1014) died during the first wave and 314 (16.0%, n = 1969) during the second (p = 0.819). The proportion of patients admitted to the ICU was lower in second wave compared to first (7.4 vs. 13.9%, p < 0.001) but their mortality was increased (33.6% vs. 25.5%, p < 0.001). Conversely, a greater proportion of patients was admitted to the IMCU in second wave compared to first (26.6% vs. 22.3%, p = 0.011). A third of patients received lopinavir (30.7%) or hydroxychloroquine (33.1%) during the first wave and none during second wave, while corticosteroids were mainly prescribed during second wave (58.1% vs. 9.1%, p < 0.001). In the multivariable analysis, a 25% reduction of mortality was observed during the second wave (HR 0.75; 95% confidence interval 0.59 to 0.96). Among deceased patients, 82.3% (78.2% during first wave and 84.4% during second wave) died without beeing admitted to the ICU. The proportion of patients with therapeutic limitations regarding ICU admission increased during the second wave (48.6% vs. 38.7%, p < 0.001). Adaptation of therapeutic strategies including corticosteroids therapy and higher admission to the IMCU to receive non-invasive respiratory support was associated with a reduction of hospital mortality in multivariable analysis, ICU admission and LOS during the second wave of COVID-19 despite an increased number of admitted patients. More patients had medical decisions restraining ICU admission during the second wave which may reflect better patient selection or implicit triaging.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/therapy , Tertiary Care Centers , Switzerland/epidemiology , Hospitalization , Length of Stay , Intensive Care Units , Hospital Mortality , Retrospective StudiesABSTRACT
BACKGROUND: The SARS-CoV-2 pandemic led to a steep increase in hospital and intensive care unit (ICU) admissions for acute respiratory failure worldwide. Early identification of patients at risk of clinical deterioration is crucial in terms of appropriate care delivery and resource allocation. We aimed to evaluate and compare the prognostic performance of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Uraemia, Respiratory Rate, Blood Pressure and Age ≥65 (CURB-65), Respiratory Rate and Oxygenation (ROX) index and Coronavirus Clinical Characterisation Consortium (4C) score to predict death and ICU admission among patients admitted to the hospital for acute COVID-19 infection. METHODS AND ANALYSIS: Consecutive adult patients admitted to the Geneva University Hospitals during two successive COVID-19 flares in spring and autumn 2020 were included. Discriminative performance of these prediction rules, obtained during the first 24 hours of hospital admission, were computed to predict death or ICU admission. We further exluded patients with therapeutic limitations and reported areas under the curve (AUCs) for 30-day mortality and ICU admission in sensitivity analyses. RESULTS: A total of 2122 patients were included. 216 patients (10.2%) required ICU admission and 303 (14.3%) died within 30 days post admission. 4C score had the best discriminatory performance to predict 30-day mortality (AUC 0.82, 95% CI 0.80 to 0.85), compared with SOFA (AUC 0.75, 95% CI 0.72 to 0.78), qSOFA (AUC 0.59, 95% CI 0.56 to 0.62), CURB-65 (AUC 0.75, 95% CI 0.72 to 0.78) and ROX index (AUC 0.68, 95% CI 0.65 to 0.72). ROX index had the greatest discriminatory performance (AUC 0.79, 95% CI 0.76 to 0.83) to predict ICU admission compared with 4C score (AUC 0.62, 95% CI 0.59 to 0.66), CURB-65 (AUC 0.60, 95% CI 0.56 to 0.64), SOFA (AUC 0.74, 95% CI 0.71 to 0.77) and qSOFA (AUC 0.59, 95% CI 0.55 to 0.62). CONCLUSION: Scores including age and/or comorbidities (4C and CURB-65) have the best discriminatory performance to predict mortality among inpatients with COVID-19, while scores including quantitative assessment of hypoxaemia (SOFA and ROX index) perform best to predict ICU admission. Exclusion of patients with therapeutic limitations improved the discriminatory performance of prognostic scores relying on age and/or comorbidities to predict ICU admission.
Subject(s)
COVID-19 , Organ Dysfunction Scores , Adult , COVID-19/diagnosis , COVID-19/therapy , Cohort Studies , Humans , Inpatients , Prognosis , ROC Curve , Retrospective Studies , SARS-CoV-2ABSTRACT
Introduction L’histologie standard et l’immunohistochimie sont les outils classiquement utilisés dans le diagnostic des dermatoses inflammatoires mais ne permettent pas une étude exhaustive du tissu. D’autres méthodes, telles que le séquençage d’ARN en cellule unique, fournissent des données quantitatives, mais nécessitent une dissociation tissulaire complète à l’origine d’une perte de l’information cruciale concernant l’organisation tissulaire. Matériel et méthodes Nous avons mis au point une technique d’imagerie analytique capable d’exploiter de multiples données de fluorescence, appelée « Unbiased cLustering of specTRal emissiON » (ULTRON). Elle permet de capturer de nombreux paramètres cellulaires, tout en préservant leur localisation spatiale à partir de coupes de peau. ULTRON permet d’acquérir jusqu’à 12 marqueurs simultanément au moyen d’un microscope confocal conventionnel. Dans un second temps, les données acquises sont traitées par des techniques poussées de modélisation informatique associées à du « machine-learning » et analysées de manière quantitative. Cette approche permet une identification automatique des sous-populations immunitaires et la conception d’une carte numérique du tissu, chaque sous-population étant associée à ses coordonnées spatiales précises sur l’image d’origine. Elle permet ainsi l’analyse exhaustive de la distribution, du phénotype, de la localisation des cellules immunitaires et de leur rapport entre elles et avec les éléments structuraux (résolution : 200nm). Trois panels d’anticorps spécifiques ont été validés. Résultats Le contexte sanitaire nous a conduit à observer avec intérêt l’apparition de cas de pseudo-engelures (et autres dermatoses) secondaires à l’infection par le SARS-CoV-2, chez des patients le plus souvent jeunes et très peu symptomatiques sur le plan respiratoire. Nous avons mené une étude multicentrique des biopsies cutanées réalisées en routine chez des patients ayant présenté des pseudo-engelures (n=15). Des patients contrôles, atteints de lupus engelures (n=5) ont également été étudiés. La technologie ULTRON a permis d’établir une signature immunitaire dans cette pathologie dermatologique émergente. Discussion Au-delà du développement d’une technique d’imagerie de pointe, ces travaux ont permis la caractérisation de populations immunitaires spécifiquement enrichies au cours des pseudo-engelures contemporaines de la COVID-19 et cela dans leur environnement tissulaire préservé.