Three-Dimensional Automated, Machine-Learning-Based Left Heart Chamber Metrics: Associations with Prevalent Vascular Risk Factors and Cardiovascular Diseases

Background. Three-dimensional transthoracic echocardiography (3DE) powered by artificial intelligence provides accurate left chamber quantification in good accordance with cardiac magnetic resonance and has the potential to revolutionize our clinical practice. Aims. To evaluate the association and the independent value of dynamic heart model (DHM)-derived left atrial (LA) and left ventricular (LV) metrics with prevalent vascular risk factors (VRFs) and cardiovascular diseases (CVDs) in a large, unselected population. Materials and Methods. We estimated the association of DHM metrics with VRFs (hypertension, diabetes) and CVDs (atrial fibrillation, stroke, ischemic heart disease, cardiomyopathies, >moderate valvular heart disease/prosthesis), stratified by prevalent disease status: participants without VRFs or CVDs (healthy), with at least one VRFs but without CVDs, and with at least one CVDs. Results. We retrospectively included 1069 subjects (median age 62 [IQR 49–74]; 50.6% women). When comparing VRFs with the healthy, significant difference in maximum and minimum indexed atrial volume (LAVi max and LAVi min), left atrial ejection fraction (LAEF), left ventricular mass/left ventricular end-diastolic volume ratio, and left ventricular global function index (LVGFI) were recorded (p < 0.05). In the adjusted logistic regression, LAVi min, LAEF, LV ejection fraction, and LVGFI showed the most robust association (OR 3.03 [95% CI 2.48–3.70], 0.45 [95% CI 0.39–0.51], 0.28 [95% CI 0.22–0.35], and 0.22 [95% CI 0.16–0.28], respectively, with CVDs. Conclusions. The present data suggested that novel 3DE left heart chamber metrics by DHM such as LAEF, LAVi min, and LVGFI can refine our echocardiographic disease discrimination capacity

Red Blood Cell Exchange as a Valid Therapeutic Approach for Pregnancy Management in Sickle Cell Disease: Three Explicative Cases and Systematic Review of Literature

Pregnancy in women with sickle cell disease (SCD) is a high-risk situation, especially during the third trimester of gestation and in the post-partum period, due to chronic hypoxia and vaso-occlusive phenomena occurring in the maternal–fetal microcirculation: as a result, unfavorable outcomes, such as intra-uterine growth restriction, prematurity or fetal loss are more frequent in SCD pregnancies. Therefore, there is a consensus on the need for a strict and multidisciplinary follow-up within specialized structures. Transfusion support remains the mainstay of treatment of SCD pregnancies, whereas more targeted modalities are still controversial: the benefit of prophylactic management, either by simple transfusions or by automated red blood cell exchange (aRBCX), is not unanimously recognized. We illustrate the cases of three SCD pregnant patients who underwent aRBCX procedures at our institution in different clinical scenarios. Moreover, we carried out a careful literature revision to investigate the management of pregnancy in SCD, with a particular focus on the viability of aRBCX. Our experience and the current literature support the use of aRBCX in pregnancy as a feasible and safe procedure, provided that specialized equipment and an experienced apheresis team is available. However, further research in this high-risk population, with appropriately powered prospective trials, is desirable to refine the indications and timing of aRBCX and to confirm the advantages of this approach on other transfusion modalities

Quantification of Myocardial Contraction Fraction with Three-Dimensional Automated, Machine-Learning-Based Left-Heart-Chamber Metrics: Diagnostic Utility in Hypertrophic Phenotypes and Normal Ejection Fraction

Aims: The differentiation of left ventricular (LV) hypertrophic phenotypes is challenging in patients with normal ejection fraction (EF). The myocardial contraction fraction (MCF) is a simple dimensionless index useful for specifically identifying cardiac amyloidosis (CA) and hypertrophic cardiomyopathy (HCM) when calculated by cardiac magnetic resonance. The purpose of this study was to evaluate the value of MCF measured by three-dimensional automated, machine-learning-based LV chamber metrics (dynamic heart model [DHM]) for the discrimination of different forms of hypertrophic phenotypes. Methods and Results: We analyzed the DHM LV metrics of patients with CA (n = 10), hypertrophic cardiomyopathy (HCM, n = 36), isolated hypertension (IH, n = 87), and 54 healthy controls. MCF was calculated by dividing LV stroke volume by LV myocardial volume. Compared with controls (median 61.95%, interquartile range 55.43–67.79%), mean values for MCF were significantly reduced in HCM—48.55% (43.46–54.86% p < 0.001)—and CA—40.92% (36.68–46.84% p < 0.002)—but not in IH—59.35% (53.22–64.93% p < 0.7). MCF showed a weak correlation with EF in the overall cohort (R2 = 0.136) and the four study subgroups (healthy adults, R2 = 0.039 IH, R2 = 0.089; HCM, R2 = 0.225; CA, R2 = 0.102). ROC analyses showed that MCF could differentiate between healthy adults and HCM (sensitivity 75.9%, specificity 77.8%, AUC 0.814) and between healthy adults and CA (sensitivity 87.0%, specificity 100%, AUC 0.959). The best cut-off values were 55.3% and 52.8%. Conclusions: The easily derived quantification of MCF by DHM can refine our echocardiographic discrimination capacity in patients with hypertrophic phenotype and normal EF. It should be added to the diagnostic workup of these patients

ESPNIC clinical practice guidelines: intravenous maintenance fluid therapy in acute and critically ill children- a systematic review and meta-analysis

PURPOSE Intravenous maintenance fluid therapy (IV-MFT) prescribing in acute and critically ill children is very variable among pediatric health care professionals. In order to provide up to date IV-MFT guidelines, the European Society of Pediatric and Neonatal Intensive Care (ESPNIC) undertook a systematic review to answer the following five main questions about IV-MFT: (i) the indications for use (ii) the role of isotonic fluid (iii) the role of balanced solutions (iv) IV fluid composition (calcium, magnesium, potassium, glucose and micronutrients) and v) and the optimal amount of fluid. METHODS A multidisciplinary expert group within ESPNIC conducted this systematic review using the Scottish Intercollegiate Guidelines Network (SIGN) grading method. Five databases were searched for studies that answered these questions, in acute and critically children (from 37 weeks gestational age to 18 years), published until November 2020. The quality of evidence and risk of bias were assessed, and meta-analyses were undertaken when appropriate. A series of recommendations was derived and voted on by the expert group to achieve consensus through two voting rounds. RESULTS 56 papers met the inclusion criteria, and 16 recommendations were produced. Outcome reporting was inconsistent among studies. Recommendations generated were based on a heterogeneous level of evidence, but consensus within the expert group was high. "Strong consensus" was reached for 11/16 (69%) and "consensus" for 5/16 (31%) of the recommendations. CONCLUSIONS Key recommendations are to use isotonic balanced solutions providing glucose to restrict IV-MFT infusion volumes in most hospitalized children and to regularly monitor plasma electrolyte levels, serum glucose and fluid balance

Allelic HLA Matching and Pair Origin Are Favorable Prognostic Factors for Unrelated Hematopoietic Stem Cell Transplantation in Neoplastic Hematologic Diseases: An Italian Analysis by the Gruppo Italiano Trapianto di Cellule Staminali e Terapie Cellulari, Italian Bone Marrow Donor Registry, and Associazione Italiana di Immunogenetica e Biologia dei Trapianti

HLA molecules are important for immunoreactivity in allogeneic hematopoietic stem cell transplantation (HSCT). The Gruppo Italiano Trapianto di Cellule Staminali e Terapie Cellulari, Italian Bone Marrow Donor Registry, and Associazione Italiana di Immunogenetica e Biologia dei Trapianti promoted a retrospective observational study to evaluate HLA matching and the impact of allelic HLA mismatching and non-HLA factors on unrelated Italian HSCT outcomes. From 2012 to 2015, 1788 patients were enrolled in the study. The average donor age was 29 years and the average recipient age was 49 years. As a conditioning regimen, 71% of the patients received myeloablative conditioning. For GVHD prophylaxis, 76% received either antithymocyte or anti-T lymphocyte globulin, cyclosporine A, and methotrexate. Peripheral blood was the stem cell source in 80%. The median duration of follow-up was 53 months. Regarding HLA matching, 50% of donor-recipient pairs were 10/10 matched, 38% had 1 mismatch, and 12% had 2 or more mismatches. A total of 302 pairs shared Italian origin. Four-year overall survival (OS), progression-free survival, GVHD-free relapse-free survival, and relapse rates were 49%, 40%, 22%, and 34%, respectively. The 4-year NRM was 27%, and the 100-day cumulative incidence of grade 65II acute GVHD (aGVHD) was 26%. In multivariate analysis, 9/10 and 648/10 HLA allele-matched pairs were associated with worse OS (P = .04 and .007, respectively), NRM (P = .007 and P < .0001, respectively), and grade III-IV aGVHD (P = .0001 and .01, respectively). Moreover, the incidences of grade II-IV aGVHD (P = .001) and chronic GVHD (P = .002) were significantly lower in Italian pairs. In conclusion, 10/10 HLA matching is a favorable prognostic factor for unrelated HSCT outcome in the Italian population. Moreover, the presence of 2 HLA-mismatched loci was associated with a higher NRM (P < .0001) and grade II-IV aGVHD (P = .006) and a poorer OS (P = .001) compared with 1 HLA-mismatched locus in early or intermediate disease phases. Finally, we found that Italian donor and recipient origin is a favorable prognostic factor for GVHD occurrence

Busulfan or Treosulfan Conditioning Platform for Allogeneic Stem Cell Transplantation in Patients Aged >60 y with Acute Myeloid Leukemia/Myelodysplastic Syndrome: A Subanalysis of the GITMO AlloEld Study

Background. The conditioning regimens with different alkylators at different doses can influence the outcome of allogeneic stem cell transplantation (SCT), but conclusive data are missing. Methods. With the aim to analyze real-life allogeneic SCTs performed in Italy between 2006 and 2017 in elderly patients (aged >60 y) with acute myeloid leukemia or myelodysplastic syndrome, we collected 780 first transplants data. For analysis purposes, patients were grouped according to the type of alkylator included in the conditioning (busulfan [BU]-based; n = 618; 79%; treosulfan [TREO]-based; n=162; 21%). Results. No significant differences were observed in nonrelapse mortality, cumulative incidence of relapse, and overall survival, although in the TREO-based group, we observed a greater proportion of elderly patients (P < 0.001); more active diseases at the time of SCT (P < 0.001); a higher prevalence of patients with either hematopoietic cell transplantation-comorbidity index ≥3 (P < 0.001) or a good Karnofsky performance status (P = 0.025); increased use of peripheral blood stem cells as graft sources (P < 0.001); and greater use of reduced intensity conditioning regimens (P = 0.013) and of haploidentical donors (P < 0.001). Moreover, the 2-y cumulative incidence of relapse with myeloablative doses of BU was significantly lower than that registered with reduced intensity conditioning (21% versus 31%; P = 0.0003). This was not observed in the TREO-based group. Conclusions. Despite a higher number of risk factors in the TREO group, no significant differences were observed in nonrelapse mortality, cumulative incidence of relapse, and overall survival according to the type of alkylator, suggesting that TREO has no advantage over BU in terms of efficacy and toxicity in acute myeloid leukemia and myelodysplastic syndrome

Solid Organ Transplantation During COVID-19 Pandemic: An International Web-based Survey on Resources’ Allocation

Background. Solid organ transplants (SOTs) are life-saving interventions, recently challenged by coronavirus disease 2019 (COVID-19). SOTs require a multistep process, which can be affected by COVID-19 at several phases. Methods. SOT-specialists, COVID-19-specialists, and medical ethicists designed an international survey according to CHERRIES guidelines. Personal opinions about continuing SOTs, safe managing of donors and recipients, as well as equity of resources' allocation were investigated. The survey was sent by e-mail. Multiple approaches were used (corresponding authors from Scopus, websites of scientific societies, COVID-19 webinars). After the descriptive analysis, univariate and multivariate ordinal regression analysis was performed. Results. There were 1819 complete answers from 71 countries. The response rate was 49%. Data were stratified according to region, macrospecialty, and organ of interest. Answers were analyzed using univariate- multivariate ordinal regression analysis and thematic analysis. Overall, 20% of the responders thought SOTs should not stop (continue transplant without restriction); over 70% suggested SOTs should selectively stop, and almost 10% indicated they should completely stop. Furthermore, 82% agreed to shift resources from transplant to COVID-19 temporarily. Briefly, main reason for not stopping was that if the transplant will not proceed, the organ will be wasted. Focusing on SOT from living donors, 61% stated that activity should be restricted only to "urgent"cases. At the multivariate analysis, factors identified in favor of continuing transplant were Italy, ethicist, partially disagreeing on the equity question, a high number of COVID-19- related deaths on the day of the answer, a high IHDI country. Factors predicting to stop SOTs were Europe except-Italy, public university hospital, and strongly agreeing on the equity question. Conclusions. In conclusion, the majority of responders suggested that transplant activity should be continued through the implementation of isolation measures and the adoption of the COVID-19-free pathways. Differences between professional categories are less strong than supposed

The role of the mitochondria and the endoplasmic reticulum contact sites in the development of the immune responses

Abstract Mitochondria and endoplasmic reticulum (ER) contact sites (MERCs) are dynamic modules enriched in subset of lipids and specialized proteins that determine their structure and functions. The MERCs regulate lipid transfer, autophagosome formation, mitochondrial fission, Ca2+ homeostasis and apoptosis. Since these functions are essential for cell biology, it is therefore not surprising that MERCs also play a critical role in organ physiology among which the immune system stands by its critical host defense function. This defense system must discriminate and tolerate host cells and beneficial commensal microorganisms while eliminating pathogenic ones in order to preserve normal homeostasis. To meet this goal, the immune system has two lines of defense. First, the fast acting but unspecific innate immune system relies on anatomical physical barriers and subsets of hematopoietically derived cells expressing germline-encoded receptors called pattern recognition receptors (PRR) recognizing conserved motifs on the pathogens. Second, the slower but very specific adaptive immune response is added to complement innate immunity. Adaptive immunity relies on another set of specialized cells, the lymphocytes, harboring receptors requiring somatic recombination to be expressed. Both innate and adaptive immune cells must be activated to phagocytose and process pathogens, migrate, proliferate, release soluble factors and destroy infected cells. Some of these functions are strongly dependent on lipid transfer, autophagosome formation, mitochondrial fission, and Ca2+ flux; this indicates that MERCs could regulate immunity

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48&nbsp;h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48&nbsp;h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home