Giovanni Barisione

This is an update of a randomized study on antithymocyte globulin (ATG; Thymoglobulin) before transplantation in patients undergoing unmanipulated marrow transplantation from unrelated donors. The median follow-up for surviving patients is 5.7 years. At last follow-up, chronic graft-versus-host disease (GVHD) was scored in 60% of non-ATG and in 37% of ATG patients (P=.05), and extensive chronic GVHD was present in 41% and 15%, respectively (P=.01). Chronic lung dysfunction was diagnosed in 51% versus 19% of patients (P=.005). Forced vital capacity decreased significantly with time in non-ATG patients (P=.005), but not in patients who received ATG (P=.30). The proportion of patients with Karnofsky scores of >or=90% at 4 years was 57% versus 89% in non-ATG versus ATG patients (P=.03). The actuarial 6-year survival for all patients randomized was 31% versus 44% (non-ATG versus ATG; P=.80). The cumulative incidence of transplant-related mortality was 51% versus 41% (P=.70) and of relapse was 32% versus 40% (P=.90). For patients who survived 1 year, transplant-related mortality was 25% versus 3% (P=.03), and actuarial survival was 58% versus 85% (P=.09). In conclusion, the addition of ATG to cyclosporine/methotrexate provides significant protection against extensive chronic GVHD and chronic lung dysfunction, reduces late transplant mortality, and improves quality of life in patients undergoing unrelated donor transplantation.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. RESULTS: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most of which performed better than the pneumonia severity index. The cut-off values of the low-, medium- and high-risk probabilities were 0.21 and 0.80. The online calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram and online calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission.

We determined the dose-response curves to inhaled methacholine (MCh) in 16 asthmatic and 8 healthy subjects with prohibition of deep inhalations (DIs) and with 5 DIs taken after each MCh dose. Flow was measured on partial expiratory flow-volume curves at an absolute lung volume (plethysmographically determined) equal to 25% of control forced vital capacity (FVC). Airway inflammation was assessed in asthmatic subjects by analysis of induced sputum. Even when DIs were prohibited, the dose of MCh causing a 50% decrease in forced partial flow at 25% of control FVC (PD(50)MCh) was lower in asthmatic than in healthy subjects (P < 0.0001). In healthy but not in asthmatic subjects, repeated DIs significantly decreased the maximum response to MCh [from 90 +/- 4 to 62 +/- 8 (SD) % of control, P < 0.001], increased PD(50)MCh (P < 0.005), without affecting the dose causing 50% of maximal response. In asthmatic subjects, neither PD(50)MCh when DIs were prohibited nor changes in PD(50)MCh induced by DIs were significantly correlated with inflammatory cell numbers or percentages in sputum. We conclude that 1) even when DIs are prohibited, the responsiveness to MCh is greater in asthmatic than in healthy subjects; 2) repeated DIs reduce airway responsiveness in healthy but not in asthmatic subjects; and 3) neither airway hyperresponsiveness nor the inability of DIs to relax constricted airways in asthmatic subjects is related to the presence of inflammatory cells in the airways.

Inhaled β₂-adrenoceptor (β₂-AR) agonists are considered essential bronchodilator drugs in the treatment of bronchial asthma, both as symptoms-relievers and, in combination with inhaled corticosteroids, as disease-controllers. In this article, we first review the basic mechanisms by which the β₂-adrenergic system contributes to the control of airway smooth muscle tone. Then, we go on describing the structural characteristics of β₂-AR and the molecular basis of G-protein-coupled receptor signaling and mechanisms of its desensitization/ dysfunction. In particular, phosphorylation mediated by protein kinase A and β-adrenergic receptor kinase are examined in detail. Finally, we discuss the pivotal role of inhaled β₂-AR agonists in the treatment of asthma and the concerns about their safety that have been recently raised.

We evaluated the capacity to predict severe respiratory complications (SRCs) following upper abdominal surgery (UAS) by using the results of a respiratory questionnaire and preoperative pulmonary function tests. Lung volumes, flows and transfer factor of the lung for carbon monoxide (TL,CO,sb) were assessed in 361 consecutive adult patients (248 males and 113 females). SRCs were diagnosed 24 h after UAS by clinical examination and chest radiography. Univariate and stepwise multiple logistic regression analyses were performed to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of each single input variable, and to determine which indices best predicted outcome. These patients had a 1% mortality rate and 14% incidence of SRCs, with a male:female ratio of 0.86. The best predictors for SRCs by multiple analysis were: preoperative current hypersecretion of mucus (OR=133; p<0.0001); an increase in residual volume (RV) (OR=3.11; p=0.01); and, to a lesser extent, low percentage of predicted values both of forced expiratory volume in one second (FEV1 % pred) and TL,CO,sb. The algorithm thus obtained (logit theta) was extremely sensitive (84%), specific (99%), and accurate (95%) for preoperative prediction of SRCs. We have found that preoperative current hypersecretion of mucus and pulmonary hyperinflation, and to a lesser extent percentage predicted values both of forced expiratory volume in one second and transfer factor of the lung for carbon monoxide, have a significant predictive capacity for severe respiratory complications following upper abdominal surgery.