8 research outputs found
Combined antiviral therapy as effective and feasible option in allogenic hematopoietic stem cell transplantation during SARS-COV-2 infection: a case report
Here we describe the case of a 51 years old Italian woman with acute lymphoblastic leukemia who underwent to hematopoietic stem cell transplantation (HSCT) during SARS-COV-2 infection. She presented a prolonged COVID-19 successfully treated with dual anti SARS-COV-2 antiviral plus monoclonal antibody therapy
Predicting respiratory failure in patients infected by SARS-CoV-2 by admission sex-specific biomarkers
Background: Several biomarkers have been identified to predict the outcome of COVID-19 severity, but few data are available regarding sex differences in their predictive role. Aim of this study was to identify sex-specific biomarkers of severity and progression of acute respiratory distress syndrome (ARDS) in COVID-19.
Methods: Plasma levels of sex hormones (testosterone and 17β-estradiol), sex-hormone dependent circulating molecules (ACE2 and Angiotensin1-7) and other known biomarkers for COVID-19 severity were measured in male and female COVID-19 patients at admission to hospital. The association of plasma biomarker levels with ARDS severity at admission and with the occurrence of respiratory deterioration during hospitalization was analysed in aggregated and sex disaggregated form.
Results: Our data show that some biomarkers could be predictive both for males and female patients and others only for one sex. Angiotensin1-7 plasma levels and neutrophil count predicted the outcome of ARDS only in females, whereas testosterone plasma levels and lymphocytes counts only in males.
Conclusions: Sex is a biological variable affecting the choice of the correct biomarker that might predict worsening of COVID-19 to severe respiratory failure. The definition of sex specific biomarkers can be useful to alert patients to be safely discharged versus those who need respiratory monitoring
Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes
Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening
Family burden between social stigma and loneliness. An exploratory investigation with Principal Caregivers (PCs) of patients with Serious Mental Illness (SMI) living in a disadvantage district in Italy
“Serious Mental Illness (SMI)” (Marquez et al. 2011) is an umbrella term covering multiple diagnoses (i. e. schizophrenia, but also bipolar and psychosis) that prompt, within the family, organizational efforts aimed at treatment and support which end up inevitably involving the whole family group (Kate et al., 2013; Nair et al., 2010). Many studies highlight the influence of the peculiarities of the social contexts in which they live. We present here a descriptive investigation about the needs of the caregivers of patients with severe mental illness (SMI) living in a working-class neighborhood of a Southern Italian city. Twelve caregivers were interviewed about their own emotional involvement and relationship with the patient by means of a semi-structured interview. Interviews were subjected to an categorial thematic analysis. The results reveal painful experiences of anguish and feelings of inadequacy stemming from care-giving, which gravely impact the caregivers' personal well-being and family relations. SMI is described as a worrisome and invasive cultural construct, because of its unfathomable. These emotional factors are further deteriorated by the cultural representation of mental disorders in a disadvantaged district, which magnifies experiences of loneliness, stigma and shame. We highlight the importance that services could be enhanced by shared specific care practices, in a multidisciplinary team, for caregivers and their relative living in disadvantaged communities. It is paramount to promote processes of elaboration and comprehension of SMI and reshape the dynamics of mutual control present in the caregiverrelative relationship, and also to support their feelings of loneliness related to high levels of social stigma typical of suburbs, in both the therapeutic setting and the integration with the local community
A machine learning approach for early identification of patients with severe imported malaria
Abstract Background The aim of this study is to design ad hoc malaria learning (ML) approaches to predict clinical outcome in all patients with imported malaria and, therefore, to identify the best clinical setting. Methods This is a single-centre cross-sectional study, patients with confirmed malaria, consecutively hospitalized to the Lazzaro Spallanzani National Institute for Infectious Diseases, Rome, Italy from January 2007 to December 2020, were recruited. Different ML approaches were used to perform the analysis of this dataset: support vector machines, random forests, feature selection approaches and clustering analysis. Results A total of 259 patients with malaria were enrolled, 89.5% patients were male with a median age of 39 y/o. In 78.3% cases, Plasmodium falciparum was found. The patients were classified as severe malaria in 111 cases. From ML analyses, four parameters, AST, platelet count, total bilirubin and parasitaemia, are associated to a negative outcome. Interestingly, two of them, aminotransferase and platelet are not included in the current list of World Health Organization (WHO) criteria for defining severe malaria. Conclusion In conclusion, the application of ML algorithms as a decision support tool could enable the clinicians to predict the clinical outcome of patients with malaria and consequently to optimize and personalize clinical allocation and treatment
Additional file 1 of A machine learning approach for early identification of patients with severe imported malaria
Additional file 1: Fig. S1. A visualization of the clusters related to the severe malaria patients, obtained using K-means
Loading and release of the complex [Pt(DTBTA)(DMSO)Cl]Cl·CHCl3 with the 2,2′-dithiobis(benzothiazole) ligand into mesoporous silica and studies of antiproliferative activity on MCF-7 cells
B-cell-depleted patients with persistent SARS-CoV-2 infection: combination therapy or monotherapy? A real-world experience
ObjectivesThe aim of the study was to describe a cohort of B-cell-depleted immunocompromised (IC) patients with prolonged or relapsing COVID-19 treated with monotherapy or combination therapy.MethodsThis is a multicenter observational retrospective study conducted on IC patients consecutively hospitalized with a prolonged or relapsing SARS-CoV-2 infection from November 2020 to January 2023. IC COVID-19 subjects were stratified according to the monotherapy or combination anti-SARS-CoV-2 therapy received.ResultsEighty-eight patients were enrolled, 19 under monotherapy and 69 under combination therapy. The study population had a history of immunosuppression (median of 2 B-cells/mm3, IQR 1–24 cells), and residual hypogammaglobulinemia was observed in 55 patients. A reduced length of hospitalization and time to negative SARS-CoV-2 molecular nasopharyngeal swab (NPS) in the combination versus monotherapy group was observed. In the univariable and multivariable analyses, the percentage change in the rate of days to NPS negativity showed a significant reduction in patients receiving combination therapy compared to those receiving monotherapy.ConclusionIn IC persistent COVID-19 patients, it is essential to explore new therapeutic strategies such as combination multi-target therapy (antiviral or double antiviral plus antibody-based therapies) to avoid persistent viral shedding and/or severe SARS-CoV-2 infection