Exploring drug consumption via an ultrametric correlation matrix

In molte applicazioni l’ipotesi dell’esistenza di un concetto generale (un fenomeno multidimensionale), definito mediante concetti più specifici, è spesso avvalorata. In letteratura, molteplici metodologie di tipo sequenziale sono state proposte con lo scopo di identificare una gerarchica di dimensioni latenti. In questo articolo indaghiamo il fenomeno del consumo di droghe mediante una matrice di correlazione ultrametrica, che permette di individuare diversi, disgiunti gruppi di droghe e le loro relazioni gerarchiche, a partire dalla matrice di correlazione dei dati osservati. Data la sua rilevanza sociale ed economica, un approccio basato su modello per lo studio del consumo di droghe può fornire una conoscenza più approfondita di tale fenomeno, che a sua volta può risultare fondamentale nella definizione di politiche volte alla sua riduzione.In many real applications, the existence of a general concept (a multidimensional phenomenon) composed of nested specific ones is often theorised. In the specialised literature, different sequential methodologies have been proposed to identify a hierarchy of latent dimensions. In this paper, we investigate drug consumption via an ultrametric correlation matrix which allows to detect different, nonoverlapping groups of drugs and their hierarchical relationships, starting from the correlation matrix of the observed data. Since its social and economic relevance, a model-based approach to drug consumption can provide an in-depth understanding of this challenging phenomenon, which turns out to be fundamental to address policies aimed at reducing it

A parsimonious parameterization of a nonnegative correlation matrix

Hierarchical relationships among manifest variables can be detected by analyzing their correlation matrix. To pinpoint the hierarchy underlying a multidimensional phenomenon, the Ultrametric Correlation Model (UCM) has been proposed with the aim of reconstructing a nonnegative correlation matrix via an ultrametric one. In this paper, we illustrate the mathematical advantages that a simple structure induced by the ultrametric property entails for the estimation of the UCM parameters in a maximum likelihood framework

Model-based clustering with parsimonious covariance structure

Complex multidimensional concepts are often explained by a tree-shape structure by considering nested partitions of variables, where each variable group is associated with a specific concept. Recalling that relations among variables can be detected by their covariance matrix, this paper introduces a covariance structure that reconstructs hierarchical relationships among variables highlighting three features of the variable groups. We finally present an application of the latter covariance structure to the model-based clustering

An ultrametric model to build a Composite Indicators system

Negli ultimi anni l’utilizzo di indicatori compositi `e costantemente cresciuto, e la necessità di costruire degli indicatori compositi model-based con un forte approccio statistico `e sempre più importante per motivi di fiducia. In questo articolo proponiamo di costruire un sistema di indicatori compositi che possa misurare diversi livelli di relazioni tra (gruppi di) variabili seguendo una forma ultrametrica che individui una gerarchia sulle (gruppi di) variabili. Al fine di mostrare il suo potenziale e la sua applicabilità, la metodologia `e applicata per analizzare un dataset che contiene variabili riguardo la raccolta differenziata in Italia considerando sia le sue prestazioni che i suoi costi.In the last years, the use of composite indicators has consistently increased, and the necessity to build model-based composite indicators with a strong methodological statistical approach becomes more and more important for reasons of trustworthiness. In this paper, we propose to build a composite indicators system able to measure different levels of relations among (group of) variables according to an ultrametric form which detects a hierarchical structure upon (group of) variables. Each dimension is measured as a specific composite indicator which reflects a subset of variables. In order to show its potential and applicability, the methodology is employed to analyze a dataset which contains variables about separated waste collection in Italy taking into consideration both its performance and its costs

In vivo validation of the adequacy calculator for continuous renal replacement therapies

INTRODUCTION: The study was conducted to validate in vivo the Adequacy Calculator, a Microsoft Excel-based program, designed to assess the prescription and delivery of renal replacement therapy in the critical care setting. METHODS: The design was a prospective cohort study, set in two intensive care units of teaching hospitals. The participants were 30 consecutive critically ill patients with acute renal failure treated with 106 continuous renal replacement therapies (CRRT). Urea clearance computation was performed with the Adequacy Calculator (K(CALC)). Simultaneous blood and effluent urea samples were collected to measure the effectively delivered urea clearance (K(DEL)) at the beginning of each treatment and, during 73 treatments, between the 18th and 24th treatment hour. The correlation between 179 computed and 179 measured clearances was assessed. Fractional clearances for urea were calculated as spKt/V (where sp represents single pool, K is clearance, t is time, and V is urea volume of distribution) obtained from software prescription and compared with the delivered spKt/V obtained from empirical data. RESULTS: We found that the value of clearance predicted by the calculator was strongly correlated with the value obtained from computation on blood and dialysate determination (r = 0.97) during the first 24 treatment hours, regardless of the renal replacement modality used. The delivered spKt/V (1.25) was less than prescribed (1.4) from the Adequacy Calculator by 10.7%, owing to therapy downtime. CONCLUSION: The Adequacy Calculator is a simple tool for prescribing CRRT and for predicting the delivered dose. The calculator might be a helpful tool for standardizing therapy and for comparing disparate treatments, making it possible to perform large multi-centre studies on CRRT

High-dose fenoldopam reduces postoperative neutrophil gelatinase-associated lipocaline and cystatin C levels in pediatric cardiac surgery

21714857 2011 11 17 1466-609X 15 3 2011 Crit Care High-dose fenoldopam reduces postoperative neutrophil gelatinase-associated lipocaline and cystatin C levels in pediatric cardiac surgery. R160 The aim of the study was to evaluate the effects of high-dose fenoldopam, a selective dopamine-1 receptor, on renal function and organ perfusion during cardiopulmonary bypass (CPB) in infants with congenital heart disease (CHD).A prospective single-center randomized double-blind controlled trial was conducted in a pediatric cardiac surgery department. We randomized infants younger than 1 year with CHD and biventricular anatomy (with exclusion of isolated ventricular and atrial septal defect) to receive blindly a continuous infusion of fenoldopam at 1 \u3bcg/kg/min or placebo during CPB. Perioperative urinary and plasma levels of neutrophil gelatinase-associated lipocaline (NGAL), cystatin C (CysC), and creatinine were measured to assess renal injury after CPB.We enrolled 80 patients: 40 received fenoldopam (group F) during CPB, and 40 received placebo (group P). A significant increase of urinary NGAL and CysC levels from baseline to intensive care unit (ICU) admission followed by restoration of normal values after 12 hours was observed in both groups. However, urinary NGAL and CysC values were significantly reduced at the end of surgery and 12 hours after ICU admission (uNGAL only) in group F compared with group P (P = 0.025 and 0.039, respectively). Plasma NGAL and CysC tended to increase from baseline to ICU admission in both groups, but they were not significantly different between the two groups. No differences were observed on urinary and plasma creatinine levels and on urine output between the two groups. Acute kidney injury (AKI) incidence in the postoperative period, as indicated by pRIFLE classification (pediatric score indicating Risk, Injury, Failure, Loss of function, and End-stage kidney disease level of renal damage) was 50% in group F and 72% in group P (P = 0.08; odds ratio (OR), 0.38; 95% confidence interval (CI), 0.14 to 1.02). A significant reduction in diuretics (furosemide) and vasodilators (phentolamine) administration was observed in group F (P = 0.0085; OR, 0.22; 95% CI, 0.07 to 0.7).The treatment with high-dose fenoldopam during CPB in pediatric patients undergoing cardiac surgery for CHD with biventricular anatomy significantly decreased urinary levels of NGAL and CysC and reduced the use of diuretics and vasodilators during CPB.Clinical Trial.Gov NCT00982527. Pediatric Cardiac Anesthesia/Intensive Care Unit, Department of Pediatric Cardiology and Cardiac Surgery, Bambino Ges\uf9 Children's Hospital, Piazza S, Onofrio 4, 00165, Rome, Italy. [email protected] Ricci Zaccaria Z Luciano Rosa R Favia Isabella I Garisto Cristiana C Muraca Maurizio M Morelli Stefano S Di Chiara Luca L Cogo Paola P Picardo Sergio S eng ClinicalTrials.gov NCT00982527 Journal Article 20110629 England Crit Care 9801902 1364-8535 IM Crit Care. 2011;15(4):177 21861863 PMC3219034 2011413201151720116292011629201171602011716020117160epublishcc1029510.1186/cc1029521714857PMC321903

Physical activity measured by implanted devices predicts atrial arrhythmias and patient outcome: Results of IMPLANTED (Italian Multicentre Observational Registry on Patients With Implantable Devices Remotely Monitored)

Background--To determine whether daily physical activity (PA), as measured by implanted devices (through accelerometer sensor), was related to the risk of developing atrial arrhythmias during long-term follow-up in a population of heart failure (HF) patients with an implantable cardioverter defibrillator (ICD). Methods and Results--The study population was divided into 2 equally sized groups (PA cutoff point: 3.5 h/d) according to their mean daily PA recorded by the device during the 30- to 60-day period post-ICD implantation. Propensity score matching was used to compare 2 equally sized cohorts with similar characteristics between lower and higher activity patients. The primary end point was time free from the first atrial high-rate episode (AHRE) of duration 656 minutes. Secondary end points were: first AHRE 656 hours, first AHRE 6548 hours, and a combined end point of death or HF hospitalization. Data from 770 patients (65\ub115 years; 66% men; left ventricular ejection fraction 35\ub112%) remotely monitored for a median of 25 months were analyzed. A PA =3.5 h/d was associated with a 38% relative reduction in the risk of AHRE 656 minutes (72-month cumulative survival: 75.0% versus 68.1%; log rank P=0.025), and with a reduction in the risk of AHRE 656 hours, AHRE 6548 hours, and the combined end point of death or HF hospitalization (all P < 0.05). Conclusions--In HF patients with ICD, a low level of daily PA was associated with a higher risk of atrial arrhythmias, regardless of the patients' baseline characteristics. In addition, a lower daily PA predicted death or HF hospitalization

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)