Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe

Epidemiological characteristics, practice of ventilation, and clinical outcome in patients at risk of acute respiratory distress syndrome in intensive care units from 16 countries (PRoVENT): an international, multicentre, prospective study

Background Scant information exists about the epidemiological characteristics and outcome of patients in the intensive care unit (ICU) at risk of acute respiratory distress syndrome (ARDS) and how ventilation is managed in these individuals. We aimed to establish the epidemiological characteristics of patients at risk of ARDS, describe ventilation management in this population, and assess outcomes compared with people at no risk of ARDS. Methods PRoVENT (PRactice of VENTilation in critically ill patients without ARDS at onset of ventilation) is an international, multicentre, prospective study undertaken at 119 ICUs in 16 countries worldwide. All patients aged 18 years or older who were receiving mechanical ventilation in participating ICUs during a 1-week period between January, 2014, and January, 2015, were enrolled into the study. The Lung Injury Prediction Score (LIPS) was used to stratify risk of ARDS, with a score of 4 or higher defining those at risk of ARDS. The primary outcome was the proportion of patients at risk of ARDS. Secondary outcomes included ventilatory management (including tidal volume [VT] expressed as mL/kg predicted bodyweight [PBW], and positive end-expiratory pressure [PEEP] expressed as cm H2O), development of pulmonary complications, and clinical outcomes. The PRoVENT study is registered at ClinicalTrials.gov, NCT01868321. The study has been completed. Findings Of 3023 patients screened for the study, 935 individuals fulfilled the inclusion criteria. Of these critically ill patients, 282 were at risk of ARDS (30%, 95% CI 27â33), representing 0·14 cases per ICU bed over a 1-week period. VTwas similar for patients at risk and not at risk of ARDS (median 7·6 mL/kg PBW [IQR 6·7â9·1] vs 7·9 mL/kg PBW [6·8â9·1]; p=0·346). PEEP was higher in patients at risk of ARDS compared with those not at risk (median 6·0 cm H2O [IQR 5·0â8·0] vs 5·0 cm H2O [5·0â7·0]; p<0·0001). The prevalence of ARDS in patients at risk of ARDS was higher than in individuals not at risk of ARDS (19/260 [7%] vs 17/556 [3%]; p=0·004). Compared with individuals not at risk of ARDS, patients at risk of ARDS had higher in-hospital mortality (86/543 [16%] vs 74/232 [32%]; p<0·0001), ICU mortality (62/533 [12%] vs 66/227 [29%]; p<0·0001), and 90-day mortality (109/653 [17%] vs 88/282 [31%]; p<0·0001). VTdid not differ between patients who did and did not develop ARDS (p=0·471 for those at risk of ARDS; p=0·323 for those not at risk). Interpretation Around a third of patients receiving mechanical ventilation in the ICU were at risk of ARDS. Pulmonary complications occur frequently in patients at risk of ARDS and their clinical outcome is worse compared with those not at risk of ARDS. There is potential for improvement in the management of patients without ARDS. Further refinements are needed for prediction of ARDS. Funding None