Additional file 1 of On the use of propensity scores in case of rare exposure

Data-generation process and simulated scenarios. (DOCX 119 kb

Ventilator-associated pneumonia in patients assisted by veno-arterial extracorporeal membrane oxygenation support: Epidemiology and risk factors of treatment failure

<div><p>Introduction</p><p>Ventilator-associated pneumonia (VAP) is frequent in Intensive Care Unit (ICU) patients. In the specific case of patients treated with Veno-Arterial Extracorporeal Membrane Oxygenation Support (VA-ECMO), VAP treatment failures (VAP-TF) have been incompletely investigated.</p><p>Methods</p><p>To investigate the risk factors of treatment failure (VAP-TF) in a large cohort of ICU patients treated with VA-ECMO, we conducted a retrospective study in a Surgical ICU about patients assisted with VA-ECMO between January 1, 2013, and December 31, 2014. Diagnosis of VAP was confirmed by a positive quantitative culture of a respiratory sample. VAP-TF was defined as composite of death attributable to pneumonia and relapse within 28 days of the first episode.</p><p>Results</p><p>In total, 152 patients underwent ECMO support for > 48h. During the VA-ECMO support, 85 (55.9%) patients developed a VAP, for a rate of 60.6 per 1000 ECMO days. The main pathogens identified were <i>Pseudomonas aeruginosa</i> and Enterobacteriaceae. VAP-TF occurred in 37.2% of patients and was associated with an increased 28-day mortality (Hazard Ratio 3.05 [1.66; 5.63], P<0.001), and VA-ECMO assistance duration (HR 1.47 [1.05–2.05], P = 0.025).</p><p>Risk factors for VAP-TF were renal replacement therapy (HR 13.05 [1.73; 98.56], P = 0.013) and documentation of <i>Pseudomonas aeruginosa</i> (HR 2.36 [1.04; 5.35], P = 0.04).</p><p>Conclusions</p><p>VAP in patients treated with VA-ECMO is associated with an increased morbidity and mortality. RRT and infection by <i>Pseudomonas aeruginosa</i> appear as strong risks factors of treatment failure. Further studies seem necessary to precise the best antibiotic management in these patients.</p></div

Baseline characteristics.

<p>Baseline characteristics.</p

Risk factors for VAP treatment failure in patients assisted with ECMO.

<p>Risk factors for VAP treatment failure in patients assisted with ECMO.</p

Pathogens isolated from respiratory samplings.

<p>Pathogens isolated from respiratory samplings.</p

日本における越境性豚伝染病のリスク評価に関する研究 [全文の要約]

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Reliability analysis of centralized versus decentralized zoning strategies for paratransit services

ADA paratransit services are a very large and ever-growing industry providing door-to-door transportation services for people with disability and elderly customers. Paratransit system, however, just like all other public transportation systems, suffers from travel time variability due to various factors and as a result gives its customers unreliable services. Although service reliability is a very important aspect in transportation study, it has not received much attention in the paratransit research community. A quantitative study evaluating the paratransit service reliability under different zoning strategies is yet to be found. This research filled this gap. Statistical models were proposed to represent travel time variability. Simulation experiments based on real demand data from Houston, Los Angeles and Boston were performed to quantitatively compare the reliability performance of centralized and decentralized operating strategies under different travel time variability levels. Results showed that the decentralized strategy, compared to the centralized no-zoning strategy, substantially improves the reliability of paratransit in terms of on-time performance. This research provides a framework for paratransit agencies to evaluate the service reliability of different organizational strategies through the simulation method

Baseline characteristics, French and Dutch population.

a<p>mean (sd).</p

Mean predicted versus observed survival.

<p>Dutch population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.</p

Mean predicted versus observed survival.

<p>French population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The grey thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.</p