9 research outputs found

    How to measure hospital antibiotic consumption: comparison of two methods from data surveillance in France

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    BACKGROUND: Antibiotic use (ABU) surveillance in healthcare facilities (HCFs) is essential to guide stewardship. Two methods are recommended: antibiotic consumption (ABC), expressed as the number of DDD/1000 patient-days; and prevalence of antibiotic prescription (ABP) measured through point prevalence surveys. However, no evidence is provided about whether they lead to similar conclusions. OBJECTIVES: To compare ABC and ABP regarding HCF ranking and their ability to identify outliers. METHODS: The comparison was made using 2012 national databases from the antibiotic surveillance network and prevalence study. HCF rankings according to each method were compared with Spearman's correlation coefficient. Analyses included the ABU from entire HCFs as well as according to type, clinical ward and by antibiotic class and specific molecule. RESULTS: A total of 1076 HCFs were included. HCF rankings were strongly correlated in the whole cohort. The correlation was stronger for HCFs with a higher number of beds or with a low or moderate proportion of acute care beds. ABU correlation between ABC or ABP was globally moderate or weak in specific wards. Furthermore, the two methods did not identify the same outliers, whichever HCF characteristics were analysed. Correlation between HCF ranking varied according to the antibiotic class. CONCLUSIONS: Both methods ranked HCFs similarly overall according to ABC or ABP; however, major differences were observed in ranking of clinical wards, antibiotic classes and detection of outliers. ABC and ABP are two markers of ABU that could be used as two complementary approaches to identify targets for improvement

    Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

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    RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

    Transient Elastography Accurately Screens for Compensated Advanced Chronic Liver Disease in Patients with Ongoing or Recent Alcohol Withdrawal

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    International audienceBACKGROUND AND AIMS: Liver stiffness measurement by transient elastography (TE) is a promising method for staging fibrosis in alcohol-related liver disease, but uncertainties remain regarding the influence of alcohol consumption and thus the ideal timing for TE performance. We evaluated the performance of TE compared with liver biopsy to exclude compensated advanced chronic liver disease (cACLD) in patients hospitalized for alcohol detoxification. METHODS: Patients were prospectively recruited at six in-patient addiction centers in France. Eligible patients exhibited increased aspartate-amino-transferases, and no history or signs of overt cirrhosis. TE, histology, and biochemistry measurements were obtained within a median of 6 days after alcohol withdrawal. TE and biochemistry were repeated one and two months later. RESULTS: The study included 259 patients for per-protocol analysis, of whom 45 (17.4%) had cACLD. TE identified patients with high accuracy at inclusion, 1-, and 2-month follow up, with area under curve values of 0.96 [95% confidence interval, CI, 0.94-0.99], 0.96 [95% CI, 0.92-0.99], and 0.93 [95% CI, 0.85-1.00], respectively. In 84% of patients, cACLD was ruled out when liver stiffness was &lt;10 kPa (negative predictive value, 99% [98-100%]) or ruled in when &gt;25 kPa (positive predictive value, 93% [83-102%]). Algorithms based on transaminases and/or bilirubin did not add to diagnostic performance of TE in this period. Among patients with initial liver stiffness of 10-25 kPa, over half of those with no cACLD exhibited liver stiffness of &lt;10 at 1- and 2 month follow-up testing. CONCLUSIONS: Transient elastography performed during the first two months following alcohol cessation is an excellent method for excluding alcohol-related cACLD

    Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome Associated with COVID-19: An Emulated Target Trial Analysis

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    Characteristics and prognosis of bloodstream infection in patients with COVID-19 admitted in the ICU: an ancillary study of the COVID-ICU study

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    International audienceBackground Patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-COV 2) and requiring intensive care unit (ICU) have a high incidence of hospital-acquired infections; however, data regarding hospital acquired bloodstream infections (BSI) are scarce. We aimed to investigate risk factors and outcome of BSI in critically ill coronavirus infectious disease-19 (COVID-19) patients. Patients and methods We performed an ancillary analysis of a multicenter prospective international cohort study (COVID-ICU study) that included 4010 COVID-19 ICU patients. For the present analysis, only those with data regarding primary outcome (death within 90 days from admission) or BSI status were included. Risk factors for BSI were analyzed using Fine and Gray competing risk model. Then, for outcome comparison, 537 BSI-patients were matched with 537 controls using propensity score matching. Results Among 4010 included patients, 780 (19.5%) acquired a total of 1066 BSI (10.3 BSI per 1000 patients days at risk) of whom 92% were acquired in the ICU. Higher SAPS II, male gender, longer time from hospital to ICU admission and antiviral drug before admission were independently associated with an increased risk of BSI, and interestingly, this risk decreased over time. BSI was independently associated with a shorter time to death in the overall population (adjusted hazard ratio (aHR) 1.28, 95% CI 1.05–1.56) and, in the propensity score matched data set, patients with BSI had a higher mortality rate (39% vs 33% p = 0.036). BSI accounted for 3.6% of the death of the overall population. Conclusion COVID-19 ICU patients have a high risk of BSI, especially early after ICU admission, risk that increases with severity but not with corticosteroids use. BSI is associated with an increased mortality rate

    Benefits and risks of noninvasive oxygenation strategy in COVID-19: a multicenter, prospective cohort study (COVID-ICU) in 137 hospitals

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    International audienceAbstract Rational To evaluate the respective impact of standard oxygen, high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) on oxygenation failure rate and mortality in COVID-19 patients admitted to intensive care units (ICUs). Methods Multicenter, prospective cohort study (COVID-ICU) in 137 hospitals in France, Belgium, and Switzerland. Demographic, clinical, respiratory support, oxygenation failure, and survival data were collected. Oxygenation failure was defined as either intubation or death in the ICU without intubation. Variables independently associated with oxygenation failure and Day-90 mortality were assessed using multivariate logistic regression. Results From February 25 to May 4, 2020, 4754 patients were admitted in ICU. Of these, 1491 patients were not intubated on the day of ICU admission and received standard oxygen therapy (51%), HFNC (38%), or NIV (11%) ( P < 0.001). Oxygenation failure occurred in 739 (50%) patients (678 intubation and 61 death). For standard oxygen, HFNC, and NIV, oxygenation failure rate was 49%, 48%, and 60% ( P < 0.001). By multivariate analysis, HFNC (odds ratio [OR] 0.60, 95% confidence interval [CI] 0.36–0.99, P = 0.013) but not NIV (OR 1.57, 95% CI 0.78–3.21) was associated with a reduction in oxygenation failure). Overall 90-day mortality was 21%. By multivariable analysis, HFNC was not associated with a change in mortality (OR 0.90, 95% CI 0.61–1.33), while NIV was associated with increased mortality (OR 2.75, 95% CI 1.79–4.21, P < 0.001). Conclusion In patients with COVID-19, HFNC was associated with a reduction in oxygenation failure without improvement in 90-day mortality, whereas NIV was associated with a higher mortality in these patients. Randomized controlled trials are needed

    Characteristics, management, and prognosis of elderly patients with COVID-19 admitted in the ICU during the first wave: insights from the COVID-ICU study

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    International audienceBackground: The COVID-19 pandemic is a heavy burden in terms of health care resources. Future decision-making policies require consistent data on the management and prognosis of the older patients (&gt; 70 years old) with COVID-19 admitted in the intensive care unit (ICU). Methods: Characteristics, management, and prognosis of critically ill old patients (&gt; 70 years) were extracted from the international prospective COVID-ICU database. A propensity score weighted-comparison evaluated the impact of intubation upon admission on Day-90 mortality. Results: The analysis included 1199 (28% of the COVID-ICU cohort) patients (median [interquartile] age 74 [72–78] years). Fifty-three percent, 31%, and 16% were 70–74, 75–79, and over 80 years old, respectively. The most frequent comorbidities were chronic hypertension (62%), diabetes (30%), and chronic respiratory disease (25%). Median Clinical Frailty Scale was 3 (2–3). Upon admission, the PaO2/FiO2 ratio was 154 (105–222). 740 (62%) patients were intubated on Day-1 and eventually 938 (78%) during their ICU stay. Overall Day-90 mortality was 46% and reached 67% among the 193 patients over 80 years old. Mortality was higher in older patients, diabetics, and those with a lower PaO2/FiO2 ratio upon admission, cardiovascular dysfunction, and a shorter time between first symptoms and ICU admission. In propensity analysis, early intubation at ICU admission was associated with a significantly higher Day-90 mortality (42% vs 28%; hazard ratio 1.68; 95% CI 1.24–2.27; p &lt; 0·001). Conclusion: Patients over 70 years old represented more than a quarter of the COVID-19 population admitted in the participating ICUs during the first wave. Day-90 mortality was 46%, with dismal outcomes reported for patients older than 80 years or those intubated upon ICU admission

    Correction to: Characteristics and prognosis of bloodstream infection in patients with COVID‑19 admitted in the ICU: an ancillary study of the COVID‑ICU study

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    Predicting 90-day survival of patients with COVID-19: Survival of Severely Ill COVID (SOSIC) scores

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    International audienceBackground Predicting outcomes of critically ill intensive care unit (ICU) patients with coronavirus-19 disease (COVID-19) is a major challenge to avoid futile, and prolonged ICU stays. Methods The objective was to develop predictive survival models for patients with COVID-19 after 1-to-2 weeks in ICU. Based on the COVID–ICU cohort, which prospectively collected characteristics, management, and outcomes of critically ill patients with COVID-19. Machine learning was used to develop dynamic, clinically useful models able to predict 90-day mortality using ICU data collected on day (D) 1, D7 or D14. Results Survival of Severely Ill COVID (SOSIC)-1, SOSIC-7, and SOSIC-14 scores were constructed with 4244, 2877, and 1349 patients, respectively, randomly assigned to development or test datasets. The three models selected 15 ICU-entry variables recorded on D1, D7, or D14. Cardiovascular, renal, and pulmonary functions on prediction D7 or D14 were among the most heavily weighted inputs for both models. For the test dataset, SOSIC-7’s area under the ROC curve was slightly higher (0.80 [0.74–0.86]) than those for SOSIC-1 (0.76 [0.71–0.81]) and SOSIC-14 (0.76 [0.68–0.83]). Similarly, SOSIC-1 and SOSIC-7 had excellent calibration curves, with similar Brier scores for the three models. Conclusion The SOSIC scores showed that entering 15 to 27 baseline and dynamic clinical parameters into an automatable XGBoost algorithm can potentially accurately predict the likely 90-day mortality post-ICU admission (sosic.shinyapps.io/shiny). Although external SOSIC-score validation is still needed, it is an additional tool to strengthen decisions about life-sustaining treatments and informing family members of likely prognosis
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