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Co-enrollment of critically ill patients into multiple studies: patterns, predictors and consequences.

ABSTRACT: Research on co-enrollment practices and their impact are limited in the ICU setting. The objectives of this study were: 1) to describe patterns and predictors of co-enrollment of patients in a thromboprophylaxis trial, and 2) to examine the consequences of co-enrollment on clinical and trial outcomes.In an observational analysis of an international thromboprophylaxis trial in 67 ICUs, we examined the co-enrollment of critically ill medical-surgical patients into more than one study, and examined the clinical and trial outcomes among co-enrolled and non-co-enrolled patients.Among 3,746 patients enrolled in PROTECT (Prophylaxis for ThromboEmbolism in Critical Care Trial), 713 (19.0%) were co-enrolled in at least one other study (53.6% in a randomized trial, 37.0% in an observational study and 9.4% in both). Six factors independently associated with co-enrollment (all P < 0.001) were illness severity (odds ratio (OR) 1.35, 95% confidence interval (CI) 1.19 to 1.53 for each 10-point Acute Physiology and Chronic Health Evaluation (APACHE) II score increase), substitute decision-makers providing consent, rather than patients (OR 3.31, 2.03 to 5.41), experience of persons inviting consent (OR 2.67, 1.74 to 4.11 for persons with > 10 years' experience compared to persons with none), center size (all ORs > 10 for ICUs with > 15 beds), affiliation with trials groups (OR 5.59, 3.49 to 8.95), and main trial rather than pilot phase (all ORs > 8 for recruitment year beyond the pilot). Co-enrollment did not influence clinical or trial outcomes or risk of adverse events.Co-enrollment was strongly associated with features of the patients, research personnel, setting and study. Co-enrollment had no impact on trial results, and appeared safe, acceptable and feasible. Transparent reporting, scholarly discourse, ethical analysis and further research are needed on the complex topic of co-enrollment during critical illness.

SUBMITTER: Cook D

PROVIDER: S-EPMC4056073 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Co-enrollment of critically ill patients into multiple studies: patterns, predictors and consequences.

Cook Deborah D McDonald Ellen E Smith Orla O Zytaruk Nicole N Heels-Ansdell Diane D Watpool Irene I McArdle Tracy T Matte Andrea A Clarke France F Vallance Shirley S Finfer Simon S Galt Pauline P Crozier Tim T Fowler Rob R Arabi Yaseen Y Woolfe Clive C Orford Neil N Hall Richard R Adhikari Neill K J NK Ferland Marie-Clauide MC Marshall John J Meade Maureen M

Critical care (London, England) 20130108 1

<h4>Introduction</h4>Research on co-enrollment practices and their impact are limited in the ICU setting. The objectives of this study were: 1) to describe patterns and predictors of co-enrollment of patients in a thromboprophylaxis trial, and 2) to examine the consequences of co-enrollment on clinical and trial outcomes.<h4>Methods</h4>In an observational analysis of an international thromboprophylaxis trial in 67 ICUs, we examined the co-enrollment of critically ill medical-surgical patients i ...[more]

PMID: 23298553

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Project description:BackgroundIt is unclear whether influenza infection and associated co-infection are associated with patient-important outcomes in critically ill immunocompromised patients with acute respiratory failure.MethodsPreplanned secondary analysis of EFRAIM, a prospective cohort study of 68 hospitals in 16 countries. We included 1611 patients aged 18 years or older with non-AIDS-related immunocompromise, who were admitted to the ICU with acute hypoxemic respiratory failure. The main exposure of interest was influenza infection status. The primary outcome of interest was all-cause hospital mortality, and secondary outcomes ICU length of stay (LOS) and 90-day mortality.ResultsInfluenza infection status was categorized into four groups: patients with influenza alone (n = 95, 5.8%), patients with influenza plus pulmonary co-infection (n = 58, 3.6%), patients with non-influenza pulmonary infection (n = 820, 50.9%), and patients without pulmonary infection (n = 638, 39.6%). Influenza infection status was associated with a requirement for intubation and with LOS in ICU (P < 0.001). Patients with influenza plus co-infection had the highest rates of intubation and longest ICU LOS. On crude analysis, influenza infection status was associated with ICU mortality (P < 0.001) but not hospital mortality (P = 0.09). Patients with influenza plus co-infection and patients with non-influenza infection alone had similar ICU mortality (41% and 37% respectively) that was higher than patients with influenza alone or those without infection (33% and 26% respectively). A propensity score-matched analysis did not show a difference in hospital mortality attributable to influenza infection (OR = 1.01, 95%CI 0.90-1.13, P = 0.85). Age, severity scores, ARDS, and performance status were all associated with ICU, hospital, and 90-day mortality.ConclusionsCategory of infectious etiology of respiratory failure (influenza, non-influenza, influenza plus co-infection, and non-infectious) was associated with ICU but not hospital mortality. In a propensity score-matched analysis, influenza infection was not associated with the primary outcome of hospital mortality. Overall, influenza infection alone may not be an independent risk factor for hospital mortality in immunosuppressed patients.

Project description:Amikacin infusion requires targeting a peak serum concentration (Cmax) 8-10 times the minimal inhibitory concentration, corresponding to a Cmax of 60-80 mg/L for the least susceptible bacteria to theoretically prevent therapeutic failure. Because drug pharmacokinetics on extracorporeal membrane oxygenation (ECMO) are challenging, we undertook this study to assess the frequency of insufficient amikacin Cmax in critically ill patients on ECMO and to identify relative risk factors.This was a prospective, observational, monocentric study in a university hospital. Patients on ECMO who received an amikacin loading dose for suspected Gram-negative infections were included. The amikacin loading dose of 25 mg/kg total body weight was administered intravenously and Cmax was measured 30 min after the end of the infusion. Independent predicators of Cmax?<?60 mg/L after the first amikacin infusion were identified with mixed-model multivariable analyses. Various dosing simulations were performed to assess the probability of reaching 60 mg/L?<?Cmax <?80 mg/L.A total of 106 patients on venoarterial ECMO (VA-ECMO) (68%) or venovenous-ECMO (32%) were included. At inclusion, their median (1st; 3rd quartile) Sequential Organ-Failure Assessment score was 15 (12; 18) and 54 patients (51%) were on renal replacement therapy. Overall ICU mortality was 54%. Cmax was <?60 mg/L in 41 patients (39%). Independent risk factors for amikacin under-dosing were body mass index (BMI)?<?22 kg/m2 and a positive 24-h fluid balance. Using dosing simulation, increasing the amikacin dosing regimen to 30 mg/kg and 35 mg/kg of body weight when the 24-h fluid balance is positive and the BMI is ??22 kg/m2 or?<?22 kg/m2 (Table 3), respectively, would have potentially led to the therapeutic target being reached in 42% of patients while reducing under-dosing to 23% of patients.ECMO-treated patients were under-dosed for amikacin in one third of cases. Increasing the dose to 35 mg/kg of body weight in low-BMI patients and those with positive 24-h fluid balance on ECMO to reach adequate targeted concentrations should be investigated.

Project description:Adequate linezolid blood concentrations have been shown to be associated with an improved clinical outcome. Our goal was to assess new predictors of inadequate linezolid concentrations often observed in critically ill patients. Fifty-two critically ill patients with severe infections receiving standard dosing of linezolid participated in this prospective observational study. Serum samples (median, 32 per patient) were taken on four consecutive days, and total linezolid concentrations were quantified. Covariates influencing linezolid pharmacokinetics were identified by multivariate analysis and a population pharmacokinetic model. Target attainment (area under the concentration-time curve over 12 h [AUC12]/MIC ratio of >50; MIC = 2 mg/liter) was calculated for both the study patients and a simulated independent patient group (n = 67,000). Target attainment was observed for only 36% of the population on both days 1 and 4. Independent covariates related to significant decreases of linezolid concentrations included higher weight, creatinine clearance rates, and fibrinogen and antithrombin concentrations, lower concentrations of lactate, and the presence of acute respiratory distress syndrome (ARDS). Linezolid clearance was increased in ARDS patients (by 82%) and in patients with elevated fibrinogen or decreased lactate concentrations. In simulated patients, most covariates, including fibrinogen and lactate concentrations and weight, showed quantitatively minor effects on target attainment (difference of ≤9% between the first and fourth quartiles of the respective parameters). In contrast, the presence of ARDS had the strongest influence, with only ≤6% of simulated patients reaching this target. In conclusion, the presence of ARDS was identified as a new and strong predictor of insufficient linezolid concentrations, which might cause treatment failure. Insufficient concentrations might also be a major problem in patients with combined alterations of other covariate parameters. (This study has been registered at ClinicalTrials.gov under registration number NCT01793012.).

Project description:Objective: COVID19 is caused by the SARS-CoV-2 virus and has been associated with severe inflammation leading to organ dysfunction and mortality. Our aim was to profile the transcriptome in leukocytes from critically ill ICU patients positive for COVID19 vs. those negative for COVID19 to better understand the COVID19 associated host response. Design: Transcriptome profiling of buffy coat cells via ribonucleic acid sequencing (RNAseq) at the time of admission to the ICU. Setting: Tertiary care ICU and academic laboratory. Subjects: All patients admitted to the ICU suspected of being infected with SARS-CoV-2, using standardized hospital screening methodologies, had blood samples collected at the time of admission to the ICU. Interventions: None. Measurement and Main Results: Age- and sex-matched ICU patients that were either COVID19+ (PCR positive, 2 genes) or COVID19- (PCR negative) were enrolled. Cohorts were well-balanced with the exception that COVID19- patients had significantly higher total white blood cell counts and circulating neutrophils and COVID19+ patients were more likely to suffer bilateral pneumonia compared to COVID19- patients. Further, the mortality rate for this cohort of COVID19+ ICU patients was 29%. Transcriptional analysis revealed that when compared to COVID19- patients, the altered transcriptional responses of leukocytes in critically ill COVID19+ ICU patients appeared to be associated with multiple interrelated outcomes, including but not limited to robust interferon (IFN)-associated transcriptional responses, a marked decrease in the transcriptional activity of genes contributing to protein synthesis and the dysregulated expression of genes that contribute to coagulation, platelet activation, Toll-like receptor activation, neurotrophin signaling, and protein SUMOylation/ubiquitination. Conclusions: COVID19+ patients on day 1 of admission to the ICU display a unique leukocyte transcriptional profile that distinguishes them from COVID19- patients. Identification of this profile provides guidance for future targeted studies exploring novel prognostic/therapeutic aspects of COVID19.

Project description:Background: Patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV) may require intensive care unit (ICU) admission due to different reasons, and the in-ICU mortality is high among AAV patients. The aim of this study was to explore the clinical features and risk factors of mortality of patients with AAV in the ICU. Methods: A retrospective study was conducted based on 83 AAV patients admitted to the ICU in a tertiary medical institution in China. Data on clinical characteristics, laboratory tests, treatment in ICU and outcomes were collected. The data were analyzed using univariate and multivariate logistic regression analysis to explore the variables that were independently related to mortality. Kaplan-Meier method was used to assess the long-term survival. Results: Among the 83 patients, 41 (49.4%) were female. The mean age of patients was 66 ± 13 years. Forty-four patients deceased, with the in-ICU mortality of 53%. The most common cause for ICU admission was active vasculitis (40/83, 48.2%). The main cause of death was infection (27/44, 61.4%) followed by active vasculitis (15/44, 34.1%). A multivariate analysis revealed that the Acute Physiology and Chronic Health Evaluation II (APACHE II) at ICU admission (OR = 1.333, 95% CI: 1.031-1.722) and respiratory failure (OR = 620.452, 95% CI: 11.495-33490.306) were independent risk factors of in-ICU death. However, hemoglobin (OR = 0.919, 95% CI: 0.849-0.995) was an independent protective factor. The nomogram established in this study was practical in predicting the risk of in-ICU mortality for AAV patients. Moreover, for 39 patients survived to the ICU stay, the cumulative survival rates at 0.5, 1, and 5 years were 58.3%, 54.2%, and 33.9%, respectively, and the median survival time was 14 months. Conclusion: In our study, active vasculitis was the most frequent reason for ICU admission, and the main cause of death was infection. APACHE II and respiratory failure were independent risk factors while hemoglobin was an independent protective factor of in-ICU mortality for AAV patients admitted to the ICU. The risk prediction model developed in this study may be a useful tool for clinicians in early recognition of high-risk patients and applying appropriate management.

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Co-enrollment of critically ill patients into multiple studies: patterns, predictors and consequences.

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Co-enrollment of critically ill patients into multiple studies: patterns, predictors and consequences.

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