scholarly journals An evaluation of factors that may influence clinicians’ decisions not to enroll eligible patients into randomized trials in critical care

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255361
Author(s):  
Mahesh Ramanan ◽  
Laurent Billot ◽  
Dorrilyn Rajbhandari ◽  
John Myburgh ◽  
Balasubramanian Venkatesh
Keyword(s):  
Intensive Care ◽  
Randomized Trials ◽  
Controlled Trial ◽  
Mixed Effects ◽  
Multivariable Model ◽  
Academic Status ◽  
Regression Modelling ◽  
Level Data ◽  
Research Coordinator ◽  
Logistic Regression Modelling

Objectives To determine the association between intensive care unit (ICU) characteristics and clinicians’ decision to decline eligible patients for randomization into a multicentered pragmatic comparative-effectiveness controlled trial. Methods Screening logs from the Adjunctive Glucocorticoid Therapy in Septic Shock Trial (ADRENAL) and site-level data from the College of Intensive Care Medicine and Australia New Zealand Intensive Care Society were examined. The effects of ICU characteristics such as tertiary academic status, research coordinator availability, number of admissions, and ICU affiliations on clinicians declining to randomize eligible patients were calculated using mixed effects logistic regression modelling. Results There were 21,818 patients screened for inclusion in the ADRENAL trial at 69 sites across five countries, out of which 5,501 were eligible, 3,800 were randomized and 659 eligible patients were declined for randomization by the treating clinician. The proportion of eligible patients declined by clinicians at individual ICUs ranged from 0 to41%. In the multivariable model, none of the ICU characteristics were significantly associated with higher clinician decline rate. Conclusions Neither tertiary academic status, nor other site-level variables were significantly associated with increased rate of clinicians declining eligible patients.

The – switch: an empirical account of the anglicisation of a Scots variant in Scotland during the sixteenth and seventeenth centuries

2019 ◽  
Vol 24 (1) ◽  
pp. 211-236
Author(s):  
SARAH VAN EYNDHOVEN ◽  
LYNN CLARK
Keyword(s):  
Logistic Regression ◽  
Language Change ◽  
Statistical Modelling ◽  
Mixed Effects ◽  
Descriptive Statistics ◽  
Statistical Techniques ◽  
Fine Grained ◽  
Regression Modelling ◽  
Modern Methods ◽  
Logistic Regression Modelling

This article explores the anglicisation of the Scots language between the sixteenth and eighteenth centuries, focusing on the variation between the orthographic clusters <quh-> and <wh-> found in relative and interrogative clause markers. Using modern statistical techniques, we provide the most comprehensive empirical analysis of this variation so far in the Helsinki Corpus of Older Scots (Meurman-Solin 1995). By combining the techniques of Variability-Based Neighbour Clustering (Gries & Hilpert 2008, 2010, 2012) with mixed-effects logistic regression modelling (Baayen et al.2008), we uncover a different trajectory of change than that which has previously been reported for this feature (Meurman-Solin 1993, 1997). We argue that by using modern methods of data reduction and statistical modelling, we can present a picture of language change in Scots that is more fine-grained than previous studies which use only descriptive statistics.

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 95-108 ◽  
Author(s):  
Steffen Nestler ◽  
Katharina Geukes ◽  
Mitja D. Back
Keyword(s):  
Multilevel Model ◽  
Multilevel Models ◽  
Mixed Effects ◽  
Repeated Measurements ◽  
Scale Model ◽  
Suggested Approach ◽  
Psychological Study ◽  
Level Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

scholarly journals Treatment of a Critically Ill COVID-19 Patient with the Seraph 100 Microbind Affinity Filter

TH Open ◽  
2021 ◽  
Vol 05 (02) ◽  
pp. e134-e138
Author(s):  
Anke Pape ◽  
Jan T. Kielstein ◽  
Tillman Krüger ◽  
Thomas Fühner ◽  
Reinhard Brunkhorst
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Randomized Trials ◽  
Clinical Course ◽  
Pharmacological Therapy ◽  
The European Union ◽  
Positive Effects ◽  
Special Patient

AbstractThe coronavirus disease 2019 (COVID-19) pandemic has a serious impact on health and economics worldwide. Even though the majority of patients present with moderate and mild symptoms, yet a considerable portion of patients need to be treated in the intensive care unit. Aside from dexamethasone, there is no established pharmacological therapy. Moreover, some of the currently tested drugs are contraindicated for special patient populations like remdesivir for patients with severely impaired renal function. On this background, several extracorporeal treatments are currently explored concerning their potential to improve the clinical course and outcome of critically ill patients with COVID-19. Here, we report the use of the Seraph 100 Microbind Affinity filter, which is licensed in the European Union for the removal of pathogens. Authorization for emergency use in patients with COVID-19 admitted to the intensive care unit with confirmed or imminent respiratory failure was granted by the U.S. Food and Drug Administration on April 17, 2020.A 53-year-old Caucasian male with a severe COVID-19 infection was treated with a Seraph Microbind Affinity filter hemoperfusion after clinical deterioration and commencement of mechanical ventilation. The 70-minute treatment at a blood flow of 200 mL/minute was well tolerated, and the patient was hemodynamically stable. The hemoperfusion reduced D-dimers dramatically.This case report suggests that the use of Seraph 100 Microbind Affinity filter hemoperfusion might have positive effects on the clinical course of critically ill patients with COVID-19. However, future prospective collection of data ideally in randomized trials will have to confirm whether the use of Seraph 100 Microbind Affinity filter hemoperfusion is an option of the treatment for COVID-19.

scholarly journals Validation of the pediatric refractory septic shock definition: post hoc analysis of a controlled trial

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luc Morin ◽  
Karthik Narayanan Ramaswamy ◽  
Muralidharan Jayashree ◽  
Arun Bansal ◽  
Karthi Nallasamy ◽  
...  
Keyword(s):  
Septic Shock ◽  
Intensive Care ◽  
Neonatal Intensive Care ◽  
Controlled Trial ◽  
Receiver Operating Curve ◽  
Double Blind ◽  
Post Hoc Analysis ◽  
Prognostic Accuracy ◽  
Refractory Septic Shock ◽  
Post Hoc

Abstract Background The European Society of Pediatric and Neonatal Intensive Care (ESPNIC) developed and validated a definition of pediatric refractory septic shock (RSS), based on two septic shock scores (SSS). Both bedside SSS (bSSS) and computed SSS (cSSS) were found to be strongly associated with mortality. We aimed at assessing the accuracy of the RSS definition on a prospective cohort from India. Methods Post hoc analysis of a cohort issued from a double-blind randomized trial that compared first-line vasoactive drugs in children with septic shock. Sequential bSSS and cSSS from 60 children (single-center study, 53% mortality) were analyzed. The prognostic value of the ESPNIC RSS definition was tested for 28-day all-cause mortality. Results In this septic shock cohort, RSS was diagnosed in 35 patients (58.3%) during the first 24 h. Death occurred in 30 RSS patients (85.7% mortality) and in 2 non-RSS patients (8% mortality), OR = 60.9 [95% CI: 10.5–676.2], p < 0.001 with a median delay from sepsis onset of 3 days [1.0–6.7]. Among patients diagnosed with RSS, the mortality was not significantly different according to vasopressors randomization. Diagnosis of RSS with bSSS and cSSS had a high discrimination for death with an area under the receiver operating curve of 0.916 [95% CI: 0.843–0.990] and 0.925 [95% CI: 0.845–1.000], respectively. High prognostic accuracy of the bSSS was found in the first hours following intensive care admission. The best interval of prognostication occurs after the 12th hour following treatment initiation (AUC 0.973 [95% CI: 0.925–1.000]). Conclusions The ESPNIC refractory septic shock definition accurately identifies, within the first 6 h of septic shock management, children with lethal outcome.

scholarly journals Proportion and risk factors for death by euthanasia in dogs in the UK

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Camilla Pegram ◽  
Carol Gray ◽  
Rowena M. A. Packer ◽  
Ysabelle Richards ◽  
David B. Church ◽  
...  
Keyword(s):  
Risk Factors ◽  
Poor Quality ◽  
Clinical Factors ◽  
Sampling Frame ◽  
Additional Risk ◽  
Factors Associated ◽  
Regression Modelling ◽  
The Uk ◽  
Logistic Regression Modelling

AbstractThe loss of a pet can be particularly distressing for owners, whether the method of death is euthanasia or is unassisted. Using primary-care clinical data, this study aimed to report the demographic and clinical factors associated with euthanasia, relative to unassisted death, in dogs. Method of death (euthanasia or unassisted) and clinical cause of death were extracted from a random sample of 29,865 dogs within the VetCompass Programme from a sampling frame of 905,544 dogs under UK veterinary care in 2016. Multivariable logistic regression modelling was used to evaluate associations between risk factors and method of death. Of the confirmed deaths, 26,676 (89.3%) were euthanased and 2,487 (8.3%) died unassisted. After accounting for confounding factors, 6 grouped-level disorders had higher odds in euthanased dogs (than dogs that died unassisted), using neoplasia as the baseline. The disorders with greatest odds included: poor quality of life (OR 16.28), undesirable behaviour (OR 11.36) and spinal cord disorder (OR 6.00). Breed, larger bodyweight and increasing age were additional risk factors for euthanasia. The results highlight that a large majority of owners will face euthanasia decisions and these findings can support veterinarians and owners to better prepare for such an eventuality.

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