scholarly journals The Effect of IL-6 Inhibitors on Mortality Among Hospitalized COVID-19 Patients: A Multicenter Study

2020 ◽  
Author(s):  
Pranay Sinha ◽  
S Reza Jafarzadeh ◽  
Sabrina A Assoumou ◽  
Catherine G Bielick ◽  
Bethanne Carpenter ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Hospital Mortality ◽  
Treatment Effect ◽  
Effect Size ◽  
Odds Ratio ◽  
Safety Net ◽  
Average Treatment Effect ◽  
Polymerase Chain Reaction Test ◽  
Average Treatment ◽  
Safety Net Hospital

Abstract Background The effectiveness of interleukin-6 inhibitors (IL-6i) in ameliorating coronavirus disease 2019 (COVID-19) remains uncertain. Methods We analyzed data for patients aged ≥18 years admitted with a positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction test at 4 safety-net hospital systems with diverse populations and high rates of medical comorbidities in 3 US regions. We used inverse probability of treatment weighting via machine learning for confounding adjustment by demographics, comorbidities, and disease severity markers. We estimated the average treatment effect, the odds of IL-6i effect on in-hospital mortality from COVID-19, using a logistic marginal structural model. Results Of 516 patients, 104 (20.1%) received IL-6i. Estimate of the average treatment effect adjusted for confounders suggested a 37% reduction in odds of in-hospital mortality in those who received IL-6i compared with those who did not, although the confidence interval included the null value of 1 (odds ratio = 0.63; 95% confidence interval, .29–1.38). A sensitivity analysis suggested that potential unmeasured confounding would require a minimum odds ratio of 2.55 to nullify our estimated IL-6i effect size. Conclusions Despite low precision, our findings suggested a relatively large effect size of IL-6i in reducing the odds of COVID-19–related in-hospital mortality.

scholarly journals Impact Visualisation in Educational Interventions

2017 ◽  
Author(s):  
ZhiMin Xiao ◽  
Steve Higgins ◽  
Adetayo Kasim
Keyword(s):  
Variable Selection ◽  
Treatment Effect ◽  
Effect Size ◽  
Evidence Synthesis ◽  
Educational Interventions ◽  
Average Treatment Effect ◽  
Average Treatment ◽  
The Impact ◽  
Analytical Approaches ◽  
Size Estimates

Reporting of research data analysis often resorts to numerical summaries, such as effect size estimates in Randomised Controlled Trials (RCTs). Summary statistics are helpful and important for evidence synthesis and decision making. However, they can be unstable and inconsistent due to diversity in research designs and variability in analytical specifications. They also mask the dynamics of individual responses to a certain intervention by focusing on average treatment effect on the treated, even though the variation in impact may be crucial information for policy makers. To establish stability and consistency of impact estimates and to reveal the dynamics of individual responses in RCTs, we conduct variable selection, harness the power of noise, implement Cumulative Quantile Analysis (CQA), and devise umbrella plots of loss and gain in this study, using real datasets from over 30 educational interventions funded by the Education Endowment Foundation (EEF) in England. For the purpose of comparison, which is essential in data visualisation, all the aforementioned methods are built upon multiple analytical approaches. We show that the importance of an intervention can be ordered through variable selection, and that the power of noise or the bias induced by inappropriate variables, can be utilised to assess the stability of an impact estimate. We also demonstrate that estimates of average treatment effect cannot fully capture the impact of an intervention on sub-groups of participants with varying levels of attainment at baseline, not to mention individual responses to the intervention. Using CQA and umbrella plots, we are able to supplement what common effect size estimates lack in educational interventions. We argue that the impact of an intervention is often more complex than the average treatment effect suggests, and that until a summary is more informative and able to speak directly to the eye, evidence-based policy and practice cannot be fully achieved.

scholarly journals Patients Retrieved to Intensive Care via a Dedicated Retrieval Service do not Have Increased Hospital Mortality Compared with Propensity-Matched Controls

2018 ◽  
Vol 46 (2) ◽  
pp. 202-206 ◽  
Author(s):  
P. T. Maclure ◽  
S. Gluck ◽  
A. Pearce ◽  
M. E. Finnis
Keyword(s):  
Intensive Care ◽  
Hospital Mortality ◽  
Treatment Effect ◽  
Diagnostic Category ◽  
Radial Distance ◽  
Adelaide Hospital ◽  
Average Treatment Effect ◽  
Royal Adelaide Hospital ◽  
Average Treatment ◽  
Apache Iii

This study was performed to estimate the effect of the retrieval process on mortality for patients admitted to a mixed adult intensive care unit (ICU) compared with propensity-matched, non-retrieved controls. Patients retrieved to the Royal Adelaide Hospital (RAH) ICU between 2011 and 2015 were propensity-score matched for age, gender, Aboriginal and Torres Strait Islander status, Acute Physiology and Chronic Health Evaluation (APACHE) III score and diagnostic group with non-retrieved ICU patients to estimate the average treatment effect of retrieval on hospital mortality. Factors associated with mortality in those retrieved were assessed by multiple logistic regression. Retrieved patients comprised 1,597 (14%) of 11,641 index ICU admissions; this group were younger, mean (standard deviation) 53 (18.5) versus 59 (17.7) years, had higher APACHE III scores, 61 (30.3) versus 56 (27.5), were more likely to be Indigenous (5.1% versus 3.7%) and to have sustained trauma (34% versus 9%). The average treatment effect for retrieval on hospital mortality, risk difference (95% confidence interval), was −0.7% (-2.8% to 1.3%), P=0.50. Variables independently associated with hospital mortality in those retrieved included age, APACHE III score and diagnostic category. Time from retrieval team activation to arrival with the patient, rural location, radial distance from the RAH and population size at the retrieval location were not significantly associated with mortality. The hospital mortality for retrieved patients was not significantly different when compared with propensity-matched controls. Mortality in those retrieved was associated with increasing age, APACHE III score and diagnostic category; however, was independent of time from team activation to arrival with the patient.

scholarly journals Evaluación de impacto académico y social en egresados universitarios

2019 ◽  
Vol 30 (3) ◽  
pp. 695-712
Author(s):  
Gabriel González ◽  
Luisa Díez-Echavarría ◽  
Elkin Zapa ◽  
Danilo Eusse
Keyword(s):  
Treatment Effect ◽  
Average Treatment Effect ◽  
Educación Superior ◽  
Educacion Superior ◽  
Average Treatment

Las instituciones de educación superior deben formar a sus estudiantes según requerimientos del contexto en que se desenvuelven, ya que, sobre la base de su desempeño, es donde se medirá si las políticas de desarrollo socioeconómico son efectivas. Para lograrlo, es necesario identificar el impacto de esa educación en sus egresados, y hacer los ajustes necesarios que generen mejora continua. El objetivo de este artículo es estimar el impacto académico y social de egresados del Instituto Tecnológico Metropolitano – Medellín, a través de un análisis multivariado y la estimación del modelo Average Treatment Effect (ATE). Se encontró que la educación ofrecida a esta población ha generado un impacto académico, asociado a los estudios de actualización, y dos impactos sociales, asociados a la situación laboral y al nivel de ingresos percibidos por los egresados. Se recomienda usar esta metodología en otras instituciones, ya que suele arrojar resultados más informativos y precisos que los estudios tradicionales de caracterización, y se puede medir el efecto de cualquier estrategia.

The Effect of Extension Services and Credit on Agricultural Production in Bolivia, Peru, and Colombia

2021 ◽  
Author(s):  
Mateus C. R. Neves ◽  
Felipe De Figueiredo Silva ◽  
Carlos Otávio Freitas
Keyword(s):  
Travel Time ◽  
Treatment Effect ◽  
Agricultural Production ◽  
Treatment Effects ◽  
Geographic Information ◽  
Average Treatment Effect ◽  
Extension Services ◽  
Average Treatment ◽  
Andean Countries ◽  
Average Treatment Effects

In this paper we estimate the average treatment effect from access to extension services and credit on agricultural production in selected Andean countries (Bolivia, Peru, and Colombia). More specifically, we want to identify the effect of accessibility, here represented as travel time to the nearest area with 1,500 or more inhabitants per square kilometer or at least 50,000 inhabitants, on the likelihood of accessing extension and credit. To estimate the treatment effect and identify the effect of accessibility on these variables, we use data from the Colombian and Bolivian Agricultural Censuses of 2013 and 2014, respectively; a national agricultural survey from 2017 for Peru; and geographic information on travel time. We find that the average treatment effect for extension is higher compared to that of credit for farms in Bolivia and Peru, and lower for Colombia. The average treatment effects of extension and credit for Peruvian farms are $2,387.45 and $3,583.42 respectively. The average treatment effect for extension and credit are $941.92 and $668.69, respectively, while in Colombia are $1,365.98 and $1,192.51, respectively. We also find that accessibility and the likelihood of accessing these services are nonlinearly related. Results indicate that higher likelihood is associated with lower travel time, especially in the analysis of credit.

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