After an extensive survey of the medical literature we present compelling evidence that the first intensive care unit was established at Kommunehospitalet in Copenhagen in December 1953. The pioneer was the Danish anaesthetist Bjørn Ibsen. The many factors that interacted favourably in Copenhagen to promote the idea of intensive care therapy, half a century ago, are also described.
A severe hemorrhage can result in death within minutes, before professional first responders have time to arrive. Thus, intervention by bystanders, who may lack medical training, may be necessary to save a victim’s life in situations with bleeding injuries. Proper intervention requires that bystanders accurately assess the severity of the injury and respond appropriately. As many bystanders lack tools and training, they are limited in terms of the information they can use in their evaluative process. In hemorrhage situations, visible blood loss may serve as a dominant cue to action. Therefore, understanding how medically untrained bystanders (i.e., laypeople) perceive hemorrhage is important. The purpose of the current study was to investigate the ability of laypeople to visually assess blood loss and to examine factors that may impact accuracy and the classification of injury severity. A total of 125 laypeople watched 78 short videos each of individuals experiencing a hemorrhage. Victim gender, volume of blood lost, and camera perspective were systematically manipulated in the videos. The results revealed that laypeople overestimated small volumes of blood loss (from 50 to 200 ml), and underestimated larger volumes (from 400 to 1900 ml). Larger volumes of blood loss were associated with larger estimation errors. Further, blood loss was underestimated more for female victims than male victims and their hemorrhages were less likely to be classified as life-threatening. These results have implications for training and intervention design.
Visual blood loss estimation occurs in a variety of medical contexts and may impact everything from interventions by immediate responders to the likelihood of receiving blood transfusions in a hospital setting. However, research suggests that visual blood loss estimation is inaccurate for laypeople and medical professionals. The aim of the current study was to conduct a systematic literature review to determine the current state of knowledge on visual blood loss estimation accuracy and identify directions for future research. A structured search resulted in 1799 titles that were subsequently screened. A total of 72 articles were coded for comparison. Based on the evaluation, several gaps were identified, most notably related to factors of the situation that may influence estimation accuracy such as blood flow and victim/patient gender. Directions for future research are proposed based on identified gaps.
Introduction:Assessing disaster preparedness in a given region is a complex problem. Current methods are often resource-intensive and may lack generalizability beyond a specific scenario. Computer-based stochastic simulations may be an additional method but would require systems that are valid, flexible, and easy to use. Emergo Train System (ETS) is an analog simulation system used for disaster preparedness assessments.Aim:To digitalize the ETS model and develop stochastic simulation software for improved disaster preparedness assessments.Methods:A simulation software was developed in C#. The simulation model was based on ETS. Preliminary verification and validation (V&V) tests were performed, including unit and integration testing, trace validation, and a comparison to a prior analog ETS disaster preparedness assessment exercise.Results:The software contains medically validated patients from ETS and is capable of automatically running disaster scenarios with stochastic variations in the injury panorama, available resources, geographical location, and other variables. It consists of two main programs: an editor where scenarios can be constructed and a simulation system to evaluate the outcome. Initial V&V testing showed that the software is reliable and internally consistent. The comparison to the analog exercise showed a general high agreement in terms of patient outcome. The analog exercise featured a train derailment with 397 injured, of which 45 patients suffered preventable death. In comparison, the computer simulation ran 100 iterations of the same scenario and indicated that a median of 41 patients (IQR 31 to 44) would suffer a preventable death.Discussion:Stochastic simulation methods can be a powerful complement to traditional capability assessments methods. The developed simulation software can be used for both assessing emergency preparedness with some validity and as a complement to analog capability assessment exercises, both as input and to validate results. Future work includes comparing the simulation to real disaster outcomes.
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