The development of the ADO-SQ model to predict 1-year mortality in patients with COPD

Background: Goals of end-of-life care must be adapted to the needs of patients with chronic obstructive pulmonary disease (COPD) who are in the last phase of life. However, identification of those patients is limited by moderate performances of existing prognostic models and by limited validation of the often-recommended surprise question. Aim: To develop a clinical prediction model to predict 1-year mortality in patients with COPD. Design: Prospective study using logistic regression to develop a model in two steps: (1) external validation of the ADO, BODEX, or CODEX models (A = age; B = body mass index; C = comorbidity; D = dyspnea; EX = exacerbations; O = airflow obstruction); (2) updating of best performing model and extending it with the surprise question. Discriminative performance of the new model was assessed using internal-external validation and measured with area under the curve (AUC). A nomogram and web application were developed. Settings/participants: Patients with COPD from five hospitals (September–November 2017). Results: Of the 358 included patients (median age 69.5 years, 50% male), 63 (17%) died within a year. The ADO index (AUC 0.73) had the best discriminative ability compared to the BODEX (AUC 0.71) or CODEX (AUC 0.68), and was extended with the surprise question. The resulting ADO-surprise question (SQ) model had an AUC of 0.79. Conclusion: The ADO-SQ model offers improved discriminative performance for predicting 1-year mortality compared to the surprise question, ADO, BODEX, or CODEX. A user-friendly nomogram and web application (https://dnieboer.shinyapps.io/copd) were developed. Further external validation of the ADO-SQ in patient groups is needed

Heat and emergency room admissions in the Netherlands

Background: Due to a global warming-related increase in heatwaves, it is important to obtain detailed understanding of the relationship between heat and health. We assessed the relationship between heat and urgent emergency room admissions in the Netherlands.Methods: We collected daily maximum temperature and relative humidity data over the period 2002–2007. Daily urgent emergency room admissions were divided by sex, age group and disease category. We used distributed lag non-linear Poisson models, estimating temperature-admission associations. We estimated the relative risk (RR) for urgent hospital admissions for a range of temperatures compared to a baseline temperature of 21 °C. In addition, we compared the impact of three different temperature scenarios on admissions using the RR.Results: There is a positive relationship between increasing temperatures above 21 °C and the RR for urgent emergency room admissions for the disease categories 'Potential heat-related diseases' and 'Respiratory diseases'. This relationship is strongest in the 85+ group. The RRs are strongest for lag 0. For admissions for 'circulatory diseases', there is only a small significant increase of RRs within the 85+ age group for moderate heat, but not for extreme heat. The RRs for a one-day event with extreme heat are comparable to the RRs for multiple-day events with moderate heat.Conclusions: Hospitals should adjust the capacity of their emergency departments on warm days, and the days immediately thereafter. The elderly in particular should be targeted through prevention programmes to reduce harmful effects of heat. The fact that this increase in admissions already occurs in temperatures above 21 °C is different from previous findings in warmer countries. Given the similar impact of three consecutive days of moderate heat and one day of extreme heat on admissions, criteria for activation of national heatwave plans need adjustments based on different temperature scenarios