Clinical epidemiology
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Aim of database: The aim of DANARREST is to collect data on processes of care and outcomes for patients with in-hospital cardiac arrest in Denmark, and thereby facilitate and monitor quality and quality improvement initiatives. Study population: In-hospital cardiac arrest patients with a clinical indication for cardiopulmonary resuscitation in Denmark. Main variables: DANARREST includes a number of descriptive variables as well as seven quality of care indicators; four related to processes of care and three related to clinical outcomes. ⋯ As of 2017, 95% of relevant hospitals are reporting data with an estimated coverage rate of approximately 80%. Conclusion: DANARREST is a relatively new national registry of in-hospital cardiac arrests in Denmark, with a high coverage rate. The registry provides an opportunity to monitor and improve quality of care for patients with in-hospital cardiac arrest.
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Clinical epidemiology · Jan 2019
Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data.
Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. ⋯ The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15-80 years old diagnosed with colon cancer in 2001-2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use.
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Clinical epidemiology · Jan 2018
ReviewMortality in people with dementia, delirium, and unspecified cognitive impairment in the general hospital: prospective cohort study of 6,724 patients with 2 years follow-up.
Cognitive impairment is common in older people admitted to hospital, but the outcomes are generally poorly understood, and previous research has shown inconsistent associations with mortality depending on the type of cognitive impairment examined and duration of follow-up. This study examines mortality in older people with any cognitive impairment during acute hospital admission. ⋯ Mortality post-admission is high in older people with CSD. Immediate risk is highest in those with delirium, while dementia or unspecified cognitive impairment is associated with medium- to long-term risk. These findings suggest that individuals without dementia who develop delirium are more seriously ill (have required a larger acute insult in order to precipitate delirium) than those with pre-existing brain pathology (dementia). Further research to explain the mortality patterns observed is required in order to translate the findings into clinical care.
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Clinical epidemiology · Jan 2018
Replacing sedentary time with physical activity: a 15-year follow-up of mortality in a national cohort.
Sedentary behavior is associated with health risks in adults. The potential benefits of reducing sedentary time may be dependent not only on decrease per se, but also on the type of activity it replaces. Few longitudinal studies have investigated the effects on mortality when replacing objectively assessed sedentary time with another physical activity (PA) behavior. ⋯ This statistical modelling study suggests that replacing sedentary time with light-intensity PA could have beneficial effect on both all-cause mortality and CVD mortality. Replacing sedentary time with MVPA could reduce CVD mortality.
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Clinical epidemiology · Jan 2017
Prediction models for the mortality risk in chronic dialysis patients: a systematic review and independent external validation study.
In medicine, many more prediction models have been developed than are implemented or used in clinical practice. These models cannot be recommended for clinical use before external validity is established. Though various models to predict mortality in dialysis patients have been published, very few have been validated and none are used in routine clinical practice. The aim of the current study was to identify existing models for predicting mortality in dialysis patients through a review and subsequently to externally validate these models in the same large independent patient cohort, in order to assess and compare their predictive capacities. ⋯ Overall, the performance of the models was poorer in the external validation than in the original population, affirming the importance of external validation. Floege et al's models showed the highest predictive performance. The present study is a step forward in the use of a prediction model as a useful tool for nephrologists, using evidence-based medicine that combines individual clinical expertise, patients' choices, and the best available external evidence.