How do hospitalised children die? The context of death and end-of-life decision-making

Aim

The decrease in childhood mortality, the growing clinical complexity and the greater technification of intensive care units have changed the circumstances of death of paediatric patients. The aim of this study is to describe the context of death and end-of-life decision-making.

Methods

Single-centre, retrospective, observational study of deaths in inpatients or home hospitalised children under 18 years old between 2011 and 2021. Demographic data, pathological history and circumstances of death were obtained from the medical record. The whole study period was divided into two halves for the analysis of the temporal trends.

Results

A total of 358 patients died, 63.2% under the age of 1 year old; 86.9% had underlying life-limiting illnesses and 73.2% died in the intensive care unit, with no differences between the two time periods. Death at home was significantly higher in the second study period (3.8% vs. 9%). A total of 20.1% died during advanced cardiopulmonary resuscitation. Life-sustaining treatment was withheld or withdrawn in 53.6%, with no differences between the time courses. Life-sustaining treatment was withheld mainly in patients with neurological, metabolic and oncological conditions, and less frequently in patients with cardiovascular or respiratory diseases or who were previously healthy. Most patients coded as palliative care (PC) or followed up by PC teams had an advance care plan (ACP) recorded, while in the others it was infrequent. PC coding, following by PC teams and ACP recording increased in the last years of the study.

Conclusions

Death of children in our setting usually occurs in relation to complex underlying pathology and after the decision of withdrawing or withholding life-sustaining treatment. In this context, PC and ACP acquire greater importance. In our study, PC involvement resulted in better documentation of ACP and PC coding.     

Quantifying Distance Overestimation From Global Positioning System in Urban Spaces

Objectives. To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City.Methods. We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System–measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk.Results. GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy).Conclusions. Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques.Global Positioning System (GPS) monitoring to study physical activity and mobility1,2 has spawned 2 threads of methodological research. One thread has established that buildings and trees can impede the space that the GPS signal must travel between a subject’s device and satellites, interfering with accuracy.3–8 Another has developed algorithms that link consecutive GPS points to identify transport mode.9–11 However, because buildings and trees vary by spatial context and may influence mode choice and physical activity,12–14 studies of the built environment and transport mode or activity may be systematically biased as a result of GPS error. We investigated accuracy of distance measures computed from GPS points in a variety of building height and tree canopy conditions.