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Which patients with advanced respiratory disease die in hospital? A 14-year population-based study of trends and associated factors

Overview of attention for article published in BMC Medicine, February 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)

Mentioned by

6 news outlets
1 blog
95 tweeters


24 Dimensions

Readers on

48 Mendeley
Which patients with advanced respiratory disease die in hospital? A 14-year population-based study of trends and associated factors
Published in
BMC Medicine, February 2017
DOI 10.1186/s12916-016-0776-2
Pubmed ID

Irene J. Higginson, Charles C. Reilly, Sabrina Bajwah, Matthew Maddocks, Massimo Costantini, Wei Gao


Strategies in many countries have sought to improve palliative care and reduce hospital deaths for non-cancer patients, but their effects are not evaluated. We aimed to determine the trends and factors associated with dying in hospital in two common progressive respiratory diseases, and the impact of a national end of life care (EoLC) strategy to reduce deaths in hospital. This population-based observational study linked death registration data for people in England dying from chronic obstructive pulmonary disease (COPD) or interstitial pulmonary diseases (IPD). We plotted age- and sex-standardised trends, assessed during the pre-strategy (2001-2004), first strategy phase (2004-2008), and strategy intensification (2009-2014) periods, and identified factors associated with hospital death using multiple adjusted proportion ratios (PRs). Over 14 years, 380,232 people died from COPD (334,520) or IPD (45,712). Deaths from COPD and IPD increased by 0.9% and 9.2% annually, respectively. Death in hospital was most common (67% COPD, 70% IPD). Dying in hospice was rare (0.9% COPD, 2.9% IPD). After a plateau in 2004-2005, hospital deaths fell (PRs 0.92-0.94). Co-morbidities and deprivation independently increased the chances of dying in hospital, with larger effects in IPD (PRs 1.01-1.55) than COPD (PRs 1.01-1.39) and dose-response gradients. The impact of multimorbidity increased over time; hospital deaths did not fall for people with two or more co-morbidities in COPD, nor one or more in IPD. Living in rural areas (PRs 0.94-0.94) or outside London (PRs, 0.89-0.98) reduced the chances of hospital death. In IPD, increased age reduced the likelihood of hospital death (PR 0.81, ≥ 85 versus ≤ 54 years); divergently, in COPD, being aged 65-74 years was associated with increased hospital deaths (PR 1.13, versus ≤ 54 years). The independent effects of sex and marital status differed for COPD versus IPD (PRs 0.89-1.04); in COPD, hospital death was associated with being married. The EoLC strategy appeared to have contributed to tangible reductions in hospital deaths, but did not reach people with multimorbidity and this gap widened over time. Integrating palliative care earlier in the disease trajectory especially in deprived areas and cities, and where multimorbidity is present, should be boosted, taking into account the different demographic factors in COPD and IPD.

Twitter Demographics

The data shown below were collected from the profiles of 95 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 11 23%
Student > Master 9 19%
Researcher 7 15%
Student > Bachelor 5 10%
Student > Postgraduate 4 8%
Other 12 25%
Readers by discipline Count As %
Medicine and Dentistry 18 38%
Unspecified 15 31%
Nursing and Health Professions 6 13%
Agricultural and Biological Sciences 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 4 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 109. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 September 2018.
All research outputs
of 13,655,079 outputs
Outputs from BMC Medicine
of 2,158 outputs
Outputs of similar age
of 346,795 outputs
Outputs of similar age from BMC Medicine
of 2 outputs
Altmetric has tracked 13,655,079 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,158 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.0. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 346,795 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them