Evidence map›Paper›PMID 30236103›Full record

ArticleBMC medicine2018

Frailty trajectories to identify end of life: a longitudinal population-based study.

Daniel Stow, Fiona E Matthews, Barbara Hanratty

Abstract read
In one paragraph

Article in BMC medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Frailty, polypharmacy, deprescribing, and 23-hour activity: insights from a mouse model.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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  10. Associations of summary measures of longitudinal frailty assessments with health outcomes.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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  16. Application of Pragmatic Criteria to Assessments of Frailty and Physical Function Among People With HIV.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Daniel StowInstitute of Health and Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK.
Fiona E MatthewsInstitute of Health and Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK.
Barbara HanrattyInstitute of Health and Society, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK. barbara.hanratty@newcastle.ac.uk.ORCID 0000-0002-3122-7190

Funding

Medical Research Council MC_U105292687
6 · The paper itself

Abstract

backgroundTimely recognition of the end of life allows patients to discuss preferences and make advance plans, and clinicians to introduce appropriate care. We examined changes in frailty over 1 year, with the aim of identifying trajectories that could indicate where an individual is at increased risk of all-cause mortality and may require palliative care.

methodsElectronic health records from 13,149 adults (cases) age 75 and over who died during a 1-year period (1 January 2015 to 1 January 2016) were age, sex and general practice matched to 13,149 individuals with no record of death over the same period (controls). Monthly frailty scores were obtained for 1 year prior to death for cases, and from 1 January 2015 to 1 January 2016 for controls using the electronic frailty index (eFI; a cumulative deficit measure of frailty, available in most English primary care electronic health records, and ranging in value from 0 to 1). Latent growth mixture models were used to investigate longitudinal patterns of change and associated impact on mortality. Cases were reweighted to the population level for tests of diagnostic accuracy.

resultsThree distinct frailty trajectories were identified. Rapidly rising frailty (initial increase of 0.022 eFI per month before slowing from a baseline eFI of 0.21) was associated with a 180% increase in mortality (OR 2.84, 95% CI 2.34-3.45) for 2.2% of the sample. Moderately increasing frailty (eFI increase of 0.007 per month, with baseline of 0.26) was associated with a 65% increase in mortality (OR 1.65, 95% CI 1.54-1.76) for 21.2% of the sample. The largest (76.6%) class was stable frailty (eFI increase of 0.001 from a baseline of 0.26). When cases were reweighted to population level, rapidly rising frailty had 99.1% specificity and 3.2% sensitivity (positive predictive value 19.8%, negative predictive value 93.3%) for predicting individual risk of mortality.

conclusionsPeople aged over 75 with frailty who are at highest risk of death have a distinctive frailty trajectory in the last 12 months of life, with a rapid initial rise from a low baseline, followed by a plateau. Routine measurement of frailty can be useful to support clinicians to identify people with frailty who are potential candidates for palliative care, and allow time for intervention.

Indexed as

Frail ElderlyFrailtyAgedAged, 80 and overElectronic Health RecordsFemaleGeriatric AssessmentHumansMaleTerminal CareEnd of lifeFrailtyGeriatricsPalliative carePrimary care

Identifiers

PMID30236103
PMCPMC6148780

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.