Evidence map›Paper›PMID 26597917›Full record

ArticleCritical care (London, England)2015

Intensive care at the end of life in patients dying due to non-cancer chronic diseases versus cancer: a nationwide study in Denmark.

Thomas Lyngaa, Christian Fynbo Christiansen, Henrik Nielsen, Mette Asbjørn Neergaard, Anders Bonde Jensen, Kristina Grønborg Laut, Søren Paaske Johnsen

Open access · goldAbstract readComparative Study
In one paragraph

Article in Critical care (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

14 citing papers in PubMed, 30 citations in OpenAlex.

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  13. End-of-Life Care Patterns by Disease Trajectory in Pediatric Intensive Care Units: A Multicenter Study.Pediatrics international : official journal of the Japan Pediatric Society
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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

7 authors at 2 institutions in 2 countries.

Thomas LyngaaDepartment of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus, Denmark. thomaslyngaa@gmail.com.
Christian Fynbo ChristiansenDepartment of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus, Denmark. cfc@clin.au.dk.
Henrik NielsenDepartment of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus, Denmark. hn@clin.au.dk.
Mette Asbjørn NeergaardDepartment of Oncology, Aarhus University Hospital, Aarhus, Denmark. mettneer@rm.dk.
Anders Bonde JensenDepartment of Oncology, Aarhus University Hospital, Aarhus, Denmark. andjense@rm.dk.
Kristina Grønborg LautDivision of Epidemiology & Biostatistics, University of Leeds, Leeds, UK. kristina@laut.dk.
Søren Paaske JohnsenDepartment of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus, Denmark. spj@clin.au.dk.
Aarhus University Hospital · DKUniversity of Leeds · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIt is unknown to what extent use of palliative care and focus on proactive planning of end-of-life (EOL) care among cancer patients is also reflected by less use of intensive care. We aimed to examine the use of intensive care in the EOL in patients dying as a result of non-cancer diseases compared with patients dying due to cancer.

methodsWe conducted a nationwide follow-up study among 240,757 adults dying as a result of either non-cancer chronic disease or cancer in Denmark between 2005 and 2011. Using the Danish Intensive Care Database, we identified all admissions and treatments in intensive care units (ICU) during the patients' last 6 months before death. We used prevalence ratios (aPRs) adjusted for age, sex, comorbidity, marital status and residential region to compare the 6-month prevalence of ICU admissions as well as treatment with invasive mechanical ventilation (MV), non-invasive ventilation (NIV), renal replacement therapy (RRT) and inotropes and/or vasopressors. In addition, length of ICU stay and death during ICU admission were compared among non-cancer and cancer patients dying between 2009 and 2011.

resultsOverall 12.3 % of non-cancer patients were admitted to an ICU within their last 6 months of life, compared with 8.7 % of cancer patients. The overall aPR for ICU admission was 2.11 [95 % confidence interval (CI) 1.98-2.24] for non-cancer patients compared with cancer patients and varied widely within the non-cancer patients (patients with dementia, aPR 0.19, 95 % CI 0.17-0.21; patients with chronic obstructive lung disease, aPR 3.19, 95 % CI 2.97-3.41). The overall aPRs for treatment among non-cancer patients compared with cancer patients were 1.40 (95 % CI 1.35-1.46) for MV, 1.62 (95 % CI 1.50-1.76) for NIV, 1.19 (95 % CI 1.07-1.31) for RRT and 1.05 (95 % CI 0.87-1.28) for inotropes and/or vasopressors. No difference in admission length was observed. Non-cancer patients had an increased risk of dying in an ICU (aPR 1.23, 95 % CI 0.99-1.54) compared with cancer patients.

conclusionsOverall, patients dying as a result of non-cancer diseases were twice as likely to be admitted to ICUs at the EOL as patients dying due to cancer. Further studies are warranted to explore whether this difference in use of intensive care reflects an unmet need of palliative care, poor communication about the EOL or lack of prognostic tools for terminally ill non-cancer patients.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsChronic DiseaseComorbidityCritical CareDenmarkFemaleHumansIntensive Care UnitsMaleMarital StatusMiddle AgedNeoplasms

Identifiers

PMID26597917
PMCPMC4657209
OpenAlexW2175553062

What OpenQuestion holds

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LicenceCC BY
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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.