Evidence map›Paper›PMID 28790815›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2017

Development of the ProPal-COPD tool to identify patients with COPD for proactive palliative care.

R G Duenk, C Verhagen, E M Bronkhorst, R S Djamin, G J Bosman, E Lammers, Pnr Dekhuijzen, Kcp Vissers, Y Engels, Y Heijdra

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 4 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

18 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  14. Preferences for Predictive Model Characteristics among People Living with Chronic Lung Disease: A Discrete Choice Experiment.Medical decision making : an international journal of the Society for Medical Decision Making · 2020
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

R G DuenkDepartment of Anesthesiology, Pain and Palliative Medicine.
C VerhagenDepartment of Anesthesiology, Pain and Palliative Medicine.
E M BronkhorstDepartment of Health Evidence, Radboud University Medical Center, Nijmegen.
R S DjaminDepartment of Respiratory Medicine, Amphia Hospital, Breda.
G J BosmanDepartment of Respiratory Medicine, Slingeland Hospital, Doetinchem.
E LammersDepartment of Respiratory Medicine, Gelre Hospitals, Zutphen.
Pnr DekhuijzenDepartment of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
Kcp VissersDepartment of Anesthesiology, Pain and Palliative Medicine.
Y EngelsDepartment of Anesthesiology, Pain and Palliative Medicine.
Y HeijdraDepartment of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur objective was to develop a tool to identify patients with COPD for proactive palliative care. Since palliative care needs increase during the disease course of COPD, the prediction of mortality within 1 year, measured during hospitalizations for acute exacerbation COPD (AECOPD), was used as a proxy for the need of proactive palliative care. PATIENTS AND

methodsPatients were recruited from three general hospitals in the Netherlands in 2014. Data of 11 potential predictors, a priori selected based on literature, were collected during hospitalization for AECOPD. After 1 year, the medical files were explored for the date of death. An optimal prediction model was assessed by Lasso logistic regression, with 20-fold cross-validation for optimal shrinkage. Missing data were handled using complete case analysis.

resultsOf 174 patients, 155 patients were included; of those 30 (19.4%) died within 1 year. The optimal prediction model was internally validated and had good discriminating power (AUC =0.82, 95% CI 0.81-0.82). This model relied on the following seven predictors: the surprise question, Medical Research Council dyspnea questionnaire (MRC dyspnea), Clinical COPD Questionnaire (CCQ), FEV

conclusionThe ProPal-COPD tool is a promising multivariable prediction tool to identify patients with COPD for proactive palliative care.

Indexed as

Clinical Decision-MakingDecision Support TechniquesPalliative CareAgedArea Under CurveBody Mass IndexComorbidityFemaleForced Expiratory VolumeHospitals, GeneralHumansLogistic ModelsLungMaleMiddle AgedMultivariate AnalysisCOPDexacerbationmortalityproactive palliative careprognosis

Identifiers

PMID28790815
PMCPMC5530053

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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.