Evidence map›Paper›PMID 25757530›Full record

ArticleInternal and emergency medicine2015

Use of a risk nomogram to predict emergency department reattendance in older people after discharge: a validation study.

Glenn Arendts, Christopher Etherton-Beer, Roslyn Jones, Kate Bullow, Ellen MacDonald, Sandra Dumas, Daniel Parker, Marani Hutton, Sally Burrows, Simon G A Brown and 1 more

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Internal and emergency medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Observational
  4. Article
  5. Article
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

11 authors.

Glenn ArendtsUniversity of Western Australia, Crawley, Australia, glenn.arendts@uwa.edu.au.
Christopher Etherton-Beer
Roslyn Jones
Kate Bullow
Ellen MacDonald
Sandra Dumas
Daniel Parker
Marani Hutton
Sally Burrows
Simon G A Brown
Osvaldo P Almeida

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In older people, revisit to the emergency department (ED) in the short period after discharge is not entirely avoidable, but in a proportion of cases is preventable, and should ideally be minimised. We have previously derived a risk probability nomogram to predict the likelihood of revisit. In this study, we sought to validate the nomogram for use as a general risk stratification tool for use in older people being discharged from ED. We conducted a prospective cohort study, applying the nomogram to consecutive community dwelling discharged patients aged 65 and over. Patients were followed up at 28 days post-discharge to determine whether there had been any unplanned ED revisit in that period. We cross tabulated predicted risk versus revisit rates. In 1143 study subjects, we find the odds of revisit increases progressively with increasing strata of predicted risk, culminating in an OR of 9.7 (95% CI 4.7-19.9) in the highest risk group. The 28-day revisit rates across strata range from 16% through 65%, with the difference between strata being statistically highly significant (p < 0.001). The area under the ROC curve is 0.65. We conclude that the risk nomogram can classify older people discharged from ED into risk strata, and has modest overall predictive value.

Indexed as

Emergency Service, HospitalNomogramsPatient ReadmissionAgedAged, 80 and overFemaleHumansMalePredictive Value of TestsProspective StudiesRisk AssessmentROC Curve

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.