Evidence map›Paper›PMID 23462889›Full record

ArticleInternal and emergency medicine2013

Derivation of a nomogram to estimate probability of revisit in at-risk older adults discharged from the emergency department.

Glenn Arendts, Sarah Fitzhardinge, Karren Pronk, Marani Hutton, Yusuf Nagree, Mark Donaldson

Abstract read
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In one paragraph

Article in Internal and emergency medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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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

6 authors at 4 institutions in 1 country.

Glenn ArendtsCentre for Clinical Research in Emergency Medicine CCREM, Western Australian Institute for Medical Research, Level 5 MRF Building, Rear 50 Murray St, Perth, WA 6000, Australia. glenn.arendts@uwa.edu.au
Sarah Fitzhardinge
Karren Pronk
Marani Hutton
Yusuf Nagree
Mark Donaldson
University of Western Australia · AUHarry Perkins Institute of Medical Research · AUNorth Metropolitan Health Service · AURoyal Perth Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Estimation of the risk of revisit to the emergency department (ED) soon after discharge in the older population may assist discharge planning and targeting of post discharge intervention in high risk patients. In this study we sought to derive a risk prediction calculator for this purpose. In a prospective observational study in two tertiary ED, we conducted a comprehensive assessment of people aged 65 and over, and followed them for a minimum of 28 days post discharge. Cox proportional hazard models relating any unplanned ED revisit in the follow up period to observed risk factors were used to compute a probability nomogram. From 1,439 patients, 189 (13.1 %) had at least one unplanned revisit within 28 days. Revisit probability was weighted towards chronic and difficult to modify risk factors such as depression, malignancy and cognitive impairment. We conclude that the risk of revisit post discharge is calculable using a probability nomogram. However, revisit is largely related to immutable factors reflecting chronic illness burden, and does not necessarily reflect poor ED care during the initial index presentation.

Indexed as

Emergency Service, HospitalNomogramsPatient DischargePatient ReadmissionAgedAged, 80 and overAge FactorsFemaleGeriatric AssessmentHumansMaleProspective StudiesRisk Factors

Identifiers

PMID23462889
OpenAlexW1987864939

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.