Evidence map›Paper›PMID 29470348›Full record

ArticleTransplantation2018

Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database.

Yvette OʼBrien, Shaila Chavan, Sue Huckson, Graeme Russ, Helen Opdam, David Pilcher

Open access · hybridAbstract read
In one paragraph

Article in Transplantation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 countries.

Yvette OʼBrienDepartment of Intensive Care Medicine, The Alfred Hospital, Commercial Road, Prahran, VIC, Australia.
Shaila ChavanThe Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE), Ievers Terrace, Carlton, VIC, Australia.
Sue HucksonThe Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE), Ievers Terrace, Carlton, VIC, Australia.
Graeme RussThe Australian and New Zealand Organ Donation Registry, Adelaide, SA, Australia.
Helen OpdamThe Australian Organ and Tissue Authority, London Circuit Canberra, ACT, Australia.
David PilcherDepartment of Intensive Care Medicine, The Alfred Hospital, Commercial Road, Prahran, VIC, Australia.
Australian and New Zealand Intensive Care Society · AUThe Alfred Hospital · AUAustin Hospital · AUAustralia and New Zealand Dialysis and Transplant Registry · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe majority of organ donations in Australia occur in the DonateLife Network of hospitals, but limited monitoring at other sites may allow donation opportunities to be missed. Our aim was to estimate expected donor numbers using routinely collected data from the Australian and New Zealand Intensive Care Society Adult Patient Database and determine whether unrecognized potential donors might exist in non-DonateLife hospitals.

methodsAll deaths at 150 Australian intensive care units (ICUs) contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database were analyzed between January 2010 and December 2015. Donor numbers were extracted from the Australian and New Zealand Organ Donor registry. A univariate linear regression model was developed to estimate expected donor numbers in DonateLife hospitals, then applied to non-DonateLife hospitals.

resultsOf 33 614 deaths at 71 DonateLife hospitals, 6835 (20%) met criteria as "ICU deaths potentially suitable to be donors," and 1992 (6%) were actual donors. There was a consistent relationship between these groups (R = 0.626, P < 0.001) allowing the development of a prediction model which adequately estimated expected donors. Of 8077 deaths in 79 non-DonateLife ICUs, 452 (6%) met criteria as potentially suitable donors. Applying the prediction model developed in DonateLife hospitals, the estimated expected donors in non-DonateLife hospitals was 130. However, there were only 75 actual donors.

conclusionsIt is possible to estimate the expected number of Australian organ donors using routinely collected registry data. These findings suggest that there may be a small but significant pool of underutilized potential donors in non-DonateLife hospitals. This may provide an opportunity to increase donation rates.

Indexed as

Organ TransplantationTissue DonorsAdolescentAdultAgedAlgorithmsAustraliaCritical CareDatabases, FactualDeathHospitalsHumansIntensive Care UnitsLinear ModelsMiddle AgedNew Zealand

Identifiers

PMID29470348
PMCPMC6072376
OpenAlexW2792338785

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.