Evidence map›Paper›PMID 37009165›Full record

ArticleTransplantation direct2023

Selecting DCD Recipients Using Predictive Indices.

Saif Ganni, Greta Handing, Adrish Anand, Spencer Barrett, Nhu Thao Nguyen Galvan, Christine O'Mahony, John A Goss, Ronald T Cotton, Abbas Rana

Open access · goldAbstract read
In one paragraph

Article in Transplantation direct, 2023. 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
–field-weighted citation impact, top 94% 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, 0 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

9 authors at 1 institution in 1 country.

Saif GanniDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
Greta HandingDepartment of Student Affairs, Baylor College of Medicine, Houston, TX.
Adrish AnandDepartment of Student Affairs, Baylor College of Medicine, Houston, TX.
Spencer BarrettDepartment of Student Affairs, Baylor College of Medicine, Houston, TX.
Nhu Thao Nguyen GalvanDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
Christine O'MahonyDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
John A GossDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
Ronald T CottonDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
Abbas RanaDivision of Abdominal Transplant, Department of Surgery, Michael E DeBakey, Houston, TX.
Baylor College of Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Donation after circulatory death (DCD) allografts might represent one of the largest untapped sources of liver allografts. Our aim was to identify independent recipient risk factors that predict mortality in DCD allograft recipients to preselect optimal candidates for successful transplantation. Furthermore, we compared the application of our newly constructed DCD Recipient Selector Index (RSI) score to previously developed models to determine superiority in predicting recipient survival. Methods: Using the Organ Procurement and Transplantation Network database, we performed univariate and multivariate retrospective analyses on 4228 DCD liver allograft recipients. Results: We identified 8 significant factors and incorporated them into the weighted RSI to predict 3-mo survival following DCD liver transplantation with a C-statistic of 0.6971. The most significant recipient risk factors were recipient serum sodium levels >150 mEq/L at transplant, recipient albumin <2.0 g/dL at transplant, and a history of portal vein thrombosis. Because Model for End-Stage Liver Disease (MELD) score components were included as individual predictors, the DCD RSI predicts survival independently of MELD. Upon comparison with 3 previous recipient risk scores-Balance of Risk, Renal Risk Index, Patient-Survival Outcomes Following Liver Transplantation-the DCD RSI was determined to be superior at selecting optimal candidates pre-DCD transplantation, yielding a C-statistic of 0.6971. Conclusions: After verifying the performance of predictive indices for selection of DCD recipients, the DCD RSI is best used to preselect patients for optimized outcomes after DCD transplantation. This can increase utilization of DCD donors by improving outcomes.

Identifiers

PMID37009165
PMCPMC10065835
OpenAlexW4361269630

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.