Evidence map›Paper›PMID 34923657›Full record

Observational studyClinical transplantation2022

Benefits of both physical assessment and electronic health record review to assess frailty prior to heart transplant.

Yoon Kyung Lee, Marina Shukman, Reshma Biniwale, Abbas Ardehali, Megan Kamath, Ali Nsair, Joanna M Schaenman, Deena Goldwater

Abstract readObservational Study
In one paragraph

Observational study in Clinical transplantation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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

  1. Article
  2. Article
  3. Article
  4. Cellular Senescence and Frailty in Transplantation.Current transplantation reports · 2023
    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

8 authors.

Yoon Kyung LeeDavid Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Marina ShukmanDivision of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Reshma BiniwaleDepartment of Cardiothoracic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Abbas ArdehaliDepartment of Cardiothoracic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Megan KamathDivision of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Ali NsairDivision of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Joanna M SchaenmanDivision of Infectious Diseases, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.ORCID 0000-0003-1174-3961
Deena GoldwaterDivision of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.ORCID 0000-0001-5722-9939

Funding

UCLA Summer Research Training in Aging for Medical Stud*T35AG026736 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Cathy Lee, John C Newman · 2005 to 2026
$3.0M
Evaluation of Epigenetic Markers of Biologic Age to Predict Adverse Outcomes after TransplantationR21AG055879 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SCHAENMAN, JOANNA M · 2018 to 2019
$429k
NIA NIH HHS R21 AG055879NIA NIH HHS T35 AG026736
6 · The paper itself

Abstract

introductionFrailty status affects outcomes after heart transplantation, but the optimal way to assess frailty prior to transplant remains unknown.

methodsThis single-center, observational study assessed 44 heart transplant candidates for frailty using three methods. The Short Physical Performance Battery (SPPB) and Fried Frailty Phenotype (FFP) were used as two physical assessments of frailty. The Frailty Risk Score (FRS) was used as a chart-review based assessment measuring 20 different biopsychosocial and functional components, including biomarkers, depression, cognitive impairment, and sleep.

resultsWe determined the correlation between FRS, SPPB, and FFP and how each correlated with clinical outcomes. Of 44 participants, mean age was 60 years. FRS correlated with SPPB and FFP (P = .043, P < .001, respectively). Higher frailty as measured by SPPB and FRS was significantly associated with lack of achieving waitlist status (P = .022; P = .002) and not being transplanted (P = .026; P = .008). Higher frailty by SPPB and FFP was also associated with mortality (P = .010; P = .025).

conclusionSPPB and chart-review FRS showed potential for predicting waitlist and transplant status of heart transplant candidates, while SPPB and FFP were associated with mortality. Additional studies may serve to validate these observations.

Indexed as

FrailtyHeart TransplantationElectronic Health RecordsHumansRisk FactorsWaiting Listscomorbiditiesheart diseaserecipient selectionrisk assessment / risk stratification

Identifiers

PMID34923657
PMCPMC9366897

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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.