Evidence map›Paper›PMID 38819823›Full record

ArticleJAMA network open2024

Geriatric End-of-Life Screening Tool Prediction of 6-Month Mortality in Older Patients.

Adrian D Haimovich, Ryan C Burke, Larry A Nathanson, David Rubins, R Andrew Taylor, Erin K Kross, Kei Ouchi, Nathan I Shapiro, Mara A Schonberg

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

9 authors.

Adrian D HaimovichDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Ryan C BurkeDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Larry A NathansonDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
David RubinsDepartment of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
R Andrew TaylorDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut.
Erin K KrossDivision of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle.
Kei OuchiDepartment of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Nathan I ShapiroDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Mara A SchonbergDepartment of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
CTSA K12 Program at Harvard Medical SchoolK12TR004381 · NCATS · HARVARD MEDICAL SCHOOL · PI Karen K Miller · 2023 to 2026
$6.5M
Research and mentoring program in shared decision making in the care of older adultsK24AG071906 · NIA · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SCHONBERG, MARA A · 2021 to 2025
$946k
NCATS NIH HHS K12 TR004381NCATS NIH HHS UL1 TR001863NIA NIH HHS K24 AG071906
6 · The paper itself

Abstract

Importance: Emergency department (ED) visits by older adults with life-limiting illnesses are a critical opportunity to establish patient care end-of-life preferences, but little is known about the optimal screening criteria for resource-constrained EDs. Objectives: To externally validate the Geriatric End-of-Life Screening Tool (GEST) in an independent population and compare it with commonly used serious illness diagnostic criteria. Design, Setting, and Participants: This prognostic study assessed a cohort of patients aged 65 years and older who were treated in a tertiary care ED in Boston, Massachusetts, from 2017 to 2021. Patients arriving in cardiac arrest or who died within 1 day of ED arrival were excluded. Data analysis was performed from August 1, 2023, to March 27, 2024. Exposure: GEST, a logistic regression algorithm that uses commonly available electronic health record (EHR) datapoints and was developed and validated across 9 EDs, was compared with serious illness diagnoses as documented in the EHR. Serious illnesses included stroke/transient ischemic attack, liver disease, cancer, lung disease, and age greater than 80 years, among others. Main Outcomes and Measures: The primary outcome was 6-month mortality following an ED encounter. Statistical analyses included area under the receiver operating characteristic curve, calibration analyses, Kaplan-Meier survival curves, and decision curves. Results: This external validation included 82 371 ED encounters by 40 505 unique individuals (mean [SD] age, 76.8 [8.4] years; 54.3% women, 13.8% 6-month mortality rate). GEST had an external validation area under the receiver operating characteristic curve of 0.79 (95% CI, 0.78-0.79) that was stable across years and demographic subgroups. Of included encounters, 53.4% had a serious illness, with a sensitivity of 77.4% (95% CI, 76.6%-78.2%) and specificity of 50.5% (95% CI, 50.1%-50.8%). Varying GEST cutoffs from 5% to 30% increased specificity (5%: 49.1% [95% CI, 48.7%-49.5%]; 30%: 92.2% [95% CI, 92.0%-92.4%]) at the cost of sensitivity (5%: 89.3% [95% CI, 88.8-89.9]; 30%: 36.2% [95% CI, 35.3-37.1]). In a decision curve analysis, GEST outperformed serious illness criteria across all tested thresholds. When comparing patients referred to intervention by GEST with serious illness criteria, GEST reclassified 45.1% of patients with serious illness as having low risk of mortality with an observed mortality rate 8.1% and 2.6% of patients without serious illness as having high mortality risk with an observed mortality rate of 34.3% for a total reclassification rate of 25.3%. Conclusions and Relevance: The findings of this study suggest that both serious illness criteria and GEST identified older ED patients at risk for 6-month mortality, but GEST offered more useful screening characteristics. Future trials of serious illness interventions for high mortality risk in older adults may consider transitioning from diagnosis code criteria to GEST, an automatable EHR-based algorithm.

Indexed as

Emergency Service, HospitalTerminal CareAgedAged, 80 and overBostonFemaleGeriatric AssessmentHumansMaleMortalityPrognosis

Identifiers

PMID38819823
PMCPMC11143461

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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.