Evidence map›Paper›PMID 41712143›Full record

ReviewGeroScience2026

Frailty assessment tools in the emergency department and their predictive value for clinical outcomes: review of the literature.

Dana Shiffer, Francesco Reggiani, Antonio Voza

Abstract readReview
PubMed Publisher
In one paragraph

Review in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

3 authors.

Dana ShifferDepartment of Emergency Medicine, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy. dana.shiffer@humanitas.it.ORCID http://orcid.org/0000-0002-8663-6899
Francesco ReggianiDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Antonio VozaDepartment of Emergency Medicine, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Frailty is increasingly recognized as been associated with adverse outcomes in older adults presenting to the emergency department (ED). Timely identification of frailty can inform clinical decision-making, guide resource allocation, and improve patient-centered care. This review summarizes findings from 33 studies published between 2019 and 2025, evaluating the diagnostic performance and predictive value of frailty screening tools in the ED. Tools assessed include the Clinical Frailty Scale (CFS), Identification of Seniors at Risk, PRISMA-7, interRAI ED Screener, electronic Frailty Index, and several hybrid or lab-based instruments. Most tools demonstrated moderate to high sensitivity but limited specificity and poor-to-fair overall accuracy in predicting outcomes such as hospitalization, ICU admission, length of stay, readmission, functional decline, and mortality. While the CFS remains the most widely used due to its simplicity and clinical familiarity, newer tools show promise in improving predictive accuracy through automation or integration with triage scores. However, no single instrument emerged as ideal. Feasibility, standardization, and implementation challenges, particularly in high-acuity ED environments, persist across all tools. This review highlights the need for ED-specific frailty strategies that balance rapid screening with comprehensive assessment.

Indexed as

Frailty in emergency departmentFrailty screening toolsGeriatric populationRisk stratification

Identifiers

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.