Evidence map›Paper›PMID 38014821›Full record

ArticleJournal of the American Geriatrics Society2024

Factors associated with disagreement between clinician app-based ultra-brief Confusion Assessment Method and reference standard delirium assessments.

Rejoice Dhliwayo, Shrunjal Trivedi, Long Ngo, Donna M Fick, Sharon K Inouye, Marie Boltz, Douglas Leslie, Erica Husser, Priyanka Shrestha, Edward R Marcantonio

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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

10 authors at 4 institutions in 1 country.

Rejoice DhliwayoTufts University School of Medicine, Boston, Massachusetts, USA.ORCID 0000-0003-1822-9906
Shrunjal TrivediDivision of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Long NgoDivision of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Donna M FickCollege of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, USA.ORCID 0000-0002-6777-1913
Sharon K InouyeDivision of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Marie BoltzRoss and Carol Nese College of Nursing, The Pennsylvania State University, University Park, Pennsylvania, USA.ORCID 0000-0003-1133-2249
Douglas LeslieCollege of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, USA.
Erica HusserRoss and Carol Nese College of Nursing, The Pennsylvania State University, University Park, Pennsylvania, USA.ORCID 0000-0002-0799-5122
Priyanka ShresthaThe George Washington University School of Nursing, Washington, DC, USA.ORCID 0000-0003-3817-747X
Edward R MarcantonioDivision of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.ORCID 0000-0002-2911-4250
Beth Israel Deaconess Medical Center · USPennsylvania State University · USGeorge Washington University · USTufts University · US

Funding

READI-SET-GO: Researching Efficient Approaches to Delirium Identification - Sustaining Effective Translation to create Gero-friendly OrganizationsR01AG030618 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI DONNA Marie FICK, EDWARD R MARCANTONIO · 2008 to 2026
$7.9M
Development and Validation of a Delirium Severity ToolkitR01AG044518 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI INOUYE, SHARON K., JONES, RICHARD N · 2014 to 2024
$7.3M
NIDUS III: Advanced-Stage Development and Utilization of the NIDUS Research Infrastructure to Advance Interdisciplinary Aging Research inDeliriumR33AG071744 · NIA · JOHNS HOPKINS UNIVERSITY · PI John W. Devlin, Esther Seunghee Oh · 2021 to 2026
$4.7M
Mid-Career Mentoring Award for Patient-Oriented Research in AgingK24AG035075 · NIA · BETH ISRAEL DEACONESS MEDICAL CENTER · PI MARCANTONIO, EDWARD R · 2010 to 2021
$1.9M
Greater Boston Medical Student Training in Aging ResearchT35AG038027 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI DRIVER, JANE A, MCLAUGHLIN-GAVIN, CARA · 2010 to 2024
$991k
NIA NIH HHS 5T35AG038027NIA NIH HHS K24 AG035075NIA NIH HHS K24AG035075NIA NIH HHS R01 AG030618NIA NIH HHS R01AG030618NIA NIH HHS R01 AG044518NIA NIH HHS R01AG044518NIA NIH HHS R33 AG071744NIA NIH HHS R33AG071744NIA NIH HHS T35 AG038027
6 · The paper itself

Abstract

backgroundRecently, the Ultra-Brief Confusion Assessment Method (UB-CAM), designed to help physicians and nurses to recognize delirium, showed high, but imperfect, accuracy compared with Research Reference Standard Delirium Assessments (RRSDAs). The aim of this study is to identify factors associated with disagreement between clinicians' app-based UB-CAM assessments and RRSDAs.

methodsThis is a secondary analysis of a prospective diagnostic test study. The study was conducted at two hospitals and included 527 inpatients (≥70 years old) and 289 clinicians (53 physicians, 236 nurses). Trained research associates performed RRSDAs and determined delirium presence using the CAM. Clinicians administered the UB-CAM using an iPad app. Disagreement factors considered were clinician, patient, and delirium characteristics. We report odds ratios and 95% confidence intervals.

resultsOne thousand seven hundred and ninety-five clinician UB-CAM assessments paired with RRSDAs were administered. The prevalence of delirium was 17%. The rate of disagreement between clinician UB-CAM assessments and RRSDAs was 12%. Significant factors associated with disagreement between clinician UB-CAM assessments and RRSDAs (OR [95% CI]) included: presence of dementia (2.7 [1.8-4.1]), patient education high school or less (1.9 [1.3-2.9]), psychomotor retardation (2.5 [1.4-4.2]), and the presence of mild delirium or subsyndromal delirium (5.5 [3.5-8.7]). Significant risk factors for false negatives were patient age less than 80 (2.2 [1.1-4.3]) and mild delirium (3.5 [1.6-7.4]). Significant risk factors for false positives were presence of dementia (4.0 [2.3-7.0]), subsyndromal delirium (5.1 [2.9-9.1]), and patient education high school or less (2.0 [1.2-3.6]). Clinician characteristics were not significantly associated with disagreement.

conclusionsThe strongest factors associated with disagreement between clinician UB-CAM screens and RRSDAs were the presence of dementia and subsyndromal delirium as risk factors for false positives, and mild delirium and younger age as a risk factor for false negatives. These disagreement factors contrast with previous studies of risk factors for incorrect clinician delirium screening, and better align screening results with patient outcomes.

Indexed as

DeliriumDementiaMobile ApplicationsAgedConfusionHumansProspective StudiesReference StandardsReproducibility of ResultsSensitivity and Specificityaccuracydeliriumscreening

Identifiers

PMID38014821
PMCPMC10947955
OpenAlexW4389083419

What OpenQuestion holds

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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.