Evidence map›Paper›PMID 23339752›Full record

ArticleBMC medical research methodology2013

Selecting optimal screening items for delirium: an application of item response theory.

Frances M Yang, Richard N Jones, Sharon K Inouye, Douglas Tommet, Paul K Crane, James L Rudolph, Long H Ngo, Edward R Marcantonio

Open access · goldAbstract read
In one paragraph

Article in BMC medical research methodology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Ultra-brief Screeners for Detecting Delirium Superimposed on Dementia.Journal of the American Medical Directors Association · 2019
    Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Delirium diagnosis, screening and management.Current opinion in supportive and palliative care · 2014
    Review
  11. 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 at 4 institutions in 1 country.

Frances M YangHarvard Medical School, Beth Israel Deaconess Medical Center, Division of Gerontology, Institute for Aging Research, Hebrew SeniorLife, 1200 Centre Street, Boston, MA 02131, USA. francesyang@hsl.harvard.edu
Richard N Jones
Sharon K Inouye
Douglas Tommet
Paul K Crane
James L Rudolph
Long H Ngo
Edward R Marcantonio
Beth Israel Deaconess Medical Center · USHebrew SeniorLife · USHarborview Medical Center · USHarvard University · US

Funding

The Role of Inflammation in the Pathophysiology of Delirium and its Associated Long-Term Cognitive DeclineP01AG031720 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI MARCANTONIO, EDWARD R · 2010 to 2022
$26.7M
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
TRIAL TO REDUCE DELIRIUM IN AGED POST ACUTE PATIENTSR01AG017649 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI MARCANTONIO, EDWARD R · 2000 to 2004
$1.9M
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
Delirium and Survival in Post-Acute CareR03AG025262 · NIA · HEBREW REHABILITATION CENTER FOR AGED · PI JONES, RICHARD N · 2005 to 2006
$127k
NIA NIH HHS K24 AG035075NIA NIH HHS P01AG031720NIA NIH HHS R01 AG030618NIA NIH HHS R01AG030618NIA NIH HHS R01AG17649NIA NIH HHS R03AG025262
6 · The paper itself

Abstract

backgroundDelirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium.

methodsOlder adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium.

resultsWe identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening.

conclusionsWe identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for screening. This reduced item set facilitates development of short screening tools suitable for use in clinical applications or research studies. This study represents the first step in the establishment of an item bank for delirium screening with potential questions for clinical researchers to select from and tailor according to their research objectives.

Indexed as

Aged, 80 and overAlgorithmsDeliriumFactor Analysis, StatisticalFemaleHumansMalePsychometricsSurveys and Questionnaires

Identifiers

PMID23339752
PMCPMC3598414
OpenAlexW2165080333

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.