Evidence map›Paper›PMID 38739670›Full record

ArticlePloS one2024

Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.

Kathleen A Sheehan, Saeha Shin, Elise Hall, Denise Y F Mak, Lauren Lapointe-Shaw, Terence Tang, Seema Marwaha, Dov Gandell, Shail Rawal, Sharon Inouye and 2 more

Abstract readComparative Study
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

12 authors.

Kathleen A SheehanDepartment of Psychiatry, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-8700-0809
Saeha ShinSt. Michael's Hospital, Unity Health Network, Toronto, ON, Canada.
Elise HallDepartment of Psychiatry, University of Toronto, Toronto, ON, Canada.
Denise Y F MakSt. Michael's Hospital, Unity Health Network, Toronto, ON, Canada.
Lauren Lapointe-ShawDepartment of Medicine, University of Toronto, Toronto ON, Canada.
Terence TangDepartment of Medicine, University of Toronto, Toronto ON, Canada.ORCID 0000-0002-1735-7298
Seema MarwahaDepartment of Medicine, University of Toronto, Toronto ON, Canada.
Dov GandellDepartment of Medicine, University of Toronto, Toronto ON, Canada.
Shail RawalDepartment of Medicine, University of Toronto, Toronto ON, Canada.
Sharon InouyeAging Brain Center, Hebrew Senior Life, Boston, MA, United States of America.
Amol A VermaDepartment of Medicine, University of Toronto, Toronto ON, Canada.
Fahad RazakDepartment of Medicine, University of Toronto, Toronto ON, Canada.

Funding

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
NIA NIH HHS R33 AG071744
6 · The paper itself

Abstract

backgroundDelirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge.

objectiveTo characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review.

methodsWe conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review.

resultsDelirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium.

conclusionsAdministrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.

Indexed as

DeliriumInternational Classification of DiseasesAgedAged, 80 and overCohort StudiesFemaleHospitalizationHumansMaleMiddle AgedOntarioRetrospective Studies

Identifiers

PMID38739670
PMCPMC11090329

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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.