Delirium prevalence in a Colombian hospital, association with geriatric syndromes and complications during hospitalization

Peralta-Cuervo, Andres F.; García-Cifuentes, Elkin; Castellanos-Perilla, Nicolás; Chavarro-Carvajal, Diego Andrés; Venegas-Sanabria, Luis Carlos; Cano-Gutiérrez, Carlos Alberto

doi:10.1016/j.regg.2020.10.007

Cited by 6 publications

(9 citation statements)

References 27 publications

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“…This difference in the prevalence could be explained by the assessment of delirium in our study in wards such as orthopedics, geriatrics, and general medicine where risk factors for delirium are commonly present [ 52 ]. Our results, however, when considering patients at risk for delirium (63%), are similar to those reported in the study of Gehrke in patients older than 90 years in an internal medicine ward (69%) [ 53 ] and in a Colombian study in a geriatric unit where the prevalence was 51.03% [ 54 ].…”

Section: Discussionsupporting

confidence: 90%

A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome

Ocagli

Bottigliengo

Lorenzoni

et al. 2021

IJERPH

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Delirium is a psycho-organic syndrome common in hospitalized patients, especially the elderly, and is associated with poor clinical outcomes. This study aims to identify the predictors that are mostly associated with the risk of delirium episodes using a machine learning technique (MLT). A random forest (RF) algorithm was used to evaluate the association between the subject’s characteristics and the 4AT (the 4 A’s test) score screening tool for delirium. RF algorithm was implemented using information based on demographic characteristics, comorbidities, drugs and procedures. Of the 78 patients enrolled in the study, 49 (63%) were at risk for delirium, 32 (41%) had at least one episode of delirium during the hospitalization (38% in orthopedics and 31% both in internal medicine and in the geriatric ward). The model explained 75.8% of the variability of the 4AT score with a root mean squared error of 3.29. Higher age, the presence of dementia, physical restraint, diabetes and a lower degree are the variables associated with an increase of the 4AT score. Random forest is a valid method for investigating the patients’ characteristics associated with delirium onset also in small case-series. The use of this model may allow for early detection of delirium onset to plan the proper adjustment in healthcare assistance.

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Section: Discussionsupporting

confidence: 90%

A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome

Ocagli

Bottigliengo

Lorenzoni

et al. 2021

IJERPH

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“…Six studies reported data only on patients with a completed delirium assessment without providing a denominator (three CAM studies, 18,28,29 one DOSS, 36 and both using the NuDESC 19,33 ) (Table 2). In the 16 studies reporting on the whole population eligible for assessment, the tool completion rate ranged from 19% (all inpatients ≥18 years, bCAM, although the center reported early data from a staged implementation process led by nursing champions and the completion rate was 63% by the end of implementation) to 100% (single orthopedic center, 4AT post-operatively) (Table 2 and Figure 2).…”

Section: Tool Completion Ratementioning

confidence: 99%

Delirium detection tools show varying completion rates and positive score rates when used at scale in routine practice in general hospital settings: A systematic review

Penfold,

Squires,

Angus

et al. 2024

J American Geriatrics Society

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BackgroundMultiple short delirium detection tools have been validated in research studies and implemented in routine care, but there has been little study of these tools in real‐world conditions. This systematic review synthesized literature reporting completion rates and/or delirium positive score rates of detection tools in large clinical populations in general hospital settings.MethodsPROSPERO (CRD42022385166).Medline, Embase, PsycINFO, CINAHL, and gray literature were searched from 1980 to December 31, 2022. Included studies or audit reports used a validated delirium detection tool performed directly with the patient as part of routine care in large clinical populations (n ≥ 1000) within a general acute hospital setting. Narrative synthesis was performed.ResultsTwenty‐two research studies and four audit reports were included. Tools used alone or in combination were the Confusion Assessment Method (CAM), 4 ‘A's Test (4AT), Delirium Observation Screening Scale (DOSS), Brief CAM (bCAM), Nursing Delirium Screening Scale (NuDESC), and Intensive Care Delirium Screening Checklist (ICDSC). Populations and settings varied and tools were used at different stages and frequencies in the patient journey, including on admission only; inpatient, daily or more frequently; on admission and as inpatient; inpatient post‐operatively. Tool completion rates ranged from 19% to 100%. Admission positive score rates ranged from: CAM 8%–51%; 4AT 13%–20%. Inpatient positive score rates ranged from: CAM 2%–20%, DOSS 6%–42%, and NuDESC 5–13%. Postoperative positive score rates were 21% and 28% (4AT). All but two studies had moderate–high risk of bias.ConclusionsThis systematic review of delirium detection tool implementation in large acute patient populations found clinically important variability in tool completion rates, and in delirium positive score rates relative to expected delirium prevalence. This study highlights a need for greater reporting and analysis of relevant healthcare systems data. This is vital to advance understanding of effective delirium detection in routine care.

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“…8(1): 23 -37 30 17,9% e a idade média de 71,2 anos. Na Colômbia, um estudo de Peralta-Cuervo et al (23) com 1599 doentes internados em enfermaria com idade media de 86 anos, a prevalência de delirium foi de 51%.…”

Section: Confusãounclassified

“…No estudo de Quaresma et al (9) , após o diagnóstico de confusão aguda, registaram-se 62 óbitos (39,5%) no período de três meses tendo sido associada a ocorrência de delirium a maior mortalidade. Também os estudos de Marco et al (8) e Peralta-Cuervo (23)…”

Section: Mortalidadeunclassified

<br/> A CONFUSÃO EM PESSOAS INTERNADAS NUMA ENFERMARIA DE MEDICINA INTERNA <br/>

Carvalho

2022

riase

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Delirium prevalence in a Colombian hospital, association with geriatric syndromes and complications during hospitalization

Cited by 6 publications

References 27 publications

A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome

A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome

Delirium detection tools show varying completion rates and positive score rates when used at scale in routine practice in general hospital settings: A systematic review

<br/> A CONFUSÃO EM PESSOAS INTERNADAS NUMA ENFERMARIA DE MEDICINA INTERNA <br/>

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