Diagnostic accuracy of delirium assessment methods in critical care patients

Barman, Angkita; Pradhan, Debasis; Bhattacharyya, Prithwis; Dey, Subhasish; Bhattacharjee, Anirban; Tesia, Sonali Shinde; Mitra, Jayanta Kumar

doi:10.1016/j.jcrc.2017.10.013

Cited by 15 publications

(15 citation statements)

References 26 publications

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“…Majority of the studies have assessed the incidence and prevalence of delirium have relied on the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV)/DSM-IV text revision (TR) criteria. 15,17,19,20,[23][24][25][26][27][29][30][31] However, some of the studies have used confusion assessment method (CAM)/CAM-ICU. 13,14,16,18,33,34 The prevalence rates in various ICUs have varied from 16.1 to 68.2%.…”

Section: Resultsmentioning

confidence: 99%

“…13,14,16,18,33,34 The prevalence rates in various ICUs have varied from 16.1 to 68.2%. [15][16][17]19,20,23 Similarly, the incidence of delirium in various ICUs ranges from 8 to 59.6%. 15,[17][18][19][20][21][22] One of the studies evaluated delirium in general medical inpatients and reported the prevalence rate to be 19%, 11 whereas another study that focused on postoperative patients reported a prevalence rate of 4%.…”

Section: Resultsmentioning

confidence: 99%

“…31 Studies have also evaluated motoric subtypes of delirium and have come up with different prevalence rates, which are mostly influenced by the study setting and the assessment scales (►Table 4). 14,15,18,23,25,29,38,44,47,51,[53][54][55] Most of the studies have relied upon the Delirium Motor Symptom Scale (DMSS)/ amended DMSS. 15,25,29,44,47,51,53 The prevalence rate of hypoactive delirium in ICUs 15,18,23,51 has varied from 26 to 65%, for mixed subtype, ranges from 10.2 to 29%, and for hyperactive subtype, ranges from 15.7 to 56.8%.…”

Section: Resultsmentioning

confidence: 99%

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Delirium Research in India: A Systematic Review

Grover

Kathiravan

Dua

2021

JNRP

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Delirium is the most common psychiatric diagnoses encountered in patients with various medical-surgical illnesses, in all the treatment set-ups, with relatively higher incidence and prevalence in the intensive care units. As delirium is encountered in multiple specialties, it is important to understand the research on this diagnosis. This study aims to assess the research output involving patients of delirium from India. A comprehensive search was undertaken using Medline (PubMed) and other databases. Search words included were “delirium,” “delirious,” “delirium tremens” AND “India.” No filters were used. Internet and hand searches yielded 305 articles. Out of these articles, 151 had the terms “delirium,” “delirious,” “delirium tremens” in the title and these were included for the review. Additionally, 14 articles were included for the review, although these did not have these terms in the title, but delirium was one of the major outcome parameters in these studies. Majority of the papers were original articles (n = 81), and these were followed by, case reports (n = 58), review articles (n = 10), letter to the editor (not as case reports but as a communication; n = 13), editorials (n = 2) and one clinical practice guideline. Most of the original papers have either focused on epidemiology (incidence, prevalence, outcome, etc.), symptom profile, with occasional studies focusing on effectiveness of various pharmacological interventions. There is a dearth of research in the field of delirium from India. There is a lack of studies on biomarkers, evaluation of nonpharmacological interventions, and evaluation of prevention strategies. It is the need of the hour to carry out more studies to further our understanding of delirium in the Indian context.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Delirium Research in India: A Systematic Review

Grover

Kathiravan

Dua

2021

JNRP

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“…Table S3 presents the characteristics of the 29 studies. Twenty-three and 8 studies reported accuracy estimates for CAM-ICU (Adamis et al, 2012;Aljuaid et al, 2018;Barman et al, 2018;Boettger et al, 2018;Chanques et al, 2018;Chuang et al, 2007;Ely, Margolin, et al, 2001;Guenther et al, 2010;Gusmao-Flores et al, 2011;Heo et al, 2011;Karlicic et al, 2016;Koga et al, 2015;Lin et al, 2004;Luetz et al, 2010;Mitášová et al, 2012;Nishimura et al, 2016;Pipanmekaporn et al, 2014;Selim et al, 2018;van Eijk et al, 2011;van Eijk et al, 2009;Vreeswijk et al, 2009;Wang et al, 2013) and ICDSC (Barman et al, 2018;Bergeron et al, 2001;Boettger et al, 2018;Chanques et al, 2018;Gusmao-Flores et al, 2011;Kose, Bolu, Ozdemir, Acikel, & Hatipolu, 2016;Nishimura et al, 2016;van Eijk et al, 2009), respectively. Two studies applied Delirium Detection Score (DDS) (Luetz et al, 2010;Otter et al, 2005), one applied Cognitive Test for Delirium (CTD) alone (Hart et al, 1996), one applied Stanford Proxy Test for Delirium (S-PTD) alone (Alosaimi et al, 2018), one applied Neelon and Champagne Confusion Scale (NEECHAM) alone (Immers, Schuurmans, & Van De Bijl, 2005), and one applied Nursing Delirium Screening Scale (Nu-DESC) for delirium assessmen...…”

Section: Resultsmentioning

confidence: 99%

Diagnostic Performance of Delirium Assessment Tools in Critically Ill Patients: A Systematic Review and Meta‐Analysis

Montgomery

Traynor

et al. 2020

Worldviews Ev Based Nurs

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Background Critical care nurses are in the best position to detect and monitor delirium in critically ill patients. Therefore, an optimum delirium assessment tool with strong evidence should be identified with critical care nurses to perform in the daily assessment. Aim To evaluate and compare the diagnostic performance of delirium assessment tools in diagnosing delirium in critically ill patients. Methods We searched five electronic databases including the Cochrane Library, PubMed, Embase, CINAHL, and a Chinese database for eligible diagnostic studies published in English or Mandarin up to December 2018. This diagnostic test accuracy meta‐analysis was limited to studies in intensive care unit (ICU) settings, using the Diagnostic and Statistical Manual of Mental Disorders (DSM) as a standard reference to test the accuracy of delirium assessment tools. Eligible studies were critically appraised by two investigators independently. The summary of evidence was conducted for pooling and comparing diagnostic accuracy by a bivariate random effects meta‐analysis model. The pooled sensitivities and specificities, summary receiver operating characteristic curve (sROC), the area under the curve (AUC), and diagnostic odds ratio (DOR) were calculated and plotted. The possibility of publication bias was assessed by Deeks’ funnel plot. Data Synthesis We identified and evaluated 23 and 8 articles focused on CAM‐ICU and ICDSC, respectively. The summary sensitivities of 0.85 and 0.87, and summary specificities of 0.95 and 0.91 were found for CAM‐ICU and ICDSC, respectively. The AUC of the CAM‐ICU was 0.96 (95% CI, 0.94–0.98), with DOR at 99 (95% CI, 55–177). The AUC of the ICDSC was 0.95 (95% CI, 0.92–0.96), and the DOR was 65 (95% CI, 27–153). Linking Evidence to Action CAM‐ICU demonstrated higher diagnostic test accuracy and is recommended as the optimal delirium assessment tool. However, the results should be interpreted with caution due to the between‐study heterogeneity of this diagnostic test accuracy meta‐analysis.

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“…After admission to the intensive care unit (ICU), patients are in danger of complications such as sepsis, ICU-acquired weakness, and delirium [1,2,3]. In particular, pneumonia is a common complication in critically ill ICU patients on mechanical ventilation.…”

Section: Introductionmentioning

confidence: 99%

Relationship between Ventilator-Associated Events and Timing of Rehabilitation in Subjects with Emergency Tracheal Intubation at Early Mobilization Facility

Shinoda

Nishihara

Shimogai

et al. 2018

IJERPH

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The present study aimed to investigate the relationship between the occurrence of ventilator-associated events (VAE) in the intensive care unit and the timing of rehabilitation intervention. We included subjects who underwent emergency tracheal intubation and received rehabilitation. We performed rehabilitation according to our hospital’s protocol. We assessed the mechanical ventilation parameters of inspired oxygen fraction and positive-end expiratory pressure, and a VAE was identified if these parameters stabilized or decreased for ≥2 days and then had to be increased for ≥2 days. We defined time in hours from tracheal intubation to the first rehabilitation intervention as Timing 1 and that to first sitting on the edge of the bed as Timing 2. Data were analyzed by the t-test and χ2 tests. We finally analyzed 294 subjects. VAE occurred in 9.9% and high mortality at 48.3%. Median values of Timing 1 and Timing 2 in the non-VAE and VAE groups were 30.3 ± 24.0 and 30.0 ± 20.7 h, and 125.7 ± 136.6 and 127.9 ± 111.4 h, respectively, and the differences were not significant (p = 0.95 and p = 0.93, respectively). We found no significant relationship between the occurrence of VAE leading to high mortality and timing of rehabilitation intervention.

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Diagnostic accuracy of delirium assessment methods in critical care patients

Cited by 15 publications

References 26 publications

Delirium Research in India: A Systematic Review

Delirium Research in India: A Systematic Review

Diagnostic Performance of Delirium Assessment Tools in Critically Ill Patients: A Systematic Review and Meta‐Analysis

Relationship between Ventilator-Associated Events and Timing of Rehabilitation in Subjects with Emergency Tracheal Intubation at Early Mobilization Facility

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