Months Backward Test a Review of Its Use in Clinical Studies
Int J Environ Res Public Health. 2020 Oct; 17(20): 7515.
Diagnostic Test Accuracy of the 4AT for Delirium Detection: A Systematic Review and Meta-Analysis
Juneyoung Lee
2Department of Biostatistics, College of Medicine, Korea University, Seoul 02841, Korea
Received 2020 Sep xx; Accustomed 2020 Oct 12.
Abstract
Under-recognition of delirium is an international problem. For the early detection of delirium, a viable and valid screening tool for healthcare professionals is needed. This study aimed to present a scientific reason for using the 4 'A's Exam (4AT) through a systematic review and meta-analysis of studies on the diagnostic test accurateness. We systematically searched articles in the EMBASE, MEDLINE, CINAHL, and PsycINFO databases and selected relevant manufactures on the basis of the predefined inclusion criteria. The quality of the included manufactures was evaluated using the Quality Assessment of the Diagnostic Accuracy Studies-ii tool. We estimated the pooled values of diagnostic exam accuracy by employing the bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model in data synthesis. A total of 3729 patients of 13 studies were included in the analysis. The pooled estimates of sensitivity and specificity of the 4AT were 81.5% (95% conviction interval: lxx.7%, 89.0%) and 87.five% (79.five%, 92.7%), respectively. Given the 4AT's testify of accurateness and practicality, nosotros suggest healthcare professionals to utilise this tool for routine screening of delirium. However, for detecting delirium in the dementia population, further work is required to evaluate the 4AT with other cut-off points or scoring methods in club for it to be more than sensitive and specific.
Keywords: 4AT, delirium, meta-analysis, sensitivity, specificity, systematic review
i. Introduction
Delirium is a neuropsychiatric syndrome characterized past acute change and fluctuation of awareness, attention, and cognitive office [i,ii]. Delirium in older adults is regarded as a medical emergency due to its high prevalence and a wide range of negative outcomes such as the increased chance of falls, pressure sores, functional refuse, higher mortality, and the new onset or deterioration of dementia [three,4]. For this reason, early detection is the key strategy for the management of delirium [v].
Despite a variety of instruments for delirium screening and diagnosis being available, under-recognition by healthcare professionals is still problematic in many care settings [6,7]. For constructive detection of delirium, continuous screening embedded in everyday practise is crucially required due to the natural characteristics of the condition presenting astute onset and fluctuating course in a day. Thus, delirium screening tools with both feasibility and accuracy should be used for successful early detection of delirium [8].
According to the recently published delirium guideline, there are several piece of cake-to-use tools for delirium detection that need a short menstruum of time to administrate (<2 min), such every bit the Simple Question in Delirium (SQiD), modified RASS (m-RASS), and 4 'A'south Examination (4AT) [9]. Amidst them, the 4AT has been particularly recommended to use in emergency departments and astute hospital settings, since the tool has been validated and widely used worldwide in those clinical settings. Moreover, the 4AT has the following strengths over other existing tools: no "special" training required, being uncomplicated and easy to administrate, no concrete responses required by patients, all patients tin can be evaluated (including those untestable due to severe drowsiness or agitation), and the possibility to screen other forms of cognitive harm due to included brief cognitive tests.
The 4AT consists of iv items: (1) alertness, (2) Abbreviated Mental Test-4 (AMT-4), (3) attention (Months Backwards test), and (four) acute change or fluctuating course. Items 1 and 4 are graded 0 (negative) or 4 (positive), while items two and iii are graded 0, 1, or two, which provides a total score of 0 to 12. The cut-off point is 4, suggesting possible delirium. This means that it reaches cut-off point solely by a single item (ane or four) since both "contradistinct alacrity" and "acute modify or fluctuating course" are considered the cadre features of delirium.
The 4AT has been translated and validated in multiple clinical settings, including acute care hospitals, emergency departments, nursing homes, and geriatric hospitals, internationally [10,eleven,12]. However, as far as we know, no meta-analysis of diagnostic test accuracy (DTA) of the 4AT for delirium detection has all the same been conducted. Therefore, a systematic review and meta-analysis of DTA of the tool are necessary in lodge to provide the best evidence of the 4AT's efficacy in clinical settings.
2. Materials and Methods
2.1. Aims and Design
This written report aimed to systematically review and perform a meta-analysis to evaluate the DTA of the 4AT. This report followed the recommended guideline of Cochrane collaboration for systematic reviews of DTA [xiii] and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-DTA (PRISMA-DTA) guidelines [14,15].
2.2. Search Methods and Eligibility Criteria
The literature was searched in Feb 2020, in EMBASE, MEDLINE, CINAHL, and PsycINFO databases. To identify relevant reports not included during the search, nosotros also reviewed references. The search was carried out using just 4AT, delirium, and DTA-related terms, not including the terms relevant to patients, reference standard tests, and outcomes for obtaining results with loftier sensitivity [xvi]. The term "delirium" was combined with validated search terms of the DTA, such every bit "sensitivity" and "specificity".
Two authors (E.J. and J.P.) independently searched, reviewed, and selected the studies, using predefined eligibility criteria. Nosotros also identified and reviewed full-texts for studies that met the inclusion criteria. When there were discrepancies, we resolved them through word with the third reviewer (J.50.).
The eligibility criteria were prepare as follows: (1) using the 4AT to detect delirium for identifying DTA of the tool; (2) applying a reference standard to diagnose delirium on the basis of a validated tool or standardized criteria of the Diagnostic and Statistical Transmission of Mental Disorders (DSM) III, IV, or 5; (3) reporting estimates of DTA including true positive, true negative, false positive, and false negative, or sufficient information to derive them; (4) being written in English, (five) being a prospective study in the full general clinical settings. Purely observational studies that were inappropriate to test diagnostic accuracy were excluded.
ii.3. Quality Cess
The quality of included studies was assessed with the Quality Cess of Diagnostic Accuracy Studies-2 (QUADAS-2) tool [17]. The QUADAS-2 is the most used and recommended quality assessment tool for DTA studies. The tool has four domains including "patient selection", "index test", "reference standard", and "flow and timing" [14]. The applicability concerns are evaluated on the basis of the get-go iii domains by identifying if the setting and included patients match the predefined research question.
In this study, a low risk of bias was alleged only when all the questions of the tool were answered with "yes". A high-risk or unclear bias was assigned to the domain if at that place was at to the lowest degree one answer was either "no" or "unclear", respectively. Ii authors (Eastward.J. and J.P.) independently evaluated the risk of bias and applicability of the included studies, and the tertiary reviewer (J.50.), who is a qualified methodologist of systematic review and meta-analysis, resolved the remaining disagreement.
2.4. Data Extraction
The two authors (E.J. and J.P.) independently extracted the information for sensitivity, specificity, and sample size of all included studies. When a study did not report these values merely provided sufficient particular for its derivation, we calculated sensitivity and specificity. The following data was extracted from all included studies using a predefined Excel spreadsheet: written report characteristics (country, clinical setting, author, and yr of publication), sample size, patient characteristics, diagnostic cut-off bespeak, and time taken for administration.
2.5. Data Synthesis
On the basis of the recommended guideline of Cochrane collaboration for systematic review (SR) of DTA [thirteen], we planned to employ hierarchical models, which are the virtually rigorous method to perform a meta-assay of DTA. Thus, we carried out meta-analysis of DTA studies using two hierarchical models, the bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model [xvi]. Using these models, we pooled the values for true positives, truthful negatives, false positives, and imitation negatives. As further summary measures, nosotros calculated positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio using the pooled sensitivity and specificity. The results described in the HSROC curve included 95% prediction and 95% confidence regions [18,19].
Moreover, we conducted a pre-planned subgroup analysis based on the quality cess, namely, subgroup analysis for the studies that have a "low" risk of bias amidst the four domains of the QUADAS-two. Another post-hoc subgroup analysis with three studies that reported the diagnostic performance of each detail [11,20,21] was also performed. Farther, we also conducted the sensitivity analysis co-ordinate to the settings (full general wards, emergency department, and stroke unit of measurement). The statistical analyses of this study were conducted using R software version iii.2.ii with the bundle of "mada" (R Foundation for Statistical Computing, Vienna, Austria) [22].
3. Results
3.1. Search Outcome
Effigy ane presents the details of the report selection menstruum. Amongst 1375 records, we identified a total of 1186 studies subsequently removing duplicated articles. Through the screening of titles and abstracts, we identified 70 potentially relevant articles on the diagnostic performance of the 4AT. Among them, we excluded 57 studies, 2 of which were validation studies of the 4AT using the aforementioned dataset with already included studies [23,24]. As a event, a full of 13 manufactures that met the inclusion criteria were finally identified in our systematic review [10,11,12,20,21,25,26,27,28,29,30,31,32].
The menstruation chart of the search for eligible studies.
3.2. Written report Characteristics
Included studies were conducted in 9 unlike countries and had sample sizes between 49 and 559 participants, comprising a total of 3729 participants. All of the included studies used 4 as the cut-off value of the 4AT for delirium detection. The characteristics of the included studies are summarized in Table 1.
Table 1
Characteristics of the studies that were systematically reviewed.
| First Author | Yr | Country | Setting | n | Historic period (M ± SD or Median [Range]) | Reference Standard | Cut-off Score | TP | FP | TN | FN | Item Assay |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Asadollahi | 2016 | Iran | Nursing homes and daily caring centers | 293 | 69.three ± i.47 | DSM-5 | >3 | 57 | 4 | 125 | 107 | Not washed |
| Myrstad | 2019 | Norway | Astute geriatric ward | 49 | 87 (68–99) | DSM-Five | >3 | x | 4 | 25 | 10 | Non done |
| Casey | 2019 | Australia | Inpatient wards | 559 | 73 ± 16.4 | 3D-CAM | >3 | 59 | 48 | 420 | 32 | Non done |
| MacLullich | 2019 | Uk | ED, medical access units, MOE units | 392 | 81.4 ± half dozen.4 | DSM-Iv | >iii | 37 | xix | 324 | 12 | Done |
| Kuladee | 2016 | Thailand | General medical wards | 97 | 73.6 ± eight.17 | DSM-IV, TDRS | >three | 20 | 10 | 63 | 4 | Done |
| Hendry | 2016 | United Kingdom | Geriatric medical cess unit | 434 | 83.1 ± 6.7 | DSM-V | >3 | 72 | 107 | 244 | 11 | Non done |
| De | 2017 | Australia | Geriatric and orthogeriatric services | 257 | 86.0 ± seven.3 | DSM-V, CAM | >three | 138 | 20 | 78 | 21 | Not done |
| Bellelli | 2014 | Italy | Acute elderliness ward and department of rehabilitation | 236 | 83.9 ± six.1 | DSM-Iv | >3 | 26 | 33 | 174 | iii | Washed |
| Gagne | 2018 | Canada | ED | 319 | 76.84 ± 7.four | CAM | >iii | 44 | 108 | 162 | v | Not done |
| O'Sullivan | 2018 | Republic of ireland | ED | 350 | 77 a | DSM-V | >3 | 54 | 25 | 267 | 4 | Non done |
| Saller | 2019 | Germany | PACU | 543 | 52 ± xviii | DSM-V, CAM-ICU | >3 | 21 | 4 | 517 | 1 | Not done |
| Infante | 2017 | Italian republic | Stroke unit | 100 | 79 (19–93) | DSM-V | >three | 48 | 12 | 38 | two | Not done |
| Lees | 2013 | United Kingdom | Astute stroke unit | 100 | 74 (64–85) b | CAM | >3 | 12 | sixteen | 72 | 0 | Not done |
3.3. Assessment of Risk of Bias
As a issue of the quality assessment, we found 9 studies to have a depression risk of bias and low applicability concerns in all domains of the QUADAS-ii tool (Table two). In that location was no disagreement in quality evaluation between reviewers.
Tabular array ii
Results of take chances of bias cess of the included studies.
| Outset Author (Twelvemonth) | Risk of Bias | Applicability Concerns | |||||
|---|---|---|---|---|---|---|---|
| Patient Pick | Index Test | Reference Standards | Flow, Timing | Patient Selection | Index Test | Reference Standard | |
| Asadollahi (2016) | unclear | low | low | unclear | low | low | low |
| Myrstad (2019) | depression | low | depression | low | low | low | low |
| Casey (2019) | high | low | high | unclear | low | low | low |
| MacLullich (2019) | low | depression | depression | low | low | low | low |
| Kuladee (2016) | low | low | depression | depression | depression | low | low |
| Hendry (2016) | low | low | low | low | low | low | low |
| De (2017) | low | low | low | low | low | depression | low |
| Bellelli (2014) | low | low | low | low | low | low | low |
| Gagne (2018) | low | loftier | high | low | depression | low | depression |
| O'Sullivan (2018) | low | depression | low | depression | low | depression | low |
| Saller (2019) | depression | low | low | low | low | low | depression |
| Infante (2017) | low | loftier | high | low | low | depression | low |
| Lees (2013) | low | low | low | depression | low | low | low |
All included studies were evaluated to accept a low run a risk of bias in the domain of "patient selection" except for two studies; one used a instance-control blueprint [12], which was categorized as unclear chance of bias, the other, which did not report articulate inclusion and exclusion criteria [10], was classified as having a high take a chance of bias in that domain. Two studies [26,28] were considered to accept a high gamble of bias in both domains of "alphabetize test" and "reference standard test" because these studies used the same tester for two tests without blinding. One report [12] was likewise assigned as having a loftier hazard of bias for the "reference standard test" domain for having no sufficient information provided in terms of whether the tester was qualified and whether there was blinding in terms of the alphabetize test. All studies except two [10,12] used patients receiving the same reference standard, including them in the analysis then that they were regarded as having a low adventure of bias in the "flow and timing" domain. The latter two studies did not bear witness a clear distinction in terms of the fourth dimension intervals between the index test and reference standard test and thus an unclear risk of bias in the domain was assigned. For applicability concerns, none of the studies received annihilation other than the designation of having a low chance of biases in the "patient selection", "index exam", and "reference standard test" domains. The included studies in this systematic review could be concluded to accept low take chances of bias, overall.
three.4. Diagnostic Examination Accuracy of the 4AT
The diagnostic performance of the 4AT is presented in Tabular array 3. All included studies reported the DTA values of the 4AT including sensitivity and specificity. As a issue of meta-analysis, its pooled estimate of sensitivity and specificity were 81.5% (95% CI = lxx.vii%–89.0%) and 87.five% (CI = 79.5%–92.7%), respectively. For subgroup analysis with nine studies with low risk of bias, nosotros constitute the pooled sensitivity to be 84.3% (75.4%–90.4%) and that of specificity was 88.five% (79.0%–94.0%). Further, the diagnostic operation of each subtest of the 4AT presented in Table iv.
Table 3
Diagnostic test accuracy of the included studies.
| Writer | Twelvemonth | n | Sn (95% CI) | Sp (95% CI) | DOR (95% CI) * | PLR (95% CI) * | NLR (95% CI) | |
|---|---|---|---|---|---|---|---|---|
| Asadollahi | 2016 | 293 | 0.35 (0.28–0.42) | 0.97 (0.92–0.99) | 14.92 (v.52–40.28) | x.07 (3.97–25.55) | 0.68 (0.sixty–0.76) | |
| Myrstad b | 2019 | 49 | 0.l (0.xxx–0.70) | 0.85 (0.68–0.94) | 5.67 (one.52–21.16) | iii.33 (1.29–8.65) | 0.59 (0.37–0.93) | |
| Casey | 2019 | 559 | 0.65 (0.55–0.74) | 0.ninety (0.87–0.92) | 15.87 (9.43–26.72) | six.25 (4.sixty–8.l) | 0.39 (0.xxx–0.52) | |
| MacLullich b | 2019 | 392 | 0.75 (0.62–0.85) | 0.94 (0.91–0.96) | 49.92 (22.74–109.62) | 13.23 (8.35–20.96) | 0.27 (0.sixteen–0.43) | |
| Kuladee b | 2016 | 97 | 0.82 (0.63–0.92) | 0.86 (0.76–0.92) | 27.55 (8.20–92.52) | 5.78 (3.21–x.42) | 0.21 (0.09–0.49) | |
| Hendry b | 2016 | 434 | 0.86 (0.77–0.92) | 0.seventy (0.65–0.74) | xiv.34 (7.40–27.80) | 2.83 (2.36–iii.38) | 0.xx (0.12–0.34) | |
| De b | 2017 | 257 | 0.87 (0.eighty–0.91) | 0.79 (0.70–0.86) | 24.67 (12.68–47.98) | four.18 (2.83–half dozen.18) | 0.17 (0.eleven–0.25) | |
| Bellelli b | 2014 | 236 | 0.88 (0.72–0.96) | 0.84 (0.78–0.88) | 39.44 (12.19–127.63) | 5.49 (3.92–seven.68) | 0.14 (0.05–0.37) | |
| Gagne | 2018 | 319 | 0.89 (0.77–0.95) | 0.60 (0.54–0.66) | 12.12 (4.84–30.36) | 2.22 (one.87–2.65) | 0.18 (0.08–0.41) | |
| O'Sullivan b | 2018 | 350 | 0.92 (0.83–0.97) | 0.91 (0.88–0.94) | 127.05 (44.74–360.75) | ten.61 (seven.27–xv.49) | 0.08 (0.03–0.twenty) | |
| Saller b | 2019 | 543 | 0.94 (0.76–0.99) | 0.99 (0.98–1.0) | 1648.33 (247.14–10993.70) | 108.44 (42.94–273.80) | 0.07 (0.01–0.31) | |
| Infante | 2017 | 100 | 0.95 (0.85–0.99) | 0.76 (0.62–0.85) | 59.75 (xiv.41–247.77) | 3.88 (2.39–6.31) | 0.07 (0.02–0.22) | |
| Lees b | 2013 | 100 | 0.96 (0.72–1.0) | 0.82 (0.72–0.88) | 109.85 (six.19–1950.64) | 5.19 (three.31–8.13) | 0.05 (0.00–0.72) | |
| Pooled estimates a | ||||||||
| All included studies | 3729 | 81.v (70.seven–89.0) | 87.5 (79.v–92.vii) | AUC: 0.911 | ||||
| Subgroup assay b | 2458 | 84.3 (75.four–90.4) | 88.5 (79.0–94.0) | AUC: 0.918 | ||||
Table 4
Diagnostic test accurateness of each detail of the 4AT.
| Author | Year | Sample Size | Sn (95% CI) | Sp (95% CI) | DOR (95% CI) * | PLR (95% CI) * | NLR (95% CI) |
|---|---|---|---|---|---|---|---|
| Item 1. Alertness (cut-off point: iv) | |||||||
| MacLullich | 2019 | 392 | 0.31 (0.20–0.45) | 0.99 (0.98–ane.00) | 50.0 (13.78–181.41) | 35.0 (ten.51–116.54) | 0.70 (0.58–0.84) |
| Kuladee | 2016 | 97 | 0.38 (0.21–0.57) | 0.97 (0.91–0.99) | 21.xxx (iv.17–108.74) | 13.69 (iii.xviii–59.0) | 0.64 (0.47–0.88) |
| Bellelli | 2014 | 236 | 0.52 (0.34–0.69) | 0.96 (0.93–0.98) | 26.65 (9.66–73.53) | 13.38 (6.23–28.76) | 0.50 (0.34–0.73) |
| Pooled estimates a | 725 | 39.vi (26.5–54.four) | 97.9 (94.half dozen–99.2) | AUC: 0.810 | |||
| Item 2. AMT-iv (cut-off point: 1) | |||||||
| MacLullich | 2019 | 392 | 0.63 (0.49–0.75) | 0.83 (0.78–0.86) | viii.29 (4.35–fifteen.eighty) | 3.68 (2.68–5.04) | 0.44 (0.31–0.64) |
| Kuladee | 2016 | 97 | 0.96 (0.80–0.99) | 0.67 (0.56–0.77) | 46.96 (five.98–368.73) | 2.92 (two.08–iv.09) | 0.06 (0.01–0.43) |
| Bellelli | 2014 | 236 | 0.97 (0.83–0.99) | 0.55 (0.48–0.61) | 33.66 (4.50–252.05) | ii.13 (1.80–2.51) | 0.06 (0.01–0.44) |
| Pooled estimates a | 725 | ninety.4 (58.5–98.4) | 69.two (49.eight–83.six) | AUC: 0.832 | |||
| Item 2. AMT-4 (cut-off point: 2) | |||||||
| MacLullich | 2019 | 392 | 0.41 (0.28–0.55) | 0.96 (0.94–0.98) | 17.51 (7.91–38.76) | 10.77 (5.73–xx.24) | 0.62 (0.49–0.78) |
| Kuladee | 2016 | 97 | 0.88 (0.69–0.96) | 0.81 (0.70–0.88) | 29.50 (7.70–112.97) | 4.56 (2.78–7.48) | 0.sixteen (0.05–0.45) |
| Bellelli | 2014 | 236 | 0.90 (0.74–0.96) | 0.80 (0.74–0.85) | 35.09 (10.12–121.62) | 4.53 (3.35–six.xi) | 0.thirteen (0.04–0.38) |
| Pooled estimates a | 725 | 77.2 (39.2–94.7) | 88.3 (69.vii–96.1) | AUC: 0.908 | |||
| Item three. Attending (cutting-off point: 1) | |||||||
| MacLullich | 2019 | 392 | 0.71 (0.58–0.82) | 0.79 (0.74–0.83) | ix.41 (iv.81–eighteen.43) | three.40 (2.60–4.46) | 0.36 (0.23–0.57) |
| Kuladee | 2016 | 97 | 0.96 (0.8–0.99) | 0.41 (0.31–0.53) | 16.05 (2.05–125.36) | 1.63 (1.32–2.01) | 0.10 (0.02–0.70) |
| Bellelli | 2014 | 236 | 0.93 (0.78–0.98) | 0.50 (0.43–0.57) | 13.37 (three.10–57.68) | 1.85 (i.57–ii.19) | 0.14 (0.04–0.53) |
| Pooled estimates a | 725 | 89.ix (68.5–97.three) | 58.one (33.six–79.ii) | AUC: 0.821 | |||
| Detail 3. Attending (cut-off betoken: 2) | |||||||
| MacLullich | 2019 | 392 | 0.31 (0.20–0.45) | 0.99 (0.98–1.00) | l.0 (thirteen.78–181.41) | 35.0 (10.51–116.54) | 0.70 (0.58–0.84) |
| Kuladee | 2016 | 97 | 0.50 (0.31–0.69) | 0.95 (0.87–0.98) | 17.25 (four.76–62.48) | 9.13 (3.25–25.65) | 0.53 (0.35–0.79) |
| Bellelli | 2014 | 236 | 0.86 (0.69–0.95) | 0.83 (0.77–0.87) | 29.69 (ix.74–90.53) | 4.96 (3.56–6.ninety) | 0.17 (0.07–0.42) |
| Pooled estimates a | 725 | 57.6 (23.eight–85.6) | 95.iv (78.eight–99.1) | AUC: 0.892 | |||
| Detail four. Acute modify or fluctuating class (cut-off indicate: 4) | |||||||
| MacLullich | 2019 | 392 | 0.63 (0.49–0.75) | 0.83 (0.78–0.86) | 8.29 (four.35–15.80) | 3.68 (2.68–v.04) | 0.44 (0.31–0.64) |
| Kuladee | 2016 | 97 | 0.75 (0.55–0.88) | 0.88 (0.78–0.93) | 21.33 (half-dozen.seventy–67.90) | 6.08 (3.16–11.70) | 0.29 (0.14–0.57) |
| Bellelli | 2014 | 236 | 0.69 (0.51–0.83) | 0.94 (0.90–0.97) | 36.11 (xiii.57–96.13) | 11.90 (half dozen.52–21.70) | 0.33 (0.19–0.57) |
| Pooled estimates a | 725 | 68.0 (57.vii–76.8) | 89.0 (79.7–94.three) | AUC: 0.760 | |||
The results of the sensitivity analysis according to the clinical settings were as follows (pooled sensitivity, specificity, respectively): (one) general wards (78.3% (66.5%–86.viii%), 83.5% (76.0%–89.1%)), (2) emergency department (91.6% (83.0%–96.0%), 79.9% (36.7%–96.v%)), and (3) stroke unit (95.3% (86.four%–98.5%), 79.one% (71.half dozen%–85.1%)).
The threshold effect is i of the most important causes of heterogeneity betwixt studies of DTA. If the sensitivity and specificity have an inverse human relationship, a coupled forest plot will evidence a V or an inverted Five shape, which represents the fact that there is a threshold effect [33]. Further, when in that location is a threshold issue, the value of the correlation coefficient between simulated positive rate and sensitivity will exist 0.6 or higher [34,35]. A coupled forest plot of sensitivity and specificity of the 4AT is presented in Figure 2, which confirmed that in that location seemed to be no threshold outcome introduced in our meta-analysis since it was a value of 0.378 and the coupled forest plot was shaped neither as a V nor an inverted 5.
Coupled woods plot of the 4AT. CI, conviction interval; 4AT, 4 'A's Test.
The HSROC curve shows a global summary of the examination's diagnostic performance and presents the trade-off between sensitivity and specificity. The HSROC curve in this study had a relatively small conviction region and was positioned in the upper left corner, which supports the desirable diagnostic performance of the 4AT (Figure 3). The overall weighted surface area nether the HSROC curve was 0.91, which besides supports at least moderate predictive validity of the tool since information technology was larger than 0.7.
Hierarchical summary receiver operating characteristics bend of the 4AT. HSROC, Hierarchical summary receiver operating characteristics curve; 4AT, 4 'A's Test.
We likewise examined an expected positive predictive value (PPV) and a negative predictive value (NPV) for the 4AT across the range of delirium prevalence from 5% to 55%, which was the range reported from the included studies. The best predictive value for the 4AT was observed at 84.vii% with a prevalence of about 46% (Figure 4). The result suggests that, when the prevalence is about 46%, the best predictive values of the tool can exist achieved. The 4AT too showed relatively loftier NPV across a wide range of prevalence (low to high) of delirium.
Predictive value of the 4AT. NPV, negative predictive value; PPV, positive predictive value; 4AT, iv 'A'due south Exam.
four. Discussion
The definition of DTA is the test's power to distinguish an incidence or absence of atmospheric condition [36]. In order to make up one's mind whether a particular tool is benign to use in clinical settings, a systematic review and meta-analysis of DTA, which is of paramount importance equally scientific prove of tool effectiveness, should exist provided to healthcare providers [18]. The 4AT is 1 of the most widely used tools for delirium screening internationally [9,37]. Thus far, there has been a systematic review of the tool'south DTA, which includes patients with a item illness (acute stroke) [38]. This review, however, did not perform a meta-analysis. All the same, since in that location have been multiple articles published on the DTA of 4AT in diverse settings other than stroke units, such as emergency departments, nursing homes, and geriatric hospitals, we debate that information technology is necessary to evaluate the pooled DTA values of the tool in terms of meta-assay.
In this study, we used ii hierarchical models (the bivariate model and HSROC model), which are the most advanced and rigorous statistical methods to conduct a meta-analysis of DTA by overcoming limitations of the traditional method. The present consequence of the meta-analysis presented that the sensitivity and specificity of 4AT were 81.5% and 87.5%, respectively, indicating that the 4AT is highly sensitive and specific for delirium detection. Further, we evaluated the hazard of bias of studies using QUADAS-2, which is the most recommended quality assessment tool for DTA studies. Our subgroup analysis for studies with a "low" take a chance of bias based on the QUADAS-2 provided higher pooled sensitivity (84.3%) and specificity (88.5%).
Ane of the almost prominent advantages of the 4AT is that it is unproblematic (<2 min) and no training is required. The Confusion Assessment Method (CAM), as another normally used tool for delirium detection, requires upward to 10 min to administrate [nine], and even the short version (Curt-CAM) takes longer than 4AT (>2 min). Furthermore, since the range of sensitivity is heterogeneous (46% to 100%) when used routinely for screening purposes, it has been evaluated that special training must be conducted to secure a high DTA of this tool [39]. However, most of the DTA studies of 4AT reported that high DTA levels were achieved without special training.
A post-hoc subgroup analysis with studies reporting diagnostic performance of each particular of the 4AT showed that all items were highly specific to delirium. Particularly, "alertness" and "astute modify or fluctuating course", which accounts for items 1 and 4, respectively, are known cadre features of delirium. For this reason, the tool was designed to use the cutting-off point of four for items 1 and 4. That is, if a patient is apparently not alert or has symptoms with astute alter/fluctuating course, delirium could be suspected. Similarly, our assay confirmed that both items were highly specific to delirium (item 1 = 97.9%, item 4 = 89.0%). Thus, we could conclude that items ane and 4 certainly account for securing the specificity of the 4AT for detecting delirium inside a high level [8,eleven].
Disorientation (detail 2, AMT-4) and inattention (item 3, Months Backwards test) are symptoms that can occur in cognitive impairment as well as delirium. The results showed that both items 2 and three were highly sensitive just less specific for detecting delirium when the cut-off is set at 1 point for each item. Nevertheless, with more severe deficits (two or more mistakes on the AMT4, or an untestable condition in both items), the specificity was improved; in detail, item iii (inattention) was highly specific (95.4%). These findings suggest that the astringent deficits both in orientation and attention are also useful indicators of delirium. Still, the point here is that the patients considered "untestable" on the AMT4 (item two, ii points) and Months Backwards exam (detail 3, 2 points) of the 4AT can also reach cutting-off point (four points) together, which can mayhap contribute the increased false positives of the tool. Yet, healthcare professionals should likewise consider the fact that, to a large degree, such untestable patients (except coma) are more than likely to exist diagnosed with delirium [40].
This issue was discussed by Richardson et al. [41], who dealt with detection of delirium superimposed on dementia (DSD) using tests for inattention and arousal, in which the sensitivity and specificity of the attention test (90%, 64%) as well as that the arousal test (85%, 82%) were increased when combined together (94%, 92%). The inability to perform simple attention tests lonely might not be a useful marker of delirium in the dementia population, but information technology could reach higher sensitivity and specificity if the core features of delirium are combined. Similarly, detection of DSD may be difficult just with disorientation (item ii) or inattention (item 3) of the 4AT; however, past combining with the key delirium symptoms such every bit altered alacrity (item 1) and acute alter (item 4), and applying different optimal cut-offs or scoring mechanisms for this population, the DTA could be improved. Further piece of work will establish if the 4AT with other cut-off points or scoring methods can provide more sensitive and specific measures of delirium in the dementia population.
The 4AT is a tool for screening rather than diagnosis of delirium. The instruction of the tool conspicuously states that further assessment to attain a diagnosis may be necessary even if cut-off bespeak or more were scored. This tool is a rapid and brief tool for the initial assessment of delirium and cognitive impairment prior to diagnosis. For the tools with primary purposes of screening, an ability to dominion out negative cases is clinically more important because the implementation of tailored preventive strategies and further diagnosis for all "possible delirium" is the central factor of delirium intendance [eight]. This implies that specificity and NPV, rather than sensitivity and PPV, are more meaningful measures. The nowadays issue confirmed that the 4AT has a high specificity and NPV, by which information technology can exist concluded that the tool is a highly effective screening tool.
The recently published bear witness-based guideline recommended using the 4AT over many other tools for delirium detection in emergency departments and acute infirmary settings [ix]. The results of this study added the all-time scientific evidence for the DTA of the 4AT and also advise this tool to be used in routine clinical practice. Still, as a result of the sensitivity analysis according to clinical settings in this study, we found that the 4AT has different DTA values depending on the settings, which showed less sensitivity but slightly more specificity in general wards (sensitivity 78.3%, specificity 83.five%) than in emergency departments (91.6% and 79.9%) and stroke units (95.3% and 79.one%). These results suggest that in that location might be a need to develop a setting-specific tool in order to attain the DTA, especially in terms of specificity.
Farther, as revealed in this study, at that place is a lack of evidence on the DTA of the tool in intensive care units (ICU), where delirium is commonly observed and has multiple adverse furnishings on the patients' prognosis [42,43]. Additionally, the testify of the possibility to address subsyndromal delirium (SSD) is too limited. SSD is a condition that does not run across the DSM-5 criteria but has ane or more features of delirium. It is considered clinically of import since it occurs often and increases mortality, length of hospital stay, cognitive harm, and new development of delirium [44,45]. For the wider use of the tool, therefore, more studies on the DTA of the tool should be further carried out, especially in ICU patients, besides as studies on the ability of the 4AT to detect SSD.
5. Limitations
Some limitations of the present study should exist acknowledged. Start, the nowadays results might non free of a publication bias that exaggerates the judge of DTA, as has been the case in other systematic reviews. Second, the 4AT was used past multiple trained or untrained raters, which makes the assessment of inter-rater reliability necessary, but this was non considered in most included studies. This should be addressed in future studies. Third, the results might be susceptible to an inherent bias considering of a threshold effect, which is known as the essential causes of heterogeneity in DTA studies. Yet, the coupled forest plot of sensitivity and specificity of the report showed that in that location was no evident threshold effect.
Lastly, the quality of this systematic review is dependent on the sample sizes of the included studies and the hazard of bias. For this reason, the additional subgroup analysis including only for low-risk bias was also conducted, showing amend DTA values. Further work is therefore needed to ostend the operation of the tool on the basis of higher-quality study designs with a larger population for a more expanded awarding of the tool.
6. Conclusions
Our study suggests that 4AT is a valid and viable delirium detection tool. Given its good diagnostic performance and practicality, information technology can be considered as an advisable delirium screening tool, specially for routine use in full general wards, emergency departments, and stroke units. Moreover, since this tool covers so-chosen "untestable" patients for delirium assessment and further intervention, information technology can be more widely used in clinical settings where those with severe cognitive impairment are common. We, therefore, advise the utilise of the tool in more varied clinical settings in which there is a demand of a delirium screening tool that has a sufficiently high DTA just where there is a lack of fourth dimension for using other longer tools or a lack of adequate preparation to apply the tools. Nevertheless, further work is required to evaluate the DTA of 4AT in ICU patients every bit well every bit the possibility of 4AT with other cut-off points or scoring methods to be more sensitive and specific measures of detecting DSD and SSD.
Author Contributions
Conceptualization, E.J., J.P., and J.50.; methodology, E.J., J.P., and J.L.; software, E.J.; validation, Eastward.J., J.P., and J.Fifty.; formal analysis, Eastward.J., J.P., and J.Fifty.; resources, E.J. and J.P.; data curation, E.J. and J.P.; writing—original draft preparation, Eastward.J.; writing—review and editing, J.P. and J.L.; visualization, J.P.; supervision, J.L.; project administration, J.50.; funding acquisition, E.H. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Educational activity (NRF-2020R1I1A1A01072281).
Conflicts of Interest
The authors declare no disharmonize of interest. The funders had no part in the design of the study; in the collection, analyses, or interpretation of information; in the writing of the manuscript; or in the conclusion to publish the results.
Footnotes
Publisher'south Annotation: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
1. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders: Dsm-five. 5th ed. American Psychiatric Publishing; Arlington, VA, U.s.: 2013. [Google Scholar]
2. De Lange E., Verhaak P.F., van der Meer K. Prevalence, presentation and prognosis of delirium in older people in the population, at dwelling house and in long term care: A review. Int. J. Geriatr. Psychiatr. 2013;28:127–134. doi: 10.1002/gps.3814. [PubMed] [CrossRef] [Google Scholar]
iii. Persico I., Cesari M., Morandi A., Haas J., Mazzola P., Zambon A., Annoni G., Bellelli G. Frailty and delirium in older adults: A systematic review and meta-analysis of the literature. J. Am. Geriatr. Soc. 2018;66:2022–2030. doi: 10.1111/jgs.15503. [PubMed] [CrossRef] [Google Scholar]
4. Reynish E.L., Hapca S.K., De Souza Northward., Cvoro V., Donnan P.T., Guthrie B. Epidemiology and outcomes of people with dementia, delirium, and unspecified cognitive harm in the general infirmary: Prospective cohort study of 10,014 admissions. BMC Med. 2017;fifteen:140. doi: 10.1186/s12916-017-0899-0. [PMC gratuitous article] [PubMed] [CrossRef] [Google Scholar]
5. Rohatgi N., Weng Y., Bentley J., Lansberg K.G., Shepard J., Mazur D., Ahuja Due north., Hopkins J. Initiative for prevention and early identification of delirium in medical-surgical units: Lessons learned in the by five years. Am. J. Med. 2019;132:1421–1430. doi: 10.1016/j.amjmed.2019.05.035. [PubMed] [CrossRef] [Google Scholar]
6. Barron East.A., Holmes J. Delirium inside the emergency care setting, occurrence and detection: A systematic review. Emerg. Med. J. 2013;xxx:263–268. doi: ten.1136/emermed-2011-200586. [PubMed] [CrossRef] [Google Scholar]
vii. Lange P.Westward., Lamanna M., Watson R., Maier A.B. Undiagnosed delirium is frequent and difficult to predict: Results from a prevalence survey of a tertiary hospital. J. Clin. Nurs. 2019;28:2537–2542. doi: 10.1111/jocn.14833. [PubMed] [CrossRef] [Google Scholar]
viii. Registered Nurses' Clan of Ontario . Delirium, Dementia, and Depression in Older Adults: Assessment and Care. Registered Nurses' Association of Ontario; Tononto, ON, Canada: 2016. [Google Scholar]
ix. Scottish Intercollegiate Guidelines Network (SIGN) Chance Reduction and Management of Delirium (Sign CPG 157) SIGN; Edinburgh, Britain: 2019. [Google Scholar]
10. Asadollahi A., Saberi M., Entezari M., Hoseini Z., Hasani S.A., Saberi L.F., Hoseini S.M., Ismaeli A. Iranian version of 4at, an instrument for rapid delirium screening for later on life. Int. J. Adv. Appl. Sci. 2016;3:33–38. [Google Scholar]
eleven. Bellelli G., Morandi A., Davis D.H., Mazzola P., Turco R., Gentile S., Ryan T., Cash H., Guerini F., Torpilliesi T., et al. Validation of the 4at, a new musical instrument for rapid delirium screening: A study in 234 hospitalised older people. Age Ageing. 2014;43:496–502. doi: 10.1093/ageing/afu021. [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
12. Casey P., Cross W., Mart M.Due west.S., Baldwin C., Riddell K., Dārziņš P. Hospital discharge data under-reports delirium occurrence: Results from a bespeak prevalence survey of delirium in a major Australian health service. Intern. Med. J. 2019;49:338–344. doi: ten.1111/imj.14066. [PubMed] [CrossRef] [Google Scholar]
13. Macaskill P., Gatsonis C., Deeks J.J., Harbord R.M., Takwoingi Y. Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy Version 0.nine. The Cochrane Collaboration; London, United kingdom: 2010. [Google Scholar]
14. Liberati A., Altman D.Chiliad., Tetzlaff J., Mulrow C., Gøtzsche P.C., Ioannidis J.P., Clarke Grand., Devereaux P.J., Kleijnen J., Moher D. The prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health intendance interventions: Explanation and elaboration. J. Clin. Epidemiol. 2009;62:e1–e34. doi: ten.1016/j.jclinepi.2009.06.006. [PubMed] [CrossRef] [Google Scholar]
xv. McInnes Grand.D.F., Moher D., Thombs B.D., McGrath T.A., Bossuyt P.M., Clifford T., Cohen J.F., Deeks J.J., Gatsonis C., Hooft 50., et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accurateness studies: The prisma-dta statement. JAMA. 2018;319:388–396. doi: 10.1001/jama.2017.19163. [PubMed] [CrossRef] [Google Scholar]
16. Kim K.W., Lee J., Choi S.H., Huh J., Park Southward.H. Systematic review and meta-analysis of studies evaluating diagnostic test accuracy: A practical review for clinical researchers-part I. Full general guidance and tips. Korean J. Radiol. 2015;16:1175–1187. doi: 10.3348/kjr.2015.16.vi.1175. [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
17. Whiting P.F., Rutjes A.W., Westwood One thousand.E., Mallett S., Deeks J.J., Reitsma J.B., Leeflang M.Chiliad., Sterne J.A., Bossuyt P.M. Quadas-ii: A revised tool for the quality assessment of diagnostic accuracy studies. Ann. Intern. Med. 2011;155:529–536. doi: 10.7326/0003-4819-155-8-201110180-00009. [PubMed] [CrossRef] [Google Scholar]
18. Lee J., Kim Yard.W., Choi S.H., Huh J., Park S.H. Systematic review and meta-analysis of studies evaluating diagnostic test accurateness: A practical review for clinical researchers-part ii. Statistical methods of meta-analysis. Korean J. Radiol. 2015;16:1188–1196. doi: 10.3348/kjr.2015.16.6.1188. [PMC gratuitous article] [PubMed] [CrossRef] [Google Scholar]
xix. Lee Y.H. Overview of the procedure of conducting meta-analyses of the diagnostic test accuracy. J. Rheum. Dis. 2018;25:3–ten. doi: 10.4078/jrd.2018.25.one.3. [CrossRef] [Google Scholar]
20. Kuladee Southward., Prachason T. Development and validation of the thai version of the 4 'a'southward test for delirium screening in hospitalized elderly patients with acute medical illnesses. Neuropsychiatr. Dis. Treat. 2016;12:437–443. doi: 10.2147/NDT.S97228. [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
21. MacLullich A.Yard., Shenkin Due south.D., Goodacre S., Godfrey M., Hanley J., Stíobhairt A., Lavender E., Boyd J., Stephen J., Weir C., et al. The four 'a's test for detecting delirium in acute medical patients: A diagnostic accuracy study. Health Technol. Assess. 2019;23:i–194. doi: x.3310/hta23400. [PMC gratuitous commodity] [PubMed] [CrossRef] [Google Scholar]
22. Doebler P., Holling H. Meta-analysis of diagnostic accuracy with mada. R Packag. 2015;ane:15. [Google Scholar]
23. Saller T., MacLullich A.1000.J., Perneczky R. The 4at—An musical instrument for delirium detection for older patients in the post-anaesthesia care unit of measurement. Anaesthesia. 2020;75:409–410. doi: 10.1111/anae.14937. [PubMed] [CrossRef] [Google Scholar]
24. Shenkin Due south.D., Fox C., Godfrey Grand., Siddiqi North., Goodacre S., Young J., Anand A., Gray A., Hanley J., MacRaild A., et al. Delirium detection in older acute medical inpatients: A multicentre prospective comparative diagnostic test accurateness report of the 4at and the confusion assessment method. BMC Med. 2019;17:138. doi: 10.1186/s12916-019-1367-9. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
25. De J., Wand A.P.F., Smerdely P.I., Hunt One thousand.E. Validating the 4a's exam in screening for delirium in a culturally diverse geriatric inpatient population. Int. J. Geriatr. Psychiatr. 2017;32:1322–1329. doi: 10.1002/gps.4615. [PubMed] [CrossRef] [Google Scholar]
26. Gagné A.J., Voyer P., Boucher V., Nadeau A., Carmichael P.H., Pelletier M., Gouin East., Berthelot South., Daoust R., Wilchesky Yard., et al. Performance of the french version of the 4at for screening the elderly for delirium in the emergency department. CJEM. 2018;twenty:903–910. doi: 10.1017/cem.2018.367. [PubMed] [CrossRef] [Google Scholar]
27. Hendry One thousand., Quinn T.J., Evans J., Scortichini 5., Miller H., Burns J., Cunnington A., Stott D.J. Evaluation of delirium screening tools in geriatric medical inpatients: A diagnostic exam accuracy study. Age Ageing. 2016;45:832–837. doi: 10.1093/ageing/afw130. [PubMed] [CrossRef] [Google Scholar]
28. Infante M.T., Pardini M., Balestrino Grand., Finocchi C., Malfatto 50., Bellelli G., Mancardi G.L., Gandolfo C., Serrati C. Delirium in the astute phase after stroke: Comparison between methods of detection. Neurol. Sci. 2017;38:1101–1104. doi: x.1007/s10072-017-2832-10. [PubMed] [CrossRef] [Google Scholar]
29. Lees R., Corbet S., Johnston C., Moffitt E., Shaw G., Quinn T.J. Exam accuracy of short screening tests for diagnosis of delirium or cognitive impairment in an acute stroke unit setting. Stroke. 2013;44:3078–3083. doi: 10.1161/STROKEAHA.113.001724. [PubMed] [CrossRef] [Google Scholar]
thirty. Myrstad M., Watne L.O., Johnsen Northward.T., Børs-Lind Eastward., Neerland B.East. Delirium screening in an acute geriatric ward by nurses using 4at: Results from a quality comeback project. Eur. Geriatr. Med. 2019;ten:667–671. doi: 10.1007/s41999-019-00215-y. [CrossRef] [Google Scholar]
31. O'Sullivan D., Brady N., Manning E., O'Shea East., O'Grady S., O'Regan Due north., Timmons S. Validation of the vi-detail cognitive impairment examination and the 4at test for combined delirium and dementia screening in older emergency department attendees. Age Ageing. 2018;47:61–68. doi: 10.1093/ageing/afx149. [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
32. Saller T., MacLullich A.1000.J., Schäfer S.T., Crispin A., Neitzert R., Schüle C., von Dossow V., Hofmann-Kiefer Chiliad.F. Screening for delirium after surgery: Validation of the 4 a's exam (4at) in the post-amazement care unit. Anaesthesia. 2019;74:1260–1266. doi: 10.1111/anae.14682. [PubMed] [CrossRef] [Google Scholar]
33. Reitsma J.B., Glas A.Southward., Rutjes A.W., Scholten R.J., Bossuyt P.One thousand., Zwinderman A.H. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J. Clin. Epidemiol. 2005;58:982–990. doi: 10.1016/j.jclinepi.2005.02.022. [PubMed] [CrossRef] [Google Scholar]
34. Devillé Westward.L., Buntinx F., Bouter Fifty.M., Montori 5.Chiliad., de Vet H.C., van der Windt D.A., Bezemer P.D. Conducting systematic reviews of diagnostic studies: Didactic guidelines. BMC Med. Res. Methodol. 2002;2:nine. doi: x.1186/1471-2288-2-nine. [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
35. Glas A.S., Lijmer J.G., Prins K.H., Bonsel One thousand.J., Bossuyt P.Grand. The diagnostic odds ratio: A single indicator of examination operation. J. Clin. Epidemiol. 2003;56:1129–1135. doi: 10.1016/S0895-4356(03)00177-X. [PubMed] [CrossRef] [Google Scholar]
37. National Found for Health and Intendance Excellence Delirium: Prevention, Diagnosis and Management. [(accessed on 20 Apr 2020)]; Available online: https://world wide web.nice.org.uk/guidance/cg103.
38. Mansutti I., Saiani 50., Palese A. Detecting delirium in patients with astute stroke: A systematic review of test accuracy. BMC Neurol. 2019;19:310. doi: 10.1186/s12883-019-1547-iv. [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
39. Wei L.A., Fearing Chiliad.A., Sternberg E.J., Inouye Southward.Thou. The confusion assessment method: A systematic review of current usage. J. Am. Geriatr. Soc. 2008;56:823–830. doi: ten.1111/j.1532-5415.2008.01674.x. [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
40. Chester J.G., Beth Harrington M., Rudolph J.L. Serial administration of a modified richmond agitation and sedation calibration for delirium screening. J. Hosp. Med. 2012;7:450–453. doi: 10.1002/jhm.1003. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
41. Richardson South.J., Davis D.H.J., Bellelli Thousand., Hasemann W., Meagher D., Kreisel South.H., MacLullich A.M.J., Cerejeira J., Morandi A. Detecting delirium superimposed on dementia: Diagnostic accurateness of a unproblematic combined arousal and attention testing procedure. Int. Psychogeriatr. 2017;29:1585–1593. doi: ten.1017/S1041610217000916. [PubMed] [CrossRef] [Google Scholar]
42. Ely E.Westward., Shintani A., Truman B., Gordon S.M., Harrell F.E., Inouye S.Yard., Bernard G.R., Dittus R.S. Delirium as apredictor of bloodshed in mechanically ventilated patients in the intensive care unit. JAMA. 2004;291:1753–1762. doi: 10.1001/jama.291.14.1753. [PubMed] [CrossRef] [Google Scholar]
43. Girard T.D., Jackson J.C., Pandharipande P.P., Pun B.T., Thompson J.L., Shintani A.Thou., Gordon Due south.M., Canonico A.East., Dittus R.S., Bernard M.R., et al. Delirium as a predictor of long-term cognitive harm in survivors of critical illness. Crit Care Med. 2010;38:1513–1520. doi: ten.1097/CCM.0b013e3181e47be1. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
44. Serafim R.B., Soares M., Bozza F.A., Silva J.R.L., Dal-Pizzol F., Paulino Thou.C., Povoa P., Salluh J.I.F. Outcomes of subsyndromal delirium in ICU: A systematic review and meta-analysis. Crit Care. 2017;21:179. doi: 10.1186/s13054-017-1765-3. [PMC gratis commodity] [PubMed] [CrossRef] [Google Scholar]
45. Cole Thousand.G., Ciampi A., Belzile E., Dubuc-Sarrasin M. Subsyndromal delirium in older people: A systematic review of frequency, risk factors, course and outcomes. FOCUS. 2013;11:534–543. doi: ten.1176/appi.focus.xi.4.534. [PubMed] [CrossRef] [Google Scholar]
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