|Year : 2019 | Volume
| Issue : 4 | Page : 213-215
Incidence and outcomes of delirium in nonintubated critically ill patients: A prospective observational cohort study
Hari Naveen1, Sooraj Kumar1, Ramesh Venkataraman2, Nagarajan Ramakrishnan2, Bharath Kumar Tirupakuzhi Vijayaraghavan2
1 Department of Critical Care Medicine, Apollo Hospitals, Chennai, Tamil Nadu, India
2 Department of Critical Care Medicine, Apollo Hospitals; Chennai Critical Care Consultants Group, Chennai, Tamil Nadu, India
|Date of Submission||23-Oct-2019|
|Date of Acceptance||30-Oct-2019|
|Date of Web Publication||12-Dec-2019|
Bharath Kumar Tirupakuzhi Vijayaraghavan
Department of Critical Care Medicine, Apollo Hospitals, Greams Road, Chennai, Tamil Nadu
Source of Support: None, Conflict of Interest: None
Objective: Delirium in intubated patients is associated with worse outcomes. However, there is a paucity of data in nonintubated patients. Our study describes the incidence, risk factors, and outcomes for delirium for this population. Methods: We conducted a prospective observational study at a tertiary care intensive care unit (ICU). Data were collected over 2 months and delirium was screened using Confusion Assessment Method for the ICU tool. Only patients with at least 48 h stay in the ICU were included. Patient demographics, risk factors for delirium, and outcomes were recorded. Results: Among 75 patients screened, 13 patients (17.3%) screened positive for delirium. Delirium was more common in patients with higher disease severity and in those with a history of prior hospitalization. In addition, physical restraint use and neurological diagnoses also seemed to be associated with delirium. The presence of delirium did not affect key outcomes. Conclusion: Delirium is common among nonintubated critically ill patients and warrants routine monitoring.
Keywords: Critical care units, delirium, noninvasive ventilation
|How to cite this article:|
Naveen H, Kumar S, Venkataraman R, Ramakrishnan N, Tirupakuzhi Vijayaraghavan BK. Incidence and outcomes of delirium in nonintubated critically ill patients: A prospective observational cohort study. Apollo Med 2019;16:213-5
|How to cite this URL:|
Naveen H, Kumar S, Venkataraman R, Ramakrishnan N, Tirupakuzhi Vijayaraghavan BK. Incidence and outcomes of delirium in nonintubated critically ill patients: A prospective observational cohort study. Apollo Med [serial online] 2019 [cited 2020 Aug 3];16:213-5. Available from: http://www.apollomedicine.org/text.asp?2019/16/4/213/272829
| Introduction|| |
Delirium is a neuropsychiatric condition characterized by acute-onset inattention, fluctuating level of consciousness, and disorganized thinking. Delirium in the intensive care unit (ICU) remains an under-recognized problem and has consistently been associated with poor outcomes., The incidence of delirium can be as high as 80% in ventilated patients. Mechanical ventilation – by virtue of its association with severity of illness, need for an invasive endotracheal tube, and/or sedative agents – may itself play an important role in the development of delirium. In contrast, there are limited data on incidence of delirium in the nonintubated cohort; it is possible that the incidence, risk factors, and outcomes for nonintubated critically ill patients are distinct. It is also likely that preventive and therapeutic strategies for delirium in the nonintubated cohort are different. We therefore led a prospective observational study to determine the incidence and examine risk factors and associations for delirium and its impact on outcomes in a nonintubated cohort of critically ill patients.
| Methods|| |
The study was conducted in a 24-bedded multidisciplinary intensive care and a 32-bedded high dependency unit at a tertiary care hospital in Chennai, India. The study design was prospective observational, and data were collected over 2 months in all critically adults (≥18 years of age) staying in the ICU for at least 48 h. The study duration was chosen as 2 months as it coincided with the Summer Observership period of the first and second authors (HN/SK). Only index ICU admission was considered for the purposes of this study.
Delirium was diagnosed using the validated Confusion Assessment Method for the ICU (CAM-ICU) tool. We used the English and the already available Hindi versions of the tool, and screening for delirium was performed by two investigators (HN and SK) who received training in use of the tool. Screening was performed on days 3, 5, and 7 or at ICU discharge (whichever was earlier). We also collected data on patient demographics, severity of illness (APACHE 4, SOFA scores) and a host of pre-ICU and ICU risk factors [Table 1]. Clinical outcomes such as mortality and length of stay were also recorded.
|Table 1: Delirium-specific preintensive care unit and intensive care unit risk factors for patients included in the analysis (n=55)|
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No formal sample size calculations were performed, and descriptive statistics are used to present the results. All associations are unadjusted as we did not have enough events to perform an adjusted analysis. Results must be considered preliminary and exploratory. Institutional Ethics Committee approved the study (IEC number: AMH-011/03-19). Individual patient-level consent requirement was waived off.
| Results|| |
In the 2-month period, 75 patients were included in the study and 13 patients (were found to have delirium by the CAM-ICU criteria. The mean age of the cohort was 60.1 (standard deviation [SD] of 15) with 49.3% being male patients. The mean APACHE 4 score was 52.8 (SD of 15.6). We further analyzed patients who completed at least two assessments (n = 55), and in this group, 6 patients (10.9%) were diagnosed to have delirium. Common risk factors for delirium are listed in [Table 1]. In general, delirium was more common in patients with higher disease severity and in those with a history of prior hospitalization.
Among ICU-specific risk factors, use of physical restraint and neurological diagnoses at admission seem to be associated with delirium. However, inferences are limited due to a small number of events.
There were no differences in mortality, ICU length of stay, or hospital length of stay between the two groups [Table 2]. Medical device dislodgement was more frequent in the delirium group (3 vs. 0).
|Table 2: Major and minor outcomes among patients completing 2 assessments|
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| Discussion|| |
Our study shows that delirium is common among nonintubated critically ill patients. The incidence of delirium as reported in the literature varies widely from 32% to 80%,, of which nearly 50% is the hypoactive form. In contrast to our study, none of these studies looked exclusively at nonintubated patients. In a study evaluating the use of dexmedetomidine for delirium among nonintubated critically ill patients, Carrasco et al. have reported an incidence of 19%; however, this study was restricted to the subgroup of agitated/hyperactive delirium patients.
We identified the use of physical restraints, history of prior hospitalization, severity of illness, and neurological diagnoses at admission as risk factors that were common in patients with delirium. In a single-center study from a 16-bedded ICU, Dubois et al. found hypertension, smoking, and the use of morphine to be strongly associated with the development of delirium. Several host-related risk factors such as age, alcoholism, and depression and critical illness-related risk factors such as infection, severity of illness, anemia, acidosis, medications, and immobilization have also been shown to be associated with delirium.
Our study did not show any differences in the major outcomes, possibly due to small sample size and limited number of events. Several studies , have demonstrated associations with poor outcomes. However, the impact of delirium in the nonintubated cohort is less well understood. Outcomes that are important for this group would include the need for intubation, physical restraint use, and length of stay in addition to other standard outcome measures. Future research should focus on understanding the epidemiology of delirium in this group along with exploration of specific therapeutic strategies. Toward this end, at least one randomized controlled trail (NCT 03317067) is investigating the impact of dexmedetomidine in treating nonintubated critically ill patients with delirium.
Our study has important strengths. We include an exclusive cohort of nonintubated patients in whom perceived severity of illness is lower and yet delirium remains common. Second, we identify a modifiable risk factor in the form of physical restraint use. Further research will be needed to understand and alleviate factors leading to physical restraint use. Finally, data were collected prospectively by two dedicated and trained personnel (HN and SK), and follow-up was complete. We used a validated tool and deployed both the English and Hindi versions, which enabled us to accurately capture information from a diverse group of patients.
Our study also has several limitations. This was a single-center study with a limited set of patients. As such, we did not have enough events to test for important associations and this has limited our inferences. Only 55 patients completed at least two assessments for delirium, further limiting our sample size. No formal sample size calculation was performed, and the study was primarily led as a preliminary and exploratory study.
We choose the CAM-ICU tool as it is a widely used and familiar tool for healthcare workers in the ICU. While CAM-ICU was primarily designed for use in intubated patients, it has been used in nonintubated patients and has also been compared with other tools in this setting. One specific limitation of CAM-ICU may be the lower sensitivity of the tool for the hypoactive form of delirium and this may have contributed to an under-estimation of delirium in our cohort.
| Conclusion|| |
Delirium is common among nonintubated critically ill patients. Future research must focus on modifiable risk factors in this cohort and on prevention and treatment strategies for the same.
We would like to thank Ms. Lakshmi Ranganathan, our Research Manager, for her insightful inputs in manuscript preparation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Salluh JI, Soares M, Teles JM, Ceraso D, Raimondi N, Nava VS, et al.
Delirium Epidemiology in Critical Care (DECCA): An international study. Crit Care 2010;14:R210.
Zhang Z, Pan L, Ni H. Impact of delirium on clinical outcome in critically ill patients: A meta-analysis. Gen Hosp Psychiatry 2013;35:105-11.
Ely EW, Shintani A, Truman B, Speroff T, Gordon SM, Harrell FE Jr., et al.
Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA 2004;291:1753-62.
Ely EW, Inouye SK, Bernard GR, Gordon S, Francis J, May L, et al.
Delirium in mechanically ventilated patients: Validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA 2001;286:2703-10.
Carrasco G, Baeza N, Cabré L, Portillo E, Gimeno G, Manzanedo D, et al.
Dexmedetomidine for the treatment of hyperactive delirium refractory to haloperidol in nonintubated ICU patients: A nonrandomized controlled trial. Crit Care Med 2016;44:1295-306.
Dubois MJ, Bergeron N, Dumont M, Dial S, Skrobik Y. Delirium in an intensive care unit: A study of risk factors. Intensive Care Med 2001;27:1297-304.
Girard TD, Pandharipande PP, Ely EW. Delirium in the intensive care unit. Crit Care 2008;12 Suppl 3:S3.
Louis C, Godet T, Chanques G, Bourguignon N, Morand D, Pereira B, et al.
Effects of dexmedetomidine on delirium duration of non-intubated ICU patients (4D trial): Study protocol for a randomized trial. Trials 2018;19:307.
Van Rompaey B, Schuurmans MJ, Shortridge-Baggett LM, Truijen S, Elseviers M, Bossaert L. A comparison of the CAM-ICU and the NEECHAM confusion scale in intensive care delirium assessment: An observational study in non-intubated patients. Crit Care 2008;12:R16.
Vasilevskis EE, Girard TD, Ely EW. The bedside diagnosis of ICU delirium: Specificity is high, let's optimize sensitivity. Am J Respir Crit Care Med 2012;185:107-8.
[Table 1], [Table 2]