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| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 27
| Issue : 1 | Page : 41-47 |
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Prevalence of delirium and predictors of longer intensive care unit stay: A prospective analysis of 207 mechanical ventilated patients
Rajesh Kumar1, Hoineiting Rebecca Haokip1, Tamanna2, Mukesh Bairwa3
1 Department of Nursing, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
2 Department of Nursing, All India Institute of Medical Sciences, Bhatinda, Punjab, India
3 Department of Internal Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India
| Date of Submission | 26-Oct-2021 |
| Date of Acceptance | 12-Dec-2021 |
| Date of Web Publication | 03-Feb-2022 |
Correspondence Address:
Dr. Rajesh Kumar
Department of Nursing, All India Institute of Medical Sciences, Rishikesh - 249 203, Uttarakhand
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jmhhb.jmhhb_228_21
Introduction: The incidence of delirium varies in literature across the globe. Delirium is reported as one of the leading causes of increased length of hospital stay and mortality among intensive care unit (ICU) patients. This study aims to determine the prevalence and independent predictors of longer ICU stay among mechanically ventilated patients admitted into a medical ICU. Methods: In this prospective investigation, 207 consecutive patients admitted to the medical ICU beyond 72 h of mechanical ventilation at a tertiary care hospital between September 2020 and July 2021 were screened for delirium. ICU nurses assessed sedation and delirium status of patients after 72 h of mechanical ventilation using the Richmond Agitation Sedation Scale and Confusion Assessment Method for ICU. A multiple linear regression model was used to identify the predictors of more extended hospital stay, and the KaplanMeier curve was used to study time-to-event analysis. Results: Findings reveal that 161 (77.8%) patients develop delirium after 72 h of mechanical ventilation in the medical ICU. Patients who experienced delirium were advanced in age (mean ± standard deviation [SD]: 51.50 ± 14.97 vs. 37.39 ± 8.31 years, P ≤ 0.001), and more critically ill (mean ± SD: 15.84 ± 4.94 vs. 6.93 ± 2.07, P ≤ .001) and have multiple organs dysfunctions (mean ± SD: 12.56 ± 3.45 vs. 5.17 ± 1.83, P ≤ 0.001) at the time of admission compared to nondelirious patients. Patients who developed delirium significantly reported a higher oxygen flow (mean ± SD: 7.38 ± 1.08 vs. 6.30 ± 1.43 L/min, P = 0.001), a long duration of ICU stay (mean ± SD: 11.61 ± 1.71 vs. 9.24 ± 1.69 days, P ≤ 0.001), longer days on mechanical ventilation (mean ± SD: 8.44 ± 1.57 vs. 6.22 ± 1.46 days, P < 0.001) and shows higher in-hospital mortality (P = 0.003). Acute Physiology and Chronic Health Evaluation-II (odds ratio [OR]: 0.068 95% CI: 0.027–0.019, P < 0.001) and SOFA (OR: 0.132, 95% CI: 0.075–0.189, P = 0.001) reported independent predictors of ICU stay after 72 h of ICU admission. Conclusions: Delirium was reported in more than two-thirds of patients after 72 h of mechanical ventilation. The severity of illness and multiple organ dysfunctions reported independent predictors for longer days of ICU stay.
Keywords: Acute Physiology and Chronic Health Evaluation, delirium, intensive care unit, predictors, Sequential Organ Failure Assessment
How to cite this article:
Kumar R, Haokip HR, Tamanna, Bairwa M. Prevalence of delirium and predictors of longer intensive care unit stay: A prospective analysis of 207 mechanical ventilated patients. J Mental Health Hum Behav 2022;27:41-7 |
How to cite this URL:
Kumar R, Haokip HR, Tamanna, Bairwa M. Prevalence of delirium and predictors of longer intensive care unit stay: A prospective analysis of 207 mechanical ventilated patients. J Mental Health Hum Behav [serial online] 2022 [cited 2023 Mar 31];27:41-7. Available from: https://www.jmhhb.org/text.asp?2022/27/1/41/337227 |
| Introduction | |  |
The experience of admission to a critical care area can have widespread and distinct ramifications for patients. Access to an acute care environment may come along with many psychological problems to patients and distinct from other areas of health care facility.[1],[2] Further, a critical care environment is widely strange and potentially hostile to develop many psychological issues.[3],[4],[5] It is commonly discussed that a patient admitted in critical care is more vulnerable to stress intolerance and low emotional resilience and thus less able to cope with frequent stressors.[5] Added to that, treating critical illness and frequent confrontation of life and death scenarios will often create a stressful environment for everyone, including patients. A limited degree of freedom, life-threatening illness, blinking lights, ambient alarm noises, the humming of suction and respirators, beeping of multipara monitors and devices, and frequent exposure to deaths and work overload will make the milieu of intensive care unit (ICU) more dreadful and frightening for both physical and mental health of patients and health care workers.[4],[6]
Patients admitted in the critical care unit are more vulnerable to developing psychosis or delirium considering multiple organ involvement, comorbidities, use of sedative and muscle relaxants, and other demographic data.[7],[8] Delirium is a common yet underdiagnosed form of organ dysfunctions in long-term critically ill patients.[1],[9] It is defined as sudden change or fluctuation in mental status, including inattention and altered consciousness or developing disorganized thinking patterns.[10] The prevalence of delirium varies in medical and surgical patients from depending on setting and diagnostic criteria used and reported to be 4%–33.96%.[11],[12],[13] However, another Indian study reported a prevalence of 64% among mechanically ventilated patients.[2] Rarely is delirium resulting from a single risk factor; instead, it is multifactorial, resulting from the interaction of many risk factors in a critical patient.[11] Multiple risk factors include the presence of severe illness, substance abuse, medication, advanced age, critical procedures, long duration of hospitalization, comorbid conditions, mechanical ventilation and sedation use, metabolic disorder, and emergency surgery.[9],[11],[14] Delirium has poor health outcomes, such as impaired activities of daily living, prolonged cognitive impairments, and poor quality of life in survivors.[15],[16] Further, it has been evident that delirium may also prolong hospital length of stay, prolonged ICU stay, long-term disability, increased hospital cost, exaggerate complications, and decreased odds of hospital discharge.[1],[11]
Further, a crunch of data concerning delirium in ICU, insufficient sample size, involvement of noncritical care area patients, and use of relatively insensitive measures failed to devise a targeted intervention approach to prevent its occurrence.[17] Moreover, the earlier studies have some methodological flaws that mandate more robust information on risk factors and many other related aspects of delirium, which was the aim of the present study.[17] Being not proactive in working on preventive and management strategies results in a higher incidence of delirium among older patients admitted in ICU.[13],[18],[19] Long term hospitalization in ICU has a strong effect on discharge rate and subsequently may hamper the quality of critical health services to other patients.[20]
Delirium has received very little attention in ICU patients considering a rare reason for admission, believed to be iatrogenic, and assumed that it does not have any adverse consequences on the patient's recovery.[19],[21] However, many previous investigations demonstrated an independent association of delirium with poor clinical outcomes, including worse long-term cognitive outcomes and mortality.[21],[22] Further, a crunch of information on well-designed trials on delirium prevention and treatment strategies fuels the controversy over risk factors.[23] Therefore, we decided to determine the prevalence of delirium and predictors of long term ICU stay among mechanically ventilated patients admitted to one of the medical ICUs.
| Methods | | |
Study design and population
A prospective observational study was conducted in one medical ICU of a tertiary care hospital, North India, from September 2020 to July 2021. The study was approved by the Institutional Ethics Committee (AIIMS/IEC/19/1092), and the manuscript adheres to the STROBE guidelines.[24] Written informed consent was obtained from a close relative of the patient present at the time of investigations after due explaining the objectives of the study. However, the patients' significant were ensured to protect privacy and confidentiality of patient at every step of data collection and during dissemination of the findings.
Two hundred seven mechanically ventilated patients after 72 h in the medical ICU of a tertiary care hospital, North India, from September 2020 to July 2021 were observed and screened for the presence of delirium. Patients aged equal to or more than 18 years admitted to the ICU and on mechanical ventilation for more than 72 h were enrolled in the study. Patients with life expectancy <24 h, who had severe hearing loss, were unconscious, currently diagnosed and on treatment for psychiatric illness or substance abuse, and were admitted with severe head injury were excluded from the study. Patients with deep sedation status (Richmond Agitation Sedation Scale [RASS] ≤-3) were also excluded, considering delirium assessment impossible for the patients.
Data collection
Baseline information on demographic and clinical parameters was collected by reviewing the physical records of the most initial admission ICU charts of the patients. ICU nurses enrolled patients as per inclusion criteria and recorded other baseline information. A structured demographic and clinical profile checklist was used to retrieve data on an individual patient.
A sociodemographic and clinical profile consists of information on age, gender, predictive body weight (kg), oxygen (L/h), hemoglobin (g/L), total bilirubin (mg/L), blood urea (mg/L), creatinine (mg/L), and C-reactive protein (CRP) of the patients admitted to the ICU. The length of a ventilator (days) and ICU stay were recorded once the patient was discharged from ICU or died. The checklist sought validation from experts of the ICU, nursing supervisors, and critical care nurses. The questionnaire consisted of a validated instrument to screen sedation status and delirium status among patients admitted to the medical ICU.
One of the ICU nurses trained to use Confusion Assessment Method for ICU (CAM-ICU) to detect delirium in the study population confirmed the presence or absence of delirium. ICU nurses enrolled patients who completed 72 h on mechanical ventilation as per inclusion criteria and were found eligible for delirium assessment after screening for sedation status using RASS. Delirium was measured using a reliable and validated instrument, the CAM-ICU.[25] The CAM assessment recorded delirium based on changes or fluctuation in the patient's mental status, plus disorganized thinking or an altered level of consciousness and inattention.[25],[26] Each patient was evaluated only once for the presence of delirium using CAM-ICU on a subsequent morning at 8:00 am after 72 h of mechanical ventilation in ICU. The findings of the presence or absence of delirium were recorded in a pretested paper checklist.
The RASS[27] was used to screen the sedation status before using the CAM-ICU to determine delirium status. The RASS was used to assess the neurologic situation of the patient by the data collecting nurse and defined as usual, delirious, or unconscious every day. RASS is an objective method that takes 1–2 min to measure the arousal or delirious status of the patient. It is a 10 point well validates and reliable scale used in many similar earlier studies[28],[29] score from +1 to +4 from agitation to combativeness where 0 means an alert and calm state, and −1 to −5 is denoted for successive levels of difficult arousal or coma.[27],[30] Patients were categorized as delirious if they responded to the verbal command to eye-opening (RASS Score of −3 to +4). Only painful/physical stimulation with movement without eye-opening (RASS score of −4) or no response to physical or verbal stimulation were recorded as comatose (RASS score of −5). Nondelirious or comatose patients were categorized in the normal category.
In case of RASS score was −4 or −5, the test was stopped, and the patient was reassessed in a subsequent shift for delirium. If RASS is above −4 (−3 through +4), then CAM-ICU was administered to assess delirium in the patient. Every patient was evaluated for severity of illness status of the patient using Acute Physiology and Chronic Health Evaluation-II (APACHE-II)[31] and Sequential Organ Failure Assessment (SOFA)[32] score to determine the progression of organ dysfunction of each patient.
| Results | | |
Of the 207 patients screened after 72 h of mechanical ventilation, 161 (77.8%) experienced delirium. Baseline characteristics of the patients presented in [Table 1]; compared the cohort of delirium and nondelirious based on the gender, age, APACHE-II, SOFA, oxygen administration, predictive body weight (kg), blood urea, hemoglobin, creatinine, total bilirubin, CRP, and types of admission in the medical ICU. Patients who experienced delirium were advanced in age (mean ± standard deviation [SD]: 51.50 ± 14.97 years vs. 37.39 ± 8.31 years, P < .001), and more critically ill (mean ± SD: 15.84 ± 4.94 vs. 6.93 ± 2.07, P < 0.001) and have multiple organs dysfunctions (mean ± SD: 12.56 ± 3.45 vs. 5.17 ± 1.83, P < 0.001) at the time of admission compared to nondelirious patients. Patients who developed delirium significantly reported on higher oxygen administration (mean ± SD: 7.38 ± 1.08 L/min vs. 6.30 ± 1.43 L/min, P = 0.001), stayed for long duration in ICU (mean ± SD: 11.61 ± 1.71 days vs. 9.24 ± 1.69 days, P < 0.001), longer days on mechanical ventilation (mean ± SD: 8.44 ± 1.57 days vs. 6.22 ± 1.46 days, P < 0.001) and shows higher in-hospital mortality (P = 0.003). More patients were admitted from medical wards (49.7%), followed by emergency areas (41.6%). In contrast, in the nondelirious cohort, this trend is reversed to the emergency department (58.7) followed by medical wards (37.0%) [Table 1]. | Table 1: Characteristics of patients admitted in intensive care unit (n=207)
Click here to view |
Clinical outcomes and multivariate analysis
Results indicate that the delirious cohort stayed for a longer duration in ICU (median days; 11 interquartile range 10–12 days, P < 0.001) and spent more days on mechanical ventilation (median days; 8 interquartile range 7–9 days, P < 0.001) than the nondelirious cohort. A KaplanMeier curve for the probability of mortality according to the given clinical variables of delirium and nondelirium cohort is shown in [Figure 1]. Further, simple linear regression (univariate analysis) was applied to identify the unique predictor of ICU stay and duration of mechanical ventilation for more than 72 h in ICU. | Figure 1: Delirium versus duration after 72 h of mechanical ventilation. This KaplanMeier plot shows the relationship between delirium and time after 72 h of mechanically ventilated by classification of ever delirium versus nondelirious (P < 0.001, univariate analysis)
Click here to view |
Using simple linear regression analysis, findings revealed that length of ICU stay of the mechanically ventilated patient was found significantly associated with age (r = 0.163, P = 0.001), APACHE-II (r = 0.406, P < 0.001), SOFA (r = 0.476, P < 0.001), and oxygen administration (r = 0.269, P < 0.001). Further, the probability of remain on mechanical ventilation after 72 h of ICU admission was found associated with SOFA (r = 0.473, P < 0.001) followed by less to APACHE (r = 0.400, P < 0.001), oxygen administration (r = 0.259, P < 0.001), and age (r = 0.239, P = 0.001) [Table 2]. | Table 2: Simple linear regression (univariate analysis): Predictors of length of stay in intensive care unit and 72 h of mechanical ventilation
Click here to view |
Using multiple linear regression analysis, APACHE-II (P < 0.001) and SOFA (P < 0.001) scores found the strongest predictors of longer duration of ICU stay. Further, APACHE-II (P < 0.001) and SOFA score (P = 0.001) reported the strongest predictors of staying on mechanical ventilation after 72 h of ICU admission [Table 3] and [Figure 2]. Represent the KaplanMeier graph for the probability of death in patients who stayed on mechanical ventilation after 72 h per the given clinical variables of delirium and nondelirium. | Figure 2: Delirium versus mortality. This KaplanMeier plot shows the relationship between delirium and in-hospital mortality by classification of delirium and nondelirium (P < 0.001, univariate analysis)
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 | Table 3: Multiple linear regression model: Predictors of length of stay after 72 h of mechanical ventilation
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| Discussion | | |
This study finding demonstrates delirium as a common complication in ICU patients, occurring in 77.8%. Where 16.5% patients developed delirium within 24 h of admission in ICU, and 33% developed delirium after 24 h of ICU stay.[33] Likewise, similar proportion of the patients developed delirium after 24 h of admission;[1] however, this proportion of delirium was high among mechanically ventilated patients.[2] Further, the same study reported mean duration of stay of patients 8.56 (6.95) days which is lower side considering the findings of the present study.[2] Likewise, another work from the United States reported delirium in 81.7% of cases during their ICU stay, similar to the evidence published by the Society of Critical Care Medicine (SCCM) clinical practice guidelines.[7],[34]Added, approximately half of the patients on noninvasive ventilation developed at least one episode of delirium (48%).[29] However, another work from Indian literature reported a lower incidence of delirium (24.4%) in ICU patients.[2] These shreds of evidence indicate substantial variability in the prevalence of delirium among ICU patients and warrant a large-scale multi-center study to reach a specific conclusion.[9] The authors believe that using different protocols to manage ICU patients, the size of the ICU, training of health personnel, and strict adherence to specific guidelines could be probable reasons for this significant variability in the prevalence of delirium across the studies.
Further, delirium is significantly more common in patients with advanced age who stayed longer in the ICU with acute and critical problems and high oxygen administration. These findings concur with the literature that reported a significant association of delirium with the severity of illness and advanced age in patients.[2],[14] Nevertheless, there are well-documented pieces of evidence that reflect a higher prevalence of delirium in patients with advanced age and have more critical illnesses in earlier published literature in Western countries as well.[35],[36]
Further, the present study findings reported a significantly longer ICU stay and mortality in the delirious cohort. These findings align with an earlier study on ICU delirium, which reported a greater risk of patients remaining in the hospital and high in-hospital mortality.[1],[2],[14],[37] The findings on the association of delirium to increase mortality among mechanically ventilated patients are further matched to the earlier work.[15] However, it is known to delirium for its relationship to higher in-hospital mortality and longer duration of hospital stay in mechanically ventilated patients.[2],[38] Further, patients with delirium remain on fewer ventilator-free days, which concurs with the present study's findings.[38],[39] The findings on delirium with a longer duration of stay and higher mortality are well documented in earlier western literature.[7],[27],[28],[35],[39],[40] The findings of the present work is in consensus to the SCCM clinical practice guidelines recommendation for routine monitoring of the delirium among adult ICU patients using a standardized and validated tool including, CAM-ICU.[9],[35]
We did not study a significant relationship between sedative drugs and mortality after the discharge of the patients from the hospital, and our mortality analysis may not be as comprehensive as published in earlier reports that use different types of follow-ups.[27],[30] A significant association of delirium with increased mortality, longer duration of stay, and subsequent institutionalization would require one to think that our study findings are not spurious and consistent with the earlier literature.[41],[42],[43],[44]
Delirium is dangerous yet received little attention and often goes neglected. More extended hospital stays and higher mortality in the delirium cohort warrant strong consideration to prevent the occurrence of delirium. Implementation of the recommendations of the SCCM clinical practice guidelines with the routine monitoring to patient can play a key role in early detection of delirium.[9],[35] Further, it has been evident that 60-80% of delirium goes undetected due to failure to use a standard monitoring approach in the ICU.[45],[46],[47]
The strength of this report includes a unique and large patient population and the long-term prospective enrollment of the patients after 72 h of mechanical ventilation. The use of widely used and validated instruments (CAM-ICU and RASS) by a trained nurse will further make the study unique. The study team performed a baseline assessment of each patient admitting to the ICU for severity of illness and organ dysfunction using APACHE-II and SOFA, indicate more accuracy. We applied the Kaplan–Meier curve to study time-to-event analysis and used mortality and delirium time-dependent covariates.
The work should be appraised under many limitations and warrant comments. First of all, we only study delirium development after 72 h of mechanical ventilation in ICU patients, which may not give apparent precision in the fluctuation and initial time of delirium development in patients. We have studied a minimal number of clinical parameters, and the role of other significant clinical variables needs to be investigated. Third, the prospective observation investigation does not fulfill the cause-and-effect relationship and warrant a randomized, prospective clinical trial. Further, we did not calculate a precise sample size; however, a large sample size considering earlier work is enrolled in the study, but still, it should be viewed as a limitation of this work. Researchers recommend using the severity index for delirium in further study to precisely measure the intensity of delirium and fluctuation in the status related to ICU days. It is also recommended to study the impact of many more biomarkers, sedative drugs, systematic infection, injury, and other brain dysfunctions on delirium.
The study findings have substantial implications for improving ICU practices for older patients admitted with complex critical illnesses. A significant prevalence of ICU delirium justifies the seriousness of the problem and the need to address the neglected issue in critical areas. Delirium has long-lasting unfavorable health outcomes, including impaired communication, decision making, and mortality in hospitals or outside, and demands the attention of medical health personals in ICU and general medical wards. An early screening, diagnosis, and judicious use of preventive strategies could be beneficial to prevent the development of delirium.
A few caveats deserve comments. There is a need for future research in this area. The authors recommend planning a large-scale study using an appropriate design such as prospective randomized controlled trials to prove a causal relationship between different clinical parameters and outcomes.
| Conclusions | | |
Delirium is a common phenomenon among patients admitted to the ICU. Delirium was found associated with a longer duration of hospital stay and higher in-hospital mortality. The authors believe in the recommendation of the SCCM clinical practice guidelines for routine delirium monitoring of all patients (including nonventilator).
Research quality and ethics statement
This study was approved by the Institutional Review Board/Ethics Committee at the All India Institute of Medical Sciences (AIIMS), Rishikesh, India (Approval No. AIIMS/IEC/19/1092; Approval date No. November 05, 2019). The authors followed the applicable EQUATOR Network (http://www.equator-network.org/) guidelines, specifically the STROBE Guidelines, during the conduct of this research project.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
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