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 Table of Contents  
Year : 2021  |  Volume : 7  |  Issue : 1  |  Page : 35-41

Clinico-etiological profiles in patients with delirium in intensive care unit setting

1 Private Consultant Psychiatrist, Hyderabad, Telangana, India
2 Department of Psychiatry, Chalmeda Anand Rao institute of Medical Science, Karimnagar, Telangana, India

Date of Submission16-Apr-2021
Date of Decision20-May-2021
Date of Acceptance22-May-2021
Date of Web Publication18-Jul-2021

Correspondence Address:
Dr. Preeti Gudlavallety
Department of Psychiatry, Chalmeda Anand Rao Institute of Medical Sciences, Karimnagar, Telangana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/tjp.tjp_14_21

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Background: Delirium is a neuropsychiatric disorder with a prevalence ranging from 16% to 53.6% in India. Although delirium is characterized as a unitary syndrome, not all symptoms follow the same trajectory over the course. Hence, there is a necessity for a larger number of studies to understand these phenomenological and etiological profiles across different regions in India.
Aim: To study the clinico-etiological variables and phenomenological profile in delirium in the intensive care unit (ICU) setting.
Materials and Methods: A longitudinal prospective study was conducted in a tertiary care hospital including all consecutive delirium patients who referred to the psychiatry department from ICU. All the participants' socioeconomic data were obtained and were administered. Charlson comorbidity index, Neelon and Champagne confusion scale, Richmond agitation sedation scale, delirium etiology checklist, delirium revised scale, revised-98, descriptive statistics, and ANOVA were used for statistical analysis.
Results: Out of 51 study population, the mean age was 57.82 ± 17.19 years, with male preponderance and belonging to lower-middle and upper-lower class. 70.58% of the patients were found to have moderate–severe delirium. Majority of the referral population are from general medicine and of hyperactive delirium. There is no association established with the number of drugs and comorbidities with delirium severity. Metabolic disturbances are most common; sleep–wake cycle disturbance has the highest score and also the most common feature in delirium severity.
Conclusion: Majority of the cases who were referred are male in moderate–severe stage and hyperactive delirium. As the detection of cases is challenging in the ICU settings, better understanding of the underlined etiological and phenomenological profiles may aid in easy identification of delirium cases at early stages.

Keywords: Clinico-etiological profile, delirium, intensive care unit, phenomenology

How to cite this article:
Reddy IS, Kulkarni PK, Gudlavallety P, Gollepally P, Sriperumbudur G. Clinico-etiological profiles in patients with delirium in intensive care unit setting. Telangana J Psychiatry 2021;7:35-41

How to cite this URL:
Reddy IS, Kulkarni PK, Gudlavallety P, Gollepally P, Sriperumbudur G. Clinico-etiological profiles in patients with delirium in intensive care unit setting. Telangana J Psychiatry [serial online] 2021 [cited 2021 Dec 2];7:35-41. Available from: http://www.:tjpipstsb.org/text.asp?2021/7/1/35/321764

  Introduction Top

The word Delirium originates from the Latin word “Delirio” which means to go crazy. Although the word delirium mention was first made 2400 years ago in the book of epidemics by Hippocrates, the significance and impact of delirium on treatment outcomes has only gained relevance in recent years.[1] The term delirium was coined by Celsius. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) defines delirium as “Disturbance in attention and awareness over a short period of time, representing a change from baseline attention and awareness with a tendency to fluctuate in severity during the course of a day.[2]

Recent studies in India reported a prevalence of delirium in the intensive care unit (ICU) ranging from 16% to 53.6%.[3],[4],[5] Incidence of new delirium per admission ranged from 3% to 29%, and 1 in 5 inpatients in a general hospital experienced delirium during some point of their hospitalization.[6] Incidence of delirium in the ICU patients ranging from 70% to 87%.[7]

The phenomenological profile is varied across clinical populations and healthcare settings.[8] Attention deficits, sleep–wake cycle disturbance, motor-activity changes, language, and thought disturbances occur more commonly than psychosis or affective changes.[8],[9] Early identification of the clinical manifestations has potential implications in the management and prevention. A range of etiologies and maintaining factors are implicated in delirium such as age on and above 65 years, male sex, cognitive dysfunction, sensory and functional impairment, decreased oral intake, on various medications, with coexisting medical conditions, hence requiring a broad multifactorial and multidisciplinary approach.[3]

Studies from developed countries emphasize older populations from geriatric and palliative care settings where particular etiologies and confounding effects of comorbid dementia are prominent. However, in developing countries, it is more common in younger subjects with different etiological underpinnings.[10] Studies from developing countries are few, and there is a paucity of Indian studies even though delirium is a common diagnosis among psychiatric referrals.[3] With this background in mind, the current study was undertaken to assess the variability in clinical and etiological profiles in patients in an ICU setting in the Indian scenario.


To study the clinico-etiological variables and phenomenological profile in delirium in ICU setting at a tertiary care hospital in Telangana.


  1. To observe the phenomenological profile in delirium patients
  2. To observe the causative factors of delirium in an ICU setting in a tertiary care hospital
  3. To determine delirium in relation to sociodemographic variables and clinical profiles.

  Materials and Methods Top

Source of data

A longitudinal prospective study was carried out at a tertiary care, multispecialty hospital over a period of 3 months from December 2018 to February 2019. Institutional ethical committee approval for the study has been taken.

All the patients who were consecutively referred from ICU for Consultation-Liaison Services and diagnosed as having delirium according to the DSM-5 criteria were included in the study. Assessments were based on all available information obtained from the medical staff and medical records. Sociodemographic variables and other medical information were collected using semi-structured pro forma and administered the following structured scales.

Charlson comorbidity index

The Charlson score takes into account the presence of 19 diseases weighted on the basis of their association with mortality. A Charlson sum is calculated according to the number of morbidities affecting an individual. This sum can be used in conjunction with the patient's age as the Charlson score to calculate the probability of survival.[11]

Neelon and Champagne confusion scale

It is a screening scale which can be used by clinicians and nurses to rate the patient's behavior while providing routine care to patients. The scale has three subscales. Subscale-1 has three items and measures cognitive processing (attention, ability to follow command, and orientation) and the rating varies from 0 to 14 for the subscale, subscale-2 has three items and measures behavior (appearance and motor and verbal behavior) and the rating varies from 0 to 10 for this subscale, and the subscale-3 also has three items to rate physiological parameters (stability of vital functions [temperature, blood pressure, heart rate and respiration], oxygen saturation stability, and urinary continence control). The total score ranges from 0 (minimal responsiveness) to 30 (normal function). A score below 20 points indicates moderate to severe delirium, while a score between 20 and 24 suggests mild or early development of delirium. A score of 25 and 26 suggests that the patient is “not delirious,” but the patients are at high risk for delirium, while a score of 27–30 indicates normal function. The scale takes 10 min to complete. It has high inter-rater reliability (r = 96), good validity, high sensitivity (95%), and specificity (78%).[12]

Richmond agitation sedation scale

Level of arousal was measured by using Richmond agitation sedation scale (RASS) which is a 10-point scale ranging from +4 to −5, with a RASS score of 0 denoting a calm and alert patient. Positive RASS scores denote positive or aggressive symptomatology ranging from +1 (mild restlessness) to +4 (dangerous agitation). The negative RASS scores differentiate between response to verbal commands (RASS score −1 to −3) and physical stimulus (RASS score −4 and −5).[13]

The delirium etiology checklist

It was used to standardize attribution of etiology on the basis of all available clinical information into 12 categories of etiological causation, each rated on a 5-point scale for degree of attribution to the delirium episode, ranging from “ruled out/not present/not relevant” (0) to “definite cause” as follows: drug intoxication/drug withdrawal (DW); metabolic/endocrine disturbance (M-ED); traumatic brain injury; seizures; infection (intracranial); infection (systemic); neoplasm (intracranial); neoplasm (systemic); cerebrovascular; organ insufficiency; other central nervous system; and other systemic causes. This system allows for the documentation of the presence and suspected role for multiple potential causes of delirium and provides more information specifically relevant to delirium than a listing of current medical conditions.[14]

The delirium rating scale, revised-98

It is designed for broad phenomenological assessment of delirium. It is a 16-item scale, with 13 severity and 3 diagnostic items, with high inter-rater reliability, sensitivity, and specificity for detecting delirium in mixed neuropsychiatric and other hospital populations. Each item is rated 0 (absent/normal) to 3 (severe impairment), with descriptions anchoring each severity level. Severity scale scores range from 0 to 39, with higher scores indicating more severe delirium. Delirium typically involves scores above 15 points (severity scale) or 18 points (total scale), when dementia is in the differential diagnosis. It has good inter-rater reliability, validity, sensitivity, and specificity for distinguishing delirium in mixed neuropsychiatric populations that include dementia, depression, and schizophrenia.[15]

Data analysis was done using Epi info version 7, Developed by center for disease control and prevention and a repository of GitHub Inc, a subsidiary of Microsoft. Descriptive statistics and ANOVA were used for statistical analysis

  Observation and Results Top

Out of 51 study population, the mean age of the sample taken is 57.82 ± 17.19 years. The mean age for moderate–severe delirium was 58.94 ± 16.53 years and for mild delirium was 54.85 ± 19.73 years [Table 1].
Table 1: Sociodemographic factors

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Out of the 51 patients in the study, 40 (78.4%) were males and 11 (21.6%) were females, with a sex ratio of 3.6:1. Among 40 male patients, 33 had moderate-to-severe delirium and 7 had mild delirium. Only four females had moderate-to-severe delirium and 7 females had mild delirium. The P = 0.002 was significant indicating male preponderance [Table 1].

Majority of the patients belonged to lower-middle (39.2%) and upper-lower class (39.2%) in the study population [Table 1].

Majority of the referral population was from general medical department (68.63%) followed by orthopedic department (15.69%) [Table 2].
Table 2: Distribution according to referring department

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Majority of the patients had 6–10 drugs (58.8%) at the time of referral followed by 1–5 drugs (37.3%), with the mean number of drugs per patient being 6.25 ± 1.96. The P = 0.315 indicating no association between number of drugs and delirium severity [Table 3].
Table 3: ANOVA for number of drugs with Neelon and Champagne confusion scale

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Majority of patients had two comorbidities (27.4%) followed by one comorbidity (25.6%). The mean score for moderate–severe delirium was 2.0 ± 1.58 and for mild delirium was 1.64 ± 1.45 [Table 4].
Table 4: ANOVA of comorbidities, Richmond agitation sedation scale, etiology with Neelon and Champagne confusion scale

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Majority of the study population was in hyperactive delirium with 21 patients (41.3%) being very agitated, 14 patients (27.4%) being agitated, and 8 patients (15.7%) being restless at presentation. Only 4 patients (7.84%) were combative and another 4 patients (7.84%) were in hypoactive presentation of delirium [Table 4].

The mean RAAS score of moderate–severe group was 2.51 ± 1.02 and mild delirium group was 1.29 ± 1.44, indicating prominence of hyperactive delirium [Table 4].

Majority of the patients had two etiologies (47.06%) implicated in the causation of delirium. The mean for etiologies in moderate-to-severe delirium was 1.81 ± 0.74 and for mild delirium was 1.36 ± 0.50. The probability of number of etiologies affecting the severity of delirium was 0.47 which is not significant [Table 4].

The phenomenological profile was derived from delirium rating scale, revised-98 (DRS R-98) scale, the mean severity score was 23.4 ± 6.76, and the mean total score was 28.8 ± 6.93.

The phenomenological profile for moderate-to-severe delirium showed the highest scores for sleep–wake cycle disturbance (96%), perceptual disturbance (90%), attention (90%), orientation (88%), and thought-process abnormality (80%). Next highest scores were for motor agitation (76%), language disturbance (53%), lability of affect (49%), delusions (45%), and long-term memory (41%).

The most common delirium features at any severity were as follows: sleep–wake cycle disturbance (100%), attention (100%), orientation (100%), language (100%), short-term memory (100%), visuospatial ability (100%), perceptual disturbances (98%), motor agitation (94%), delusions (92%), thought-process abnormalities (88%), lability of affect (76%), long-term memory (67%), and motor retardation (11%) [Table 5].
Table 5: Delirium revised scale, revised-98 item frequencies and mean (standard deviation) scores for the delirium patients

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M-EDs were the most common etiologies observed (54.98%) followed by cerebrovascular accident (CVA, 23.52%) and DW (23.52%) [Table 6].
Table 6: Frequency and percentage of individual etiologies

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  Discussion Top

In the current study, 51 patients were recruited after obtaining ethical clearance.


Age of the sample population ranged from 20 to 85 years with the mean age of 57.82 ± 17.19 years. Majority of the subjects were aged between 61 and 80. There was no statistical significance between severity of delirium and age in this study which is similar to the study done by Jayaswal AK et al. on ICU patients, wherein the mean age for patients with delirium was 56.72 ± 18.9 years.[3] Another study done by Grover et al. on 66 patients admitted in the ICU reported a mean age of 40.9 ± 17.5 and no association between age and onset of delirium.[16]


Predominance of male patients was identified in the current study and found to be statistically significant. A previous study conducted by Grover et al. in the ICU settings on 66 patients in India observed male patients outnumbered the female patients similar to our study.[16] In a study done by Valenzuela et al., women were found to have a more late life active cognitive lifestyle than men, which helps them to maintain a better cognitive reserve and less susceptibility to dementia or delirium which may explain the reason for less susceptibility of females in our study.[17]

Socioeconomic status

Majority of the study population belonged to lower middle and upper lower socioeconomic classes. In the current study, there was no association of socioeconomic profile with severity of delirium.

Referral source

68.6% of the patients were referred from general medical department (68.6%) followed by orthopedic department (15.8%). In a study done by Pavan et al., psychiatry referrals were from acute medical care and general medicine ward followed by orthopedic ward similar to the current study. This could be due to long stay of patients in orthopedics and medicine wards.[18]

Severity of delirium

According to results obtained from Neelon and Champagne confusion scale, about 70.58% of the patients were found to have moderate-to-severe delirium and 29.41% of patients had mild delirium.


The average number of drugs the patients were on at the time of referral was between 1 and 10 drugs, with the mean number of drugs per patient being 6.25. A study done in India indicated no relation with number of drugs and delirium, but benzodiazepine administration was identified as a precipitating factor.[3] Polypharmacy is usually a sequelae of admission to the ICU, is associated with medication-related side effects and drug interactions, and is one of the major modifiable risk factors for delirium. Many studies have reported polypharmacy as an independent risk factor for developing delirium in elderly patients.[19] Although polypharmacy is a known risk factor for developing delirium, there was no significant association between delirium severity and the number of drugs the patient was on at the time of referral in this study. A study done in India on cardiac care unit patients revealed that the mean number of medications received per patient was 6.65 similar to the current study and those with more than 5 medications were more susceptible to delirium.[20]


Comorbidities as ascertained by Charlson comorbidity index (CCI) ranged from 1 to 8 per patient with the mean number of comorbidities per patient being 2. The comorbidity profile did not affect the severity of delirium in this study, the same findings were replicated in the study by Jayaswal AK et al.[3] A study by Grover et al. reported a mean comorbidity score in delirium as 0.98 with a significant association of CCI score with delirium.[16] CCI was significantly associated with delirium in postoperative patients.[21] A large study done in North London has highlighted that patients with undetected delirium were more likely to display high levels of medical comorbidity on CCI, which could be due to focus on treatment of comorbidities over delirium.[22]

Hypoactive versus hyperactive delirium

In the current study, majority of the patients fell under the motor sub-type of hyperactive delirium compared to the hypoactive delirium based on the RASS. According to a study done by Grover et al., hypoactive delirium was the most common form characterized by psychomotor slowing, apathy, and decreased responsiveness.[16] Alternatively, a purely hyperactive subtype of delirium, characterized by psychomotor agitation, hallucinations, and emotional lability is very infrequent in the intensive care setting. When hyperactive delirium does occur, it is usually not the only subtype experienced but rather may fluctuate with hypoactive delirium and be considered a mixed sub-type.[23] In a study by Meagher, the motor-subtype patterns in delirium were reviewed and it highlighted the occurrence of relative hyperactivity of clinical presentation as reason for psychiatry consultation versus elderly medical, palliative care, and ICU populations, which was similar to the results showing higher number of hyperactive delirium in the current study referral population.[24] This discrepancy could be due to the knowledge gap in identifying delirium amongst the doctors in various specialties as cases presenting with motor agitation, perceptual disturbance and suspected aetiology being alcohol withdrawal are only referred to psychiatrist.

Phenomenological profile

The phenomenological profile was derived from DRS R-98 scale, the mean severity score was 23.4 ± 6.76, and the mean total score was 28.8 ± 6.93. The most common delirium features were disturbances in sleep–wake cycle disturbance, attention, orientation, language, short-term memory, visuospatial ability, perceptual disturbances, motor agitation followed by delusions, thought process abnormalities, lability of affect, and long-term memory. Only 11% of the patients had motor retardation. Perceptual disturbances that were more common in this study could possibly reflect the difference in setting of the study and attitude of referring patients who are difficult to manage or concern from caregivers due to perceptual disturbances. The results in this study are comparable to a study done by Mattoo et al. and Grover et al., reemphasizing the role of circadian rhythm disturbances in delirium and need for environmental changes in the treatment of delirium.[16],[25]

Etiological profile

In the current study, metabolic-endocrine disturbance (M-ED) was the highest frequency among the etiologies followed by CVAs, drug/alcohol withdrawals, and other organic insufficiency conditions leading to delirium. Mattoo et al. had also done a study with delirium etiology checklist (DEC) and obtained similar results with M-EDs constituting about 70% of the etiologies for delirium.[25] In fact, very few studies have focused on the ICU referrals to psychiatry department for consultation and liaison and for understanding the phenomenological profiles in delirium in the Indian setting.


This cross-sectional study has several limitations. As the sample size studied is small and the study population being a referral population, it does not reflect the current prevalence and incidence of delirium.

Although literature exists suggesting that there is no phenomenological difference in delirium patients with and without dementia, the cognitive profile of the sample in this study could not be assessed to rule out dementia which may have been a confounding factor.

  Conclusion Top

Majority of the cases that were referred are male in moderate-to-severe stage and hyperactive delirium. As detection of cases is challenging in ICU settings, better understanding of the underlined etiologies and phenomenological profiles may aid in easy identification of delirium cases at early stages. Prompt identification of delirium and a multidisciplinary approach to its treatment will improve the outcomes in delirium.

Recommendations for future direction

Although delirium is characterized as a unitary syndrome, not all symptoms follow the same trajectory over the course of delirium episode. Delineating delirium phenomenology facilitates detection, understanding neuroanatomical endophenotypes, and patient management.

Prompt identification of delirium and a multidisciplinary approach to its treatment will improve the outcomes in delirium. Consultation Liaison Psychiatry with the primary treating doctors and anesthesiologist in the ICU can confer better outcomes for the patient.

Early identification of delirium onset and prompt referrals might happen if the ICU staff are trained in detection of delirium. There are several tools for the detection of delirium in the ICU setting being used by nurses internationally for the detection of delirium, which is currently lagging in the Indian setting.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]


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