Abstract
Background:
Delirium, an acute and often fluctuating disorder of attention and cognition, poses significant challenges in clinical care due to its varied presentation and complex etiological factors. In rural healthcare settings, where resources and awareness are limited, delirium is frequently under-recognized and inadequately managed.
Aim:
To investigate the factors associated with and types of delirium and their correlation with sociodemographic profiles in hospitalized patients at a tertiary care rural hospital in Central India.
Materials and Methods:
This cross-sectional observational study was conducted on 120 patients diagnosed with delirium and referred to the Department of Psychiatry. A comprehensive assessment was performed using the Delirium Etiology Checklist (DEC) and Richmond Agitation Sedation Scale (RASS), and data spanning various associated factors, subtypes, and demographic variables were analyzed using SPSS version 27.0.
Results:
The cohort had a mean age of 48.2 ± 15.96 years, with a predominance of male patients (84.2%). Substance withdrawal (16.96%), anemia (12.5%), and renal derangement (11.6%) emerged as the major factors associated with delirium. Hyperactive delirium was observed in 88.3% of patients, while hypoactive delirium was found in 11.7%. A significant association was noted between cardiac decompensation and sepsis with hypoactive delirium, while substance withdrawal with hyperactive delirium.
Conclusion:
The study highlights the need for a systematic approach to identify and manage delirium’s underlying associated factors, particularly in resource-limited settings, to prevent adverse outcomes.
Keywords: Delirium, etiological factors, hyperactive delirium, hypoactive delirium, rural healthcare
Delirium is an acute neuropsychiatric syndrome marked by a disturbance in attention, cognition, and consciousness. It is typically characterized by an acute onset and a fluctuating course.[1] Delirium affects a wide range of hospitalized patients, particularly the elderly, and is associated with multiple adverse outcomes, including increased mortality, longer hospital stays, and long-term functional impairment.[2] The pathophysiology of delirium is multifactorial, involving an interplay between predisposing factors such as advanced age, dementia, and frailty. It has precipitating factors such as infections and metabolic derangements post-surgery and substance withdrawal.[3]
Globally, delirium’s prevalence in hospital settings ranges from 11%–35% in general medical wards to 70%–87% among postoperative and intensive care unit (ICU) patients.[4] In India, a country experiencing a significant demographic shift toward an aging population, delirium is increasingly recognized as a common and serious condition among hospitalized elderly patients. However, it remains under-recognized, particularly in rural areas where healthcare resources are often limited.[5] Studies have highlighted that delirium in these settings is not only prevalent but also frequently misdiagnosed or overlooked due to the subtle presentation of hypoactive forms, lack of standardized screening protocols, and limited clinical awareness.[6]
The clinical manifestations of delirium are broadly classified into three subtypes: hyperactive, hypoactive, and mixed. Hyperactive delirium is characterized by agitation, restlessness, and hallucinations, whereas hypoactive delirium presents with lethargy, reduced motor activity, and unresponsiveness, often leading to its misdiagnosis as depression.[7] Mixed delirium features alternating symptoms of hyperactivity and hypoactivity. This variability in clinical presentation, combined with the broad spectrum of associated factors, complicates the diagnosis and management of delirium. As such, a thorough understanding of the various factors and types is critical for effective diagnosis and treatment of delirium.
Current literature suggests that delirium results from complex neurobiological processes, including neurotransmitter imbalances, inflammatory responses, and oxidative stress. For example, disruptions in cholinergic and dopaminergic neurotransmission are commonly implicated in delirium pathophysiology.[8] Furthermore, systemic inflammation, often secondary to infections or surgical trauma, is known to contribute to delirium onset by promoting neuroinflammation and blood-brain barrier dysfunction.[9] Metabolic disturbances such as hyponatremia and hypoxia have also been identified as significant contributors, especially in elderly patients who are more vulnerable to such changes.[10]
In this scenario, the management of delirium requires a comprehensive approach that addresses both the predisposing and precipitating factors. This is particularly relevant in rural healthcare settings where challenges related to early recognition and appropriate management are compounded by limited healthcare infrastructure and expertise.[11] Thus, this study aimed to explore the etiological spectrum and motor subtypes of delirium in a rural tertiary care hospital in Central India, offering insights into its association with sociodemographic factors. Such data is essential to improve clinical practices and healthcare outcomes for delirium patients in resource-limited settings.
MATERIALS AND METHODS
Study design and setting
This was a cross-sectional study conducted in a tertiary care hospital located in a rural setting. The study was conducted in general wards and ICUs, where patients with altered mental status were routinely evaluated for delirium. The study duration was of 18 months from June 2022 to December 2023.
Study population
Inclusion criteria
All cases of delirium more than 18 years of age admitted to the hospital and referred for psychiatric evaluation.
Exclusion criteria
Intubated Patients
Caregivers not consenting for the study.
Tools
Delirium Etiology Checklist (DEC): The DEC was employed to document and evaluate multiple potential associated factors contributing to delirium. This tool ensures a systematic approach to identifying underlying associated factors by considering medical history, physical examination findings, and relevant laboratory results.[12]
Richmond Agitation Sedation Scale (RASS): The RASS is a widely validated tool used to assess the level of sedation and agitation in patients, ranging from +4 (combative) to −5 (unarousable). It was used in differentiating hyperactive and hypoactive delirium.
Study procedure
The study was conducted after obtaining approval from the institutional ethics committee (MGIMS/IEC/PSY/25/2023). Patients with altered sensorium admitted to various clinical departments were referred to the Department of Psychiatry for assessment and management. Initial evaluation was done by a psychiatry resident, who identified cases suggestive of delirium, which were then confirmed by the consultant using DSM-5 criteria. Cases were then consecutively selected as per the inclusion and exclusion criteria. Potential associated factors were identified based on clinical and laboratory findings by using the Delirium Etiology Checklist (DEC). The type of delirium was classified as hypoactive or hyperactive using the Richmond Agitation-Sedation Scale (RASS).
Data collection and analysis
Data were collected from patients and caregivers using semi-structured Google Forms and then exported to Microsoft Excel for cleaning. Descriptive statistics, including frequencies and percentages, described the distribution of variables such as age, sex, and source of referral. The Richmond Agitation Sedation Scale (RASS) and the DEC were used to assess the types and causes of delirium, respectively. Fisher’s exact test was used for the correlation between the factors associated and subtypes of delirium. Statistical analysis was carried out using SPSS software version 27.0.
RESULTS
Sociodemographic profile
The mean age of the patients was 48.2 years (SD ± 15.96), with most patients falling within the age group of 30–49 years (46.6%). The sample had a marked male predominance (84.2%), and most patients were referred from the Medicine ICU (41.7%) [Table 1].
Table 1.
Sociodemographic profile of the study population (n=120)
| Variables | n (%) | |
|---|---|---|
| Ages (in years) | Mean±SD | 48.2±15.96 |
| Age group (years) | 20–29 | 10 (8.3) |
| 30–49 | 56 (46.6) | |
| 50–69 | 38 (31.7) | |
| ≥70 | 16 (13.3) | |
| Sex | Male | 101 (84.2) |
| Female | 19 (15.8) | |
| Source of referral | Psychiatry ward | 25 (20.8) |
| Medicine ward | 12 (10) | |
| Medicine ICU | 50 (41.7) | |
| Surgery ward | 7 (5.8) | |
| Surgery ICU | 19 (15.8) | |
| Orthopedics ward | 5 (4.2) | |
| Orthopedics ICU | 2 (1.7) | |
Factors associated with delirium
The leading factors associated with delirium identified were substance withdrawal (16.96%), anemia (12.5%), and renal derangement (11.6%). Other contributing factors included hepatic derangement (9.82%), hypoxia (2.23%), and sepsis (2.23%) [Table 2].
Table 2.
Factors associated with delirium according to the delirium etiology checklist (n=120)
| Factors associated with Delirium | n (%) |
|---|---|
| Anemia | 28 (12.5) |
| Hypoxia | 5 (2.2) |
| Hyponatremia | 26 (11.6) |
| Hypokalemia | 15 (6.7) |
| Hypernatremia | 8 (3.6) |
| Hyperkaliemia | 2 (0.9) |
| Renal derangement | 26 (11.6) |
| Hepatic derangement | 22 (9.9) |
| Pancreatitis | 8 (3.6) |
| Lung disease | 6 (2.7) |
| Cardiac decompensation | 2 (0.9) |
| Sepsis | 5 (2.2) |
| Seizures | 1 (0.4) |
| Trauma | 2 (2.2) |
| Substance withdrawal | 38 (17) |
| CNS pathology | 12 (5.4) |
| Fracture/dislocation | 8 (3.6) |
| Post operation | 10 (4.5) |
Types of delirium
Hyperactive delirium was observed in 106 patients (88.3%), characterized by motor agitation and perceptual disturbances, while hypoactive delirium, marked by motor retardation and reduced responsiveness, was noted in 14 patients (11.7%).
Correlation analysis
Significant associations were identified between factors associated with delirium and delirium subtypes. Cardiac decompensation (P = 0.0127) and sepsis (P = 0.0112) were significantly correlated with hypoactive delirium, while substance withdrawal was found to be significantly correlated with hyperactive delirium (P = 0.0047). These findings suggest that specific underlying conditions may predispose patients to different clinical manifestations of delirium [Table 3].
Table 3.
Correlation of factors associated and type of delirium (n=120)
| Factors | Hyperactive (n=106) | Hypoactive (n=14) | P |
|---|---|---|---|
| Anemia | 24 (22.6) | 4 (28.6) | 0.73 |
| Hypoxia | 3 (2.8) | 2 (14.3) | 0.10 |
| Hyponatremia | 21 (19.8) | 5 (35.7) | 0.18 |
| Hypokalemia | 14 (13.2) | 1 (7.1) | 1.00 |
| Hypernatremia | 8 (7.5) | 0 (0) | 0.59 |
| Hyperkalemia | 2 (1.9) | 0 (0) | 1.00 |
| Renal derangement | 22 (20.7) | 4 (28.6) | 0.50 |
| Hepatic derangement | 22 (20.7) | 0 (0) | 0.07 |
| Pancreatitis | 8 (7.5) | 0 (0) | 0.59 |
| Lung disease | 5 (4.7) | 1 (7.1) | 0.53 |
| Cardiac decompensation | 0 (0) | 2 (14.3) | 0.0127* |
| Sepsis | 2 (1.9) | 3 (21.4) | 0.0112* |
| Seizures | 1 (0.9) | 0 (0) | 1.00 |
| Trauma | 2 (1.9) | 0 (0) | 1.00 |
| Substance withdrawal | 38 (35.8) | 0 (0) | 0.0047* |
| CNS pathology | 10 (9.4) | 2 (14.3) | 0.63 |
| Fracture/dislocation | 6 (5.6) | 2 (14.3) | 0.23 |
| Post operation | 8 (7.5) | 2 (14.3) | 0.32 |
Fisher’s exact test used; *Significant P<0.05
DISCUSSION
The findings of this study highlight the multifaceted interplay of factors associated with delirium among hospitalized patients in a rural tertiary care setting. The study observed a marked male predominance (84.2%), with the majority being in the age range of 30–50 years. This could reflect the higher prevalence of conditions such as substance abuse, prevalent among adult males more than females.
Substance withdrawal, particularly from alcohol, was identified as the most common cause of delirium (16.96%) in this study. This finding is consistent with previous research highlighting that alcohol withdrawal delirium is frequently encountered in clinical practice, especially in regions with high rates of alcohol use disorders.[6] The study also found a significant association of substance withdrawal with hyperactive delirium. This is consistent with an earlier study that focused on patients admitted to the hospital with alcohol withdrawal; it was also found that hyperactive delirium was a common manifestation, affecting nearly 25% of patients with alcohol withdrawal.[13] Moreover, the association of substance withdrawal with hyperactive delirium underscores the need for targeted management strategies.[7]
Anemia (12.5%) and renal derangement (11.6%) were significant contributors to delirium in this cohort, emphasizing the systemic nature of the condition. Anemia, a common risk factor, is known to affect cerebral oxygenation, potentially leading to cognitive impairment and delirium.[14] Similarly, renal dysfunction can result in the accumulation of uremic toxins, electrolyte imbalances, and acid-base disturbances, all of which are implicated in delirium pathogenesis.[15] These findings highlight the importance of early identification and correction of metabolic and hematological abnormalities in patients at risk of delirium, particularly in resource-constrained settings where access to specialist care may be limited.[16]
Hypoactive delirium, often underdiagnosed due to its subtle presentation, poses unique challenges in clinical management.[17] Hypoactive delirium was found to be significantly associated with factors such as sepsis and cardiac decompensation in this cohort. A previous study highlights that hypoactive delirium tends to be prevalent in patients with significant cardiac decompensation, leading to worse outcomes such as increased mortality and prolonged hospital stays.[18] Another study also found that hypoxia and cardiac issues were significantly associated with hypoactive delirium.[19] A study on ICU patients found that hypoactive delirium is more common in patients with sepsis compared to those without sepsis.[20] This study also highlighted that hypoactive delirium is associated with worse outcomes, including longer ICU stays and increased mortality.[20]
Strengths and limitations
The use of a validated tool such as the Richmond Agitation Sedation Scale (RASS) in this study strengthens the reliability of the findings; this tool enables a comprehensive assessment of the subtyping of delirium. However, the study’s limitations, including its cross-sectional design and the potential for referral bias, must be considered when interpreting the results. Future research should focus on prospective studies with larger sample sizes and diverse populations to validate the findings and explore additional factors contributing to delirium.
CONCLUSION
In conclusion, the diverse range of associated factors contributing to delirium necessitates a multifaceted approach to its management, particularly in resource-limited rural settings. Integrating delirium screening protocols into routine clinical practice, alongside educational interventions for healthcare providers, can significantly enhance the quality of care for patients suffering from this complex condition.
Authors’ contributions
Concept, design, definition of intellectual content by KKM, Literature search and Data acquisition by SM and Manuscript review and editing by KKM and SM.
Data availability statement
Data can be made available on reasonable request.
Ethical statement
All ethical standards were maintained and reviewed by the Institutional Ethical Committee.
Consent
Consent was taken from the primary caregiver.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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Associated Data
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Data Availability Statement
Data can be made available on reasonable request.
