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 Table of Contents    
ORIGINAL ARTICLE  
Year : 2019  |  Volume : 61  |  Issue : 4  |  Page : 352-358
Delirium in medical intensive care units: Incidence, subtypes, risk factors, and outcome


1 Department of Psychiatry, AIIMS, Patna, Bihar, India
2 Department of Psychiatry, Sikkim Manipal Institute of Medical Sciences, Sikkim Manipal University, Sikkim, India

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Date of Web Publication16-Jul-2019
 

   Abstract 


Background: Delirium is a frequent yet underdiagnosed neuropsychiatric condition encountered in intensive care units (ICUs). Being both a preventable and potentially reversible process associated with significant morbidity and mortality, understanding risk factors that predispose and precipitate delirium in any given patient are critical in ICUs.
Aims and Objectives: The aim of this study is to evaluate the incidence, motor subtypes, risk factors, and clinical outcome of delirium in the medical ICU.
Materials and Methods: We used a prospective study design on a cohort of consecutive medical ICU admissions of a tertiary care teaching hospital. The Confusion Assessment Method-ICU and Richmond Agitation Sedation Scale were used to diagnose and motor subtype delirium, respectively, along with a checklist to assess risk factors.
Results: Of the 280 ICU admissions, 88 (31.4%) developed delirium. Hypoactive delirium was the most common motor subtype (55.7%). The detection rate of delirium was 12.5% (lowest for hypoactive delirium at 2.04%). Age, gender, and years of education did not significantly predict delirium (all P > 0.05). Tobacco use, chronic liver disease, and past episodes of delirium significantly predisposed, while mechanical ventilation, hypoxia, fever, raised levels of bilirubin and creatinine, and benzodiazepine administration significantly precipitated ICU delirium. Delirium was significantly associated with longer ICU stay (t = 4.23, P = 0.000) and 1-month postdischarge mortality (χ2 = 6.867, P = 0.009).
Conclusion: Detection of delirium is challenging, especially in ICU patients on mechanical ventilation and hypoactive delirium. Screening and monitoring for predisposing and precipitating risk factors can greatly improve the odds of detection and intervention as ICU delirium is associated with significant morbidity and mortality.

Keywords: Delirium, incidence, intensive care units, mortality, risk factors

How to cite this article:
Jayaswal AK, Sampath H, Soohinda G, Dutta S. Delirium in medical intensive care units: Incidence, subtypes, risk factors, and outcome. Indian J Psychiatry 2019;61:352-8

How to cite this URL:
Jayaswal AK, Sampath H, Soohinda G, Dutta S. Delirium in medical intensive care units: Incidence, subtypes, risk factors, and outcome. Indian J Psychiatry [serial online] 2019 [cited 2019 Aug 26];61:352-8. Available from: http://www.indianjpsychiatry.org/text.asp?2019/61/4/352/262811





   Introduction Top


Delirium is a neuropsychiatric condition marked by a disturbance in the level of consciousness of relatively acute onset, associated with an inability to focus, sustain, and shift attention along with an impairment of recent and immediate memory. It has fluctuating course due to the direct physiologic consequence of a general medical condition, an intoxicating substance, or medication use.[1] Despite being extremely common [2] and capable of complicating any medical or surgical diagnosis,[3] it often goes unrecognized.[4] This is unfortunate as delirium to a large extent is preventable and treatable.[5] Failure to diagnose delirium not only increases morbidity and mortality rates but is also a source of distress to caregivers and the medical team.[6]

The incidence of delirium varies widely depending on the setting [7] (hospital versus old age care centers) and the diagnostic criteria used.[8] Even within the hospital, the incidence varies in general wards, surgical wards, postoperative care, and ICUs, each of which has its unique risk factors and complications.[9] ICU delirium is especially important as it is associated with diagnostic challenges, greater morbidity, mortality, and therapeutic dilemma.[10],[11]

Risk factors for delirium are categorized into predisposing factors and potentially modifiable/precipitating factors.[9] While precipitating factors are those that operate in the ICU, predisposing factors are those that are present well before admission to the hospital. The complexity of delirium lies in the fact that predisposing and precipitating factors interact in a myriad of ways randomly to influence the outcome at any given point in time.[12] Although more than 100 putative risk factors have been suggested in the literature, the evidence points to less than a dozen risk factors that are supported by either strong or moderate level of evidence.[13] Conventionally, delirium has been conceptualized as a temporary condition, but accumulating evidence suggests that it independently impacts on length of hospital stay, increased mortality both in the short- and long-term irrespective of the severity of the comorbid medical condition.[14]

There is a paucity of Indian studies that have systematically assessed the incidence, risk factors, and outcomes of delirium in ICU settings.[15],[16],[17],[18],[19],[20] The aim of the present study was to explore delirium in a medical ICU setting. Our objectives were to study the (a) incidence, (b) recognition rate by ICU staff, (c) motoric subtypes, (d) predisposing factors, (e) precipitating factors, and (f) clinical outcome in terms of morbidity and mortality of medical ICU delirium.


   Materials and Methods Top


The study was prospective and observational in design conducted on all patients (consecutive sampling) aged 18 years and above admitted to the medical ICU of a tertiary care teaching hospital for 9 months. The research proposal was cleared by the Institute Ethics Committee. Patients were excluded if they were: (a) were delirious at the time of admission, (b) comatose throughout their ICU stay, (c) severely aphasic interfering with assessment, and (d) not willing to consent (proxy or self). All consecutive admissions in the medical ICU were assessed within 24 hs and every day thereafter, in the morning and late evenings. The endpoint was either a positive identification of delirium, discharge of the patient from the ICU or death. The following rating scales and questionnaires were administered:

Sociodemographic proforma: Information regarding age, gender, and education.

The Confusion Assessment Method-Intensive Care Unit (CAM-ICU) scale was used to diagnose delirium. The scale was specifically developed for use in ICU settings even ON mechanically ventilated patients and requires <5 min to complete. When compared with the diagnosis of delirium made by experts based on Diagnostic and Statistical Manual of Mental Disorders criteria, CAM-ICU has a sensitivity of 95%–100%, specificity of 93%–98%, and inter-rater reliability of 0.79–0.95.[21]

The Richmond Agitation–Sedation Scale (RASS)[22] was used to identify the motoric subtypes of delirium.[2] It is a 10 point scale with scores ranging from +4 to −5. Hyperactive delirium is defined as a persistent rating of +1 to +4 during all assessments. Hypoactive delirium is defined as a persistent rating of 0 to −3 during all assessments and mixed subtype is defined as present when the patients have rating of both hyperactive and hypoactive values.

Risk factors for delirium were assessed after an extensive literature review of studies, including those variables that had moderate-to-strong evidence.[13],[23],[24],[25] Risk factors were divided into predisposing and precipitating factors. The predisposing factors studied included age, gender, education, preexisting cognitive impairment, baseline physical status (Charlson Comorbidity Index), past episodes of delirium, depression, tobacco use, visual impairment, immobility, diabetes, hypertension, chronic kidney and liver disease, cardiac failure, stroke, and tuberculosis. Precipitating factors studied was anemia, hypoxia, fever, hypoalbuminemia, electrolyte imbalance, increased levels of bilirubin and creatinine, mechanical ventilation, pain, fractures, and medications such as anticholinergics, opiates, benzodiazepines, and steroids.

Preexisting cognitive impairment was assessed using the Short Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).[26] It is a 16-item instrument scored on a 5-point Likert type scale that evaluates cognitive functioning in the past 6 months using inputs from the caregiver. The scale demonstrates high reliability (coefficient alpha 0.93–0.97) and acceptable validity against a clinical diagnosis of dementia. Scores >3.44 were taken to indicate preexisting cognitive impairment.[27] Visual impairment was defined as impairment in activities of daily living despite the use of visual aids (glasses, contact lenses) as defined by O'Keeffe and Lavan.[28] Preexisting medical comorbidity was assessed using the Charlson Comorbidity Index (CCI) which includes 22 conditions, each of which is assigned a score of 1, 2, 3, or 6 depending on the risk of dying associated with that diagnosis.[29] The total score gives an indication of the comorbid medical burden. The CCI has been used as an index of medical comorbidity in delirium studies.[15]

The Behavioral Pain Scale (BPS) can be used in ICU settings both on verbal on nonverbal mechanically ventilated patients was used to quantify pain.[30] It comprises three observational items (facial expression, upper limbs, and compliance with ventilation) that are scored from 1 to 4, with higher numbers indicating higher levels of pain. The BPS demonstrates good internal consistency and inter-rater agreement.[31]

The outcome of delirium was assessed by the duration of hospital stay, in-hospital mortality, and 1-month postdischarge mortality (assessed through telephonic contact). All the study instruments were administered by Ayush KJ under the supervision of Harshavardhan S.

MINITAB 17™ software was used for statistical analysis. Descriptive data are expressed in mean, standard deviation, and percentages were appropriate. The Chi-square statistics (categorical data) and Student's t-test (continuous data) were used for analytical statistics.


   Results Top


Of the 280 consecutive ICU admissions that fulfilled the inclusion and exclusion criteria, 88 patients (31.4%) developed delirium. [Table 1] illustrates the characteristics of the patients who developed delirium during their ICU stay.
Table 1: Distribution of variables in patients who developed intensive care unit delirium (n=88)

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Age (t = −0.05, P = 0.964, confidence interval [CI] 4.71, 4.93) and years of education (t = −1.57, P = 0.118, CI 0.272, 2.394) of patients did not significantly differ among ICU patients who did and did not develop delirium. There were no significant gender differences between patients who did and did not develop delirium (χ2 = 3.547, P = 0.06).

Medical comorbidity at baseline (Charlson Comorbidity Index) did not differentiate patients who did or did not develop delirium in the ICU (t = 1.57, P = 0.12). Preexisting cognitive impairment was assessed for patients aged 50 years and above (n = 188). Thirty-seven patients had preexisting cognitive impairment (IQCODE scores >3.44). There were no significant differences in cognitive impairment in patients with and without delirium (χ2 = 2.72, P = 0.099). Among the predisposing risk factors, only a history of delirium, tobacco use, and chronic liver disease were significantly associated with the development of delirium [Table 2].
Table 2: Distribution of predisposing risk factors between patients who did and did not develop delirium in the intensive care unit

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With regard to the precipitating risk factors, hyperbilirubinemia, raised serum creatinine, hypoxia, mechanical ventilation, fever, and administration of benzodiazepines were significantly associated with the occurrence of delirium [Table 3]. There were no significant differences between BPS scores (t = 0.22, P = 0.825) and the total number of medications administered (t = 1.68, P = 0.095) between patients who did and did not develop delirium.
Table 3: Distribution of precipitating risk factors between patients who did and did not develop delirium in the intensive care unit

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Regarding the outcome of delirium, duration of ICU stay (t = 4.23, P = 0.000), and 1-month postdischarge mortality (χ2 = 6.867, P = 0.009) were significantly worse for patients who developed delirium than those who did not. Death during ICU stay was greater in the delirium group (9.09%) as compared to that of the nondelirious group (5.21%), but the differences were not statistically significant (χ2 = 1.512, P = 0.219).


   Discussion Top


Using the CAM-ICU, 88 patients (31.4%) were diagnosed to have developed delirium during their ICU stay. In a systemic review of 48 studies, Krewulak et al. reported an overall pooled incidence of 21% in ICU settings (medical, surgical, and specialty).[32] Indian studies in the ICU setting have reported prevalence rates ranging from 16% to 53.6%.[15],[16],[17] This wide variation in rates could be due to the type of ICU setting (medical, postoperative, cardiac ICU), instruments used (CAM-ICU versus others), and hospital setting (tertiary care referral centers tend to get more severe cases). Although Indian studies have investigated ICU delirium, they were not done exclusively on patients in the medical ICU setting. As discussed earlier, the nature of ICU setting (medical, surgical, neurology, cardiac, and respiratory) has a significant impact on the incidence, risk factors, and prognosis of delirium.[9] The following Indian studies [Table 4] are similar to the present study methodologically (ICU settings and/or CAM-ICU rated and in patients belonging to all age groups). A study from PGIMER, Chandigarh, which evaluated patients admitted to the respiratory ICU reported a delirium incidence (using Delirium Rating Scale–Revised) of 24.4% with mechanically ventilated patients showing a higher rate.[15] Another study from the same center in the coronary ICU reported an incidence rate of 9.3% using the CAM-ICU.[16] Bamalwa et al. from Kasturba Medical College, Manipal reported a delirium incidence of 16% in the cardiac ICU among 50 consecutively admitted patients using the CAM.[17] Among patients admitted to medical and cardiac ICU (data not available separately for medical ICU), delirium was found in 10.3% using the Memorial Delirium Assessment Scale.[17] George et al., in their study, reported a delirium rate of 32% (17 of 53 patients) using Intensive Care Delirium Screening Checklist in medical and cardiac ICU settings (data not available separately for medical ICU) in a medical college hospital in Kerala.[19] Since this is the first Indian study of delirium exclusively in a medical ICU, our results need to be corroborated by future research in this specific setting.
Table 4: Indian studies on delirium in the intensive care unit setting

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Hypoactive subtype constituted more than half of the cases of delirium (n = 49, 55.68%) [Table 1]. Hypoactive delirious states have been the predominant subtype in ICU settings in previous studies.[2],[32] Delirium was recognized only in 13.63% of the ICU patients, which was lowest for the hypoactive subtype (2.04%) [Table 1]. This is primarily due to the very nature of hypoactive delirium that does not draw the attention of the ICU staff. Moreover, the fluctuating nature of delirium per se might not coincide with assessments.

Of the predisposing risk factors, only tobacco use, past episodes of delirium, and chronic liver disease were significantly associated with ICU delirium in our analysis. We found nicotine use as a significant modifiable risk factor for delirium in medical ICU patients. Pathophysiologically, both delirium and nicotine withdrawal (during hospitalization) are associated with cholinergic deficiency.[33] In a systematic review, nicotine use was independently associated with delirium and showed a dose-response relationship.[34] We also found that past episodes of delirium significantly predisposed patients to develop another episode. Lahariya et al. too found such an association.[16] Evidence from alcohol withdrawal delirium suggests that a kindling mechanism might explain this vulnerability.[35] However, it must be pointed out that past episodes of delirium were gathered from case records, self-report, or caregiver interviews, which might be subject to recall bias and poor data keeping all of which could lead to under-reporting. Despite this, we found this variable to be a significant risk factor for ICU delirium. The evidence for chronic hepatic dysfunction as a predisposing risk factor is mixed.[3],[13] Our results support the view that chronic liver disease (CLD) is significantly associated with the development of ICU delirium. We would like to disclose here that a diagnosis of CLD was made based on previous medical records (albeit incomplete).

Although the age of patients who developed ICU delirium was greater than those who did not, the differences were not statistically significant (P = 0.096). At admission, age is a strong predisposing risk factor for delirium in previous studies.[13] Patients with delirium had greater levels of pre-admission medical comorbidity (CCI score = 3.78; standard deviation [SD] = 2.40) than those who did not develop ICU delirium (CCI score = 3.30; SD = 2.43). However, the differences did not approach statistical significance. Patients who developed ICU delirium (aged 50 years and above) had a greater preexisting cognitive impairment, but the risk was not statistically significant (χ2 = 2.72, P = 0.099). Although the evidence for dementia as a risk factor for delirium is fairly established, various studies have defined and assessed cognitive impairment differently.[36] Most studies have performed a cognitive assessment during admission using the Mini-Mental Status Examination. However, we believe that the assessment of cognition in a critically ill patient admitted to the ICU would spuriously indicate impaired cognition. Hence, we assessed cognition by proxy retrospectively using a key informant/caregiver (IQCODE). The only Indian study to have used the IQCODE reported cognitive impairment as a significant risk factor for delirium (χ2 = 22.52, P = 0.0001).[16] However, the authors have used a cutoff of 3.3 to detect impaired cognition, which is lower than that suggested by a review of the scale by Jorm et al.[37] These factors could have hindered our ability to arrive at a statistically significant result. Visual impairment was not significantly associated with delirium in our study. This is surprising as research evidence points to impaired vision being a predisposing risk factor for delirium.[36] However, the differential measurement of visual impairment in literature is quite evident.[36] Visual impairment has been variously defined as vision worse than 20/70, vision requiring aids and continuing to interfere with activities and an abnormal Jaeger test. This and the number of patients with visual impairment (n = 4) in the delirium group could be reasons why we could not find a significant association between visual impairment and delirium. Interestingly, no Indian study has systematically investigated for visual impairment as a risk factor for delirium in the ICU setting. History of depression did not significantly predict ICU delirium in our study. The relevance of depression as a predisposing risk factor is mixed with conflicting reports.[38],[39] A systematic review by O'Sullivan et al. found 17 studies which reported that depression conferred a 1.3–9-fold increased risk for delirium. However, the authors also note that these studies were predominantly in the geriatric population in postoperative surgical settings where the confounding effect of shared risk factors in the form of physical and psychological vulnerabilities conferred by cognitive impairment and frailty have not been accounted for.[40]

Among the precipitating risk factors increased bilirubin, creatinine, mechanical ventilation, hypoxia, fever, and benzodiazepine administration were significantly associated with ICU delirium. Hyperbilirubinemia (total bilirubin >2 mg/dl) has been shown to precipitate delirium in the ICU.[41] Hepatic encephalopathy, a prototype of impaired liver function, leads to portosystemic shunting of toxic metabolites, primarily ammonia, which overwhelms the blood–brain barrier precipitating delirium. Raised creatinine levels have been significantly associated with delirium after adjusting for multiple confounders.[42] Renal damage can lead to inflammation in the brain, reduce the clearance of medications, metabolites, or other potential neurotoxins all of which can potentially precipitate delirium. Patients on mechanical ventilation, in our study, were three times (73.3%) more likely to develop delirium (χ2 = 7.38, P = 0.000). Mechanical ventilation has strong evidence as a precipitating factor for ICU delirium.[13] The pain, agitation, and sedation involved in the process can all contribute to the development of delirium in this population. On subanalysis, we found that only 1 in 22 delirious patients on ventilation who were recognized by the ICU staff. This could not be explained by motoric subtypes as even hyperactive (n = 2) and mixed (n = 4) subtypes of delirium were missed in our sample (recognition rate 0%). One possible explanation is that ICU staff lack training in recognition of delirium in mechanically ventilated nonverbal patients. By using the CAM-ICU which has demonstrated high levels of sensitivity, specificity, and inter-rater reliability along with minimizing the assessment time to <2 min, we were able to detect delirium in this vulnerable population. Fever was a significant predictor of ICU delirium in our study (χ2 = 4.71, P = 0.03). Febrile states are, perhaps, the earliest known precipitants of delirium, recognized since the time of Hippocrates. Currently, the term sepsis-associated encephalopathy manifesting as fever has been implicated in direct cellular damage to the brain, mitochondrial and endothelial dysfunction, neurotransmission disturbances, and derangement of calcium homeostasis in brain tissue manifesting as delirium.[43] The study found hypoxia (SaO2<90%) to be a significant precipitating factor for delirium (χ2 = 7.38, P = 0.007). Cerebral hypoxia, at least in the early stages (hypoxic-ischemic encephalopathy) manifests as hypoactive or mixed delirious states. If unattended, critical neuronal injury supervenes leading to widespread cortical damage and coma.[44] Hence, it is imperative to recognize hypoxic delirious states since the precipitating events are usually cardiovascular in nature. Among medications administered in the ICU, only benzodiazepines were significantly associated with the development of delirium. We ruled out the possibility of this association being the confounding effect of benzodiazepines being administered for controlling hyperactive delirium (Chi-square test of significance of benzodiazepine use and motoric delirium subtype was nonsignificant χ2 = 3.53, P = 0.17). Benzodiazepines increase the level of neurotransmitter GABA, resulting in increased sedation, especially when administered in hypoactive delirium. Indian studies by Sharma et al.[16] and Lahariya et al.[17] too concur with our findings. It is a common practice among ICU staff to manage behavioral problems with benzodiazepines like midazolam. However, the inherent risks of precipitating patients in pre-delirium to full-blown delirium must not be overlooked.

Pain levels were minimally different between delirious and nondelirious patients in our study. Although an association between postoperative pain and delirium [44] has been reported previously, they might not be relevant in the ICU setting due to the availability of adequate analgesia. Moreover, Indian studies of ICU delirium have not measured pain as a precipitating factor for delirium.[15],[16],[17],[18],[19],[20]

The study indicates that delirium adversely impacts patient outcomes in terms of duration of ICU stay, ICU mortality and 1-month postdischarge mortality, all of which were greater in patients who developed delirium in the ICU. Poor outcomes of ICU delirium in terms of morbidity and mortality have been documented in systematic reviews.[10] Indian studies by Sharma et al.[15] and Lahariya et al.[16] have found a significant difference in both duration of stay and ICU mortality rates in delirious patients. However, we went a step further to follow-up the discharged patients (1-month postdischarge mortality) who experienced delirium to know the outcome. Surprisingly, we noted that these patients experienced significantly greater mortality rates (15.9%) within a month of discharge from the hospital. Thus, the impact of delirium, even when reversed or managed in the ICU seems to impact the postdischarge outcomes of patients. Given the increased morbidity and mortality associated with delirium, earlier diagnosis and treatment in ICU patients are important to improve prognosis, especially when reversible causes of delirium can be addressed.

The strength of the present study lies in its prospective nature and twice daily assessment of delirium (to not miss its fluctuating course). It is the largest Indian study of delirium in the medical ICU setting (n = 280). By using standardized rating scales and instruments such as the CAM-ICU, RASS, IQCODE, CCI, and BPS, the results of our study can be replicated and verified. This is also the first Indian study to assess pain as a precipitating factor for ICU delirium. This study is not without limitations. We relied on case records and possibly incomplete clinical history given by key caregivers of ICU patients. ICU staff could have recognized delirium but failed to make a diagnosis of delirium in the case files, which could have resulted in undervaluing recognition rates. The diagnosis of depression was made using a clinical interview of the patient and caregiver, the validity of which is difficult to establish in critically ill ICU patients. Preexisting cognitive impairment was assessed by proxy information using the IQCODE. Although this is not the ideal way to assess dementia, assessing for cognitive impairment in a critically ill ICU patient who is delirious by mental status examination could confound the findings. Since this was an observational study, we had no control over the laboratory tests and investigations ordered and had to make do with the available data.


   Conclusion Top


Delirium, especially the hypoactive subtype is a frequent occurrence in critically ill ICU patients, goes unrecognized. Tobacco use, previous episodes of delirium, chronic liver disease were significant predisposing risk factors while mechanical ventilation, hypoxia, fever, raised levels of bilirubin, creatinine, and benzodiazepine administration significantly precipitated delirium in the medical ICU. When delirium develops in critical care patients, it is associated with poor outcomes in terms of greater duration of hospitalization, mortality both in the ICU and shortly after discharge.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). Arlington, VA: American Psychiatric Publication; 2013.  Back to cited text no. 1
    
2.
Peterson JF, Pun BT, Dittus RS, Thomason JW, Jackson JC, Shintani AK, et al. Delirium and its motoric subtypes: A study of 614 critically ill patients. J Am Geriatr Soc 2006;54:479-84.  Back to cited text no. 2
    
3.
Ely EW, Shintani A, Truman B, Speroff T, Gordon SM, Harrell FE Jr. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA 2004;291:1753-62.  Back to cited text no. 3
    
4.
Flaherty JH, Rudolph J, Shay K, Kamholz B, Boockvar KS, Shaughnessy M, et al. Delirium is a serious and under-recognized problem: Why assessment of mental status should be the sixth vital sign. J Am Med Dir Assoc 2007;8:273-5.  Back to cited text no. 4
    
5.
Serafim RB, Bozza FA, Soares M, do Brasil PE, Tura BR, Ely EW, et al. Pharmacologic prevention and treatment of delirium in intensive care patients: A systematic review. J Crit Care 2015;30:799-807.  Back to cited text no. 5
    
6.
Partridge JS, Martin FC, Harari D, Dhesi JK. The delirium experience: What is the effect on patients, relatives and staff and what can be done to modify this? Int J Geriatr Psychiatry 2013;28:804-12.  Back to cited text no. 6
    
7.
Davis DH, Kreisel SH, Muniz Terrera G, Hall AJ, Morandi A, Boustani M, et al. The epidemiology of delirium: Challenges and opportunities for population studies. Am J Geriatr Psychiatry 2013;21:1173-89.  Back to cited text no. 7
    
8.
O'Regan NA, Ryan DJ, Boland E, Connolly W, McGlade C, Leonard M, et al. Attention! A good bedside test for delirium? J Neurol Neurosurg Psychiatry 2014;85:1122-31.  Back to cited text no. 8
    
9.
Vasilevskis EE, Han JH, Hughes CG, Ely EW. Epidemiology and risk factors for delirium across hospital settings. Best Pract Res Clin Anaesthesiol 2012;26:277-87.  Back to cited text no. 9
    
10.
Salluh JI, Wang H, Schneider EB, Nagaraja N, Yenokyan G, Damluji A, et al. Outcome of delirium in critically ill patients: Systematic review and meta-analysis. BMJ 2015;350:h2538.  Back to cited text no. 10
    
11.
Polderman KH, Smit E. Dealing with the delirium dilemma. Crit Care 2005;9:335-6.  Back to cited text no. 11
    
12.
Inouye SK, Charpentier PA. Precipitating factors for delirium in hospitalized elderly persons. Predictive model and interrelationship with baseline vulnerability. JAMA 1996;275:852-7.  Back to cited text no. 12
    
13.
Zaal IJ, Devlin JW, Peelen LM, Slooter AJ. A systematic review of risk factors for delirium in the ICU. Crit Care Med 2015;43:40-7.  Back to cited text no. 13
    
14.
Siddiqi N, House AO, Holmes JD. Occurrence and outcome of delirium in medical in-patients: A systematic literature review. Age Ageing 2006;35:350-64.  Back to cited text no. 14
    
15.
Sharma A, Malhotra S, Grover S, Jindal SK. Incidence, prevalence, risk factor and outcome of delirium in intensive care unit: A study from India. Gen Hosp Psychiatry 2012;34:639-46.  Back to cited text no. 15
    
16.
Lahariya S, Grover S, Bagga S, Sharma A. Delirium in patients admitted to a cardiac intensive care unit with cardiac emergencies in a developing country: Incidence, prevalence, risk factor and outcome. Gen Hosp Psychiatry 2014;36:156-64.  Back to cited text no. 16
    
17.
Bamalwa M, Mahmood SN, Praharaj SK. Delirium in cardiac ICU patients. Ann Clin Psychiatry 2016;28:51-5.  Back to cited text no. 17
    
18.
Shyamsundar G, Raghuthaman G, Rajkumar AP, Jacob KS. Validation of memorial delirium assessment scale. J Crit Care 2009;24:530-4.  Back to cited text no. 18
    
19.
George C, Nair JS, Ebenezer JA, Gangadharan A, Christudas A, Gnanaseelan LK, et al. Validation of the intensive care delirium screening checklist in nonintubated intensive care unit patients in a resource-poor medical intensive care setting in South India. J Crit Care 2011;26:138-43.  Back to cited text no. 19
    
20.
Grover S, Ghosh A, Sarkar S, Desouza A, Yaddanapudi LN, Basu D. Delirium in intensive care unit: Phenomenology, subtypes, and factor structure of symptoms. Indian J Psychol Med 2018;40:169-77.  Back to cited text no. 20
[PUBMED]  [Full text]  
21.
Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI. Clarifying confusion: The confusion assessment method. A new method for detection of delirium. Ann Intern Med 1990;113:941-8.  Back to cited text no. 21
    
22.
Sessler CN, Gosnell MS, Grap MJ, Brophy GM, O'Neal PV, Keane KA, et al. The richmond agitation-sedation scale: Validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med 2002;166:1338-44.  Back to cited text no. 22
    
23.
Van Rompaey B, Schuurmans MJ, Shortridge-Baggett LM, Truijen S, Bossaert L. Risk factors for intensive care delirium: A systematic review. Intensive Crit Care Nurs 2008;24:98-107.  Back to cited text no. 23
    
24.
Ahmed S, Leurent B, Sampson EL. Risk factors for incident delirium among older people in acute hospital medical units: A systematic review and meta-analysis. Age Ageing 2014;43:326-33.  Back to cited text no. 24
    
25.
Huai J, Ye X. A meta-analysis of critically ill patients reveals several potential risk factors for delirium. Gen Hosp Psychiatry 2014;36:488-96.  Back to cited text no. 25
    
26.
Jorm AF, Scott R, Cullen JS, MacKinnon AJ. Performance of the informant questionnaire on cognitive decline in the elderly (IQCODE) as a screening test for dementia. Psychol Med 1991;21:785-90.  Back to cited text no. 26
    
27.
Jorm AF. A short form of the informant questionnaire on cognitive decline in the elderly (IQCODE): Development and cross-validation. Psychol Med 1994;24:145-53.  Back to cited text no. 27
    
28.
O'Keeffe ST, Lavan JN. Predicting delirium in elderly patients: Development and validation of a risk-stratification model. Age Ageing 1996;25:317-21.  Back to cited text no. 28
    
29.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373-83.  Back to cited text no. 29
    
30.
Puntillo KA, Miaskowski C, Kehrle K, Stannard D, Gleeson S, Nye P. Relationship between behavioral and physiological indicators of pain, critical care patients' self-reports of pain, and opioid administration. Crit Care Med 1997;25:1159-66.  Back to cited text no. 30
    
31.
Aïssaoui Y, Zeggwagh AA, Zekraoui A, Abidi K, Abouqal R. Validation of a behavioral pain scale in critically ill, sedated, and mechanically ventilated patients. Anesth Analg 2005;101:1470-6.  Back to cited text no. 31
    
32.
Krewulak KD, Stelfox HT, Leigh JP, Ely EW, Fiest KM. Incidence and prevalence of delirium subtypes in an adult ICU: A systematic review and meta-analysis. Crit Care Med 2018;46:2029-35.  Back to cited text no. 32
    
33.
Hshieh TT, Fong TG, Marcantonio ER, Inouye SK. Cholinergic deficiency hypothesis in delirium: A synthesis of current evidence. J Gerontol A Biol Sci Med Sci 2008;63:764-72.  Back to cited text no. 33
    
34.
Hsieh SJ, Shum M, Lee AN, Hasselmark F, Gong MN. Cigarette smoking as a risk factor for delirium in hospitalized and intensive care unit patients. A systematic review. Ann Am Thorac Soc 2013;10:496-503.  Back to cited text no. 34
    
35.
Gilbert ME. Neurotoxicants and limbic kindling. In: Isaacson RL, Jensen KF, editors. The Vulnerable Brain and Environmental Risks. New York: Plenum Press; 1992. p. 173-92.  Back to cited text no. 35
    
36.
Cull E, Kent B, Phillips NM, Mistarz R. Risk factors for incident delirium in acute medical in-patients. A systematic review. JBI Libr Syst Rev 2012;10:1-2.  Back to cited text no. 36
    
37.
Jorm AF, Jacomb PA. The informant questionnaire on cognitive decline in the elderly (IQCODE): Socio-demographic correlates, reliability, validity and some norms. Psychol Med 1989;19:1015-22.  Back to cited text no. 37
    
38.
Jankowski CJ, Trenerry MR, Cook DJ, Buenvenida SL, Stevens SR, Schroeder DR, et al. Cognitive and functional predictors and sequelae of postoperative delirium in elderly patients undergoing elective joint arthroplasty. Anesth Analg 2011;112:1186-93.  Back to cited text no. 38
    
39.
Detroyer E, Dobbels F, Verfaillie E, Meyfroidt G, Sergeant P, Milisen K. Is preoperative anxiety and depression associated with onset of delirium after cardiac surgery in older patients? A prospective cohort study. J Am Geriatr Soc 2008;56:2278-84.  Back to cited text no. 39
    
40.
O'Sullivan R, Inouye SK, Meagher D. Delirium and depression: Inter-relationship and clinical overlap in elderly people. Lancet Psychiatry 2014;1:303-11.  Back to cited text no. 40
    
41.
Aldemir M, Ozen S, Kara IH, Sir A, Baç B. Predisposing factors for delirium in the surgical intensive care unit. Crit Care 2001;5:265-70.  Back to cited text no. 41
    
42.
Siew ED, Fissell WH, Tripp CM, Blume JD, Wilson MD, Clark AJ, et al. Acute kidney injury as a risk factor for delirium and coma during critical illness. Am J Respir Crit Care Med 2017;195:1597-607.  Back to cited text no. 42
    
43.
Flierl MA, Rittirsch D, Huber-Lang MS, Stahel PF. Pathophysiology of septic encephalopathy – An unsolved puzzle. Crit Care 2010;14:165.  Back to cited text no. 43
    
44.
Yogaratnam J, Jacob R, Naik S, Magadi H, Sim K. Prolonged delirium secondary to hypoxic-ischemic encephalopathy following cardiac arrest. Clin Psychopharmacol Neurosci 2013;11:39-42.  Back to cited text no. 44
    

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Correspondence Address:
Dr. Harshavardhan Sampath
Department of Psychiatry, Sikkim Manipal Institute of Medical Sciences, Sikkim Manipal University, 5th Mile, Tadong, Gangtok - 737 102, Sikkim
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/psychiatry.IndianJPsychiatry_583_18

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    Tables

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



 

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