A reorientation strategy for reducing delirium in the critically ill. Results of an interventional study

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1 This document is protected by international copyright laws. No additional reproduction is authorized. It is permitted for personal use to download and save only one file and print only one copy of this Article. It is not permitted to make additional copies Critically ill patients are at great risk of delirium, 1-4 being one of the most frequent organ dysfunction, as it occurs from 22% to 87% of mechanically ventilated patients 5-8 and may negatively affects their survival. 9 Since patients usually experience delirium both in the Intensive Care Unit (ICU) and in hospital wards or emergency departments in its hypoactive form, it remains unrecognized in 66% to 84% of cases. 10, 11 O R I G I N A L A R T I C L E A reorientation strategy for reducing delirium in the critically ill. Results of an interventional study R., A. CORONA, F. PRAGA, C. MINARI C. GIANNOTTI, A. CASTELLI, F. RAIMONDI Intensive Care Unit, Azienda Ospedaliera Luigi Sacco, University of Milan, Milan, Italy A B S T R A C T Background. A wide variability in the approach towards delirium prevention and treatment in the critically ill results from the dearth of prospective randomised studies. Methods. We launched a two-stage prospective observational study to assess delirium epidemiology, risk factors and impact on patient outcome, by enrolling all patients admitted to our Intensive Care Unit (ICU) over a year. The first step from January to June 2008 was the observational phase, whereas the second one from July to December 2008 was interventional. All the patients admitted to our ICU were recruited but those with pre-existing cognitive disorders, dementia, psychosis and disability after stroke were excluded from the data analysis. Delirium assessment was performed according with Confusion Assessment Method for the ICU twice per day after sedation interruption. During phase 2, patients underwent both a re-orientation strategy and environmental, acoustic and visual stimulation. Results. We admitted a total of respectively 170 (I-ph) and 144 patients (II-ph). The delirium occurrence was significantly lower in (II-ph) 22% vs. 35% in (I-ph) (P=0.020). A Cox s Proportional Hazard model found the applied reorientation strategy as the strongest protective predictors of delirium: (HR 0.504, 95% C.I , P=0.034), whereas age (HR 1.034, 95% CI: , P=0.001) and sedation with midazolam plus opiate (HR 2.145, 95% CI: , P=0.018) were negative predictors. Conclusion. A timely reorientation strategy seems to be correlated with significantly lower occurrence of delirium. (Minerva Anestesiol 2012;78: ) Key words: Intensive care unit - Delirium - Risk factors. Pathophysiological mechanisms of delirium are poorly understood and likely related both to anatomic deficits 12, 13 and imbalances in the neurotransmitters modulating the control of cognitive function, behaviour and mood. Impairment of cerebral metabolism, primary intracranial disease, secondary brain infection, hypoxemia, systemic illnesses, metabolic disturbances, exogenous toxic agents, withdrawal from substances of abuse, sedatives, hypnotics or 1026 MINERVA ANESTESIOLOGICA September 2012

2 Delirium in the critically ILL PATIENTS psychoactive drugs such as benzodiazepines and narcotics are the main causal factors of the above derangements. A few risk factors for delirium are iatrogenic or modifiable (e.g., length and type of sedation) whereas others not (e.g., severity of illness, preexisting dementia). Moreover, delirium in ICU has been found to be associated with: 1) patient age, severity of illness and the administered dose of lorazepam; 14, 15 2) prolonged hospital and ICU length of stay; 16 3) in-hospital mortality. 17 There is only little and scattered evidence about the efficacy of strategies to prevent delirium and only sedation with dexmedetomidine versus midazolam has been shown to reduce its duration in the critically ill. 18 On the other hand, the implementation of a protocol to reduce modifiable risk factors was found to be effective in reducing the incidence of delirium in medical wards. 19, 20 Up to this day no evidence can be found to assess the efficacy of the strategies (orienting communication, adaptive equipment for vision and acoustic impairment) suggested to prevent or reduce the occurrence of delirium in the critically ill. 2, 21, 22 We performed this prospective interventional audit to assess: 1) the occurrence of delirium, its risk factors and impact on critically ill outcome; 2) the efficacy of our reorientation protocol, based on mnemonical and environmental stimulation. Patients Materials and methods Our ICU is a mixed medical-surgical one provided by 8-bed, all enclosed in single boxes providing reduction of night noises (alarms, telephones and working staff). We launched a two-stage research project to assess Delirium epidemiology, risk factors and impact on patient outcome, by enrolling all patients admitted to our ICU over a year. The first step February-June was the observational phase, whereas the second one - July-December was interventional. Patients with pre-existing cognitive disorders, dementia, psychosis and Table I. The modified five Ws and one H scale used by health care staff at least one time per nurse shift. Who? Who are you? Who is the nurse/physician? What? What happened? When? When did it happen and what is the date? Where? Where are you/we? Why? Why did it happen? How? How did it happen? And what is the illness progression? disability after stroke were excluded from the data analysis. Before phase one: 1) four research nurses have been adequately trained to assess delirium, collect and input data into an electronic database; 2) all nurses have been trained to apply the Confusion Assessment Method for the ICU (CAM- ICU). In both phases patients underwent a sedation algorythm modified from De Jonghe et al. 20 according with a Richmond Agitation and Sedation Scale (RASS), 24, 25 ranging from -2 to +0 as sedation target. Mechanically ventilated patients underwent daily interruption of sedation along with spontaneous breathing trial when clinically possible. 26 Delirium assessment was performed according with CAM-ICU 27 twice per day at 10 a.m. and 10 p.m. after sedation interruption. Pain was measured by using Numerical Rating Scale (NRS) 28 and, when the patients were unable to express it, an estimation value based on behavioral and physiological estimation of pain. 29 During phase II, since the first day of admission, patients underwent a reorientation strategy (shown in Table I), by using the five Ws and one H scale (modified from journalism practice), 30 commenced timely as soon as a -3 RASS +3 was reached and before the onset of the delirium. They were frequently: 1) called by their first-name; 2) given information on the ward, hospital (i.e., hospital name, ICU-length of stay [LoS]) and illness progression; 3) mnemonically stimulated (on their recent clinical findings, by remembering relatives first-names and the date and the time of the specific day). Moreover, patients underwent environmental, acoustic and visual stimulation. A wall clock was placed in front of every ICU bed and the patients were asked to read newspapers/books, listen music or Vol No. 9 MINERVA ANESTESIOLOGICA 1027

3 radio during the day. At the night ICU lights and noises were reduced to a minimum, unless necessary. In both phases patients with delirium were given pharmacological treatment with haloperidol, or olanzapine in case of QT lengthening. One of us (RC) super-viewed the proper application of the shared interventional algorithm of re-orientation. Study was approved by the Internal Review Board. Definitions Type of patient Patients were considered medical (without surgery from 7 days to 24 hours after the ICU admission), surgical (with emergency or elective surgery from 7 days to 24 hours after the ICU admission); trauma: a serious injury or shock by violent event. Cardiogenic shock Hypotension with hypoperfusion due cardiac failure (Cardiac Index <2.5 L/min/BSA), requiring inotropic pharmacological support or intraaortic balloon. Septic shock Hypotension not responsive to fluid challenge but requiring catecholamine infusion (norepinephrine and dobutamine). Hypovolemic shock Hypotension with signs of hypoperfusion due to hypovolemia or blood loss. Coma (or CNS failure) Glasgow Coma Score (GCS) 8 before sedation. Respiratory failure Need for mechanical ventilation (invasive and not-invasive). Renal failure DELIRIUM IN THE CRITICALLy ILL PATIENTS Plasma creatinine >2 mg/dl, or plasma creatinine increase of 1 mg/dl/24 h or diuresis <500 ml/24 h, or kidney SOFA score >2. Liver failure Bilirubine >2 mg/dl in association with aptt and apt >twofold normal values in absence of anticoagulation and plasma glucose <70 mg/dl and/or hepatic encephalopathy; or liver SOFA-score >2. Acid-base disorder Severe acidemia (ph<7.25), plasma lactate >2 mmol/l, plasma albumin 2 g/l, phosphate >4.5 mg/dl, strong ion difference <38 meq/l, plasma anion gap <8 or >16 meq/l. Coagulation disorder Platelets per mm 3, aptt and apt above twofold normal values or clinical evidence of disseminated intravascular coagulopathy; or coagulation SOFA-score >2. Statistical analyses SPSS 15.1 software (SPSS Inc., Chicago, IL) was used for statistical analysis. For continuous variables, we used mean (SD) or median (IQR) whether not normally distributed, comparing rank values using non parametric tests. Differences in proportions were compared with χ 2 test or Fisher exact test, in case of expected frequencies <5. A Cox s Proportional Hazard Regression model was fitted, using a step-by-step enter approach, to identify independent predictors of delirium as the outcome. The method used for the Cox s Proportional Hazard Regression model was the enter approach, therefore all the independent variables were mandatorily forced into the model itself despite the results of the univariate analysis. By the enter approach different models were compared by the likelihood ratio test, using P 0.05 as level of significance. Independent variables entered in the model were divided into the following groups: 1) demographics: gender, 1028 MINERVA ANESTESIOLOGICA September 2012

4 Delirium in the critically ILL PATIENTS Table II. Univariate analysis. Variables Patients with delirium age; 2) severity score and risk factors: SAPS II, GCS, diabetes (yes/no); 3) patient type: medical/surgical/trauma; 4) presence of organ failure: respiratory (yes/no), liver (yes/no), kidney (yes/ no), heart (yes/no) septic-shock (yes/no), coma (yes/no), acid base equilibrium disorder (yes/ no); 5) presence (yes/no) and kind of sedation and mg of drug/given every day; 6) reorientation of the patients (yes/no). We defined the discrete variable sedation free day ratio (SFD-R) as the difference between ICU-LoS and sedation days, divided by ICU-LoS. Two tailed P values <0.05 were considered statistically significant. Patients without delirium Results Population general characteristics Odd ratios 95% C.I. P values Quantitative Age (years) 75 ( ) 67.5 ( ) SAPS II 38.5 (32-48) 29 (21-42) - <0.001 Propofol daily infusion (total mg) 36 (4.5-81) 26.5 ( ) - <0.001 Propofol total infusion (total mg) 104 (40-301) 72 (13-221) - <0.001 Midazolam daily infusion (total mg) 37 ( ) 27.5 ( ) - <0.001 Midazolam total infusion (total mg) 104 (24-230) 95.5 ( ) - <0.001 Opiate daily infusion (total mg) 15 (5-20) 7.5 (1.5-15) Opiate total infusion (total mg) 30 ( ) 20 ( ) Sedation duration (days) 3 (2-4) 0.5 (0.5-2) - <0.001 Delirium onset day 2 (1-4) Delirium duration (days) 2 (1-4) ICU length of stay (days) 6 ( ) 4 (2-7) - <0.001 Hospital length of stay (days) 37.5 ( ) 20 (10-36) - <0.001 Categorical Gender M:F 1.5 : : ( ) Patient type: medical: surgical 1.5 : : ( ) <0.001 Diabetes 17% 22.6% 0.7 ( ) Immunosuppression 5% 6% 0.8 ( ) Respiratory failure 82.5% 64.5% 2.6 ( ) Kidney failure 28.8% 17.1% 1.9 ( ) Hepatic failure 3.8% 6.4% 0.6 (0.2-2) Heart failure 15% 10.3% 1.5 ( ) Coma 20% 9.8% 2.3 ( ) Septic shock 22.5% 14.1% 1.7 ( ) Acid-base disorder 16.3% 13.7% 1.2 ( ) Sedation: pts. percentage 88.8% 34.6% 14.9 ( ) <0.001 Sedation: midazolam + opiate 43.8% 11.1% 6.2 ( ) <0.001 Sedation: propofol + opiate 31.3% 12% 3.3 ( ) <0.001 For quantitative variable: data are shown as median and IQR. Opiate are expressed in morphine equivalent. For Proportional variables: Under the conditional independence assumption, Cochran s statistic is asymptotically distributed as a 1 df chi-squared distribution, only if the number of strata is fixed, while the Mantel-Haenszel statistic is always asymptotically distributed as a 1 df chi-squared distribution. Out of the 366 patients admitted during the study period 314 patients met the inclusion criteria of the study with a median (IQR) age of 69.8 ( ) years. Overall percentage of patients who develop delirium was 25.5% with a median (IQR) onset of 2 (1-4) days and duration of 2 (1-3) days. The matching of the main demographics and clinical characteristics of the patients of the two phases (phase I [observational]=170 and phase II [interventional]=144 Vol No. 9 MINERVA ANESTESIOLOGICA 1029

5 Figure 1. Kaplan-Meier plots of survival stratified according with presence or not of delirium. patients) shows no significant differences, but for 1) diabetes (phase I=16.5% phase II=27.1%, P=0.027); 2) septic shock (phase I=24.1% phase II=6.9%, P<0.001); 3) median (IQR) ICU length of stay (phase I=3.5 [2-7], phase II=5 [3-8], P<0.001) and (obviously) 4) delirium occurrence (phase I=35.5%, phase II=22%, P<0.020). Univariate analyses Table II shows the univariate intergroup comparison. Multivariate predictive Cox s proportional hazard model The Cox s Proportional Hazard Model identified age (HR: 1.034, [95% CI: ], P=0.001), and the association of midazolam with opiate infusion (HR: 2.145, [95% CI: ], P=0.018) as independent negative predictors of the Delirium, whilst reorientation was found as the only protective (HR: 0.504, [95% CI: ], P=0.034) predictive variable. For all other variables no significant prediction power was found. To clarify the model: a patient, during the first phase of the study, who was sedated with the association of midazolam and an opiate, had about a twofold risk (HR=2.1, 95% CI 2.2-4) of developing delirium during his/her DELIRIUM IN THE CRITICALLy ILL PATIENTS stay in ICU. The same patient, during the second phase of the study, by undergoing a reorientation (HR=0.5, 95% CI ) strategy, normalised such risk. The sensitivity analysis results corroborated Cox s model as it found a bivariate inverse correlation between delirium occurrence and reorientation strategy (Pearson correlation coefficient and Spearman rho=-0.185, P=0.001). Moreover, the variable SFD-R is itself a strong predictor of delirium. ROC curve analysis showed that a sedation lasting longer than 30% of the whole patient ICU length of stay constitutes a predictor with a sensitivity of 78% and specificity of 71% (ROC area=0.793, 95% CI , P<0.001). Mortality The overall recorded crude mortality was respectively 10.8% in ICU and 14.7% in hospital. Critically ill patients developing delirium have a statistically significant lower mortality (Log- Rank 6.024, P=0.014) (Figure 1). A higher, but not statistically significant, mortality was found among patients experiencing delirium but not undergoing the re-orientation strategy (yes=4.5%, no=6.9%, P=0.907, Log-Rank 0.020, P=0.887). Discussion Critically ill patients are at high risk of experiencing delirium 2-11 and the wide variability in the recorded occurrence is likely to be associated with the dearth of PRCT that may inform physicians in their daily practice both to prevent and treat it. Inoyue et al. 19 showed a statistically significant reduction of prevalence and duration of delirium in the interventional group of elder patients admitted to a general medical ward and undergoing a multimodal risk-reduction strategy. In a more recent PRCT, Schweickert et al. 20 studied the application of an early exercise and mobilisation protocol for critically ill, finding a better functional performance at hospital discharge and a shorter duration of delirium. Ely et al. 13, 14 demonstrated that the presence of delirium was 1030 MINERVA ANESTESIOLOGICA September 2012

6 Delirium in the critically ILL PATIENTS outcome (delirium yes/no) to get the proper prediction value of each involved independent variable on it. Cox s Proportional Hazard model showed that the only independent protective predictor of Delirium was the timely re-orientation strategy (HR=0.504, 95% CI , P=0.034). Moreover, Kaplan-Meier analysis and plots suggests the hypothesis that the less a patient survives (i.e., sicker patients) the lower is the probability of developing delirium. Pandharipande et al. found midazolam to be the strongest independent risk factor for delirium in surgical and trauma critically ill patients, whereas opiates showed inconsistent results. 35 Our study population differed from Pandharipande because it lacked trauma patients. We decided to consider benzodiazepine and opiates as single variable as our sedation protocol was based on a combination of both drugs in agreement with Italian and international guidelines. 36, 37 Our model showed that sedation with opiate and midazolam were predictors that significantly increased occurrence of delirium. Even though the two groups of patients were similar, using the Cox s model, a more precise estimate of the treatment effect may be produced by narrowing the confidence interval, target which was definitely obtained. As delirium resulted to be directly associated with ICU length of stay 31, we chose Cox s model as it leaves the baseline hazard function unspecified. The multivariate model was corroborated by a sensitive analysis showing an inverse correlation between delirium occurrence and reorientation strategy. Skrobik et al. found that the titration of analgesic sedatives and anti-psychotics (based on sedation, analgesia, and delirium scores), in order to reduce the need of iatrogenic coma, is associated with better outcome. 33 Similarly, considering the assessed SDF-R predictive value on delirium, we found the importance of keeping patients as free from sedation as possible. The major weakness of this study is its observational nature, even though a more methodological strength comes from the interventional nature of the second phase. The match of the general characteristics of the two groups allowed us to reduce the likely biases affecting the results and the stability of the Cox s model. The choice of enrollan independent risk factor both for six month mortality and for longer hospital LoS in medical ICU patients. In a recent study, Lat et al. 31 found a high incidence of delirium in young trauma and surgical patients albeit mortality was not associated with Delirium. Van den Boogaard et al. 32 found that delirium is a significant predictor of mortality in ICU patients. As well, Shebabi et al. found a significantly lower mortality in patients free from delirium (11.9% vs. 36.3%, P=0.001). 9 Furthermore, there are too little evidence about efficacy of non-pharmacologic strategies for prevention of ICU Delirium. Schweickert et al. 20 obtained a significant reduction of delirium duration and lower duration of mechanical ventilation in patients undergoing both a daily sedation break and an early and intensive rehabilitation program. Skrobik et al. 33 in a large ICU population applied a careful management protocol with individualized titration of sedation, analgesia, and sub-syndromal delirium treatment. Their strategy was associated with better outcomes in treatment group vs. standard treatment, albeit a limited non-pharmacologic treatment was applied (portable radios and CD players were installed at each ICU patient s bedside). Our study showed that a bedside re-orientation strategy easily applied - seems to be significantly correlated with a reduction in delirium. A recent review by key opinion leaders, proposed the implementation of the ABCDE bundle - de facto the reorientation strategy applied by us in our unit - to achieve the mitigation of delirium in the critically ill. 34 Table II shows the main variables impacting on delirium occurrence. As in the two phase a difference has been recorded: 1) in terms of severity of illness (i.e., median SAPS II and rate of septic shock); 2) in diabetes rate, we did set a Cox s proportional Hazard model up to assess the specific weight of each variable. In terms of univariate analysis, we do agree that the single variable may have an effect on the studied outcome. Cox s model can involve observation and analysis of more than one statistical variable at a time, taking into account the effects of all variables on the responses of interest, that is our main Vol No. 9 MINERVA ANESTESIOLOGICA 1031

7 ing all the patients admitted to the ICU despite their life and ICU-staying expectance might have generated a selection bias, albeit patients with an ICU-LoS less than 24 h, were excluded from the statistical analysis. Moreover this may theoretically reflect what generally happens in daily clinical practice. Delirium generally has a fluctuating course over the day and our decision to perform assessment only twice per day might have been a underestimation bias source. On the other hand, we used CAM-ICU as validated tool to detect and monitor delirium (in according to the literature). Delirium is often undiagnosed in clinical setting. In medical ward non-detection rates as high as 66% have been reported. 41, 42 Validation of data in terms of Delirium diagnosis - has been warranted by the training of a team of four nurses in using the CAM-ICU tool and by a further review by one of us (RC). Conclusions Despite its limitations and biases, this clinical audit permitted us to build a multivariate bedside predictive model that was able to help us to identify predictors of delirium in the critically ill. We did realise that a major rationalisation of the sedation is to be mandatory, both in terms of duration and of association of used drugs. The main and final result of our prospective two-stage audit has been the implementation of a re-orientation strategy, as the main pre-emptive approach to reduce delirium occurrence. Key messages Re-orientation seems to be efficacious in reducing the occurrence of delirium in the critically ill patient. The occurrence of delirium in the critically ill seems significantly associated with the drug combination: midazolam plus opiate. The occurrence of delirium in the critically ill is likely to be correlated with ICU length of stay and shows an exponential increasing after the first five-seven days. 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