Regarding pediatric studies, two recent reviews evaluated 23 and 33 studies, respectively, of WS done in the PICU population . Of note, there is no valid and reliable WS assessment tool available for the adult ICU population, although there are two tools for pediatrics. These tools are the Withdrawal Assessment Tool-1 and the Sophia Observation withdrawal Symptoms-scale . The lack of a WS assessment tool for adult ICU patients may have contributed to the lower number of publications about WS in adults. This difficulty in the ability for clinicians to measure adult WS is particulary relevant considering the current U.S. opioid epidemic and was one of the reasons we undertook this exploratory work. Little is known about the actual occurrence of WS, risk factors, and its consequence in adult patients. Therefore, the objectives of this exploratory study were to identify risk factors associated with probable WS among adult TICU patients exposed to opioids and/or benzodiazepines; explore clinical characteristics, signs and symptoms, and outcomes among patients who developed probable WS, questionable WS, and patients who did not develop WS.As established earlier, currently there is no validated tool for assessing WS in adult ICU patients which is a challenge in the study of WS in this population. Other challenges are that the signs and symptoms lack specificity, and there are similarities in these WS and signs and symptoms seen in other conditions like delirium, undersedation, pain,indoor hydroponics cannabis and anticholinergic toxidrome . This is particularly true for sign and symptoms related to CNS irritability and some nervous system activation . However, although not specific, WS has unique signs and symptoms related to gastrointestinal system dysfunction and some nervous system activation .
Since we recognized the limitation of no validated assessment tool for adult ICU patients, we created a sign and symptom checklist to measure potential indicators of WS of opioids and/or benzodiazepines. For our checklist, we retrieved potential indicators from the Diagnostic and Statistical Manual of Mental Disorders , the International Classification of Diseases, 10th Edition Classification of Mental and Behavioral Disorders , and previous WS research in adult ICU patients to develop the checklist . Figure 2 depicts the signs and symptoms of opioid and/or benzodiazepine WS that were included on the checklist. Tachycardia and tachypnea were defined as more than 100 beats per minute and more than 30 breaths per minute, respectively, high blood pressure as a systolic pressure more than 150mm Hg, and/or diastolic pressure more than 90mm Hg. We used the Richmond Agitation-Sedation Scale score to determine level of arousal and the Confusion Assessment Method-ICU to determine delirium. Recruitment and data collection were performed in TICU patients as well as patients with admission orders for TICU . If study patients were transferred to the intermediate unit while data collection was ongoing in the TICU, data collection continued in this unit. Baseline data were obtained from the patient’s clinical record or by family or patient interview. Daily and cumulative amounts of opioids and benzodiazepines and daily doses of other sedatives such as propofol and antipsychotics used from the arrival at Trauma Hospital and during the TICU stay were also collected. Patient days on MV, length of TICU stay, and length of hospital stay were documented. Bedside patient assessment data using the sign and symptom checklist were collected on the fourth day of patients receiving opioids and/or benzodiazepines in order to establish baseline data. After the fourth day of receiving opioids and/or benzodiazepines, bedside patient assessment data were also collected once the start of the weaning process for up to 72 hours after the beginning of opioid and/or benzodiazepine weaning.
If weaning was stopped and the patient returned to a similar previous dose, bedside measures ceased. When the weaning process was reestablished, measures began again and continued for up to 72 hours. Data on each of the signs and symptoms were collected twice a day . Vital sign abnormalities from the previous 8–12 hours were recorded during each patient assessment. Due to a limited budget for this exploratory study, all data collection and assessments were performed by the first author.Patient demographic and clinical data are presented as medians for continuous variables and frequencies for categorical variables for patients as a total group and also according to WS category . To compare demographic and clinical characteristics in patients by WS category, we conducted Fisher exact test for categorical variables and Kruskal-Wallis test for continuous variables. A Bonferroni correction to adjust alpha for 13 comparisons was calculated, and a p value of less than 0.004 was necessary to determine statistical significance. A mixed-effects logistic regression was conducted to determine the contribution of demographic and clinical variables to the development of probable WS. We evaluated several candidate models for WS , in terms of their fit, using Akaike information criterion and Bayesian information criterion . AIC and BIC are the most commonly used criteria for candidate model selection in regression analysis, with lower values reflecting a better fit of the candidate model to the existing data . McFadden’s pseudo-R2 was also calculated, comparing each model to the null model. The predictors considered in the multivariate models were age, severity of illness measured by the Acute Physiology and Chronic Health Evaluation II score, cumulative dose amounts of both opioids and benzodiazepines from time of first administration to a WS assessment day, days on both opioids and benzodiazepines, history of previous drug use, duration on MV, and both length of stay in ICU and hospital. These predictors were included in the model since there have been identified as risk factors in several studies with adults and/or PICU populations cited in two recent literature reviews .
We then included two WS signs to this best prediction model to determine if the model improved its fit. Our rationale for examining these variables was that they were highly correlated with WS occurrence in a bivariate analysis. Spearman correlation coefficients were used to further explore the relation between “days on opioid treatment” and “cumulative dose of opioid” variables .Two-hundred thirty-two patients admitted to TICU from September 2016 to May 2017 were screened. Fifty-five patients’ family members or patients consented for the study. Of those, five withdrew from the study before all data were collected, and data from 50 patients were analyzed . The majority of patients were male with a median age of 37 ; 90% were mechanically ventilated and 34% used drugs , either illicitly or per prescription, prior to hospitalization. The median APACHE II score was 15 . Mechanism of trauma was blunt , penetrating , or burns . Patients spent 13 days in the ICU and 21 days in the Trauma Hospital. The 45 patients who were mechanically ventilated spent 11 days on MV. Patients received both opioids and benzodiazepines or only opioids or benzodiazepines . Patients received continuous infusions and/or intermittent doses of fentanyl and/or morphine for analgesia and midazolam and/or lorazepam for sedation. Patients received a median cumulative dose of 1,144 mg of opioids over 11 days and 688 mg of benzodiazepines over 11 days , until the last bedside patient assessment. The daily median opioid dose was 109 mg , and the daily median benzodiazepine dose was 72 mg . In 50% of patients, continuous propofol was administered as a single agent or in combination with benzodiazepines. Thirteen patients and three patients received antipsychotics or neuromuscular blockers, respectively. Probable WS occurred in 22 patients , questionable WS in 10 patients ,pots for cannabis plant and no WS in 18 patients . In those patients who developed probable WS, WS occurred a median of 2 times during the measurement period. A total of 49 events of probable WS occurred in the 22 patients.As shown in Table 2, we evaluated several candidate models for WS , in terms of their fit, using AIC and BIC. When comparing the first five models, multivariate model no. 4, with age, benzodiazepine and opioid cumulative dose, days on benzodiazepine and opioid, previous drug use, and duration on MV presented the best AIC and BIC. After adjusting for all of these variables in the model, we found the following: increase in age was inversely associated with the odds of developing probable WS , there was a 10% increase in the odds of probable WS for each 100mg increase in the cumulative dose amounts of opioids prior to weaning, those with previous drug use compared with drug naive patients had 5.21 times higher odds of having probable WS . We then analyzed the addition of the RASS and delirium to the regression model no. 6 and found that doing so improved the model fit significantly, as reflected by AIC, BIC, and the pseudo-R2 statistics . In this model , after adjusting for all variables, the older age no longer had the protective effect. On the other hand, the association between WS and duration on MV, as well as number of days on opioids strengthened and became significant.
After additionally adjusting for delirium and RASS, each additional day on MV was associated with an 8% increase in odds of probable WS . In this model, interestingly, the number of days on opioids prior to weaning process was protective for the odds of developing probable WS . In addition, the odds of presence of probable WS were 4.13 for every one-point increase in RASS score, and patients with delirium had 2.69 times higher odds of probable WS compared with those without delirium .Opioid and benzodiazepine WS in adult ICU patients have been given little attention in the past years. Literature has established that there is a lack of recognition of WS due to the similarity between WS and delirium, the worsening of the critical illness, and the use of multiple drugs that have the potential to cause withdrawal if they are discontinued together . One third of our sample had a history of illicit drug use prior to their admission to ICU. In light of an increased number of ICU admissions for opioid overdose care , it is important to include those with a pre-existing drug condition in ICU studies of WS. When evaluating just our drug naive patients from the total sample, 38% developed probable WS, which is similar to the occurrence reported in the study by Korak et al . Although Wang et al studied trauma patients, as did we, they found a relatively lower occurrence of WS in their drug naive patients compared with our drug naive patients ; however, they attributed the low occurrence in their drug naive patients to the short duration of both MV and opioid exposure and their short-term evaluation of WS. It is important to point out that each one of those studies used a different instrument to measure WS, possibly influencing the findings of the study. In addition, in order to evaluate each study findings, it is important to take into account other differences between studies such as patient diagnosis, inclusion/exclusion criteria , and timing of data collection . WS literature in adults has generally not reported the specific sign and symptoms that commonly occur. However, in the abstract of one recent study of opioid-associated WS that enrolled 25 ICU patients, investigators reported similar signs and symptoms of WS found in our study . They included restlessness, high blood pressure, lacrimation, diarrhea, agitation, and hallucinations. Those investigators used a standardized form with potential WS sign and symptoms, and concomitantly, a physician assessed the patients with the DSM-5 criteria . Based on the findings of the mentioned study and ours, the research basis for identifying WS may be evolving. In our study, younger participants had higher odds of WS . Cammarano et al also found a significantly higher occurrence of WS in younger versus older patients . As expected, our patients who previously used drugs were significantly more likely to develop probable WS than drug naive patients. Cammarano et al did not find differences; however, they only had two patients with a history of drug use. Similar to our findings, Cammarano et al found that patients in the WS group had longer durations of MV than did non-WS patients . Furthermore, like us, Wang et al found that patients in the WS group had a longer duration of MV, longer ICU stays, and higher cumulative opioid dose prior the weaning, but their findings were not statistically significant.