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 .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 ,vertical grow system 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. In our multivariate analysis that included RASS and CAM-ICU findings, age did not continue to be a predictor of WS . However, the RASS and delirium findings, when added to the model, significantly increased the model fit.
That is, we found that they are both related to WS. From a conceptual and clinical perspective, it could be important for providers to recognized agitation/restlessness and delirium when caring for ICU patients being weaned from opioids and/or benzodiazepines.The final model also showed that cumulative opioid dose amounts prior to weaning were associated with development of WS, although the number of days that patients received opioids was protective. In our study, as expected, days on opioids and cumulative opioid dose were strongly correlated . The nature and the strength of the relationship between these two variables could be the reason behind our findings: in the multivariate regression analysis, while holding the cumulative opioid dose constant, the “days on opioid” variable showed a slightly protective odds ratio for WS . That is, given the same cumulative dose of opioid, patients with longer duration on opioid had lower odds of developing WS. Another explanation for this finding is that there are several factors that can cause differences in opioid tolerance, the precursor to WS, at the opioid receptor level . Cumulative doses may affect the opioid receptor differently than length of time receiving opioids. In addition, genetic differences in opioid receptor synthesis and variable opioid receptor affinity, the difference in type of opioid administered, and the use of continuous versus intermittent administration may be influential factors . Use of multimodal analgesia may help to counteract development of WS through reduction of opioid amounts administered to the patient . However, further research is warranted on time versus amount differences in opioids and their risk for WS. This study has several strengths. The assessment of WS was done using a prospective approach two times a day for 72 hours or more. Furthermore, in the absence of an instrument validated to measure opioid and benzodiazepine WS in ICU adults, we developed a checklist using several reliable sources: the DSM-5 criteria, International Classification of Diseases, 10th Edition criteria WS, and symptoms identified in previous adult WS studies. Therefore, the checklist had content validity. Furthermore, given that our study was exploratory in nature, we were able to conduct several analyses by constructing various models between patient- and clinical-related factors and the probable presence of WS. Our study has notable limitations. Consistent with other WS studies in ICU , our sample was small. In addition, the TICU did not have a protocol for daily sedation interruption or a pain management protocol. Therefore, there was a large degree of variability in the opioid and/or benzodiazepine weaning process between patients; this could have influenced differences in WS development.
In addition, we were unable to evaluate some symptoms on the checklist in patients with RASS –3 to –5 such as hallucinations, delusions, illusions, dysphoria, nausea, insomnia, and delirium. Also, the intensity of the probable WS sign and symptoms was not evaluated. Our checklist has not yet undergone a formal validation process and reliability testing. Interrater or intrarater reliability was not possible because only one person performed all measures and the occurrence of WS was not constant between measurements. Finally, the signs and symptoms on our checklist are not specific for WS; thus, we could not rule out other conditions associated with these signs or symptoms. Further research on the psychometric characteristics of our checklist is warranted.The emergency department is often referred to as the ideal setting to identify patients with high-risk health behaviors, such as substance use, and link them to evidence-based treatment services. The clinical model of screening patients, providing a brief psychosocial and/or pharmacological intervention, and directly referring them to treatment has become increasingly more common in the acute care setting.The ED SBIRT, originally developed for unhealthy alcohol use, has expanded to identify and treat ED patients who report use of other substances including opioids.Substance use is known to be associated with risk-taking related negative consequences such as injury occurrence. As a result, more than two decades ago, the American College of Surgeons mandated the practice of SBIRT for all trauma centers.This renders the ED an important opportunity to provide substance use treatment and potentially reduce the risk of re-injury. Intentional injury, specifically assault-injury, presents a formidable public health burden in the United States . Annually, US EDs treat approximately 1.5 million individuals for non-fatal assault injuries.Previous literature reports reoccurrence rates from 1% to as high as 44%.Assault-injured individuals who report substance use are at even greater risk for re-injury.One study demonstrated that approximately 55% of assault-injured youth compared to 40% of non-assault-injured youth in the ED have a previous history of substance use.16 These findings suggest that ED SBIRT may be an applicable model to identify drug use among assault-injured individuals, a population at high risk for drug use and drug use disorders,cannabis grow equipment and to initiate treatment in the busy ED setting. In this review, we sought to assess the prevalence of cooccurring drug use and non-partner assault-injury in the ED. To accomplish this, our study objective was to determine what types of ED-based strategies have been reported in the published literature that screen for drug use and/or prescription medication misuse, deliver a brief intervention that targets drug use and/or prescription medication misuse, or directly refer to specialized treatment services among individuals injured by non-partner assault, each components of the SBIRT model. We further categorized each study as to whether it evaluated screening, a brief intervention, and/ or referral to specialized treatment services for drug use in accordance with the SBIRT model. We also determined the screening method for substance use that each study used . For the purposes of this study, we defined non-partner assault-injury as an intentional injury inflicted by another person not considered to be a boy/girlfriend, fiancé, or spouse . This includes individuals who may have been either the victim or aggressor. Although many studies have used the term “violence” or “violent-injury” when referring to an intentional injury inflicted by another person, in this review we will use the term “assault” or “assault-injury” for the purposes of maintaining consistency and clarity.
We use the term “drug use” to refer solely to the use of drugs and the term “substance use” to refer to the use of both drugs and alcohol. We limited our search to literature in the US population with participants of all ages. Studies of secondary analyses were included if they reported results collected from the parent study that were deemed relevant to the study objective . Studies were excluded if they examined only intimate partner assault injury, tobacco, or alcohol use alone. We excluded studies that examined alcohol use only to intentionally highlight knowledge gaps in the existing literature surrounding drug use and non-partner assault-injury, particularly in the setting of increasing legalization and use of cannabis.We excluded studies that examined intimate partner assault injury only because there is a paucity of literature that evaluates drug use in non-partner assault-injury comparatively to intimate partner assault-injury. Further, we sought to intentionally identify existing knowledge gaps in the literature and inform future areas of research by consolidating the existing state of knowledge in non-partner assault-injury and drug use. All disagreements in study selection were adjudicated by a third author. After final screening of the published manuscripts, there were 26 studies used in the final analysis. The final 26 studies had substantial heterogeneity in study design, population, and main outcome. All studies were non-experimental. Of the final 26 studies, only six were prospective. The strength of clinical data was graded according to the Oxford Centre for Evidence-Based Medicine levels of evidence, by two authors independently.Disputes were resolved after discussion. Levels of evidence are as follows: level 1, randomized clinical trials or systematic reviews ; level 2, well designed controlled trials or prospective comparative cohort trials; level 3, case-control or retrospective cohort studies; level 4, cases series or cross-sectional studies; level 5, opinion of respected authorities or case reports. Data extraction was completed in full by the first author with input from the remaining authors. The identifying study information extracted included the title, first author, journal, specialty focus of journal, study funder, and year of publication.