Association of opioid exposure during intensive care unit stays with post-discharge opioid use: A retrospective study and literature review

2021 ◽  
Vol 17 (6) ◽  
pp. 511-516
Author(s):  
Yoonsun Mo, MS, PharmD, BCPS, BCCCP ◽  
John Zeibeq, MD ◽  
Nabil Mesiha, MD ◽  
Abou Bakar, PharmD ◽  
Maram Sarsour, PharmD ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Retrospective Study ◽  
Hospital Discharge ◽  
Invasive Mechanical Ventilation ◽  
High Dose ◽  
Opioid Use ◽  
Electronic Health Record Data ◽  
Icu Patients ◽  
Mechanically Ventilated

Objective: To evaluate whether pain management strategies within intensive care unit (ICU) settings contribute to chronic opioid use upon hospital discharge in opioid-naive patients requiring invasive mechanical ventilation. Design: A retrospective, observational study.Setting: An 18-bed mixed ICU at a community teaching hospital located in Brooklyn, New York.Participants: This study included mechanically ventilated patients requiring continuous opioid infusion from April 25, 2017 to May 16, 2019. Patients were excluded if they received chronic opioid therapy at home or expired during this hospital admission. Eligible patients were identified using an electronic health record data query.Main outcome measure(s): The proportion of ICU patients who continued to require opioids upon ICU and hospital discharge. Results: A total of 196 ICU patients were included in this study. Of these, 22 patients were transferred to a regular floor while receiving a fentanyl transdermal patch. However, the fentanyl patch treatment was continued only for three patients (2 percent) at hospital discharge.Conclusions: This retrospective study suggested that high-dose use of opioids in mechanically ventilated, opioid-naive ICU patients was not associated with continued opioid use upon hospital discharge.

scholarly journals Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Comparative Machine Learning Study (Preprint)

2020 ◽  
Author(s):  
Sujeong Hur ◽  
Ji Young Min ◽  
Junsang Yoo ◽  
Kyunga Kim ◽  
Chi Ryang Chung ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Patient Safety ◽  
Intensive Care ◽  
Predictive Value ◽  
Prediction Models ◽  
Support Vector ◽  
Unplanned Extubation ◽  
Electronic Health Record Data ◽  
Icu Patients

BACKGROUND Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered as the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS This study was conducted an academic tertiary hospital in Seoul. The hospital had approximately 2,000 inpatient beds and 120 intensive care unit (ICU) beds. The number of patients, on daily basis, was approximately 9,000 for the out-patient. The number of annual ICU admission was approximately 10,000. We conducted a retrospective study between January 1, 2010 and December 31, 2018. A total of 6,914 extubation cases were included. We developed an unplanned extubation prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model’s performance, we used area under the receiver operator characteristic curve (AUROC). Sensitivity, specificity, positive predictive value negative predictive value, and F1-score were also determined for each model. For performance evaluation, we also used calibration curve, the Brier score, and the Hosmer-Lemeshow goodness-of-fit statistic. RESULTS Among the 6,914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was more likely to occur during the night shift compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality was higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.762, and for SVM was 0.740. CONCLUSIONS We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787, which was obtained using RF. CLINICALTRIAL N/A

scholarly journals CLINICAL CHARACTERISTICS OF 28 PATIENTS WITH DIABETES AND COVID-19 IN WUHAN, CHINA

2020 ◽  
Vol 26 (6) ◽  
pp. 668-674 ◽  
Author(s):  
Feng Wang ◽  
Yan Yang ◽  
Kun Dong ◽  
Yongli Yan ◽  
Shujun Zhang ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Brain Natriuretic Peptide ◽  
Natriuretic Peptide ◽  
Clinical Characteristics ◽  
Troponin I ◽  
Clinical Laboratory ◽  
Invasive Mechanical Ventilation ◽  
Icu Patients ◽  
Patients With Diabetes

Objective: Previous studies on coronavirus disease 2019 (COVID-19) were based on information from the general population. We aimed to further clarify the clinical characteristics of diabetes with COVID-19. Methods: Twenty-eight patients with diabetes and COVID-19 were enrolled from January 29, 2020, to February 10, 2020, with a final follow-up on February 22, 2020. Epidemiologic, demographic, clinical, laboratory, treatment, and outcome data were analyzed. Results: The average age of the 28 patients was 68.6 ± 9.0 years. Most (75%) patients were male. Only 39.3% of the patients had a clear exposure of COVID-19. Fever (92.9%), dry cough (82.1%), and fatigue (64.3%) were the most common symptoms, followed by dyspnea (57.1%), anorexia (57.1%), diarrhea (42.9%), expectoration (25.0%), and nausea (21.4%). Fourteen patients were admitted to the intensive care unit (ICU). The hemoglobin A1c level was similar between ICU and non-ICU patients. ICU patients had a higher respiratory rate, higher levels of random blood glucose, aspartate transaminase, bilirubin, creatine, N-terminal prohormone of brain natriuretic peptide, troponin I, D-dimers, procalcitonin, C-reactive protein, ferritin, interleukin (IL)-2R, IL-6, and IL-8 than non-ICU patients. Eleven of 14 ICU patients received noninvasive ventilation and 7 patients received invasive mechanical ventilation. Twelve patients died in the ICU group and no patients died in the non-ICU group. Conclusion: ICU cases showed higher rates of organ failure and mortality than non-ICU cases. The poor outcomes of patients with diabetes and COVID-19 indicated that more supervision is required in these patients. Abbreviations: COVID-19 = coronavirus disease 2019; ICU = intensive care unit; MERS-CoV = middle East respiratory syndrome-related coronavirus; 2019- nCoV = 2019 novel coronavirus; NT-proBNP = N-terminal prohormone of brain natriuretic peptide; SARS-CoV = severe acute respiratory syndrome-related coronavirus

scholarly journals Assessment of Postresuscitation Volume Status by Bioimpedance Analysis in Patients with Sepsis in the Intensive Care Unit: A Pilot Observational Study

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Bram Rochwerg ◽  
Jason H. Cheung ◽  
Christine M. Ribic ◽  
Faraz Lalji ◽  
France J. Clarke ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Venous Pressure ◽  
Invasive Mechanical Ventilation ◽  
Kidney Injury ◽  
Volume Status ◽  
Bioimpedance Analysis ◽  
Consent Rate ◽  
Icu Patients ◽  
Unit Increase

Background. Bioimpedance analysis (BIA) is a novel method of assessing a patient’s volume status.Objective. We sought to determine the feasibility of using vector length (VL), derived from bioimpedance analysis (BIA), in the assessment of postresuscitation volume status in intensive care unit (ICU) patients with sepsis.Method. This was a prospective observational single-center study. Our primary outcome was feasibility. Secondary clinical outcomes included ventilator status and acute kidney injury. Proof of concept was sought by correlating baseline VL measurements with other known measures of volume status.Results. BIA was feasible to perform in the ICU. We screened 655 patients, identified 78 eligible patients, and approached 64 for consent. We enrolled 60 patients (consent rate of 93.8%) over 12 months. For each 50-unit increase in VL, there was an associated 22% increase in the probability of not requiring invasive mechanical ventilation (IMV) (p=0.13). Baseline VL correlated with other measures of volume expansion including serum pro-BNP levels, peripheral edema, and central venous pressure (CVP).Conclusion. It is feasible to use BIA to predict postresuscitation volume status and patient-important outcomes in septic ICU patients.Trial Registration. This trial is registered with clinicaltrials.govNCT01379404registered on June 7, 2011.

scholarly journals THE VALUE OF ROUTINE CHEST X-RAY (CXR) IN MECHANICALLY VENTILATED INTENSIVE CARE UNIT (ICU) PATIENTS

CHEST Journal ◽  
2005 ◽  
Vol 128 (4) ◽  
pp. 208S
Author(s):  
Marleen E. Graat ◽  
Esther K. Wolthuis ◽  
Goda Choi ◽  
Johanna C. Korevaar ◽  
Marcus J. Schultz
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Icu Patients ◽  
Mechanically Ventilated ◽  
X Ray ◽  
Chest X Ray ◽  
Routine Chest

scholarly journals Comparing the Effect of Neostigmine and Metoclopramide on Gastric Residual Volume of Mechanically Ventilated Patients in Intensive Care Unit: A Double-Blind Randomized Clinical Trial

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Alireza Rahat-Dahmardeh ◽  
Sara Saneie-Moghadam ◽  
Masoum Khosh-Fetrat
Keyword(s):  
Clinical Trial ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Randomized Clinical Trial ◽  
Normal Saline ◽  
Residual Volume ◽  
Gastric Residual Volume ◽  
Double Blind ◽  
Icu Patients ◽  
Mechanically Ventilated

Introduction. The gastric residual volume (GRV) monitoring in patients with mechanical ventilation (MV) is a common and important challenge. The purpose of this study was to compare the effect of neostigmine and metoclopramide on GRV among MV patients in the intensive care unit (ICU). Methods. In a double-blind randomized clinical trial, a total of 200 mechanically ventilated ICU patients with GRV > 120   ml (6 hours after the last gavage) were randomly assigned into two groups (A and B) with 100 patients in each group. Patients in groups A and B received intravenous infusion of neostigmine at a dose of 2.5 mg/100 ml normal saline and metoclopramide at a dose of 10 mg/100 ml normal saline, within 30 minutes, respectively. GRV was evaluated 5 times for each patient, once before the intervention and 4 times (at 3, 6, 9, and 12 hours) after the intervention. In addition, demographic characteristics including age and gender, as well as severity illness based on the sequential organ failure assessment score (SOFA), were initially recorded for all patients. Results. After adjusting of demographic and clinical characteristics (age, gender, and SOFA score), the generalized estimating equation (GEE) model revealed that neostigmine treatment increased odds of GRV improvement compared to the metoclopramide group ( OR = 2.45 , 95% CI: 1.60-3.76, P < 0.001 ). However, there is a statistically significant time trend (within-subject differences or time effect) regardless of treatment groups ( P < 0.001 ). Conclusion. According to the results, although neostigmine treatment significantly improved GRV in more patients in less time, within 12 hours of treatment, all patients in both groups had complete recovery. Considering that there was no significant difference between the two groups in terms of side effects, it seems that both drugs are effective in improving the GRV of ICU patients.

scholarly journals Analgesia and sedation in surgery Intensive Care Unit (ICU)

2017 ◽  
Vol 64 (1) ◽  
pp. 21-26
Author(s):  
Sanja Maric ◽  
Dalibor Boskovic
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Pain Management ◽  
Clinical Outcomes ◽  
Therapeutic Interventions ◽  
Negative Consequences ◽  
Icu Patients ◽  
Mechanically Ventilated ◽  
Pain At Rest

The goals of analgesia and sedation at the intensive care unit (ICU) are to facilitate mechanical ventilation, prevent patient and caregiver injury, and avoid the psychological and physiologic consequences of inadequate treatment of pain, anxiety, agitation, and delirium. Most ICU patients, especially the surgical and trauma ones, routinely experience pain at rest and with routine procedures. Treating pain in ICU patients depends on a clinician?s ability to perform a reproducible pain assessment and to monitor patients over time to determine the adequacy of therapeutic interventions to treat pain. Implementation of behavioral pain scales improves ICU pain management and clinical outcomes, including better use of analgesic and sedative agents and shorter durations of mechanical ventilation and ICU stay. Opioids are the primary medications for managing pain in critically ill patients. Multimodal approach to pain management in ICU patients has been recommended. Sedatives are commonly administered to ICU patients to treat agitation and its negative consequences. Sedation strategies using nonbenzodiazepine sedatives (propofol or dexmedetomidine) may be preferred over sedation with benzodiazepines (midazolam or lorazepam) to improve clinical outcomes in mechanically ventilated adult ICU patients. It is recommend daily sedation interruption or a light target level of sedation be routinely used in adult intensive care patients using mechanical ventilation. Delirium affecting up to 80% of mechanically ventilated adult ICU patients. ICU protocols that combine routine pain and sedation assessments, with pain management and sedation-minimizing strategies, along with delirium monitoring and prevention, may be the best strategy for avoiding the complications of oversedation. Protocolized pain, agitation and delirium assessment (PAD ICU), is significantly associated with a reduction in the use of analgesic medications, ICU length of stay, and duration of mechanical ventilation.

scholarly journals Insulin-like growth factor 1 and delirium

2012 ◽  
Vol 24 (11) ◽  
pp. 1872-1872 ◽  
Author(s):  
Catherine Motosko ◽  
Kristine Brown ◽  
Madan Kwatra
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Growth Factor ◽  
Preliminary Investigation ◽  
Serum Levels ◽  
Insulin Like Growth Factor ◽  
Icu Patients ◽  
Mechanically Ventilated ◽  
Mechanically Ventilated Patients ◽  
Ventilated Patients

The paper by Morandi et al. (2011), entitled “Insulin-like growth factor-1 and delirium in critically ill mechanically ventilated patients: a preliminary investigation,” is of great interest due to its lack of finding a correlation between serum levels of insulin-like growth factor-1 (IFG-1) and delirium in intensive care unit (ICU) patients.

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