The ICU Bridge Program: volunteers bridging medicine and people together.

BACKGROUND: The intensive care unit (ICU) is an emotionally taxing environment. Patients and family members are at an increased risk of long-term physical and psychological consequences of critical illness, known collectively as post-intensive care syndrome (PICS). These environmental strains can lead to a high incidence of staff turnover and burnout. AIM: The ICU Bridge Program (ICUBP) is a student-led organization that attempts to mitigate these stressors on patients, family, and staff, by assigning university volunteers to ICUs across Montreal. SETTING: ICU. PARTICIPANTS: ICU volunteers, staff, patients, and families. PROGRAM DESCRIPTION: The ICUBP volunteers support staff by orienting patients and families, while using effective communication strategies to provide comfort and promote a calm environment. The presence of volunteer visitors is helpful to patients who do not have the support of family members and/or friends. The program provides students with profound learning experiences by allowing them to shadow multidisciplinary teams, gaining a privileged and varied exposure to an acute medical environment, while developing their communications skills. PROGRAM EVALUATION: The program reassesses its methods and impact via internal student-designed surveys distributed on a yearly basis to staff and volunteers. DISCUSSION: Research is warranted to assess the impact of the program on ICU patients, visitors, staff, and volunteers.

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning.

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the course of the disease is closely linked to the outcome. As such, evaluation of future severity from current CXR would be highly desirable. We trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from an open-source dataset (COVID-19 image data collection) and from a multi-institutional local ICU dataset. The data was grouped into pairs of sequential CXRs and were categorized into three categories: 'Worse', 'Stable', or 'Improved' on the basis of radiological evolution ascertained from images and reports. Classical machine-learning algorithms were trained on the deep learning extracted features to perform immediate severity evaluation and prediction of future radiological trajectory. Receiver operating characteristic analyses and Mann-Whitney tests were performed. Deep learning predictions between "Worse" and "Improved" outcome categories and for severity stratification were significantly different for three radiological signs and one diagnostic ('Consolidation', 'Lung Lesion', 'Pleural effusion' and 'Pneumonia'; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between 'Worse' and 'Improved' cases with a 0.81 (0.74-0.83 95% CI) AUC in the open-access dataset and with a 0.66 (0.67-0.64 95% CI) AUC in the ICU dataset. Features extracted from the CXR could predict disease severity with a 52.3% accuracy in a 4-way classification. Severity evaluation trained on the COVID-19 image data collection had good out-of-distribution generalization when testing on the local dataset, with 81.6% of intubated ICU patients being classified as critically ill, and the predicted severity was correlated with the clinical outcome with a 0.639 AUC. CXR deep learning features show promise for classifying disease severity and trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions.

Outcomes and clinical practice in patients with COVID-19 admitted to the intensive care unit in Montréal, Canada: a descriptive analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is responsible for millions of infections worldwide, and a substantial number of these patients will be admitted to the intensive care unit (ICU). Our objective was to describe the characteristics, outcomes and management of critically ill patients with COVID-19 pneumonia at a single designated pandemic centre in Montréal, Canada. METHODS: A descriptive analysis was performed on consecutive critically ill patients with COVID-19 pneumonia admitted to the ICU at the Jewish General Hospital, a designated pandemic centre in Montréal, between Mar. 5 and May 21, 2020. Complete follow-up data corresponding to death or discharge from hospital health records were included to Aug. 4, 2020. We summarized baseline characteristics, management and outcomes, including mortality. RESULTS: A total of 106 patients were included in this study. Twenty-one patients (19.8%) died during their hospital stay, and the ICU mortality was 17.0% (18/106); all patients were discharged home or died, except for 4 patients (2 awaiting a rehabilitation bed and 2 awaiting long-term care). Twelve of 65 patients (18.5%) requiring mechanical ventilation died. Prone positioning was used in 29 patients (27.4%), including in 10 patients who were spontaneously breathing; no patient was placed on extracorporeal membrane oxygenation. High-flow nasal cannula was used in 51 patients (48.1%). Acute kidney injury was the most common complication, seen in 20 patients (18.9%), and 12 patients (11.3%) required renal replacement therapy. A total of 53 patients (50.0%) received corticosteroids. INTERPRETATION: Our cohort of critically ill patients with COVID-19 had lower mortality than that previously described in other jurisdictions. These findings may help guide critical care decision-making in similar health care systems in further COVID-19 surges.

An interaction between levodopa and enteral nutrition resulting in neuroleptic malignant-like syndrome and prolonged ICU stay.

OBJECTIVE: To describe a probable interaction between enteral feeds and levodopa leading to neuroleptic malignant-like syndrome (NMLS) in a polytrauma patient with Parkinson's disease (PD). CASE SUMMARY: A 63-year-old morbidly obese male polytrauma patient with PD and type 2 diabetes mellitus was admitted to our intensive care unit postoperatively. Enteral feeds were administered per nasogastric tube and provided 0.88 g /kg/day of protein based on ideal body weight (IBW). His PD medications (pramipexole, entacapone, and immediate-release levodopa/carbidopa 100 mg/25 mg, 1.5 tablets 4 times daily) were administered via nasogastric tube. To achieve better glycemic control, his enteral feeds were changed to a formula that provided 1.8 g/kg/day of protein based on IBW. In the following 24 hours, the patient's mental status deteriorated and he was reintubated. He developed a high fever (40.5 degrees C), leukocytosis, elevated serum creatine kinase (CK) (480-1801 units/L), and acute renal impairment. His enteral nutrition was changed to decrease protein intake to 1.0 g/kg/day based on IBW and he was given bromocriptine 5 mg 3 times daily via nasogastric tube. Within 24 hours, the patient's mental status improved, his temperature and CK decreased, and his renal function began to improve; the values returned to baseline levels on the 18th day of admission. DISCUSSION: Withdrawal or dose reduction of levodopa in patients with PD has been reported to precipitate NMLS, which is potentially fatal. Because dietary protein can decrease the absorp0tion of levodopa, a potential for an interaction between levodopa and enteral feedings exists, although published reports of such an interaction are limited. In this patient, the likelihood that a drug-nutrient interaction occurred between levodopa and enteral feedings is considered to be probable based on the Naranjo probability scale and the Horn Drug Interaction Probability Scale. CONCLUSIONS: Health-care professionals should be aware of the interaction between levodopa and protein content of enteral nutrition to avoid the occurrence of NMLS in patients with PD.

Critically ill patients with 2009 influenza A(H1N1) infection in Canada.

CONTEXT: Between March and July 2009, the largest number of confirmed cases of 2009 influenza A(H1N1) infection occurred in North America. OBJECTIVE: To describe characteristics, treatment, and outcomes of critically ill patients in Canada with 2009 influenza A(H1N1) infection. DESIGN, SETTING, AND PATIENTS: A prospective observational study of 168 critically ill patients with 2009 influenza A(H1N1) infection in 38 adult and pediatric intensive care units (ICUs) in Canada between April 16 and August 12, 2009. MAIN OUTCOME MEASURES: The primary outcome measures were 28-day and 90-day mortality. Secondary outcomes included frequency and duration of mechanical ventilation and duration of ICU stay. RESULTS: Critical illness occurred in 215 patients with confirmed (n = 162), probable (n = 6), or suspected (n = 47) community-acquired 2009 influenza A(H1N1) infection. Among the 168 patients with confirmed or probable 2009 influenza A(H1N1), the mean (SD) age was 32.3 (21.4) years; 113 were female (67.3%) and 50 were children (29.8%). Overall mortality among critically ill patients at 28 days was 14.3% (95% confidence interval, 9.5%-20.7%). There were 43 patients who were aboriginal Canadians (25.6%). The median time from symptom onset to hospital admission was 4 days (interquartile range [IQR], 2-7 days) and from hospitalization to ICU admission was 1 day (IQR, 0-2 days). Shock and nonpulmonary acute organ dysfunction was common (Sequential Organ Failure Assessment mean [SD] score of 6.8 [3.6] on day 1). Neuraminidase inhibitors were administered to 152 patients (90.5%). All patients were severely hypoxemic (mean [SD] ratio of Pao(2) to fraction of inspired oxygen [Fio(2)] of 147 [128] mm Hg) at ICU admission. Mechanical ventilation was received by 136 patients (81.0%). The median duration of ventilation was 12 days (IQR, 6-20 days) and ICU stay was 12 days (IQR, 5-20 days). Lung rescue therapies included neuromuscular blockade (28% of patients), inhaled nitric oxide (13.7%), high-frequency oscillatory ventilation (11.9%), extracorporeal membrane oxygenation (4.2%), and prone positioning ventilation (3.0%). Overall mortality among critically ill patients at 90 days was 17.3% (95% confidence interval, 12.0%-24.0%; n = 29). CONCLUSION: Critical illness due to 2009 influenza A(H1N1) in Canada occurred rapidly after hospital admission, often in young adults, and was associated with severe hypoxemia, multisystem organ failure, a requirement for prolonged mechanical ventilation, and the frequent use of rescue therapies.