Ischemic Stroke in the Cardiac Surgery Intensive Care Unit: A Quality Improvement Study.

OBJECTIVE: To investigate the frequency of stroke and code stroke activation and the factors influencing code stroke management in postoperative cardiac surgical patients. DESIGN: A retrospective quality improvement study was conducted between January 1, 2016, and December 31, 2021. SETTING: The Cardiac Surgery Recovery Unit (CSRU) at London Health Sciences Centre in London, Ontario, Canada. PARTICIPANTS: Postcardiac surgery patients aged 18 years or older who developed ischemic stroke during their admission to the CSRU. INTERVENTIONS: No specific interventions were administered as part of this study. Code stroke activation mobilizes a specialized team. The objectives include assessment by a physician within 10 minutes, obtaining neuroimaging and interpretation within 45 minutes, and beginning treatment within 60 minutes. MEASUREMENTS AND MAIN RESULTS: The incidence rate of stroke in the CSRU was 1.3%, and 34% of these patients had code stroke activated. The time since the last known well status was 11 ± 8 hours. The most common reasons for not activating code stroke were not meeting both timing and clinical criteria. The average time for computed tomography (CT) scan was 36 ± 22 minutes. Among patients who had code stroke activated, 24% had large- vessel occlusion (LVO), and 67% of those with LVO had an established stroke on their initial CT. CONCLUSION: Code stroke was activated in only one-third of patients who experienced a stroke following cardiac surgery. Additionally, out of those who had code stroke activated, only one-fourth were diagnosed with LVO. Among those with LVO, two-thirds were found to have a well-established stroke on noncontrast CT scans and were deemed ineligible for intervention.

Assessing quality of critical care during an ongoing health emergency-a novel approach to evaluate quality of care at Lebanese public ICUs during COVID-19.

BACKGROUND: Quality of care has been systematically monitored in hospitals in high-income countries to ensure adequate care. However, in low- and middle-income countries, quality indicators are not readily measured. The primary aim of this study was to assess to what extent it was feasible to monitor the quality of intensive care in an ongoing health emergency, and the secondary aim was to assess a quality of care intervention (twinning project) focused on Intensive Care Unit (ICU) quality of care in public hospitals in Lebanon. METHODS: We conducted a retrospective cohort study nested within an intervention implemented by the World Health Organization (WHO) together with partners. To assess the quality of care throughout the project, a monitoring system framed in the Donabedian model and included structure, process, and outcome indicators was developed and implemented. Data collection consisted of a checklist performed by external healthcare workers (HCWs) as well as collection of data from all admitted patients performed by each unit. The association between the number of activities within the interventional project and ICU mortality was evaluated. RESULTS: A total of 1679 patients were admitted to five COVID-19 ICUs during the study period. The project was conducted fully across four out of five hospitals. In these hospitals, a significant reduction in ICU mortality was found (OR: 0.83, P < 0.05, CI: 0.72-0.96). CONCLUSION: We present a feasible way to assess quality of care in ICUs and how it can be used in assessing a quality improvement project during ongoing crises in resource-limited settings. By implementing a quality of care intervention in Lebanon's public hospitals, we have shown that such initiatives might contribute to improvement of ICU care. The observed association between increased numbers of project activities and reduced ICU mortality underscores the potential of quality assurance interventions to improve outcomes for critically ill patients in resource-limited settings. Future research is needed to expand this model to be applicable in similar settings.

Selection of knowledge translation strategies to implement best practices on nonpharmacological prevention of delirium in intensive care unit / Sélection de stratégies de transfert des connaissances visant à implanter les pratiques recommandées de prévention non pharmacologiques du délirium en soins intensifs.

Background: Delirium prevention in the ICU should focus on a non-pharmacological approach. However, these recommendations are not always applied by care providers. Objective: To select knowledge translation strategies to facilitate the implementation of non-pharmacological best practices to prevent delirium in the ICU. Method: A consensus study was conducted. Barriers and facilitators to the implementation of nonpharmacological methods, and knowledge translation strategies, were identified in two nominal groups. A context assessment was also carried out. Nine professionals and one patient-partner participated. Results: The barriers and facilitators on which consensus was reached were most frequently related to environmental context and resources, intention, and knowledge. The areas of organizational context with the highest levels of agreement were interpersonal relations, culture and leadership. Consequently, knowledge translation strategies were selected to facilitate practices, as well as to modify the environment and improve knowledge. Conclusion: A structured method was used during this study to guide the selection of knowledge translation strategies. The application of these strategies could potentially improve clinical practice in intensive care.

Introduction: La prévention du délirium aux soins intensifs devrait être axée sur les méthodes non pharmacologiques. Toutefois, ce type de recommandation n'est pas toujours appliqué. Objectif: Sélectionner des stratégies de transfert des connaissances afin de faciliter l'implantation des pratiques non pharmacologiques pouvant prévenir le délirium en soins intensifs. Méthode: Une étude de consensus a été réalisée autour de deux thèmes. Deux groupes nominaux ont été constitués pour identifier les barrières et les facilitateurs à l'implantation des méthodes et les stratégies de transfert des connaissances. Une évaluation du contexte a aussi été réalisée. Neuf professionnels et une patiente-partenaire ont participé. Résultats: Les barrières et les facilitateurs ayant fait l'objet d'un consensus étaient plus fréquemment reliés au contexte environnemental et aux ressources, à l'intention et aux connaissances. Les domaines du contexte organisationnel qui ont obtenu le plus haut niveau d'accord sont les relations interpersonnelles, la culture et le leadership. Conséquemment, des stratégies de transfert des connaissances pour faciliter les pratiques, modifier l'environnement et améliorer les connaissances ont été sélectionnées. Conclusion: Une méthode structurée a été utilisée afin de guider la sélection de stratégies de transfert des connaissances. L'application de ces stratégies pourrait potentiellement améliorer la pratique clinique en soins intensifs.

Effectiveness of nonpharmacological interventions to prevent adverse events in the intensive care unit: A review of systematic reviews.

BACKGROUND: Different types of interventions have been assessed for the prevention of adverse events. However, determining which patient-safety practice is most effective can be challenging when there is no systematised evidence synthesis. An overview following the best methodological standards can provide the best reliable integrative evidence. OBJECTIVES: The objective of this study was to provide an overview of effectiveness nonpharmacological interventions aimed at preventing adverse events in the intensive care unit. METHODS: A review of systematic reviews (SRs) was conducted according to the Cochrane Handbook and PRISMA recommendations. PubMed, CINAHL, and Cochrane Library were searched for SRs published until March 2022. Two reviewers independently assessed the study's quality, using AMSTAR-2, and extracted data on intervention characteristics and effect on prevention of adverse events. RESULTS: Thirty-seven SRs were included, and 27 nonpharmacological interventions were identified to prevent 11 adverse events. Most of the reviews had critically low methodological quality. Among all the identified interventions, subglottic secretion drainage, semirecumbent position, and kinetic bed therapy were effective in preventing ventilator-associated pneumonia; the use of earplugs, early mobilisation, family participation, and music in reducing delirium; physical rehabilitation in improving muscle strength; use of respiratory support in preventing reintubation; the use of a computerised physician order entry system in reducing risk of medication errors; and the use of heated water humidifier was effective in reducing artificial airway occlusion. CONCLUSIONS: Some nonpharmacological interventions reduced adverse events in the intensive care setting. These findings should be interpreted carefully due to the low methodological quality. SRs on preventing adverse events in the intensive care unit should adhere to quality assessment tools so that best evidence can be used in decision-making.

Mechanical ventilation in COVID-19: A physiological perspective.

NEW FINDINGS: What is the topic of this review? This review presents the fundamental concepts of respiratory physiology and pathophysiology, with particular reference to lung mechanics and the pulmonary phenotype associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent coronavirus disease 2019 (COVID-19) pneumonia. What advances does it highlight? The review provides a critical summary of the main physiological aspects to be considered for safe and effective mechanical ventilation in patients with severe COVID-19 in the intensive care unit. ABSTRACT: Severe respiratory failure from coronavirus disease 2019 (COVID-19) pneumonia not responding to non-invasive respiratory support requires mechanical ventilation. Although ventilation can be a life-saving therapy, it can cause further lung injury if airway pressure and flow and their timing are not tailored to the respiratory system mechanics of the individual patient. The pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to a pattern of lung injury in patients with severe COVID-19 pneumonia typically associated with two distinct phenotypes, along a temporal and pathophysiological continuum, characterized by different levels of elastance, ventilation-to-perfusion ratio, right-to-left shunt, lung weight and recruitability. Understanding the underlying pathophysiology, duration of symptoms, radiological characteristics and lung mechanics at the individual patient level is crucial for the appropriate choice of mechanical ventilation settings to optimize gas exchange and prevent further lung injury. By critical analysis of the literature, we propose fundamental physiological and mechanical criteria for the selection of ventilation settings for COVID-19 patients in intensive care units. In particular, the choice of tidal volume should be based on obtaining a driving pressure < 14 cmH2 O, ensuring the avoidance of hypoventilation in patients with preserved compliance and of excessive strain in patients with smaller lung volumes and lower lung compliance. The level of positive end-expiratory pressure (PEEP) should be informed by the measurement of the potential for lung recruitability, where patients with greater recruitability potential may benefit from higher PEEP levels. Prone positioning is often beneficial and should be considered early. The rationale for the proposed mechanical ventilation settings criteria is presented and discussed.

Intensive Care Unit- Acquired Weakness and Hospital Functional Mobility Outcomes Following Invasive Mechanical Ventilation in Patients with COVID-19: A Single-Centre Prospective Cohort Study.

Background: Acute physical function outcomes in ICU survivors of COVID-19 pneumonia has received little attention. Critically ill patients with COVID-19 infection who require invasive mechanical ventilation may undergo greater exposure to some risk factors for ICU-acquired weakness (ICUAW). Purpose: To determine incidence and factors associated with ICUAW at ICU discharge and gait dependence at hospital discharge in mechanically ventilated patients with COVID-19 pneumonia. Methods: Single-centre, prospective cohort study conducted at a tertiary hospital in Madrid, Spain. We evaluated ICUAW with the Medical Research Council Summary Score (MRC-SS). Gait dependence was assessed with the Functional Status Score for the ICU (FSS-ICU) walking subscale. Results: During the pandemic second wave, between 27 July and 15 December, 2020, 70 patients were enrolled. ICUAW incidence was 65.7% and 31.4% at ICU discharge and hospital discharge, respectively. Gait dependence at hospital discharge was observed in 66 (54.3%) patients, including 9 (37.5%) without weakness at ICU discharge. In univariate analysis, ICUAW was associated with the use of neuromuscular blockers (crude odds ratio [OR] 9.059; p = 0.01) and duration of mechanical ventilation (OR 1.201; p = 0.001), but not with the duration of neuromuscular blockade (OR 1.145, p = 0.052). There was no difference in corticosteroid use between patients with and without weakness. Associations with gait dependence were lower MRC-SS at ICU discharge (OR 0.943; p = 0.015), older age (OR 1.126; p = 0.001), greater Charlson Comorbidity Index (OR 1.606; p = 0.011), longer duration of mechanical ventilation (OR 1.128; p = 0.001) and longer duration of neuromuscular blockade (OR 1.150; p = 0.029). Conclusions: In critically ill COVID-19 patients, the incidence of ICUAW and acute gait dependence were high. Our study identifies factors influencing both outcomes. Future studies should investigate optimal COVID-19 ARDS management and impact of dyspnea on acute functional outcomes of COVID-19 ICU survivors.

Implementation and evaluation of sepsis surveillance and decision support in medical ICU and emergency department.

OBJECTIVE: To improve the timely diagnosis and treatment of sepsis many institutions implemented automated sepsis alerts. Poor specificity, time delays, and a lack of actionable information lead to limited adoption by bedside clinicians and no change in practice or clinical outcomes. We aimed to compare sepsis care compliance before and after a multi-year implementation of a sepsis surveillance coupled with decision support in a tertiary care center. DESIGN: Single center before and after study. SETTING: Large academic Medical Intensive Care Unit (MICU) and Emergency Department (ED). POPULATION: Patients 18 years of age or older admitted to *** Hospital MICU and ED from 09/4/2011 to 05/01/2018 with severe sepsis or septic shock. INTERVENTIONS: Electronic medical record-based sepsis surveillance system augmented by clinical decision support and completion feedback. MEASUREMENTS AND MAIN RESULTS: There were 1950 patients admitted to the MICU with the diagnosis of severe sepsis or septic shock during the study period. The baseline characteristics were similar before (N = 854) and after (N = 1096) implementation of sepsis surveillance. The performance of the alert was modest with a sensitivity of 79.9%, specificity of 76.9%, positive predictive value (PPV) 27.9%, and negative predictive value (NPV) 97.2%. There were 3424 unique alerts and 1131 confirmed sepsis patients after the sniffer implementation. During the study period average care bundle compliance was higher; however after taking into account improvements in compliance leading up to the intervention, there was no association between intervention and improved care bundle compliance (Odds ratio: 1.16; 95% CI: 0.71 to 1.89; p-value 0.554). Similarly, the intervention was not associated with improvement in hospital mortality (Odds ratio: 1.55; 95% CI: 0.95 to 2.52; p-value: 0.078). CONCLUSIONS: A sepsis surveillance system incorporating decision support or completion feedback was not associated with improved sepsis care and patient outcomes.

Prevention of Complications in the Cardiac Intensive Care Unit: A Scientific Statement From the American Heart Association.

Contemporary cardiac intensive care units (CICUs) have an increasing prevalence of noncardiovascular comorbidities and multisystem organ dysfunction. However, little guidance exists to support the development of best-practice principles specific to the CICU. This scientific statement evaluates strategies to avoid the potentially preventable complications encountered within contemporary CICUs, focusing on those that are most applicable to the CICU environment. This scientific statement reviews evidence-based practices derived in non-CICU populations, assesses their relevance to CICU practice, and highlights key knowledge gaps warranting further investigation to attenuate patient risk.

Effectiveness of Bundle Interventions on ICU Delirium: A Meta-Analysis.

OBJECTIVE: To evaluate the impact of bundle interventions on ICU delirium prevalence, duration, and other patients' adverse outcomes. DATA SOURCES: The Cochrane Library, PubMed, CINAHL, EMBASE, PsychINFO, and MEDLINE from January 2000 to July 2020. The protocol of the study was registered in International prospective register of systematic reviews (CRD42020163147). STUDY SELECTION: Randomized clinical trials or cohort studies that examined the following outcomes were included in the current study: ICU delirium prevalence and duration, proportion of patient-days with coma, ventilator-free days, mechanical ventilation days, ICU or hospital length of stay, and ICU or inhospital or 28-day mortality. DATA EXTRACTION: Using a standardized data-collection form, two authors screened the studies and extracted the data independently, and assessed the studies' quality using the Modified Jadad Score Scale for randomized clinical trials and the Newcastle-Ottawa Scale for cohort studies. DATA SYNTHESIS: Eleven studies with a total of 26,384 adult participants were included in the meta-analysis. Five studies (three randomized clinical trials and two cohort studies) involving 18,638 patients demonstrated that ICU delirium prevalence was not reduced (risk ratio = 0.92; 95% CI, 0.68-1.24). Meta-analysis showed that the use of bundle interventions was not associated with shortening the duration of ICU delirium (mean difference = -1.42 d; 95% CI, -3.06 to 0.22; two randomized clinical trials and one cohort study), increasing ventilator-free days (mean difference = 1.56 d; 95% CI, -1.56 to 4.68; three randomized clinical trials), decreasing mechanical ventilation days (mean difference = -0.83 d; 95% CI, -1.80 to 0.14; four randomized clinical trials and two cohort studies), ICU length of stay (mean difference = -1.08 d; 95% CI, -2.16 to 0.00; seven randomized clinical trials and two cohort studies), and inhospital mortality (risk ratio = 0.86; 95% CI, 0.70-1.06; five randomized clinical trials and four cohort studies). However, bundle interventions are effective in reducing the proportion of patient-days experiencing coma (risk ratio = 0.47; 95% CI, 0.39-0.57; two cohort studies), hospital length of stay (mean difference = -1.47 d; 95% CI, -2.80 to -0.15; four randomized clinical trials and one cohort study), and 28-day mortality by 18% (risk ratio = 0.82; 95% CI, 0.69-0.99; three randomized clinical trials). CONCLUSIONS: This meta-analysis fails to support that bundle interventions are effective in reducing ICU delirium prevalence and duration, but supports that bundle interventions are effective in reducing the proportion of patient-days with coma, hospital length of stay, and 28-day mortality. Larger randomized clinical trials are needed to evaluate the impact of bundle interventions on ICU delirium and other clinical outcomes.

Derivation and Validation of an Ensemble Model for the Prediction of Agitation in Mechanically Ventilated Patients Maintained Under Light Sedation.

OBJECTIVES: Light sedation is recommended over deep sedation for invasive mechanical ventilation to improve clinical outcome but may increase the risk of agitation. This study aimed to develop and prospectively validate an ensemble machine learning model for the prediction of agitation on a daily basis. DESIGN: Variables collected in the early morning were used to develop an ensemble model by aggregating four machine learning algorithms including support vector machines, C5.0, adaptive boosting with classification trees, and extreme gradient boosting with classification trees, to predict the occurrence of agitation in the subsequent 24 hours. SETTING: The training dataset was prospectively collected in 95 ICUs from 80 Chinese hospitals on May 11, 2016, and the validation dataset was collected in 20 out of these 95 ICUs on December 16, 2019. PATIENTS: Invasive mechanical ventilation patients who were maintained under light sedation for 24 hours prior to the study day and who were to be maintained at the same sedation level for the next 24 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 578 invasive mechanical ventilation patients from 95 ICUs in 80 Chinese hospitals, including 459 in the training dataset and 119 in the validation dataset, were enrolled. Agitation was observed in 36% (270/578) of the invasive mechanical ventilation patients. The stepwise regression model showed that higher body temperature (odds ratio for 1°C increase: 5.29; 95% CI, 3.70-7.84; p < 0.001), greater minute ventilation (odds ratio for 1 L/min increase: 1.15; 95% CI, 1.02-1.30; p = 0.019), higher Richmond Agitation-Sedation Scale (odds ratio for 1-point increase: 2.43; 95% CI, 1.92-3.16; p < 0.001), and days on invasive mechanical ventilation (odds ratio for 1-d increase: 0.95; 95% CI, 0.93-0.98; p = 0.001) were independently associated with agitation in the subsequent 24 hours. In the validation dataset, the ensemble model showed good discrimination (area under the receiver operating characteristic curve, 0.918; 95% CI, 0.866-0.969) and calibration (Hosmer-Lemeshow test p = 0.459) in predicting the occurrence of agitation within 24 hours. CONCLUSIONS: This study developed an ensemble model for the prediction of agitation in invasive mechanical ventilation patients under light sedation. The model showed good calibration and discrimination in an independent dataset.

End-of-Life-Care Quality in ICUs Is Associated With Family Surrogates' Severe Anxiety and Depressive Symptoms During Their First 6 Months of Bereavement.

OBJECTIVES: Evidence linking end-of-life-care quality in ICUs to bereaved family members' psychologic distress remains limited by methodological insufficiencies of the few studies on this topic. To examine comprehensively the associations of family surrogates' severe anxiety and depressive symptoms with end-of-life-care quality in ICUs over their first 6 months of bereavement. DESIGN: Prospective, longitudinal, observational study. SETTING/PARTICIPANTS: Family surrogates (n = 278) were consecutively recruited from seven medical ICUs at two academically affiliated medical centers in Taiwan. MEASUREMENTS AND STATISTICAL ANALYSIS: Family surrogates' anxiety and depressive symptoms were assessed 1, 3, and 6 months postloss using the Hospital Anxiety and Depression Scale. Family satisfaction with end-of-life care in ICUs was assessed 1-month postloss by the Family Satisfaction in the ICU questionnaire. Patients' end-of-life care was documented over the patient's ICU stay. Associations of severe anxiety and depressive symptoms (scores ≥ 8 for each subscale) with end-of-life-care quality in ICUs (documented by patient care received and family satisfaction with end-of-life care in ICUs) were examined by multivariate logistic regression models with generalized estimating equation. MAIN RESULTS: Prevalence of severe anxiety and depressive symptoms decreased significantly over time. Surrogates' lower likelihood of severe anxiety or depressive symptoms 3-6 month postloss was associated with death without cardiopulmonary resuscitation, withdrawing life-sustaining treatments, and higher family satisfaction with end-of-life care in ICUs. Bereaved surrogates' higher likelihood of these symptoms was associated with physician-surrogate prognostic communication and conducting family meetings before patients died. CONCLUSIONS: End-of-life-care quality in ICUs is associated with bereaved surrogates' psychologic well-being. Enhancing end-of-life-care quality in ICUs by improving the process of end-of-life care, for example, promoting death without cardiopulmonary resuscitation, withdrawing life-sustaining treatments, and increasing family satisfaction with end-of-life care, can lighten bereaved family surrogates' severe anxiety symptoms and severe depressive symptoms.

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example.

OBJECTIVES: Critical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate vast amounts of data. However, technical, legal, ethical, and privacy concerns have so far limited the critical care medicine community from making these data readily available. The Society of Critical Care Medicine and the European Society of Intensive Care Medicine have identified ICU patient data sharing as one of the priorities under their Joint Data Science Collaboration. To encourage ICUs worldwide to share their patient data responsibly, we now describe the development and release of Amsterdam University Medical Centers Database (AmsterdamUMCdb), the first freely available critical care database in full compliance with privacy laws from both the United States and Europe, as an example of the feasibility of sharing complex critical care data. SETTING: University hospital ICU. SUBJECTS: Data from ICU patients admitted between 2003 and 2016. INTERVENTIONS: We used a risk-based deidentification strategy to maintain data utility while preserving privacy. In addition, we implemented contractual and governance processes, and a communication strategy. Patient organizations, supporting hospitals, and experts on ethics and privacy audited these processes and the database. MEASUREMENTS AND MAIN RESULTS: AmsterdamUMCdb contains approximately 1 billion clinical data points from 23,106 admissions of 20,109 patients. The privacy audit concluded that reidentification is not reasonably likely, and AmsterdamUMCdb can therefore be considered as anonymous information, both in the context of the U.S. Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The ethics audit concluded that responsible data sharing imposes minimal burden, whereas the potential benefit is tremendous. CONCLUSIONS: Technical, legal, ethical, and privacy challenges related to responsible data sharing can be addressed using a multidisciplinary approach. A risk-based deidentification strategy, that complies with both U.S. and European privacy regulations, should be the preferred approach to releasing ICU patient data. This supports the shared Society of Critical Care Medicine and European Society of Intensive Care Medicine vision to improve critical care outcomes through scientific inquiry of vast and combined ICU datasets.

Protocol Use in Surgical Intensive Care Units.

BACKGROUND: Protocols are common in intensive care, however the association between protocol prevalence and outcomes in surgical ICU patients is unclear. We hypothesized that ICUs in a multicenter database using more protocols had better outcomes. MATERIAL AND METHODS: This is a retrospective analysis of prospectively collected data from a 2-d prevalence study with 30-d follow up, on surgical and trauma patients in ICUs at 42 trauma centers. Use of forty clinical protocols was queried. Protocol prevalence was categorized by quartile into Low (first), Moderate (second and third), or High (fourth) use ICUs. The primary outcome was in-hospital mortality; secondary outcomes were ventilator, ICU, and hospital days, mechanical ventilation, tracheostomy, renal replacement, transfusion, and hospital-acquired infections. RESULTS: Data from 1044 surgical and trauma patients were analyzed. Protocol use was not different for "closed" (n = 20), "open" (n = 9), or "semi-open" (n = 13) ICUs (P= 0.20). Thirty-day in-hospital mortality was 8.4%, and not associated with number of protocols (OR 1.01 [95% CI 0.98-1.03], P= 0.65). There was no statistically significant difference between High and Low use ICUs for ventilator days (OR 0.86; 0.52-1.43), tracheostomy (OR 0.8; 0.47-1.38), renal replacement therapy (OR 0.66; 0.04-9.82), transfusion (OR 0.95; 0.58-1.57), or hospital-acquired infections (OR 1.07; 0.67-1.7). Higher mortality was seen in open (versusclosed; OR 1.74 [1.05-2.89], P= 0.033), and surgical/trauma (versustrauma; OR 1.86 [1.33-2.61]; P< 0.001). CONCLUSIONS: In this multicenter observational study of surgical ICU patients, no association was found between the number of protocols used and patient outcomes.

Short-term Outcomes for Patients and Providers After Elective Tracheostomy in COVID-19-Positive Patients.

BACKGROUND: Urgent guidance is needed on the safety for providers of percutaneous tracheostomy in patients diagnosed with COVID-19. The objective of the study was to demonstrate that percutaneous dilational tracheostomy (PDT) with a period of apnea in patients requiring prolonged mechanical ventilation due to COVID-19 is safe and can be performed for the usual indications in the intensive care unit. METHODS: This study involves an observational case series at a single-center medical intensive care unit at a level-1 trauma center in patients diagnosed with COVID-19 who were assessed for tracheostomy. Success of a modified technique included direct visualization of tracheal access by bronchoscopy and a blind dilation and tracheostomy insertion during a period of patient apnea to reduce aerosolization. Secondary outcomes include transmission rate of COVID-19 to providers and patient complications. RESULTS: From April 6th, 2020 to July 21st, 2020, 2030 patients were admitted to the hospital with COVID-19, 615 required intensive care unit care (30.3%), and 254 patients required mechanical ventilation (12.5%). The mortality rate for patients requiring mechanical ventilation was 29%. Eighteen patients were assessed for PDT, and 11 (61%) underwent the procedure. The majority had failed extubation at least once (72.7%), and the median duration of intubation before tracheostomy was 15 d (interquartile range 13-24). The median positive end-expiratory pressure at time of tracheostomy was 10.8. The median partial pressure of oxygen (PaO2)/FiO2 ratio on the day of tracheostomy was 142.8 (interquartile range 104.5-224.4). Two patients had bleeding complications. At 1-week follow-up, eight patients still required ventilator support (73%). At the most recent follow-up, eight patients (73%) have been liberated from the ventilator, one patient (9%) died as a result of respiratory/multiorgan failure, and two were discharged on the ventilator (18%). Average follow-up was 20 d. None of the surgeons performing PDT have symptoms of or have tested positive for COVID-19. CONCLUSIONS: and relevance: PDT for patients with COVID-19 is safe for health care workers and patients despite higher positive end-expiratory pressure requirements and should be performed for the same indications as other causes of respiratory failure.

Prognostic association of routinely measured biomarkers in patients admitted to critical care: a systematic review.

PURPOSE: To examine reported prognostic associations of routine blood measurements in the intensive care unit. MATERIALS AND METHODS: We searched PubMed, EMBASE through 28th May 2020 to identify all studies in adult critical care investigating associations between parameters measured routinely in whole blood, plasma or serum, and length of stay or mortality. Registration: PROSPERO; CRD42019122058. RESULTS: A total of 128 studies, reporting 28 different putative prognostic biomarkers, met eligibility criteria. Those most frequently examined were red cell distribution width, neutrophil-to-lymphocyte ratio, C-reactive protein, and platelet count. A higher red cell distribution width, a lower platelet count, and a higher neutrophil-to-lymphocyte ratio were consistently associated with both increased mortality and length of stay. A lower level of albumin was consistently associated with greater mortality. C-reactive protein was inconsistent. Most studies (n = 110) used regression modelling with wide variation in variable selection and covariate-adjustment; none externally validated the proposed predictive models. CONCLUSIONS: Simple regression models have so far proved inadequate for the complexity of data available from routine blood sampling in critical care. Adoption of a direct causal framework may help better assess mechanistic processes, aid design of future studies, and guide clinical decision making using routine data.

Genomic surveillance of antimicrobial resistant bacterial colonisation and infection in intensive care patients.

BACKGROUND: Third-generation cephalosporin-resistant Gram-negatives (3GCR-GN) and vancomycin-resistant enterococci (VRE) are common causes of multi-drug resistant healthcare-associated infections, for which gut colonisation is considered a prerequisite. However, there remains a key knowledge gap about colonisation and infection dynamics in high-risk settings such as the intensive care unit (ICU), thus hampering infection prevention efforts. METHODS: We performed a three-month prospective genomic survey of infecting and gut-colonising 3GCR-GN and VRE among patients admitted to an Australian ICU. Bacteria were isolated from rectal swabs (n = 287 and n = 103 patients ≤2 and > 2 days from admission, respectively) and diagnostic clinical specimens between Dec 2013 and March 2014. Isolates were subjected to Illumina whole-genome sequencing (n = 127 3GCR-GN, n = 41 VRE). Multi-locus sequence types (STs) and antimicrobial resistance determinants were identified from de novo assemblies. Twenty-three isolates were selected for sequencing on the Oxford Nanopore MinION device to generate completed reference genomes (one for each ST isolated from ≥2 patients). Single nucleotide variants (SNVs) were identified by read mapping and variant calling against these references. RESULTS: Among 287 patients screened on admission, 17.4 and 8.4% were colonised by 3GCR-GN and VRE, respectively. Escherichia coli was the most common species (n = 36 episodes, 58.1%) and the most common cause of 3GCR-GN infection. Only two VRE infections were identified. The rate of infection among patients colonised with E. coli was low, but higher than those who were not colonised on admission (n = 2/33, 6% vs n = 4/254, 2%, respectively, p = 0.3). While few patients were colonised with 3GCR- Klebsiella pneumoniae or Pseudomonas aeruginosa on admission (n = 4), all such patients developed infections with the colonising strain. Genomic analyses revealed 10 putative nosocomial transmission clusters (≤20 SNVs for 3GCR-GN, ≤3 SNVs for VRE): four VRE, six 3GCR-GN, with epidemiologically linked clusters accounting for 21 and 6% of episodes, respectively (OR 4.3, p = 0.02). CONCLUSIONS: 3GCR-E. coli and VRE were the most common gut colonisers. E. coli was the most common cause of 3GCR-GN infection, but other 3GCR-GN species showed greater risk for infection in colonised patients. Larger studies are warranted to elucidate the relative risks of different colonisers and guide the use of screening in ICU infection control.

Partnership among hospitals to reduce healthcare associated infections: a quasi-experimental study in Brazilian ICUs.

BACKGROUND: Healthcare-associated infections (HAIs) are relevant in developing countries where frequencies can be at least 3 times higher than in developed countries. The purpose of this research was to describe the intervention implemented in intensive care units (ICUs) to reduce HAIs through collaborative project and analyze the variation over 18 months in the incidence density (ID) of the three main HAIs: ventilator associated pneumonia (VAP), central line-associated bloodstream infections (CLABSIs) and catheter-related urinary tract infections (CAUTIs) and also the length of stay and mortality in these ICUs. METHODS: A quasi-experimental study in five public adult clinical-surgical ICUs, to reduce HAIs, through interventions using the BTS-IHI "Improvement Model", during 18 months. In the project, promoted by the Ministry of Health, Brazilian philanthropic hospitals certified for excellence (HE), those mostly private, certified as excellence and exempt from security contributions, regularly trained and monitored public hospitals in diagnostics, data collection and in developing cycles to improve quality and to prevent HAIs (bundles). In the analysis regarding the length of stay, mortality, the IDs of VAP, CLABSIs and CAUTIs over time, a Generalized Estimating Equation (GEE) model was applied for continuous variables, using the constant correlation (exchangeable) between assessments over time. The model estimated the average difference (ß coefficient of the model) of the measures analyzed during two periods: a period in the year 2017 (prior to implementing the project) and in the years 2018 and 2019 (during the project). RESULT: A mean monthly reduction of 0.427 in VAP ID (p = 0.002) with 33.8% decrease at the end of the period and 0.351 in CAUTI ID (p = 0.009) with 45% final decrease. The mean monthly reduction of 0.252 for CLABSIs was not significant (p = 0.068). Length of stay and mortality rates had no significant variation. CONCLUSIONS: Given the success in reducing VAP and CAUTIs in a few months of interventions, the achievement of the collaborative project is evident. This partnership among public hospitals/HE may be applied to other ICUs including countries with fewer resources.

Development of Machine Learning Models to Validate a Medication Regimen Complexity Scoring Tool for Critically Ill Patients.

INTRODUCTION: The Medication Regimen Complexity -Intensive Care Unit (MRC-ICU) is the first tool for measuring medication regimen complexity in critically ill patients. This study tested machine learning (ML) models to investigate the relationship between medication regimen complexity and patient outcomes. METHODS: This study was a single-center, retrospective observational evaluation of 130 adults admitted to the medical ICU. The MRC-ICU score was utilized to improve the inpatient model's prediction accuracy. Three models were proposed: model I, demographic data without medication data; model II, demographic data and medication regimen complexity variables; and model III: demographic data and the MRC-ICU score. A total of 6 ML classifiers was developed: k-nearest neighbor (KNN), naïve Bayes (NB), random forest, support vector machine, neural network, and logistic classifier (LC). They were developed and tested using electronic health record data to predict inpatient mortality. RESULTS: The results demonstrated that adding medication regimen complexity variables (model II) and the MRC-ICU score (model III) improved inpatient mortality prediction.. The LC outperformed the other classifiers (KNN and NB), with an overall accuracy of 83%, sensitivity (Se) of 87%, specificity of 67%, positive predictive value of 93%, and negative predictive value of 46%. The APACHE III score and the MRC-ICU score at the 24-hour interval were the 2 most important variables. CONCLUSION AND RELEVANCE: Inclusion of the MRC-ICU score improved the prediction of patient outcomes on the previously established APACHE III score. This novel, proof-of-concept methodology shows promise for future application of the MRC-ICU scoring tool for patient outcome predictions.

Prescribing Practices of Valproic Acid for Agitation and Delirium in the Intensive Care Unit.

BACKGROUND: Analgesics, sedatives, and antipsychotics are commonly prescribed for agitation and delirium in the intensive care unit (ICU), but their use is limited by adverse effects and lack of efficacy. Valproic acid is an alternative treatment option. OBJECTIVE: The primary objective of this study was to describe valproic acid prescribing in our institution's ICUs when used for agitation or delirium. Measures of effectiveness and safety were also assessed. METHODS: This was a single-center, retrospective, institutional review board-approved cohort study of adult inpatients admitted to the ICU between January 2018 and August 2018. Patients who received valproic acid for the treatment of agitation or delirium for ≥24 hours were included. Prescribing practices were evaluated for dose, frequency, and route of administration. Effectiveness was assessed via agitation and delirium assessment tools and quantity of adjunctive agents used. RESULTS: A total of 80 patients were included, with 35 receiving valproic acid alone and 45 in conjunction with antipsychotics. The most common valproic acid regimen was 250 mg orally 3 times daily. Delirium resolution occurred in 55% of patients: 24 in the valproic acid monotherapy group and 20 in the valproic acid plus antipsychotic group (69% vs 44%; P = 0.03). The incidence of delirium decreased from valproic acid day 0 to day 3 (93% vs 68%; P < 0.01), with no change in agitation (64% vs 63%; P = 0.28). CONCLUSION AND RELEVANCE: Valproic acid is frequently prescribed in agitated, delirious patients at our institution and may have a role in the management of ICU delirium.

Systematic early versus late mobilization or standard early mobilization in mechanically ventilated adult ICU patients: systematic review and meta-analysis.

BACKGROUND: This systematic review and meta-analysis aimed to determine the effectiveness of systematic early mobilization in improving muscle strength and physical function in mechanically ventilated intensive care unit (ICU) patients. METHODS: We conducted a two-stage systematic literature search in MEDLINE, EMBASE and the Cochrane Library until January 2019 for randomized controlled trials (RCTs) examining the effects of early mobilization initiated within 7 days after ICU admission compared with late mobilization, standard early mobilization or no mobilization. Priority outcomes were Medical Research Council Sum Score (MRC-SS), incidence of ICU-acquired weakness (ICUAW), 6-min walk test (6MWT), proportion of patients reaching independence, time needed until walking, SF-36 Physical Function Domain Score (PFS) and SF-36 Physical Health Component Score (PCS). Meta-analysis was conducted where sufficient comparable evidence was available. We evaluated the certainty of evidence according to the GRADE approach. RESULTS: We identified 12 eligible RCTs contributing data from 1304 participants. Two RCTs were categorized as comparing systematic early with late mobilization, nine with standard early mobilization and one with no mobilization. We found evidence for a benefit of systematic early mobilization compared to late mobilization for SF-36 PFS (MD 12.3; 95% CI 3.9-20.8) and PCS (MD 3.4; 95% CI 0.01-6.8), as well as on the proportion of patients reaching independence and the time needed to walking, but not for incidence of ICUAW (RR 0.62; 95% CI 0.38-1.03) or MRC-SS. For systematic early compared to standard early mobilization, we found no statistically significant benefit on MRC-SS (MD 5.8; 95% CI - 1.4 to 13.0), incidence of ICUAW (RR 0.90; 95% CI 0.63-1.27), SF-36 PFS (MD 8.1; 95% CI - 15.3 to 31.4) or PCS (MD - 2.4; 95% CI - 6.1 to 1.3) or other priority outcomes except for change in 6MWT from baseline. Generally, effects appeared stronger for systematic early compared to late mobilization than to standard early mobilization. We judged the certainty of evidence for all outcomes as very low to low. CONCLUSION: The evidence regarding a benefit of systematic early mobilization remained inconclusive. However, our findings indicate that the larger the difference in the timing between the intervention and the comparator, the more likely an RCT is to find a benefit for early mobilization. STUDY REGISTRATION: PROSPERO (CRD42019122555).