Effect of Tele-ICU on Clinical Outcomes of Critically Ill Patients: The TELESCOPE Randomized Clinical Trial.

Importance: Despite its implementation in several countries, there has not been a randomized clinical trial to assess whether telemedicine in intensive care units (ICUs) could improve clinical outcomes of critically ill patients. Objective: To determine whether an intervention comprising daily multidisciplinary rounds and monthly audit and feedback meetings performed by a remote board-certified intensivist reduces ICU length of stay (LOS) compared with usual care. Design, Setting, and Participants: A parallel cluster randomized clinical trial with a baseline period in 30 general ICUs in Brazil in which daily multidisciplinary rounds performed by board-certified intensivists were not routinely available. All consecutive adult patients (aged ≥18 years) admitted to the participating ICUs, excluding those admitted due to justice-related issues, were enrolled between June 1, 2019, and April 7, 2021, with last follow-up on July 6, 2021. Intervention: Remote daily multidisciplinary rounds led by a board-certified intensivist through telemedicine, monthly audit and feedback meetings for discussion of ICU performance indicators, and provision of evidence-based clinical protocols. Main Outcomes and Measures: The primary outcome was ICU LOS at the patient level. Secondary outcomes included ICU efficiency, in-hospital mortality, incidence of central line-associated bloodstream infections, ventilator-associated events, catheter-associated urinary tract infections, ventilator-free days at 28 days, patient-days receiving oral or enteral feeding, patient-days under light sedation, and rate of patients with oxygen saturation values under that of normoxemia, assessed using generalized linear mixed models. Results: Among 17 024 patients (1794 in the baseline period and 15 230 in the intervention period), the mean (SD) age was 61 (18) years, 44.7% were female, the median (IQR) Sequential Organ Failure Assessment score was 6 (2-9), and 45.5% were invasively mechanically ventilated at admission. The median (IQR) time under intervention was 20 (16-21) months. Mean (SD) ICU LOS, adjusted for baseline assessment, did not differ significantly between the tele-critical care and usual care groups (8.1 [10.0] and 7.1 [9.0] days; percentage change, 8.2% [95% CI, -5.4% to 23.8%]; P = .24). Results were similar in sensitivity analyses and prespecified subgroups. There were no statistically significant differences in any other secondary or exploratory outcomes. Conclusions and Relevance: Daily multidisciplinary rounds conducted by a board-certified intensivist through telemedicine did not reduce ICU LOS in critically ill adult patients. Trial Registration: ClinicalTrials.gov Identifier: NCT03920501.

Comparing causal random forest and linear regression to estimate the independent association of organisational factors with ICU efficiency.

PURPOSE: Parametric regression models have been the main statistical method for identifying average treatment effects. Causal machine learning models showed promising results in estimating heterogeneous treatment effects in causal inference. Here we aimed to compare the application of causal random forest (CRF) and linear regression modelling (LRM) to estimate the effects of organisational factors on ICU efficiency. METHODS: A retrospective analysis of 277,459 patients admitted to 128 Brazilian and Uruguayan ICUs over three years. ICU efficiency was assessed using the average standardised efficiency ratio (ASER), measured as the average of the standardised mortality ratio (SMR) and the standardised resource use (SRU) according to the SAPS-3 score. Using a causal inference framework, we estimated and compared the conditional average treatment effect (CATE) of seven common structural and organisational factors on ICU efficiency using LRM with interaction terms and CRF. RESULTS: The hospital mortality was 14 %; median ICU and hospital lengths of stay were 2 and 7 days, respectively. Overall median SMR was 0.97 [IQR: 0.76,1.21], median SRU was 1.06 [IQR: 0.79,1.30] and median ASER was 0.99 [IQR: 0.82,1.21]. Both CRF and LRM showed that the average number of nurses per ten beds was independently associated with ICU efficiency (CATE [95 %CI]: -0.13 [-0.24, -0.01] and -0.09 [-0.17,-0.01], respectively). Finally, CRF identified some specific ICUs with a significant CATE in exposures that did not present a significant average effect. CONCLUSION: In general, both methods were comparable to identify organisational factors significantly associated with CATE on ICU efficiency. CRF however identified specific ICUs with significant effects, even when the average effect was nonsignificant. This can assist healthcare managers in further in-dept evaluation of process interventions to improve ICU efficiency.

Epidemiology of Renal Replacement Therapy for Critically Ill Patients across Seven Health Jurisdictions.

INTRODUCTION: Acute kidney injury (AKI) requiring treatment with renal replacement therapy (RRT) is a common complication after admission to an intensive care unit (ICU) and is associated with significant morbidity and mortality. However, the prevalence of RRT use and the associated outcomes in critically patients across the globe are not well described. Therefore, we describe the epidemiology and outcomes of patients receiving RRT for AKI in ICUs across several large health system jurisdictions. METHODS: Retrospective cohort analysis using nationally representative and comparable databases from seven health jurisdictions in Australia, Brazil, Canada, Denmark, New Zealand, Scotland, and the USA between 2006 and 2023, depending on data availability of each dataset. Patients with a history of end-stage kidney disease receiving chronic RRT and patients with a history of renal transplant were excluded. RESULTS: A total of 4,104,480 patients in the ICU cohort and 3,520,516 patients in the mechanical ventilation cohort were included. Overall, 156,403 (3.8%) patients in the ICU cohort and 240,824 (6.8%) patients in the mechanical ventilation cohort were treated with RRT for AKI. In the ICU cohort, the proportion of patients treated with RRT was lowest in Australia and Brazil (3.3%) and highest in Scotland (9.2%). The in-hospital mortality for critically ill patients treated with RRT was almost fourfold higher (57.1%) than those not receiving RRT (16.8%). The mortality of patients treated with RRT varied across the health jurisdictions from 37 to 65%. CONCLUSION: The outcomes of patients who receive RRT in ICUs throughout the world vary widely. Our research suggests that differences in access to and provision of this therapy are contributing factors.

Challenges for a broad international implementation of the current severe community-acquired pneumonia guidelines.

Severe community-acquired pneumonia (sCAP) remains one of the leading causes of admission to the intensive care unit, thus consuming a large share of resources and is associated with high mortality rates worldwide. The evidence generated by clinical studies in the last decade was translated into recommendations according to the first published guidelines focusing on severe community-acquired pneumonia. Despite the advances proposed by the present guidelines, several challenges preclude the prompt implementation of these diagnostic and therapeutic measures. The present article discusses the challenges for the broad implementation of the sCAP guidelines and proposes solutions when applicable.

Biomarkers: Are They Useful in Severe Community-Acquired Pneumonia?

Community acquired pneumonia (CAP) is a prevalent infectious disease often requiring hospitalization, although its diagnosis remains challenging as there is no gold standard test. In severe CAP, clinical and radiologic criteria have poor sensitivity and specificity, and microbiologic documentation is usually delayed and obtained in less than half of sCAP patients. Biomarkers could be an alternative for diagnosis, treatment monitoring and establish resolution. Beyond the existing evidence about biomarkers as an adjunct diagnostic tool, most evidence comes from studies including CAP patients in primary care or emergency departments, and not only sCAP patients. Ideally, biomarkers used in combination with signs, symptoms, and radiological findings can improve clinical judgment to confirm or rule out CAP diagnosis, and may be valuable adjunctive tools for risk stratification, differentiate viral pneumonia and monitoring the course of CAP. While no single biomarker has emerged as an ideal one, CRP and PCT have gathered the most evidence. Overall, biomarkers offer valuable information and can enhance clinical decision-making in the management of CAP, but further research and validation are needed to establish their optimal use and clinical utility.

The Association Between Prepandemic ICU Performance and Mortality Variation in COVID-19: A Multicenter Cohort Study of 35,619 Critically Ill Patients.

BACKGROUND: During the COVID-19 pandemic, ICUs remained under stress and observed elevated mortality rates and high variations of outcomes. A knowledge gap exists regarding whether an ICU performing best during nonpandemic times would still perform better when under high pressure compared with the least performing ICUs. RESEARCH QUESTION: Does prepandemic ICU performance explain the risk-adjusted mortality variability for critically ill patients with COVID-19? STUDY DESIGN AND METHODS: This study examined a cohort of adults with real-time polymerase chain reaction-confirmed COVID-19 admitted to 156 ICUs in 35 hospitals from February 16, 2020, through December 31, 2021, in Brazil. We evaluated crude and adjusted in-hospital mortality variability of patients with COVID-19 in the ICU during the pandemic. Association of baseline (prepandemic) ICU performance and in-hospital mortality was examined using a variable life-adjusted display (VLAD) during the pandemic and a multivariable mixed regression model adjusted by clinical characteristics, interaction of performance with the year of admission, and mechanical ventilation at admission. RESULTS: Thirty-five thousand six hundred nineteen patients with confirmed COVID-19 were evaluated. The median age was 52 years, median Simplified Acute Physiology Score 3 was 42, and 18% underwent invasive mechanical ventilation. In-hospital mortality was 13% and 54% for those receiving invasive mechanical ventilation. Adjusted in-hospital mortality ranged from 3.6% to 63.2%. VLAD in the most efficient ICUs was higher than the overall median in 18% of weeks, whereas VLAD was 62% and 84% in the underachieving and least efficient groups, respectively. The least efficient baseline ICU performance group was associated independently with increased mortality (OR, 2.30; 95% CI, 1.45-3.62) after adjusting for patient characteristics, disease severity, and pandemic surge. INTERPRETATION: ICUs caring for patients with COVID-19 presented substantial variation in risk-adjusted mortality. ICUs with better baseline (prepandemic) performance showed reduced mortality and less variability. Our findings suggest that achieving ICU efficiency by targeting improvement in organizational aspects of ICUs may impact outcomes, and therefore should be a part of the preparedness for future pandemics.

Development and validation of a machine learning model to predict the use of renal replacement therapy in 14,374 patients with COVID-19.

PURPOSE: To develop a model to predict the use of renal replacement therapy (RRT) in COVID-19 patients. MATERIALS AND METHODS: Retrospective analysis of multicenter cohort of intensive care unit (ICU) admissions of Brazil involving COVID-19 critically adult patients, requiring ventilatory support, admitted to 126 Brazilian ICUs, from February 2020 to December 2021 (development) and January to May 2022 (validation). No interventions were performed. RESULTS: Eight machine learning models' classifications were evaluated. Models were developed using an 80/20 testing/train split ratio and cross-validation. Thirteen candidate predictors were selected using the Recursive Feature Elimination (RFE) algorithm. Discrimination and calibration were assessed. Temporal validation was performed using data from 2022. Of 14,374 COVID-19 patients with initial respiratory support, 1924 (13%) required RRT. RRT patients were older (65 [53-75] vs. 55 [42-68]), had more comorbidities (Charlson's Comorbidity Index 1.0 [0.00-2.00] vs 0.0 [0.00-1.00]), had higher severity (SAPS-3 median: 61 [51-74] vs 48 [41-58]), and had higher in-hospital mortality (71% vs 22%) compared to non-RRT. Risk factors for RRT, such as Creatinine, Glasgow Coma Scale, Urea, Invasive Mechanical Ventilation, Age, Chronic Kidney Disease, Platelets count, Vasopressors, Noninvasive Ventilation, Hypertension, Diabetes, modified frailty index (mFI) and Gender, were identified. The best discrimination and calibration were found in the Random Forest (AUC [95%CI]: 0.78 [0.75-0.81] and Brier's Score: 0.09 [95%CI: 0.08-0.10]). The final model (Random Forest) showed comparable performance in the temporal validation (AUC [95%CI]: 0.79 [0.75-0.84] and Brier's Score, 0.08 [95%CI: 0.08-0.1]). CONCLUSIONS: An early ML model using easily available clinical and laboratory data accurately predicted the use of RRT in critically ill patients with COVID-19. Our study demonstrates that using ML techniques is feasible to provide early prediction of use of RRT in COVID-19 patients.

National ICU Registries as Enablers of Clinical Research and Quality Improvement.

OBJECTIVES: Clinical quality registries (CQRs) have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. This narrative review describes the challenges, proposed solutions, and evidence generated by National ICU registries as facilitators for research and quality improvement. DATA SOURCES: English language articles were identified in PubMed using phrases related to ICU registries, CQRs, outcomes, and case-mix. STUDY SELECTION: Original research, review articles, letters, and commentaries, were considered. DATA EXTRACTION: Data from relevant literature were identified, reviewed, and integrated into a concise narrative review. DATA SYNTHESIS: CQRs have been implemented worldwide by several medical specialties aiming to generate a better characterization of epidemiology, treatments, and outcomes of patients. National ICU registries were created almost 3 decades ago to improve the understanding of case-mix, resource use, and outcomes of critically ill patients. The initial experience in European countries and in Oceania ensured that through locally generated data, ICUs could assess their performances by using risk-adjusted measures and compare their results through fair and validated benchmarking metrics with other ICUs contributing to the CQR. The accomplishment of these initiatives, coupled with the increasing adoption of information technology, resulted in a broad geographic expansion of CQRs as well as their use in quality improvement studies, clinical trials as well as international comparisons, and benchmarking for ICUs. CONCLUSIONS: ICU registries have provided increased knowledge of case-mix and outcomes of ICU patients based on real-world data and contributed to improve care delivery through quality improvement initiatives and trials. Recent increases in adoption of new technologies (i.e., cloud-based structures, artificial intelligence, machine learning) will ensure a broader and better use of data for epidemiology, healthcare policies, quality improvement, and clinical trials.

ICU registries: From tracking to fostering better outcomes.

NA.

Subsyndromal Delirium in Critically Ill Patients-Cognitive and Functional Long-Term Outcomes.

Subsyndromal delirium (SSD) in the Intensive Care Unit (ICU) is associated with an increased morbidity with unknown post-discharge functional and cognitive outcomes. We performed a prospective multicenter study to analyze the mental status of patients during their first 72 h after ICU admission and its trajectory, with follow-ups at 3 and 6 months after hospital discharge. Amongst the 106 included patients, SSD occurred in 24.5% (n = 26) and was associated with the duration of mechanical ventilation (p = 0.003) and the length of the ICU stay (p = 0.002). After the initial 72 h, most of the SSD patients (30.8%) improved and no longer had SSD; 19.2% continued to experience SSD and one patient (3.8%) progressed to delirium. The post-hospital discharge survival rate for the SSD patients was 100% at 3 months and 87.5% at 6 months. At admission, 96.2% of the SSD patients were fully independent in daily living activities, 66.7% at 3-month follow-up, and 100% at 6-month follow-up. Most SSD patients demonstrated a cognitive decline from admission to 3-month follow-up and improved at 6 months (IQCODE-SF: admission 3.13, p < 0.001; 3 months 3.41, p = 0.019; 6 months 3.19, p = 0.194). We concluded that early SSD is associated with worse outcomes, mainly a transitory cognitive decline after hospital discharge at 3 months, with an improvement at 6 months. This highlights the need to prevent and identify this condition during ICU stays.

Trends in Intensive Care Admissions and Outcomes of Stroke Patients Over 10 Years in Brazil: Impact of the COVID-19 Pandemic.

BACKGROUND: The coronavirus 2019 (COVID-19) pandemic affected stroke care worldwide. Data from low- and middle-income countries are limited. RESEARCH QUESTION: What was the impact of the pandemic in ICU admissions and outcomes of patients with stroke, in comparison with trends over the last 10 years? STUDY DESIGN AND METHODS: Retrospective cohort study including prospectively collected data from 165 ICUs in Brazil between 2011 and 2020. We analyzed clinical characteristics and mortality over a period of 10 years and evaluated the impact of the pandemic on stroke outcomes, using the following approach: analyses of admissions for ischemic and hemorrhagic strokes and trends in in-hospital mortality over 10 years; analysis of variable life-adjusted display (VLAD) during 2020; and a mixed-effects multivariable logistic regression model. RESULTS: A total of 17,115 stroke admissions were analyzed, from which 13,634 were ischemic and 3,481 were hemorrhagic. In-hospital mortality was lower after ischemic stroke as compared with hemorrhagic (9% vs 24%, respectively). Changes in VLAD across epidemiological weeks of 2020 showed that the rise in COVID-19 cases was accompanied by increased mortality, mainly after ischemic stroke. In logistic regression mixed models, mortality was higher in 2020 compared with 2019, 2018, and 2017 in patients with ischemic stroke, namely, in those without altered mental status. In hemorrhagic stroke, the increased mortality in 2020 was observed in patients 50 years of age or younger, as compared with 2019. INTERPRETATION: Hospital outcomes of stroke admissions worsened during the COVID-19 pandemic, interrupting a trend of improvements in survival rates over 10 years. This effect was more pronounced during the surge of COVID-19 ICU admissions affecting predominantly patients with ischemic stroke without coma, and young patients with hemorrhagic stroke.

Impact of Subsyndromal Delirium Occurrence and Its Trajectory during ICU Stay.

Despite recent advances in the field, the association between subsyndromal delirium (SSD) in the ICU and poor outcomes is not entirely clear. We performed a retrospective multicentric observational study analyzing mental status during the first 72 h of ICU stay. Of the 681 patients included, SSD occurred in 22.7%. Considering the worst cognitive assessment during the first 72 h, 233 (34%) patients had normal mental status, 124 (18%) patients had SSD and 324 (48%) patients had delirium or coma. SSD was not independently associated with an increased risk of death when compared with normal mental status (OR 95%IC 1.0 vs. 1.35 [0.73−1.49], p = 0.340), but was associated with a longer ICU LOS (7.0 (4−12) vs. 4 (3−8) days, p < 0.001). SSD patients who deteriorated to delirium or coma (21%) had a longer ICU LOS in comparison with those who improved or maintained mental status (8 (5−11) vs. 6 (4−8) days, p = 0.025), but did not have an increase in mortality. The main factors associated with the progression from SSD to delirium or coma were the use of mechanical ventilation, the use of intravenous benzodiazepines and a baseline APACHE II score > 23 points. Our findings support the association of SSD with increased ICU LOS, but not with ICU mortality. Monitoring the trajectory of SSD early at ICU admission can help to identify patients with increased risk of conversion from SSD to delirium or coma.