Aim of the study: To determine which out-of-hospital cardiac arrest (OHCA) patients should receive advanced treatment is extremely challenging. The objective was to identify sub-phenotypes predicting the prognoses of adult OHCA patients by latent class analysis (LCA) using data up to just after admission.
Material and Methods: We conducted a retrospective observational study using multicentre OHCA registry from 95 Japanese hospitals including adult non-traumatic hospitalized OHCA. The primary outcome was 30-day favourable neurological outcome. Our LCA used clinically relevant variables up to just after admission and the optimal class number was determined from clinical importance and Bayesian information criterion. The associations between sub-phenotypes and outcomes were analysed using univariate logistic regression analysis with odds ratios (ORs) and 95% confidence intervals (CIs).
Results: Our LCA included 2,162 patients and identified four sub-phenotypes. The base excess on hospital arrival had the highest discriminative power. Thirty-day favourable neurological outcomes were observed in 526 patients (24.3%), including 284 (53.8%) in Group 1, 179 (21.2%) in Group 2, 26 (11.4%) in Group 3, and 37 (6.6%) in Group 4. Prehospital return of spontaneous circulation (ROSC) was achieved in 1,009 patients (46.7%), including 379 (81.8%) in Group 1, 340 (40.3%) in Group 2, 115 (50.4%) in Group 3, and 175 (31.1%) in Group 4. Univariate logistic regression analysis for primary outcome using Group 4 as reference revealed ORs (95% CI) of 16.5 (11.4–24.1) in Group 1, 3.83 (2.64–5.56) in Group 2, and 1.83 (1.08–3.10) in Group 3.
Conclusions: Our LCA classified OHCA into four sub-phenotypes showing significant differences for prognosis. In cases who achieved prehospital ROSC, it might be meaningful to continue advanced therapeutic interventions.
Author Archives: administrare
Use of prone position in spontaneous breathing in patients with COVID-19
Objective: To investigate if awake prone position (PP) reduces the rate of endotracheal intubation and mortality in patients with COVID-19 admitted to the intensive care unit (ICU).
Methods: This was a retrospective cohort study of 726 patients who were admitted to the ICU with acute hypoxic respiratory failure secondary to COVID-19. The protocol of the institution recommended the use of awake PP in patients with nasal catheter with an oxygen flow ≥ 5 L/min and SpO2 ≤ 90% or a high-flow nasal catheter (HFNC) with FiO2 ≥ 50% and SpO2 ≤ 90%. The following data were collected: age, comorbidities, SAPS-3 score, onset of symptoms, the degree of pulmonary involvement, duration of invasive and noninvasive MV, HFNC therapy, nitric oxide therapy, hemodialysis and PP while spontaneously breathing.
Results: There was a higher mortality rate in the supine position group (27.1%) than in the awake PP group (13.9%). There was no significant difference in the time on MV or number of patients on MV (p>0.05). The variables with p < 0.05 in the bivariate analysis were entered into the Cox regression model. The model was adjusted for awake PP, sex, age, SAPS-3 score, onset of symptoms, the degree of pulmonary involvement, chronic arterial disease, and noninvasive ventilation. The only variable associated with lower mortality over time was awake PP (hazard ratio: 0.55; 95% confidence interval: 0.33-0.92).
Conclusion: Awake prone position has been shown to be a safe and effective therapy that reduced mortality but not the risk of intubation in patients with COVID-19.
The effect of antiseizure medication on mortality in spontaneous aneurysmal subarachnoid hemorrhage
Background: Spontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a major cause of morbidity and mortality in the United States. The efficacy of early antiseizure medication (ASM) is debated. Recent literature reports seizure rates ranging from 7.8% to 15.2% following spontaneous aSAH. Current guidelines recommend use of early ASM in patients with “high-risk features,” but whether early ASM use decreases the rate of death associated with aSAH remains unclear. This study assessed whether early administration of early ASM impacts mortality rates after spontaneous aSAH.
Methods: We conducted a retrospective cohort study using a publicly available dataset from the Massachusetts Institute of Technology, Medical Information Mart for Intensive Care-III (MIMIC) database of all patients over the age of 18 with spontaneous aSAH resulting in an intensive care unit (ICU) admission to a major United States trauma center from 2001 to 2012. The primary exposure was receiving early ASM and primary outcome of death within 7 days. Different regression models were created to explore the association between early ASM administration within 24 hours of admission and a composite outcome of seizure and/or death within 7 days of admission. Secondary outcomes included 30-day and one-year mortality.
Results: Of 253 patients with spontaneous aSAH, 148 received early ASM within 24 hours. Patients who did receive early ASM were less likely to die within 7 days of admission (adjusted odd ratio, [aOR]: 0.26 95% CI 0.10 to 0.68; P=0.006) but were more likely to have a seizure (aOR: 7.63 95% CI 2.07 to 28.17; P=0.002).
Conclusion: Early ASM administration was associated with lower rates of death and composite death/seizure within 7 days of admission among patients who presented to an ICU with spontaneous aSAH. These findings suggest broader use of early ASM in patients who present with spontaneous aSAH may improve early mortality.
Management strategies and outcomes predictors of interstitial lung disease exacerbation admitted to an intensive care setting: A narrative review
Background: Interstitial lung disease (ILD) is a cluster of diseases that affect the lungs, characterized by different degrees of inflammation and fibrosis within the parenchyma. In the intensive care unit (ICU), ILD poses substantial challenges because of its complicated nature and high morbidity and mortality rates in severe cases. ILD pathophysiology frequently entails persistent inflammation that results in fibrosis, disrupting the typical structure and function of the lung. Patients with ILD frequently experience dyspnea, non-productive cough, and tiredness. In the ICU setting, these symptoms may worsen and lead to signs of acute respiratory failure with significantly impaired gas physiology.
Methodology: A systematic search was conducted in reputable databases, including PubMed, Google Scholar, and Embase. To ensure a comprehensive search, a combination of keywords such as “interstitial lung disease,” “intensive care,” and “outcomes” was used. Studies published within the last ten years reporting on the outcomes of ILD patients admitted to intensive care included.
Result: Effective management of ILD in an ICU setting is challenging and requires a comprehensive approach to address the triggering factor and providing respiratory support, Hypoxemia severity is a critical predictor of mortality, with lower PaO2/FiO2 ratios during the first three days of ICU admission associated with increased mortality rates. The need for mechanical ventilation, particularly invasive mechanical ventilation (IMV), is a significant predictor of poor outcomes in ILD patients. Additionally, higher positive end-expiratory pressure (PEEP) settings, and severity of illness scores, such as the Acute Physiology and Chronic Health Evaluation (APACHE) score, are also linked to increased mortality. Other poor prognostic factors include the presence of shock and pulmonary fibrosis on computed tomography (CT) images. Among the various types of ILDs, idiopathic pulmonary fibrosis (IPF) is associated with the highest mortality rate. Furthermore, a high ventilatory ratio (VR) within 24 hours after intubation independently predicts ICU mortality.
Conclusion: This literature review points out outcome predictors of interstitial lung disease in intensive care units, which are mainly hypoxemia, the severity of the illness, invasive ventilation, the presence of shock, and the extent of fibrosis on CT Images.
Poor clinical outcomes among hospitalized obese patients with COVID-19 are related to inflammation and not respiratory mechanics
Introduction: The coronavirus disease 2019 (COVID-19) has infected millions of people worldwide resulting in high morbidity and mortality. Obesity is known to cause metabolic derangements and precipitate worse outcomes from viral pneumonia, potentially secondary to increased inflammation and/or altered respiratory mechanics.
Aim of the Study: Our study’s aim was to examine the relationships among BMI, systemic inflammation, and respiratory mechanics in determining clinical outcomes.
Materials and Methods: This retrospective, observational cohort study included 199 adult patients with confirmed COVID-19 who were hospitalized at a quaternary-referral academic health system. Data were manually extracted from electronic medical records, including baseline demographics and clinical profiles, inflammatory markers, measures of respiratory mechanics, and clinical outcomes. We used the rank-sum test to compare the distributions of BMI and inflammatory markers between those with and without specific clinical outcomes, and the Pearson correlation to measure the correlations between BMI and inflammatory markers or respiratory mechanics.
Results: Higher BMI was associated with worse clinical outcomes, including the need for Intensive Care Unit (ICU) admission, invasive mechanical ventilation (IMV), neuromuscular blockade, and prone positioning, particularly in male patients. Inflammation, as measured by C-reactive protein, lactate dehydrogenase (LDH), ferritin, and D-Dimer, was also increased in both male and female patients who required ICU admission, IMV, neuromuscular blockade, and prone positioning. However, only male patients had a positive correlation of LDH and D-Dimer levels with BMI. There was no correlation between BMI and respiratory mechanics, as measured by static compliance and the response to prone positioning.
Conclusions: Our findings suggest that the metabolic dysfunction and systemic inflammation seen in obesity, and not dysfunctional respiratory physiology, drive the negative clinical outcomes seen in this cohort of hospitalized COVID-19 patients.
The implementation gap in critical care: From nutrition to ventilation
Critical care medicine pushes boundaries. We talk about personalized medicine and wax poetic on sophisticated trial design, all while debating using diaphragmatic ultrasound for ventilator weaning. Our excitement about the latest mechanical circulatory support device or novel vasopressor is matched only by the rush to share the latest “groundbreaking” meta-analysis – inevitably analyzing the same five trials as the last one, just with a different statistical twist. None of this is to say that such discussions do not have merit. But our fascination with tomorrow’s breakthroughs disguises a more fundamental challenge: we consistently fail to deliver basic, routine care at the bedside.[More]
Volume 11, Issue 1, January 2025
Machine learning to predict extubation success using the spontaneous breathing trial, objective cough measurement, and diaphragmatic contraction velocity: Secondary analysis of the COBRE-US trial
Introduction: Determining the optimal timing for extubation in critically ill patients is essential to prevent complications. Predictive models based on Machine Learning (ML) have proven effective in anticipating weaning success, thereby improving clinical outcomes.
Aim of the study: The study aimed to evaluate the predictive capacity of five ML techniques, both supervised and unsupervised, applied to the spontaneous breathing trial (SBT), objective cough measurement (OCM), and diaphragmatic contraction velocity (DCV) to estimate a favorable outcome of SBT and extubation in critically ill patients.
Material and Methods: A post hoc analysis conducted on the COBRE-US study. The study included ICU patients who underwent evaluation of SBT, OCM, and DCV. Five ML techniques were applied: unsupervised and supervised to the data in both a training group and a test group. The diagnostic performance of each method was determined using accuracy.
Results: In predicting SBT success, all supervised methods displayed the same accuracy in the training group (77.3%) and in the test group (69.6%). In predicting extubation success, decision trees demonstrated the highest diagnostic accuracy, 89.8% for the training group and 95.7% for the test group. The other supervised methods also showed a good diagnostic accuracy: 85.9% for the training group and 93.5% for the test group.
Conclusions: In predictive models using OCM, DCV, and SBT as input variables through five ML techniques, decision trees and artificial neural networks demonstrated the best diagnostic performance. This suggests that these models can effectively classify patients who are likely to succeed in SBT and extubation during the weaning process from mechanical ventilation.
Choking and laryngospasm: Exploring commonalities and treatment strategies
Choking is a significant health concern associated with substantial morbidity and mortality. Despite ongoing efforts, an optimal solution remains elusive. We propose that this may stem from an overemphasis on mechanical obstruction as the primary cause. Notably, a foreign body does not always completely occlude the airway. For instance, Saccomanno et al. reported that fish bones were implicated in 67% of choking incidents [1], suggesting that defensive airway reflexes may play a critical role beyond mere mechanical obstruction. [More]
Risk factors and outcomes of critically ill pregnant COVID-19 patients: Experience from the first and second waves of the pandemic
Introduction: Understanding the association between risk factors and clinical outcomes of COVID-19 can lead to identifying suitable management strategies for reducing the mortality rate among maternal COVID-19 patients in the ICU.
Aim of the Study: This study aims to investigate the clinical outcomes and risk factors associated with pregnant and postpartum women diagnosed with COVID-19 and admitted to the intensive care unit (ICU) between May 2020 and September 2021.
Materials and Methods: This retrospective cohort study was conducted at the Universitas Indonesia Hospital. Secondary data was collected from the medical records to include all pregnant and postpartum women diagnosed with confirmed COVID-19 admitted to the hospital during the research period.
Results: The study included 113 patients and found that admission to the ICU, age, and gestational age significantly influenced clinical outcomes, with a mortality rate of 42.11% among ICU-admitted patients. Pre-existing comorbidities such as type-2 diabetes mellitus, congestive heart failure, and coronary artery disease were associated with ICU admission. Having at least one comorbidity was found to increase the mortality rate by six-fold.
Conclusions: The study emphasizes the importance of monitoring and evaluating maternal and fetal complications during COVID-19 infection, highlighting the need for multidisciplinary management involving intensivists, obstetricians, anesthesiologists, and infectious disease specialists. The findings underscore the significance of baseline health status in treatment planning and the potential for evidence-based interventions to improve maternal outcomes and pregnancy preservation. Further research is warranted to validate these results and enhance understanding of the underlying pathophysiology.