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Ability to identify patient-ventilator asynchronies in intensive care unit professionals: A multicenter cross-sectional analytical study

Andrés Mauricio Enríquez Popayán1, Iván Ignacio Ramírez2, Juan Felipe Zúñiga3, Ruvistay Gutierrez-Arias4, Mayda Alejandra Jiménez Pérez5, Henry Mauricio Parada-Gereda6, Luis Fernando Pardo Cocuy7, Ana Lucia Rangel Colmenares8, Nubia Castro Chaparro9, Ana Pinza Ortega10, Jorge Martínez Díaz11, Johanna Hurtado Laverde12, Joismer Alejandro Henao Cruz13

1 Departamento de Fisioterapia en Cuidado Intensivo, GyO Medical, Yopal, Colombia; Departamento de Fisioterapia en Cuidado Intensivo, Clínica SIMALINK, Yopal, Colombia
2 Departamento de Apoyo en Rehabilitación Cardiopulmonar Integral, Instituto Nacional del Tórax, Santiago, Chile; INTRehab Research Group, Instituto Nacional del Tórax, Santiago, Chile; Escuela de Kinesiología, Facultad de Ciencias de la Salud, Universidad Diego Portales, Santiago, Chile
3 Departamento de Fisioterapia en Cuidado Intensivo, Clínica de Occidente, Cali, Colombia
4 Departamento de Apoyo en Rehabilitación Cardiopulmonar Integral, Instituto Nacional del Tórax, Santiago, Chile; INTRehab Research Group, Instituto Nacional del Tórax, Santiago, Chile; Exercise and Rehabilitation Sciences Institute, Faculty of Rehabilitation Sciences, Universidad Andres Bello, Santiago, Chile
5 Departamento de Fisioterapia en Cuidado Intensivo, Fundación Hospital San Pedro, Pasto, Colombia
6 Unidad de Cuidado Intensivo, Clínica Reina Sofia, Bogotá, Colombia; Clínica Colsanitas, Grupo de Investigación en Nutrición Clínica y Rehabilitación-Keralty, Bogotá, Colombia. ???Especialización de Fisioterapia en Paciente Adulto Critico, Universidad del Rosario, Bogotá, Colombia.
7 Departamento de Fisioterapia en Cuidado Intensivo, Hospital Universitario Mayor Méderi, Bogotá, Colombia; Especialización de Fisioterapia en Paciente Adulto Critico, Universidad del Rosario, Bogotá, Colombia.
8 Departamento de Fisioterapia en Cuidado Intensivo, Clínica Norte, Cúcuta, Colombia; Departamento de Fisioterapia en Cuidado Intensivo, Clínica San José, Cúcuta, Colombia
9 Departamento de Cuidado Intensivo, Lumira SAS, Cali, Colombia
10 Departamento de Fisioterapia en Cuidado Intensivo, Fundación Hospital San Pedro, Pasto, Colombia; Programa de Fisioterapia, Universidad Mariana, Pasto, Colombia; Grupo de Investigación en Medicina Critica GMC, Fundación Hospital San Pedro, Pasto, Colombia
11 Departamento de Cuidado Intensivo, Fundación Hospital San Pedro, Pasto, Colombia; Programa de Medicina, Fundación Universidad San Martin, Pasto, Colombia; Grupo de Investigación en Medicina Critica GMC, Fundación Hospital San Pedro, Pasto, Colombia
12 Programa de Terapia Respiratoria, Universidad Manuela Beltrán, Bogotá, Colombia
13 Departamento de Fisioterapia en Cuidado Intensivo, Hospital Universitario de Caldas, Manizales, Colombia

DOI: 10.2478/jccm-2025-0017

Introduction: Patient-ventilator asynchrony (PVA) is frequent in intensive care. Its presence is associated with prolonged days of mechanical ventilation and may lead to increased mortality in the intensive care unit (ICU) and hospital. Little is known about the ability of Colombian intensive care professionals to identify asynchronies, and the factors associated with their correct identification are not apparent.
Aim of the study: To describe the ability of Colombian intensive care professionals to identify patient-ventilator asynchronies (PVA) using waveform analysis. In addition, to define the characteristics associated with correctly detecting PVA.
Material and methods: We conducted a multicenter, cross-sectional, national survey-based study between January and August 2024. Colombian physiotherapists, respiratory therapists, nurses and intensive care physicians from 24 departments participated in the study. An online survey was used. They were asked to identify six different PVAs presented as videos. The videos were displayed using pressure/time and flow/time waveform of a Puritan Bennett 840 ventilator.
Results: We recruited 900 participants, 60% female, most of whom were physiotherapists (53%). Most professionals had specialty training in critical care (42%), and 32% reported having specific PVA training. Double triggering was the most frequently identified PVA (75%). However, only 3.67% of participants recognized all six PVAs. According to multiple logistic regression analysis, working in a mixed unit (OR 2.59; 95% CI 1.19 – 5.54), caring for neonates (OR 5.19; 95% CI 1.77 – 15.20), and having specific training (OR 2.38; 95% CI 1.16 – 4.76) increases the chance of correctly recognizing all PVAs.
Conclusion: In Colombia, a low percentage of professionals recognize all PVAs. Having specific training in this topic, working in mixed ICUs and neonatal intensive care was significantly associated with identifying all PVAs.

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Latent class analysis for identification of sub-phenotypes predicting prognosis in hospitalized out-of-hospital cardiac arrest

Yuki Kishihara1, Hideto Yasuda1–4, Masahiro Kashiura1, Shunsuke Amagasa5, Hiroyuki Tamura1, Yutaro Shinzato1, Takashi Moriya1

1 Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
2 Department of Clinical Research Education and Training Unit, Keio University Hospital Clinical and Translational Research Center, Tokyo, Japan
3 School of Nursing, Midwifery and Social Work, UQ Centre for Clinical Research, The University of Queensland, Australia
4 School of Nursing and Midwifery; Alliance for Vascular Access Teaching and Research, Griffith University, Australia
5 Department of Emergency and Transport Medicine, National Center for Child Health and Development, Tokyo, Japan

DOI: 10.2478/jccm-2025-0016

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.

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Use of prone position in spontaneous breathing in patients with COVID-19

Rodrigo Cerqueira Borges1, Isadora Salvador Rocco2, Camila Botana Alves Ferreira1, Mauricio Kenzo Tobara1, Cristiane Helena Papacidero1, Vanessa Chaves Barreto Ferreira1, Andrey Wirgues Sousa1

1 Hospital Samaritano Higienópolis, São Paulo, Brazil
2 Universidade Federal de Sao Paulo, Brazil

DOI: 10.2478/jccm-2025-0015

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.

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The effect of antiseizure medication on mortality in spontaneous aneurysmal subarachnoid hemorrhage

John Harold Kanter, Adam C. Glaser, Pablo Martinez-Camblor, Jakob V.E. Gerstl, Anna B. Lebouille-Veldman, Harshit Arora, Lauren Buhl, Myles D. Boone, Christopher S. Ogilvy

1 Department of Neurological Surgery, University of California, San Francisco, California; Brain and Spinal Injury Center, Zuckerberg San Francisco General Hospital, San Francisco, California, USA
2 Department of Neurological Surgery, Brigham and Women’s Hospital, Harvard Medical School Department of Neurological Surgery, Boston Children’s Hospital, USA
3 Department of Anesthesiology, Dartmouth Health Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Dartmouth Hitchcock Medical Center, USA
4 Department of Neurosurgery, Computational Neuroscience Outcomes Center, Brigham and Women’s Hospital, Boston, USA
5 Department of Neurosurgery, Computational Neuroscience Outcomes Center, Brigham and Women’s Hospital, Boston, USA; Department of Neurosurgery, Leiden University Medical Center, Leiden, The Netherlands
6 Department of Neurosurgery, Computational Neuroscience Outcomes Center, Brigham and Women’s Hospital, Boston, USA. Department of Neurosurgery, University of Kentucky, Lexington, KY, USA
7 Department of Anesthesiology, Dartmouth Health, Dartmouth Hitchcock Medical Center, USA
8 Department of Anesthesiology, Dartmouth Health Department of Neurology, Dartmouth Health, Dartmouth Hitchcock Medical Center, USA
9 Neurosurgical Service, BIDMC Brain Aneurysm Institute, Harvard Medical School, Beth Israel Deaconess Medical Center, USA

DOI: 10.2478/jccm-2025-0014

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.

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Management strategies and outcomes predictors of interstitial lung disease exacerbation admitted to an intensive care setting: A narrative review

Ans Alamami

Department of Critical Care Medicine, Hamad General Hospital, Doha, Qatar

DOI: 10.2478/jccm-2025-0013

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.

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Poor clinical outcomes among hospitalized obese patients with COVID-19 are related to inflammation and not respiratory mechanics

Jordan N Edwards, Tomas Ganz, Elizabeta Nemeth, Emily J Martin, Nicholas J Jackson, Airie Kim

David Geffen School of Medicine, University of California Los Angeles, CA, USA

DOI: 10.2478/jccm-2025-0012

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.

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The implementation gap in critical care: From nutrition to ventilation

Razvan Azamfirei

Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA

DOI: 10.2478/jccm-2025-0011

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]

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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

Fabio Varón-Vega1,2, Eduardo Tuta-Quintero1,2,3, Adriana Maldonado-Franco3, Henry Robayo-Amórtegui3, Luis F Giraldo-Cadavid1,3, Daniel Botero-Rosas3

1 Fundación Neumológica Colombiana, Bogotá, Colombia
2 Fundación Cardioinfantil Instituto de Cardiología, Bogotá, Colombia
3 Universidad de La Sabana, Chía, Colombia

DOI: 10.2478/jccm-2025-0009

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.

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Choking and laryngospasm: Exploring commonalities and treatment strategies

Gad Estis1, Asia Estis-Deaton2, Tiberiu Ezri3

1 Herzliya Medical Center, Herzliya, Israel
2 Assuta Ashdod Hospital, Ashdod, Israel
3 Kaplan Medical Center, Rehovot, Israel

DOI: 10.2478/jccm-2025-0010

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]

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