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Gutiérrez L, Araya K, Becerra M, Pérez C, Valenzuela J, Lera L, Lizana PA, Del Sol M, Muñoz-Cofré R. Predictive value of invasive mechanical ventilation parameters for mortality in COVID-19 related ARDS: a retrospective cohort study. Sci Rep 2024; 14:13725. [PMID: 38877186 PMCID: PMC11178920 DOI: 10.1038/s41598-024-64725-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 06/12/2024] [Indexed: 06/16/2024] Open
Abstract
The 2019 coronavirus (COVID-19) can generate acute respiratory distress syndrome (ARDS), requiring advanced management within the Intensive Care Unit (ICU) using invasive mechanical ventilation (IMV However, managing this phenomenon has seen learning and improvements through direct experience. Therefore, this study aims were to describe the assessment of the different IMV variables in patients with post-COVID-19 hospitalized in the ICU and their relation with mortality. Observational and retrospective study. The sample was divided into two, the surviving group (SG) and the non-surviving group (NSG). Clinical data were extracted from the electronic clinical file and the respiratory therapist record sheet. The following information was obtained: Patient medical history: gender, age, co-morbidities, arterial gases, days on IMV, and IMV parameters. Out of a total of 101 patients, the total mortality was 32%. There was a significant decrease in respiratory rate (RR) (29.12 ± 4.24-26.78 ± 3.59, p = 0.006), Driving pressure (DP) (11.33 ± 2.39-9.67 ± 1.84, p = 0.002), Ventilatory rate (VR) (2.26 ± 0.66-1.89 ± 0.45, p = 0.001) and a significant rise in Static compliance (Cest) (35.49 ± 8.64-41.45 ± 9.62, p = 0.003) and relation between Arterial oxygen pressure/Inspirated oxygen fraction (PaO2/FiO2) (201.5 ± 53.98- 227.8 ± 52.11, p = 0.008) after 72 h of IMV, within the NSG compared to the SG. Apart from these points, multi-morbidity (HR = 3.208, p = 0.010) and DP (HR = 1.228, p = 0.030) and VR variables (HR = 2.267, p = 0.027) had more death probabilities. The results of this study indicate that there was a significant increase in RR, DP, VR, and CO2 and a significant drop in Cest and PaO2/FiO2 among the NSG compared with the SG. Apart from this, the DP and VR variables, multi-morbidity and being male. have more possibility of death.
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Affiliation(s)
- Luis Gutiérrez
- Servicio de Medicina Física y Rehabilitación, Hospital El Carmen de Maipú, Camino A Rinconada 1201, Santiago, Chile.
| | - Karina Araya
- Servicio de Medicina Física y Rehabilitación, Hospital El Carmen de Maipú, Camino A Rinconada 1201, Santiago, Chile
| | - Mara Becerra
- Servicio de Medicina Física y Rehabilitación, Hospital El Carmen de Maipú, Camino A Rinconada 1201, Santiago, Chile
| | - Camilo Pérez
- Servicio de Medicina Física y Rehabilitación, Hospital El Carmen de Maipú, Camino A Rinconada 1201, Santiago, Chile
| | - Jorge Valenzuela
- Servicio de Medicina Física y Rehabilitación, Hospital El Carmen de Maipú, Camino A Rinconada 1201, Santiago, Chile
| | - Lydia Lera
- Latin Division, Keiser University eCampus, Fort Lauderdale, FL, USA
| | - Pablo A Lizana
- Laboratory of Epidemiology and Morphological Sciences, Instituto de Biología, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
| | - Mariano Del Sol
- Programa de Doctorado en Ciencias Morfológicas, Universidad de La Frontera, Temuco, Chile
| | - Rodrigo Muñoz-Cofré
- Programa de Doctorado en Ciencias Morfológicas, Universidad de La Frontera, Temuco, Chile
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Fumagalli J, Pesenti A. Ventilation during extracorporeal gas exchange in acute respiratory distress syndrome. Curr Opin Crit Care 2024; 30:69-75. [PMID: 38085872 PMCID: PMC10919266 DOI: 10.1097/mcc.0000000000001125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
PURPOSE OF REVIEW Accumulating evidence ascribes the benefit of extracorporeal gas exchange, at least in most severe cases, to the provision of a lung healing environment through the mitigation of ventilator-induced lung injury (VILI) risk. In spite of pretty homogeneous criteria for extracorporeal gas exchange application (according to the degree of hypoxemia/hypercapnia), ventilatory management during extracorporeal membrane oxygenation (ECMO)/carbon dioxide removal (ECCO 2 R) varies across centers. Here we summarize the recent evidence regarding the management of mechanical ventilation during extracorporeal gas exchange for respiratory support. RECENT FINDINGS At present, the most common approach to protect the native lung against VILI following ECMO initiation involves lowering tidal volume and driving pressure, making modest reductions in respiratory rate, while typically maintaining positive end-expiratory pressure levels unchanged.Regarding ECCO 2 R treatment, higher efficiency devices are required in order to reduce significantly respiratory rate and/or tidal volume. SUMMARY The best compromise between reduction of native lung ventilatory load, extracorporeal gas exchange efficiency, and strategies to preserve lung aeration deserves further investigation.
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Affiliation(s)
- Jacopo Fumagalli
- Department of Anesthesia, Critical Care and Emergency, Fondazione Istituto di Ricovero e cura a Carattere Scientifico Ca’ Granda Ospedale Maggiore Policlinico
| | - Antonio Pesenti
- Department of Anesthesia, Critical Care and Emergency, Fondazione Istituto di Ricovero e cura a Carattere Scientifico Ca’ Granda Ospedale Maggiore Policlinico
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
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Li M, Liu F, Yang Y, Lao J, Yin C, Wu Y, Yuan Z, Wei Y, Tang F. Identifying vital sign trajectories to predict 28-day mortality of critically ill elderly patients with acute respiratory distress syndrome. Respir Res 2024; 25:8. [PMID: 38178157 PMCID: PMC10765902 DOI: 10.1186/s12931-023-02643-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 12/18/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND The mortality rate of acute respiratory distress syndrome (ARDS) increases with age (≥ 65 years old) in critically ill patients, and it is necessary to prevent mortality in elderly patients with ARDS in the intensive care unit (ICU). Among the potential risk factors, dynamic subphenotypes of respiratory rate (RR), heart rate (HR), and respiratory rate-oxygenation (ROX) and their associations with 28-day mortality have not been clearly explored. METHODS Based on the eICU Collaborative Research Database (eICU-CRD), this study used a group-based trajectory model to identify longitudinal subphenotypes of RR, HR, and ROX during the first 72 h of ICU stays. A logistic model was used to evaluate the associations of trajectories with 28-day mortality considering the group with the lowest rate of mortality as a reference. Restricted cubic spline was used to quantify linear and nonlinear effects of static RR-related factors during the first 72 h of ICU stays on 28-day mortality. Receiver operating characteristic (ROC) curves were used to assess the prediction models with the Delong test. RESULTS A total of 938 critically ill elderly patients with ARDS were involved with five and 5 trajectories of RR and HR, respectively. A total of 204 patients fit 4 ROX trajectories. In the subphenotypes of RR, when compared with group 4, the odds ratios (ORs) and 95% confidence intervals (CIs) of group 3 were 2.74 (1.48-5.07) (P = 0.001). Regarding the HR subphenotypes, in comparison to group 1, the ORs and 95% CIs were 2.20 (1.19-4.08) (P = 0.012) for group 2, 2.70 (1.40-5.23) (P = 0.003) for group 3, 2.16 (1.04-4.49) (P = 0.040) for group 5. Low last ROX had a higher mortality risk (P linear = 0.023, P nonlinear = 0.010). Trajectories of RR and HR improved the predictive ability for 28-day mortality (AUC increased by 2.5%, P = 0.020). CONCLUSIONS For RR and HR, longitudinal subphenotypes are risk factors for 28-day mortality and have additional predictive enrichment, whereas the last ROX during the first 72 h of ICU stays is associated with 28-day mortality. These findings indicate that maintaining the health dynamic subphenotypes of RR and HR in the ICU and elevating static ROX after initial critical care may have potentially beneficial effects on prognosis in critically ill elderly patients with ARDS.
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Affiliation(s)
- Mingzhuo Li
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Data Open Innovative Application Laboratory, Jinan, China
| | - Fen Liu
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China
| | - Yang Yang
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Data Open Innovative Application Laboratory, Jinan, China
| | - Jiahui Lao
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Data Open Innovative Application Laboratory, Jinan, China
| | - Chaonan Yin
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Data Open Innovative Application Laboratory, Jinan, China
| | - Yafei Wu
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhongshang Yuan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Fang Tang
- Department of Critical Care Medicine, Shandong Medicine and Health Key Laboratory of Emergency Medicine, Shandong Institute of Anesthesia and Respiratory Critical Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jingshi Road 16766, Jinan, China.
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
- Shandong Data Open Innovative Application Laboratory, Jinan, China.
- Shandong Provincial Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
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Pittman E, Martin-Flores M, Mosing M, Lorenzutti M, Retamal J, Staffieri F, Adler A, Campbell M, Araos J. Preliminary evaluation of the effects of a 1:1 inspiratory-to-expiratory ratio in anesthetized and ventilated horses. Vet Anaesth Analg 2022; 49:645-649. [DOI: 10.1016/j.vaa.2022.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 10/15/2022]
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