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Lee KG, Roca O, Casey JD, Semler MW, Roman-Sarita G, Yarnell CJ, Goligher EC. When to intubate in acute hypoxaemic respiratory failure? Options and opportunities for evidence-informed decision making in the intensive care unit. THE LANCET. RESPIRATORY MEDICINE 2024; 12:642-654. [PMID: 38801827 DOI: 10.1016/s2213-2600(24)00118-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/08/2024] [Accepted: 04/05/2024] [Indexed: 05/29/2024]
Abstract
The optimal timing of intubation in acute hypoxaemic respiratory failure is uncertain and became a point of controversy during the COVID-19 pandemic. Invasive mechanical ventilation is a potentially life-saving intervention but carries substantial risks, including injury to the lungs and diaphragm, pneumonia, intensive care unit-acquired muscle weakness, and haemodynamic impairment. In deciding when to intubate, clinicians must balance premature exposure to the risks of ventilation with the potential harms of unassisted breathing, including disease progression and worsening multiorgan failure. Currently, the optimal timing of intubation is unclear. In this Personal View, we examine a range of parameters that could serve as triggers to initiate invasive mechanical ventilation. The utility of a parameter (eg, the ratio of arterial oxygen tension to fraction of inspired oxygen) to predict the likelihood of a patient undergoing intubation does not necessarily mean that basing the timing of intubation on that parameter will improve therapeutic outcomes. We examine options for clinical investigation to make progress on establishing the optimal timing of intubation.
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Affiliation(s)
- Kevin G Lee
- Department of Physiology, Toronto, ON, Canada; Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Oriol Roca
- Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Parc Taulí-I3PT, Sabadell, Spain; Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain; Ciber Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Jonathan D Casey
- Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Matthew W Semler
- Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Christopher J Yarnell
- Interdepartmental Division of Critical Care Medicine University of Toronto, Toronto, ON, Canada; Department of Medicine, Division of Respirology, University Health Network, Toronto, ON, Canada; Institute of Health Policy, Management, and Evaluation at the University of Toronto, Toronto, ON, Canada; Scarborough Health Network, Department of Critical Care Medicine, Toronto, ON, Canada; Scarborough Health Network Research Institute, Toronto, ON, Canada.
| | - Ewan C Goligher
- Department of Physiology, Toronto, ON, Canada; Interdepartmental Division of Critical Care Medicine University of Toronto, Toronto, ON, Canada; Department of Medicine, Division of Respirology, University Health Network, Toronto, ON, Canada; Toronto General Hospital Research Institute, Toronto, ON, Canada
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Gallardo A, Vivanco Aravena P, Ramírez-Santana M, Sepúlveda Barisich P. Is the flow rate the missing link in the evolution of clinical outcome of patients using high-flow nasal cannula? J Crit Care 2024; 79:154443. [PMID: 37826998 DOI: 10.1016/j.jcrc.2023.154443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/26/2023] [Accepted: 09/30/2023] [Indexed: 10/14/2023]
Affiliation(s)
- Adrián Gallardo
- Servicio de Kinesiología, Cuidados Respiratorios, Sanatorio Clínica Modelo de Morón, Morón, Buenos Aires, Argentina; Kinesiology Department, Respiratory Care, Moron Model Clinic, Morón, Buenos Aires, Argentina.
| | - Paulina Vivanco Aravena
- Unidad de Cuidados Intensivos, Hospital de Urgencia y Asistencia Pública, Santiago de Chile, Chile; Intensive Care Unit, Emergency and Public Assistance Hospital, Santiago de Chile, Chile
| | - Muriel Ramírez-Santana
- Departamento de Salud Pública, Facultad de Medicina, Universidad Católica del Norte, Coquimbo, Chile; Public Health Department, School of Medicine, Northern Catholic University, Coquimbo, Chile
| | - Patrick Sepúlveda Barisich
- Servicio de Medicina Física y Rehabilitación, Hospital San Juan de Dios, La Serena, Chile; Physical Medicine and Rehabilitation Department, San Juan de Dios Hospital, La Serena, Chile
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Janssen ML, Jonkman AH, Wennen M, Wils EJ, Endeman H, Heunks L. Diaphragm excursions as proxy for tidal volume during spontaneous breathing in invasively ventilated ICU patients. Intensive Care Med Exp 2023; 11:73. [PMID: 37891413 PMCID: PMC10611662 DOI: 10.1186/s40635-023-00553-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
There is a need to monitor tidal volume in critically ill patients with acute respiratory failure, given its relation with adverse clinical outcome. However, quantification of tidal volume in non-intubated patients is challenging. In this proof-of-concept study, we evaluated whether ultrasound measurements of diaphragm excursion could be a valid surrogate for tidal volume in patients with respiratory failure. Diaphragm excursions and tidal volumes were simultaneously measured in invasively ventilated patients (N = 21) and healthy volunteers (N = 20). Linear mixed models were used to estimate the ratio between tidal volume and diaphragm excursion. The tidal volume-diaphragm excursion ratio was 201 mL/cm in ICU patients [95% confidence interval (CI) 161-240 mL/cm], and 361 (294-428) mL/cm in healthy volunteers. An excellent association was shown within participants (R2 = 0.96 in ICU patients, R2 = 0.90 in healthy volunteers). However, the differences between observed tidal volume and tidal volume as predicted by the linear mixed models were considerable: the 95% limits of agreement in Bland-Altman plots were ± 91 mL in ICU patients and ± 396 mL in healthy volunteers. Likewise, the variability in tidal volume estimation between participants was large. This study shows that diaphragm excursions measured with ultrasound correlate with tidal volume, yet quantification of absolute tidal volume from diaphragm excursion is unreliable.
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Affiliation(s)
- Matthijs L Janssen
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands
| | - Annemijn H Jonkman
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Myrte Wennen
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Evert-Jan Wils
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands
| | - Henrik Endeman
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Leo Heunks
- Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.
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Yang L, Li Z, Dai M, Fu F, Möller K, Gao Y, Zhao Z. Optimal machine learning methods for prediction of high-flow nasal cannula outcomes using image features from electrical impedance tomography. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 238:107613. [PMID: 37209577 DOI: 10.1016/j.cmpb.2023.107613] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 04/26/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
BACKGROUND High-flow nasal cannula (HNFC) is able to provide ventilation support for patients with hypoxic respiratory failure. Early prediction of HFNC outcome is warranted, since failure of HFNC might delay intubation and increase mortality rate. Existing methods require a relatively long period to identify the failure (approximately 12 h) and electrical impedance tomography (EIT) may help identify the patient's respiratory drive during HFNC. OBJECTIVES This study aimed to investigate a proper machine-learning model to predict HFNC outcomes promptly by EIT image features. METHODS The Z-score standardization method was adopted to normalize the samples from 43 patients who underwent HFNC and six EIT features were selected as model input variables through the random forest feature selection method. Machine-learning methods including discriminant, ensembles, k-nearest neighbour (KNN), artificial neural network (ANN), support vector machine (SVM), AdaBoost, xgboost, logistic, random forest, bernoulli bayes, gaussian bayes and gradient-boosted decision trees (GBDT) were used to build prediction models with the original data and balanced data proceeded by the synthetic minority oversampling technique. RESULTS Prior to data balancing, an extremely low specificity (less than 33.33%) as well as a high accuracy in the validation data set were observed in all the methods. After data balancing, the specificity of KNN, xgboost, random forest, GBDT, bernoulli bayes and AdaBoost significantly reduced (p<0.05) while the area under curve did not improve considerably (p>0.05); and the accuracy and recall decreased significantly (p<0.05). CONCLUSIONS The xgboost method showed better overall performance for balanced EIT image features, which may be considered as the ideal machine learning method for early prediction of HFNC outcomes.
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Affiliation(s)
- Lin Yang
- Department of Aerospace Medicine, Fourth Military Medical University, Xi'an, China
| | - Zhe Li
- Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Meng Dai
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.
| | - Feng Fu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Knut Möller
- Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany
| | - Yuan Gao
- Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhanqi Zhao
- Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany
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Chen D, Heunks L, Qiu H, Yang Y, Liu L. Reply to Li et al.. Am J Respir Crit Care Med 2023; 207:491-492. [PMID: 36198173 PMCID: PMC9940150 DOI: 10.1164/rccm.202209-1830le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Dongyu Chen
- Southeast UniversityNanjing, China,The First People’s Hospital of YanchengYancheng, Jiangsu, China
| | - Leo Heunks
- Erasmus University Medical CenterRotterdam, the Netherlands
| | | | - Yi Yang
- Southeast UniversityNanjing, China
| | - Ling Liu
- Southeast UniversityNanjing, China,Corresponding author (e-mail: )
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Li Z, Gao Y, Zhao Z. Volume-OXygenation Index to Predict High-flow Nasal Cannula Failure: How to Capture the Tidal Volume Matters. Am J Respir Crit Care Med 2023; 207:490-491. [PMID: 36198170 PMCID: PMC9940149 DOI: 10.1164/rccm.202209-1659le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Zhe Li
- Shanghai Jiao Tong University School of Medicine Affiliated Renji HospitalShanghai, China
| | - Yuan Gao
- Shanghai Jiao Tong University School of Medicine Affiliated Renji HospitalShanghai, China,Corresponding author (e-mail: )
| | - Zhanqi Zhao
- Fourth Military Medical UniversityXi’an, China and,Furtwangen UniversityVillingen-Schwenningen, Germany
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Liu J, Li D, Luo L, Liu Z, Li X, Qiao L. Analysis of risk factors for the failure of respiratory support with high-flow nasal cannula oxygen therapy in children with acute respiratory dysfunction: A case-control study. Front Pediatr 2022; 10:979944. [PMID: 36081624 PMCID: PMC9445578 DOI: 10.3389/fped.2022.979944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Evidence-based clinical practice guidelines regarding high-flow nasal cannula (HFNC) use for respiratory support in critically ill children are lacking. Therefore, we aimed to determine the risk factors for early HFNC failure to reduce the failure rate and prevent adverse consequences of HFNC failure in children with acute respiratory dysfunction. METHODS Demographic and laboratory data were compared among patients, admitted to the pediatric intensive care unit between January 2017 and December 2018, who were included in a retrospective cohort study. Univariate and multivariate analyses were performed to determine risk factors for eventual entry into the predictive model for early HFNC failure and to perform an external validation study in a prospective observational cohort study from January to February 2019. Further, the association of clinical indices and trends pre- and post-treatment with HFNC treatment success or failure in these patients was dynamically observed. RESULTS In total, 348 pediatric patients were included, of these 282 (81.0%) were included in the retrospective cohort study; HFNC success was observed in 182 patients (64.5%), HFNC 0-24 h failure in 74 patients (26.2%), and HFNC 24-48 h failure in 26 patients (9.2%). HFNC 24 h failure was significantly associated with the pediatric risk of mortality (PRISM) III score [odds ratio, 1.391; 95% confidence interval (CI): 1.249-1.550], arterial partial pressure of carbon dioxide-to-arterial partial pressure of oxygen (PaCO2/PaO2) ratio (odds ratio, 38.397; 95% CI: 6.410-230.013), and respiratory rate-oxygenation (ROX) index (odds ratio, 0.751; 95% CI: 0.616-0.915). The discriminating cutoff point for the new scoring system based on the three risk factors for HFNC 24 h failure was ≥ 2.0 points, with an area under the receiver operating characteristic curve of 0.794 (95% CI, 0.729-0.859, P < 0.001), sensitivity of 68%, and specificity of 79%; similar values were noted on applying the model to the prospective observational cohort comprising 66 patients (AUC = 0.717, 95% CI, 0.675-0.758, sensitivity 83%, specificity 44%, P = 0.009). In this prospective cohort, 11 patients with HFNC failure had an upward trend in PaCO2/PaO2 ratio and downward trends in respiratory failure index (P/F ratio) and ROX index; however, opposite directions of change were observed in 55 patients with HFNC success. Furthermore, the fractional changes (FCs) in PaCO2/PaO2 ratio, P/F ratio, percutaneous oxygen saturation-to-fraction of inspired oxygen (S/F) ratio, and ROX index at 2 h post-HFNC therapy onset were statistically significant between the two groups (all, P < 0.05). CONCLUSION In the pediatric patients with acute respiratory insufficiency, pre-treatment PRISM III score, PaCO2/PaO2 ratio, and ROX index were risk factors for HFNC 24 h failure, and the direction and magnitude of changes in the PaCO2/PaO2 ratio, P/F ratio, and ROX index before and 2 h after HFNC treatment were warning indicators for HFNC 24 h failure. Further close monitoring should be considered for patients with these conditions.
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Affiliation(s)
- Jie Liu
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
| | - Deyuan Li
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
| | - Lili Luo
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
| | - Zhongqiang Liu
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
| | - Xiaoqing Li
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
| | - Lina Qiao
- Department of Pediatric Intensive Care Unit, West China Second Universal Hospital, Sichuan University, Chengdu, China.,NHC Key Laboratory of Chronobiology (Sichuan University), Ministry of Education, Chengdu, China
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