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| Name | Class |
|---|---|
| International Association of Non Invasive Ventilation | UNKNOWN |
| International Academy of Non Invasive Ventilation | UNKNOWN |
| International College of Experts of Non Invasive Ventilation | UNKNOWN |
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Mechanical insufflation-exsufflation (MI-E) is an established airway clearance technique for patients with chronic conditions like neuromuscular diseases. However, its use in critically ill ICU patients remains inconsistent and lacks standardized guidelines. Despite growing research, current practices vary widely in patient selection, treatment protocols, and safety management, with limited high-quality evidence to support clear recommendations. To address this gap, an international, multidisciplinary Delphi consensus study is needed to establish expert-based best practices and feasible guidelines for the safe and effective implementation of MI-E in the intensive care setting.
Background: Mechanical insufflation-exsufflation (MI-E) functions as a noninvasive method which clears airways through its ability to enhance cough performance by delivering positive pressure to initiate airflow and then rapidly applies negative pressure for exhalation. MI-E enables bronchial secretions to be moved and eliminated through its ability to produce high expiratory flows while decreasing the chances of secretions being retained in the lungs.
MI-E is well established in patients with neuromuscular diseases and chronic respiratory disorders, in which weak cough and airway clearance dysfunction are the main contributors to respiratory morbidity. Nevertheless, the use of this technique in critically ill patients, particularly those admitted to the intensive care unit (ICU), is still diverse and insufficiently standardized. Invasive and non invasive ventilation, sedation, impaired consciousness, artificial airways, and respiratory muscle dysfunction substantially alter cough physiology in ICU patients, increasing risk of secretion retention, atelectasis, extubation failure, and reintubation.
Research on MI-E applications for ICU patients has become more popular but current clinical practices show different standards for selecting patients and determining treatment times and establishing device settings and conducting safety checks and managing restricted treatment conditions and integrating MI-E use with other ventilation modalities. A few studies available are restricted by small sample sizes, mixed populations, and varying outcome definitions, thus no clear recommendations can be made. Concerns about safety, such as the risk of barotrauma and damage to the airway, changes in clinical practice, and the requirement for staff skills and training are some of the factors that cause uncertainty and inconsistency in the use of MI-E in critically ill patients.
In situations where there are few high-quality randomized trials giving the evidence, expert consensus is now generally considered to be a proper and effective methodology to determine clinical best practice. The Delphi method with the addition of fuzzy logic is a way of systematically collecting and combining the experts' opinions, and it also counteracts the influence of the strongest participants and allows the identification of the recommendations that should be given priority, both from the point of view of their clinical relevance and of their feasibility.
Therefore, it is necessary to carry out a global, multidisciplinary Delphi consensus study in order to identify best practices and agree on consensus, based guidelines for implementing MI-E therapy in critical care patients.
Study Objectives: To achieve international expert consensus on the clinical use of MI-E in critically ill patients Fuzzy Delphi methodology, and to develop consensus-based recommendations applicable to intensive care practice.
Sample Size: As this study is an expert consensus study using Delphi and Fuzzy Delphi methodology, the sample size refers to the number of participating experts rather than patient enrollment. An international, multidisciplinary panel of 20-25 experts with recognized experience in critical care and/or mechanical insufflation-exsufflation (MI-E) will be included in the study. To account for potential attrition across Delphi rounds, approximately 30 experts will be invited initially, with the aim of retaining at least 20 experts through the final consensus round. This panel size is considered sufficient to achieve stable and reliable consensus while maintaining feasibility and diversity of expert perspectives.
Ethical Approval and Informed Consent: Ethical approval for this study has been obtained from the appropriate Ethics Committee (The Campania 2 Territorial Ethics Committee) Approval Number: AOC/0018028/2026) prior to study initiation.
All participating experts will be provided with detailed written information regarding the study objectives, methodology, data management procedures, and their rights as participants. Electronic informed consent will be obtained from all experts before participating in the first Delphi round.
Participation will be voluntary, and experts may withdraw from the study at any stage without providing justification. Expert responses will be collected anonymously using secure electronic survey platforms. Personal identifiers (such as name and email address) will be stored separately from survey data and accessed only by the study coordination team. All data will be handled confidentially and in accordance with applicable data protection regulations.
Primary Consensus Output: Development of a core set of international consensus statements on the clinical use of MI-E in critically ill patients, finalized through predefined Fuzzy Delphi consensus criteria (agreement level, threshold value, and defuzzified score).
Secondary Outcomes: Consensus-based identification and prioritization of key clinical domains related to MI-E use in critical care, including:
Identification of areas of strong agreement and persistent disagreement among experts regarding MI-E practices in critically ill patients.
Consensus-derived description of organizational, educational, and practical barriers to MI-E implementation in intensive care units.
Definition of priority areas for future research based on items that fail to reach consensus or are considered clinically important but insufficiently supported by existing evidence.
Duration of Study: The total duration of the study is planned to be 12 months, including expert recruitment, execution of all Delphi and Fuzzy Delphi rounds, data analysis, and finalization of the consensus statements.
Data Collection and Anonymization: Data will be collected using secure, web-based electronic survey platforms specifically designed for Delphi studies. Each participating expert will be assigned a unique anonymous identification code to ensure confidentiality and to allow tracking of responses across Delphi rounds without revealing personal identity. All Delphi rounds will be conducted electronically. Experts will complete structured questionnaires, including open-ended questions in the initial round and structured rating scales in subsequent Fuzzy Delphi rounds. No patient-level data or sensitive personal information will be collected.
Personal identifiers (such as name, institutional affiliation, and email address) will be stored separately from survey responses in a password-protected file accessible only to the study coordination team. Survey data will be anonymized prior to analysis and will be used exclusively for research purposes. Anonymized datasets will be exported for statistical and Fuzzy Delphi analysis. Results will be reported in aggregate form, ensuring that individual experts cannot be identified. Data storage, handling, and sharing procedures will comply with applicable data protection regulations and institutional policies.
Qualitative Analysis (Delphi Round 1):
Responses from the first open-ended Delphi round will be analyzed using thematic content analysis. Two members of the research team will independently review and code the responses to identify recurring themes, concepts, and recommendations related to the clinical use of MI-E in critically ill patients. Discrepancies in coding will be resolved through discussion and consensus. The resulting themes will be used to generate a refined list of statements for subsequent Delphi rounds.
Fuzzy Delphi Analysis (Rounds 2 and 3):
In the structured Delphi rounds, experts will rate each consensus statement using a 5-point Likert scale based on predefined dimensions (e.g., clinical importance and feasibility). Likert-scale responses will be transformed into Triangular Fuzzy Numbers (TFNs).
For each statement:
Consensus will be defined according to prespecified criteria:
Statistical Analysis:
Descriptive statistics will be used to summarize expert characteristics and response distributions. Categorical variables will be reported as frequencies and percentages. Continuous variables derived from defuzzified scores will be presented as means and standard deviations or medians with interquartile ranges, as appropriate. Analysis will be performed using IBM SPSS Statistics 26 (IBM Corp., Armonk, NY, USA) and jamovi v.2.6 (The jamovi project, Sydney, Australia).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experts | Healthcare professionals with documented clinical experience in critical care medicine, pulmonology, anesthesiology, respiratory therapy, or physiotherapy with involvement in airway clearance strategies. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Delphi Questionnaire | Other | Statements on MI-E topics, rated along their level of appropriateness on a scale from 1 to 5. Multiple rounds are organised to reach consensus on a topic. |
| Measure | Description | Time Frame |
|---|---|---|
| Primary Consensus Output | Number (or Proportion) of clinical practice statements achieving international expert consensus on the use of Mechanical Insufflation-Exsufflation (MI-E) in critically ill patients. | through study completion, an average of 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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experts on MI-E
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Berkan Basançelebi | Contact | +90 444 8 544 | berkan.basancelebi@medipol.edu.tr |
| Name | Affiliation | Role |
|---|---|---|
| Berkan Basançelebi | Medipol University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Monaldi Hospital A.O.R.N. dei Colli | Recruiting | Naples | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39186713 | Background | Niederberger M, Schifano J, Deckert S, Hirt J, Homberg A, Koberich S, Kuhn R, Rommel A, Sonnberger M; DEWISS network. Delphi studies in social and health sciences-Recommendations for an interdisciplinary standardized reporting (DELPHISTAR). Results of a Delphi study. PLoS One. 2024 Aug 26;19(8):e0304651. doi: 10.1371/journal.pone.0304651. eCollection 2024. | |
| Background | Ishikawa A, Amagasa M, Shiga T, Tomizawa G, Tatsuta R, Mieno H. The max-min Delphi method and fuzzy Delphi method via fuzzy integration. Fuzzy Sets Syst. 1993;55(3):241-253. doi:10.1016/0165-0114(93)90251-C | ||
| Background | Hsu CC, Sandford BA. The Delphi Technique: Making Sense of Consensus - Practical Assessment, Research & Evaluation. Practical Assessment, Research, and Evaluation. 2007;12(10):1-8. | ||
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| University of Naples Federico II | Recruiting | Naples | Italy |
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| Hospital General Universitario Morales Meseguer | Recruiting | Murcia | Spain |
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| İstanbul Medipol University | Recruiting | Istanbul | Istanbul | Turkey (Türkiye) |
|
| Background |
| Niederberger M, Spranger J. Delphi Technique in Health Sciences: A Map. Front Public Health. 2020 Sep 22;8:457. doi: 10.3389/fpubh.2020.00457. eCollection 2020. |
| 28190381 | Background | Junger S, Payne SA, Brine J, Radbruch L, Brearley SG. Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care: Recommendations based on a methodological systematic review. Palliat Med. 2017 Sep;31(8):684-706. doi: 10.1177/0269216317690685. Epub 2017 Feb 13. |
| 33598572 | Background | Saitoh Y, Miyazaki M, Arai N, Takahashi Y. Pneumomediastinum while using mechanical insufflation-exsufflation after recovery from riluzole-induced interstitial lung disease. eNeurologicalSci. 2021 Feb 2;22:100326. doi: 10.1016/j.ensci.2021.100326. eCollection 2021 Mar. |
| 36878644 | Background | Fossat G, Desmalles E, Courtes L, Fossat C, Boulain T. Cough Peak Flow Assessment Without Disconnection From the ICU Ventilator in Mechanically Ventilated Patients. Respir Care. 2023 Apr;68(4):470-477. doi: 10.4187/respcare.10412. Epub 2023 Mar 6. |
| 32712584 | Background | Volpe MS, Guimaraes FS, Morais CC. Airway Clearance Techniques for Mechanically Ventilated Patients: Insights for Optimization. Respir Care. 2020 Aug;65(8):1174-1188. doi: 10.4187/respcare.07904. |
| 12615633 | Background | Maggiore SM, Lellouche F, Pigeot J, Taille S, Deye N, Durrmeyer X, Richard JC, Mancebo J, Lemaire F, Brochard L. Prevention of endotracheal suctioning-induced alveolar derecruitment in acute lung injury. Am J Respir Crit Care Med. 2003 May 1;167(9):1215-24. doi: 10.1164/rccm.200203-195OC. Epub 2003 Feb 13. |
| 23641924 | Background | Thille AW, Richard JC, Brochard L. The decision to extubate in the intensive care unit. Am J Respir Crit Care Med. 2013 Jun 15;187(12):1294-302. doi: 10.1164/rccm.201208-1523CI. |
| 33292485 | Background | Swingwood E, Stilma W, Tume L, Cramp F, Paulus F, Schultz M, Scholte Op Reimer W, Rose L. The use of mechanical insufflation-exsufflation in invasively ventilated critically ill adults: a scoping review protocol. Syst Rev. 2020 Dec 8;9(1):287. doi: 10.1186/s13643-020-01547-8. |
| 35610033 | Background | Swingwood EL, Stilma W, Tume LN, Cramp F, Voss S, Bewley J, Ntoumenopoulos G, Schultz MJ, Scholte Op Reimer W, Paulus F, Rose L. The Use of Mechanical Insufflation-Exsufflation in Invasively Ventilated Critically Ill Adults. Respir Care. 2022 Aug;67(8):1043-1057. doi: 10.4187/respcare.09704. Epub 2022 May 24. |
| 36464804 | Background | Stilma W, Verweij L, Spek B, Scholte Op Reimer WJM, Schultz MJ, Paulus F, Rose L. Mechanical insufflation-exsufflation for invasively ventilated critically ill patients-A focus group study. Nurs Crit Care. 2023 Nov;28(6):923-930. doi: 10.1111/nicc.12858. Epub 2022 Dec 4. |
| 11359958 | Background | Sivasothy P, Brown L, Smith IE, Shneerson JM. Effect of manually assisted cough and mechanical insufflation on cough flow of normal subjects, patients with chronic obstructive pulmonary disease (COPD), and patients with respiratory muscle weakness. Thorax. 2001 Jun;56(6):438-44. doi: 10.1136/thorax.56.6.438. |
| 19245730 | Background | Toussaint M, Boitano LJ, Gathot V, Steens M, Soudon P. Limits of effective cough-augmentation techniques in patients with neuromuscular disease. Respir Care. 2009 Mar;54(3):359-66. |
| 15078752 | Background | Sancho J, Servera E, Diaz J, Marin J. Efficacy of mechanical insufflation-exsufflation in medically stable patients with amyotrophic lateral sclerosis. Chest. 2004 Apr;125(4):1400-5. doi: 10.1378/chest.125.4.1400. |
| 8222823 | Background | Bach JR. Mechanical insufflation-exsufflation. Comparison of peak expiratory flows with manually assisted and unassisted coughing techniques. Chest. 1993 Nov;104(5):1553-62. doi: 10.1378/chest.104.5.1553. |
| 12172066 | Background | Gomez-Merino E, Sancho J, Marin J, Servera E, Blasco ML, Belda FJ, Castro C, Bach JR. Mechanical insufflation-exsufflation: pressure, volume, and flow relationships and the adequacy of the manufacturer's guidelines. Am J Phys Med Rehabil. 2002 Aug;81(8):579-83. doi: 10.1097/00002060-200208000-00004. |
| 12662009 | Background | Chatwin M, Ross E, Hart N, Nickol AH, Polkey MI, Simonds AK. Cough augmentation with mechanical insufflation/exsufflation in patients with neuromuscular weakness. Eur Respir J. 2003 Mar;21(3):502-8. doi: 10.1183/09031936.03.00048102. |
| ID | Term |
|---|---|
| D016638 | Critical Illness |
| ID | Term |
|---|---|
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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